Study	Methodology	Research topics	Findings
	Literature review	Stress, absenteeism, cost	Stress contributes to 19% of absenteeism costs, 30% of disability costs, at least 60% of workplace accidents and 40% of staff turnover costs Positive impact of healthy workplaces on staff turnover and sick leave, resulting in cost reduction Cost–benefit ratio may range from €1.25 to €5 for every Euro invested. Great cost savings can be gained, when health promotion programs are implemented in a supportive work environment
	Employee surveys, interviews with managers and data about sickness absence in a multi-site organization in the logistics sector	Absenteeism	Good consultation and communication at the local level, and absence management that emphasizes employee well-being, is associated with lower absenteeism In a case study, absence rates fell from 6.5%–7% to 4%–5%
	Qualitative sorting task of employees’ preferences and ratings; in-depth interviews with 98 office employees; evaluation of physical office conditions, lighting qualities and quantities by 175 employees; questionnaire survey and physical health screening forms of employees’ health conditions	Biophilic relationship between views on nature and daylighting in the workplace and impacts on sick leave	Workers in offices with poor ratings of light quality and poorer views used significantly more sick leave hours. Taken together, the two variables explained 6.5% of the variation in sick leave use, which was statistically significant The combination of view quality, lighting quality and glazing area explained 10% of the variation in sick leave days
	Analysis of small investments involving very low or no up-front cost, such as providing employees access to plants, natural views, daylight and other biophilic design elements	Costs and benefit of biophilic design	Integrating quality daylighting schemes can save over €1.65 per employee per year in office costs; over €76m could be saved annually in health-care costs as a result of providing patients with views to nature. Biophilic changes can reduce absenteeism over a long period of time, reduce complaints that drain human resource productivity and help retain employees
	Literature study	Costs of stress and psychosocial risks at work, on national level and per sector	Stress and psychological risks result in increased medical and insurance costs, higher sickness absence, higher staff turnover, early retirement, more accidents and errors, loss of productivity and lower quality of life. It is estimated that 30% of sickness absence is directly caused by stress. Every €1 of expenditure in promotion and prevention programs generates net economic benefits over a one-year period of up to €13.62
(2014)	Data from 1,852 employees working in Sweden in different office types	Sick leave	Significant higher short sick leave among women in small, medium-sized and large open-plan offices and among men in flex-offices A significantly higher risk on long sick leave was found among women in large open-plan and for the total number of sick days among men in flex offices
	Analysis of 11 cases	Impact of green features, location and amenities, IAQ, acoustics, look-and-feel on health and well-being benefits, occupant satisfaction and economic benefits	Because of the variety in projects regarding its size, type of organization and interventions, calculated economic benefits showed a wide range with drops in employee sick days of 25%–58%, reductions in staff turnover of 27% and annual savings up to €85,000 per year
(2017)	Study of 16,926 employees who participated in a worksite wellness program	Workplace safety, employees’ health conditions and absenteeism	Poor workplace safety and employees’ chronic health conditions contributed to absenteeism and job performance. Their impact was influenced by the physical and cognitive difficulty of the job
(2017/ )	Property Health and Wellness ROI (Return of Investment)	Financial and health impact of investments in a hypothetical investment in the WELL Building Standard for a 18,500 m office building	Over a period of five years, the Internal Rate of Return from WELL investments is estimated to be almost 300%. Sensitivity analysis around a range of potential cost estimates (e.g. more or less than 0.5% productivity growth, taking into account initial investments to learn new rating systems) results in other figures
	Analysis of cost data from Investopedia and the International Well Building Institute	Productivity loss and absenteeism	In the USA, the total annual costs of lost productivity because of employee absenteeism counts €69bn. Creating and implementing well-being programs can reduce employee “sick days” by 26%. A real estate agency that achieved a WELL Gold certification mentioned a reduction of four sick days per year per employee and a 27% reduction in staff turnover
Measurement (no year)	Literature review and data from internet	Stress, engagement and productivity	57% of employees with high amounts of stress are disengaged in the workplace. Organizations with engaged employees experience increase profitability by more than 20%. Healthy workers are 11% more productive

Al Horr , Y. , Arif , M. , Kaushik , A. , Mazroei , A. , Katafygiotou , M. and Elsarrag , E. ( 2016 ), “ Occupant productivity and office indoor environment quality: a review of the literature ”, Building and Environment , Vol. 105 , pp. 369 - 389 , doi: 10.1016/j.buildenv.2016.06.001 .

Appel-Meulenbroek , R. , Van der Voordt , T. , Le Blanc , P. , Aussems , R. and Arentze , T. ( 2020 ), “ Impact of activity-based workplaces on burnout and engagement ”, Journal of Corporate Real Estate , Vol. 22 No. 4 , pp. 279 - 296 , doi: 10.1108/JCRE-09-2019-0041 .

Bauer , A. ( 2020 ), “ Pride and productivity: post occupancy evaluation of the healing office design concept ”, Journal of Corporate Real Estate , Vol. 22 No. 4 , pp. 313 - 340 , doi: 10.1108/JCRE-02-2019-0012 .

Bodin Danielsson , C. and Bodin , L. ( 2008 ), “ Office-type in relation to health, well-being and job satisfaction among employees ”, Environment and Behavior , Vol. 40 No. 5 , pp. 636 - 668 , doi: 10.1177/0013916507307459\

Bodin Danielsson , C.B. , Chungkham , H.S. , Wulff , C. and Westerlund , H. ( 2014 ), “ Office design’s impact on sick leave rates ”, Ergonomics , Vol. 57 No. 2 , pp. 139 - 147 , doi: 10.1080/00140139.2013.871064 .

British Council for Offices ( 2018 ), “ Wellness matters ”, Report , available at: www.bco.org.uk/HealthWellbeing/WellnessMatters.aspx

Burton , J. ( 2008 ), The Business Case for a Healthy Workplace , Toronto , Industrial Accident Prevention Association IAPA .

Candido , C. , Marzban , S. , Haddad , S. , Mackey , M. and Loder , A. ( 2021 ), “ Designing healthy workspaces: results from Australian certified open-plan offices ”, Facilities , Vol. 39 Nos 5/6 , pp. 411 - 433 , doi: 10.1108/F-02-2020-0018 .

Candido , C. , Thomas , L. , Haddad , S. , Zhang , F. , Mackey , M. and Ye , W. ( 2019 ), “ Designing activity-based workspaces: satisfaction, productivity and physical activity ”, Building Research and Information , Vol. 47 No. 3 , pp. 275 - 289 , doi: 10.1080/09613218.2018.1476372 .

Candido , C. , Zhang , J. , Kim , J. , De Dear , R. , Thomas , L. , Strapasson , P. and Joo , C. ( 2016 ), “ Impact of workspace layout on occupant satisfaction, perceived health and productivity ”, Proceedings of 9th Windsor Conference: Making Comfort Relevant , Windsor , available at: http://nceub.org.uk/

Chambers , A.J. , Robertson , M.M. and Baker , N.A. ( 2019 ), “ The effect of sit-stand desks on office worker behavioral and health outcomes: a scoping review ”, Applied Ergonomics , Vol. 78 , pp. 37 - 53 , doi: 10.1016/j.apergo.2019.01.015 .

Clements-Croome , D. ( 2018 ), “ Effects of the built environment on health and well-being ”, in Clements-Croome , D. (Ed.), Creating the Productive Workplace: Places to Work Creatively , 3rd ed ., London , Routledge , pp. 3 - 40 .

Colenberg , S. , Jylhä , T. and Arkesteijn , M. ( 2020 ), “ The relationship between interior office space and employee health and well-being ”, Building Research and Information , Vol. 49 No. 3 , doi: 10.1080/09613218.2019.1710098 .

Cordero , A.B. , Babapour , M. and Karlsson , M. ( 2020 ), “ Feel well and do well at work: a post-relocation study on the relationships between employee wellbeing and office landscape ”, Journal of Corporate Real Estate , Vol. 22 No. 2 , pp. 113 - 137 , doi: 10.1108/JCRE-01-2019-0002 .

Davis , M.C. , Leach , D.J. and Clegg , D.J. ( 2020 ), “ Breaking out of open-plan: extending social interference theory through an evaluation of contemporary offices ”, Environment and Behavior , Vol. 52 No. 9 , pp. 945 - 978 , doi: 10.1177/0013916519878211 .

Eichholtz , P. , Kok , N. and Palacios , P. ( 2019 ), “ Moving to productivity: the benefits of healthy buildings ”, Preliminary Working Paper , Maastricht University , doi: 10.7910/DVN/ALUUEC .

Elnaklah , R. , Walker , I. and Natarajan , S. ( 2021 ), “ Moving to a green building: indoor environment quality, thermal comfort and health ”, Building and Environment , Vol. 191 , pp. 1 - 19 , doi: 10.1016/j.buildenv.2021.107592 .

Elzeyadi , I. ( 2011 ), “ Daylighting-Bias and biophilia: quantifying the impacts of daylight on occupants health ”, Thought and Leadership in Green Buildings Research. Greenbuild Proceedings , Washington, DC , USGBC Press .

Engelen , L. , Chau , J. , Young , S. , Mackey , M. , Jeyapalan , D. and Bauman , A. ( 2019 ), “ Is activity-based working impacting health, work performance and perceptions? A systematic review ”, Building Research and Information , Vol. 47 No. 4 , pp. 468 - 479 , doi: 10.1080/09613218.2018.1440958 .

European Agency for Safety and Health at Work ( 2014 ), Calculating the Cost of Work-Related Stress and Psychosocial Risks , Luxembourg , Publications Office of the European Union . 10.2802/20493

Ferrari , R. ( 2015 ), “ Writing narrative style literature reviews ”, The European Medical Writers Association , doi: 10.1179/2047480615Z.000000000329 .

Forooraghi , M. , Miedema , E. , Ryd , N. and Wallbaum , H. ( 2020 ), “ Scoping review of health in office design approaches ”, Journal of Corporate Real Estate , Vol. 22 No. 2 , pp. 155 - 180 , doi: 10.1108/JCRE-08-2019-0036 .

Franke , M. and Nadler , C. ( 2020 ), “ Towards a holistic approach for assessing the impact of IEQ on satisfaction, health, and productivity ”, Building Research and Information , Vol. 49 No. 4 , pp. 417 - 444 , doi: 10.1080/09613218.2020.1788917 .

Garland , E. , Watts , A. , Doucette , J. , Foley , M. , Senerat , A. and Sanchez , S. ( 2018 ), “ Stand up to work: assessing the health impact of adjustable workstations ”, International Journal of Workplace Health Management , Vol. 11 No. 2 , pp. 85 - 95 , doi: 10.1108/IJWHM-10-2017-0078 .

Green , B.N. , Johnson , C.D. and Adams , A. ( 2006 ), “ Writing narrative literature reviews for peer-reviewed journals: secrets of the trade ”, Journal of Chiropractic Medicine , Vol. 5 No. 3 , pp. 101 - 117 , doi: 10.1016/S0899-3467(07)60142-6 .

Groen , B. , van der Voordt , T. , Hoekstra , B. and van Sprang , H. ( 2019 ), “ Impact of employee satisfaction with facilities on self-assessed productivity support ”, Journal of Facilities Management , Vol. 17 No. 5 , pp. 442 - 462 , doi: 10.1108/JFM-12-2018-0069 .

Haapakangas , A. , Hallman , D.M. , Mathiassen , S.E. and Jahncke , H. ( 2018b ), “ Self-rated productivity and employee well-being in activity-based offices: the role of environmental perceptions and workspace use ”, Building and Environment , Vol. 145 , pp. 115 - 124 .

Haapakangas , A. , Hongisto , V. , Varjo , J. and Lahtinen , M. ( 2018a ), “ Benefits of quiet workspaces in open-plan offices: evidence from two office relocations ”, Journal of Environmental Psychology , Vol. 56 , pp. 63 - 75 , doi: 10.1016/j.jenvp.2018.03.003 .

Hähn , N. , Essah , E. and Blanusa , T. ( 2020 ), “ Biophilic design and office planting: a case study of effects on perceived health, well-being and performance metrics ”, Intelligent Buildings International , doi: 10.1080/17508975.2020.1732859 .

Herbig , B. , Schneider , A. and Nowak , D. ( 2016 ), “ Does office space occupation matter? The role of the number of persons per enclosed office space, psychosocial work characteristics, and environmental satisfaction in the physical and mental health of employees ”, Indoor Air 2016 , Vol. 26 No. 5 , pp. 755 - 767 , doi: 10.1111/ina.12263 .

Hodzic , S. , Kubicek , B. , Uhlig , L. and Korunka , C. ( 2021 ), “ Activity-based flexible offices: effects on work-related outcomes in a longitudinal study ”, Ergonomics , Vol. 64 No. 4 , pp. 455 - 473 , doi: 10.1080/00140139.2020.1850882 .

Isham , A. , Mair , S. and Jackson , T. ( 2019 ), Wellbeing and Productivity: A Review of the Literature , Report for the Economic and Social Research Council , December 2019 .

Jamrozik , A. , Clements , N. , Hasana , S.S. , Zhaoa , J. , Zhanga , R. , Campanellaa , C. , Loftness , V. , Portera , P. , Lya , S. , Wanga , S. and Bauera , B. ( 2019 ), “ Access to daylight and view in an office improves cognitive performance and satisfaction and reduces eyestrain: a controlled crossover study ”, Building and Environment , Vol. 165 , p. 106379 , doi: 10.1016/j.buildenv.2019.106379 .

Jensen , P.A. and Van der Voordt , T. (Eds) ( 2017 ), Facilities Management and Corporate Real Estate Management as Value Drivers: How to Manage and Measure Adding Value , London/New York, NY , Routledge

Jensen , P.A. and Van der Voordt , T. ( 2020 ), “ Healthy workplaces: what we know and what we should know ”, Journal of Corporate Real Estate , Vol. 22 No. 2 , pp. 95 - 112 , doi: 10.1108/JCRE-11-2018-0045 .

Jinnett , K. , Schwatka , N. , Tenney , L. , Brockbank , C.V.S. and Newman , L. ( 2017 ), “ Chronic conditions, workplace safety, and job demands contribute to absenteeism and job performance ”, Health Affairs , Vol. 36 No. 2 , pp. 237 - 244 , doi: 10.1377/hlthaff.2016.1151 .

Kar , G. and Hedge , A. ( 2021 ), “ Effect of workstation configuration on musculoskeletal discomfort, productivity, postural risks, and perceived fatigue in a sit-stand-walk intervention for computer-based work ”, Applied Ergonomics , Vol. 90 , pp. 1 - 11 , doi: 10.1016/j.apergo.2020.103211 .

Karakolis , T. and Callaghan , J.P. ( 2014 ), “ The impact of sit-stand office workstations on worker discomfort and productivity: a review ”, Applied Ergonomics , Vol. 45 No. 3 , pp. 799 - 806 , doi: 10.1016/j.apergo.2013.10.001 .

Kaushik , A. , Arif , M. , Tumula , P. and Ebohon , O.J. ( 2020 ), “ Effect of thermal comfort on occupant productivity in office buildings: response surface analysis ”, Building and Environment , Vol. 180 , pp. 1 - 9 , doi: 10.1016/j.buildenv.2020.107021 .

Kim , J. , Candido , C. , Thomas , L. and De Dear , R. ( 2016 ), “ Desk ownership in the workplace: the effect of non-territorial working on employee workplace satisfaction, perceived productivity and health ”, Building and Environment , Vol. 103 , pp. 203 - 214 , doi: 10.1016/j.buildenv.2016.04.015 .

Ko , W.H. , Schiavon , S. , Zhang , Z. , Graham , L.T. , Brager , G. , Mauss , I. and Lin , Y.-W. ( 2020 ), “ The impact of a view from a window on thermal comfort, emotion, and cognitive performance ”, Building and Environment , Vol. 175 , pp. 1 - 15 , doi: 10.1016/j.buildenv.2020.106779 .

Lamb , S. and Kwok , K.C.S. ( 2016 ), “ A longitudinal investigation of work environment stressors on the performance and wellbeing of office workers ”, Applied Ergonomics , Vol. 52 , pp. 104 - 111 , doi: 10.1016/j.apergo.2015.07.010 .

Lamb , S. and Kwok , K.C.S. ( 2017 ), “ Sopite syndrome in wind-excited buildings: productivity and wellbeing impacts ”, Building Research and Information , Vol. 45 No. 3 , pp. 347 - 358 , doi: 10.1080/09613218.2016.1190140 .

Laski , J. ( 2016 ), “ Doing right by planet and people ”, The Business Case for Health and Wellbeing in Green Building , London/Toronto , World Green Building Council .

Licina , D. and Yildirim , S. ( 2021 ), “ Occupant satisfaction with indoor environmental quality, sick building syndrome (SBS) symptoms and self-reported productivity before and after relocation into WELL-certified office buildings ”, Building and Environment , Vol. 204 , pp. 1 - 12 , doi: 10.1016/j.buildenv.2021.108183 .

Lu , M. , Hu , S. , Mao , Z. , Liang , P. , Xin , S. and Guan , H. ( 2020 ), “ Research on work efficiency and light comfort based on EEG evaluation method ”, Building and Environment , Vol. 183 , pp. 1 - 11 , doi: 10.1016/j.buildenv.2020.107122 .

MacNaughton , P. , Satish , U. , Laurent , J.G.C. , Flanigan , S. , Vallarino , J. , Coull , B. , Spengler , J.D. and Allen , J.G. ( 2017 ), “ The impact of working in a green certified building on cognitive function and health ”, Building and Environment , Vol. 114 , pp. 178 - 186 , doi: 10.1016/j.buildenv.2016.11.041 .

Marsden , D. and Moriconi , S. ( 2009 ), “ 'The value of rude health’: employees’ well being, absence and workplace performance ”, CEP Discussion Paper No 919 . London , The London School of Economics, Centre for Economic Performance .

Marsh , P. and French , S. ( 2020 ), “ The GSK workspace performance hub: promoting productivity and wellbeing through office design ”, Corporate Real Estate Journal , Vol. 9 No. 4 , pp. 345 - 360 .

Marson , M. ( 2018 ), “ The business value of an innovative building ”, Corporate Real Estate Journal , Vol. 8 No. 2 , pp. 154 - 164 .

Morrison , R.L. and Smollan , R.K. ( 2020 ), “ Open plan office space? If you're going to do it, do it right: a fourteen-month longitudinal case study ”, Applied Ergonomics , Vol. 82 , pp. 1 - 18 , doi: 10.1016/j.apergo.2019.102933 .

Muldavin , S. , Miers , C.R. and McMackin , K. ( 2017 /2018), “ Buildings emerge as drivers of health and profits ”, Corporate Real Estate Journal , Vol. 7 No. 2 , pp. 177 - 193 .

Nappi , I. , De Campos Ribeiro , G. and Cochard , N. ( 2020 ), “ The interplay of stress and workspace attachment on user satisfaction and workspace support to labour productivity ”, Journal of Corporate Real Estate , Vol. 22 No. 3 , pp. 215 - 237 , doi: 10.1108/JCRE-05-2019-0026 .

Nelson , E. and Holzer , D. ( 2017 ), The Healthy Office Revolution , Amstelveen , Learn Adapt Build Publishing .

Rasheed , E.O. , Khoshbakht , M. and Baird , G. ( 2021 ), “ Time spent in the office and workers’ productivity, comfort and health: a perception study ”, Building and Environment , Vol. 195 , pp. 1 - 9 , doi: 10.1016/j.buildenv.2021.107747 .

Roskams , M. and Haynes , B. ( 2019 ), “ An experience sampling approach to the workplace environment survey ”, Facilities , Vol. 38 Nos 1/2 , pp. 72 - 85 , doi: 10.1108/F-04-2019-0050 .

Seddigh , A. , Berntson , E. , Bodin Danielson , C. and Westerlund , H. ( 2014 ), “ Concentration requirements modify the effect of office type on indicators of health and performance ”, Journal of Environmental Psychology , Vol. 38 , pp. 167 - 174 , doi: 10.1016/j.jenvp.2014.01.009 .

Soriano , A. , Kozusnik , M.W. and Peiró , J.M. ( 2020 ), “ The role of employees’ work patterns and office type fit (and misfit) in the relationships between employee Well-Being and performance ”, Environment and Behavior , Vol. 52 No. 2 , pp. 111 - 138 , doi: 10.1177/0013916518794260 .

Tan , Z. , Roberts , A.C. , Lee , E.L. , Kwok , K.-W. , Car , J. , Soh , C.K. and Christopoulos , G. ( 2020 ), “ Transitional areas affect perception of workspaces and employee well-being: a study of underground and above-ground workspaces ”, Building and Environment , Vol. 179 , pp. 1 - 10 , doi: 10.1016/j.buildenv.2020.106840 .

Terrapin Bright Green ( 2012 ), “ The economics of biophilia ”, Why Designing with Nature in Mind Makes Financial Sense , New York, NY and Washington, DC .

Thatcher , A. , Adamson , K. , Bloch , L. and Kalantzis , A. ( 2020 ), “ Do indoor plants improve performance and well-being in offices? Divergent results from laboratory and field studies ”, Journal of Environmental Psychology , Vol. 71 No. 1.11 , p. 101487 , doi: 10.1016/j.jenvp.2020.101487 .

Van der Voordt , T. ( 2021 ), “ Designing for health and wellbeing: various concepts, similar goals ”, Gestão and Tecnologia de Projetos , Vol. 16 No. 4 , pp. 13 - 31 , doi: 10.11606/gtp.v16i4.178190 .

Van der Voordt , T. and Jensen , P.A. ( 2014 ), “ Adding value by FM: exploration of management practice in The Netherlands and Denmark ”, EFMC 2014 , Berlin , 4-6 June 2014 .

Wargocki , P. ( 2019 ), “ Productivity and health effects of high indoor air quality ”, Encyclopedia of Environmental Health , 2nd edition , Vol. 5 , pp. 382 - 388 , doi: 10.1016/B978-0-12-409548-9.01993-X .

Wijk , K. , Bergsten , E.L. and Hallman , D.M. ( 2020 ), “ Sense of coherence, health, Well-Being, and work satisfaction before and after implementing activity-based workplaces ”, International Journal of Environmental Research and Public Health , Vol. 17 No. 14 , p. 5250 , doi: 10.3390/ijerph17145250 .

Wolkoff , P. ( 2020 ), “ Dry eye symptoms in offices and deteriorated work performance. A perspective ”, Building and Environment , Vol. 172 , p. 106704 , doi: 10.1016/j.buildenv.2020.106704 .

Zerguine , H. , Johnston , V. , Healy , G.N. , Abbott , A. and Goode , A.D. ( 2021 ), “ Usage of sit-stand workstations: benefits and barriers from decision makers’ perspective in Australia ”, Applied Ergonomics , Vol. 94 , pp. 1 - 11 , doi: 10.1016/j.apergo.2021.103426 .

Further reading

Jensen , P.A. and Van der Voordt , T. ( 2021 ), “ Productivity as a value parameter for FM and CREM ”, Facilities , Vol. 39 Nos 5/6 , pp. 305 - 320 , doi: 10.1108/F-04-2020-0038 .

Measuremen consultancy (no year ), “ Why should you incorporate a healthy workplace strategy? ”, available at: www.measuremen.io/wp-content/uploads/2018/10/Measuremen-Whitepaper-Why-should-you-incorporate-a-healthy-workplace-strategy.pdf

Pejtersen , J.H. , Feveile , H. , Christensen , K.B. and Burr , H. ( 2011 ), “ Sickness absence associated with shared and open-plan offices – a national cross sectional questionnaire survey ”, Scandinavian Journal of Work, Environment and Health , Vol. 37 No. 5 , pp. 376 - 382 , doi: 10.5271/sjweh.3167 .

Platts , L.G. , Seddigh , A. , Berntson , E. and Westerlund , H. ( 2020 ), “ Sickness absence and sickness presence in relation to office type: an observational study of employer-recorded and self-reported data from Sweden ”, Plos One , Vol. 15 No. 4 , p. e0231934 , doi: 10.1371/journal.pone.0231934 .

Roskams , M. and Haynes , B. ( 2020 ), “ Salutogenic design in the workplace: Supporting sense of coherence through resources in the workplace environment ”, Journal of Corporate Real Estate , Vol. 22 No. 2 , pp. 193 - 153 , doi: 10.1108/JCRE-01-2019-0001 .

WHO ( 2021 ), “ Constitution of the world health organization ”, available at: www.who.int/about/governance/constitution . ( accessed August 30, 2021 ).

World Green Building Council ( 2014 ), “ Health, wellbeing and productivity in offices: the next chapter for green building ”, available at: www.worldgbc.org/sites/default/files/compressed_

Corresponding author

Related articles, we’re listening — tell us what you think, something didn’t work….

Report bugs here

All feedback is valuable

Please share your general feedback

Join us on our journey

Platform update page.

Visit emeraldpublishing.com/platformupdate to discover the latest news and updates

Questions & More Information

Answers to the most commonly asked questions here

• Specialisations
• Meet the team
• Wellness Program
• Join our talent pool

Posts by Tag

• contract engineering (16)
• contract solutions (10)
• Specialist Recruitment (8)
• technical resourcing (8)
• gig economy (7)
• Recruitment (5)
• job seeker (4)
• Insider (1)
• Resources (1)

The true impact of workplace wellbeing: two case studies

Embedded Expertise, Published: January 29, 2020 - Updated: August 22, 2022

Mental health concerns are a leading cause of workplace absence , and as we see increasing incidents of mental health-related sick days, workplace wellbeing is paramount for both organisational and individual success.

Below I’ve written two real-life stories where bettering the wellbeing of a workplace can have dramatic effects on the individuals and business profitability itself. Hopefully this will inspire you to incorporate a wellness approach into your organisation or team, or take more notice of your own mental health.

Case study one: Michael thought he was fine

Michael* realised he was arguing a lot with his family at home and was becoming increasingly more reactive to situations that probably didn’t warrant it. He wasn’t terribly great at conducting conversations or maintaining relationships with coworkers and this spilled outside of work. Body aches and excessive headaches had also started to culminate: all obvious signs of deep stress that Michael was ignoring.

The thing is, he thought he was actually doing really well and managing his stress levels appropriately and that his behaviour and experiences were quite normal.

But in fact, he was suffering extreme levels of stress . Something he didn’t even comprehend until he connected with a workplace wellbeing expert and he had the opportunity to observe his behaviours.

After one week of dedicated and concentrated awareness on how he was reacting and experiencing situations and noticing stress levels, triggers and emotions as they arose, he started to really notice a difference.

‘After one week of dedicated and concentrated awareness… he started to really notice a difference.’

To mitigate his stress levels and improve his workplace wellbeing and relations, Michael also engaged in visualisations (similar to what athletes do ), particularly with conversations, which creates different pathways in the brain . From here he started acting differently, having better discussions and decisions and was significantly calmer everywhere throughout his life, not just in the workplace.

Case study two: bad behaviour, great worker

Company owner, Rajiv, was experiencing some staff problems that he’d tried to handle but wasn’t seeing any changes. One of his contract managers, Tom, was displaying bad behaviour whenever things would go wrong.

The thing was, it was abundantly clear that what Tom was saying and the problems that he identified were absolutely correct. And the company valued his hard work and how exceptional he was at his job, so there was no desire to terminate his contract early. Which can often be a case for difficult situations in the workplace— many people are too eager to throw the ‘baby out with the bathwater’ so to speak, rather than experiment with some alternative ways of reaching conflict resolution. Or even taking the time to discover what is really going on, stepping away from the ego and its primal behaviour of flight or fight mode.

After supportive discussions with Tom, the wellness team discovered that actually he felt isolated , alone and that he didn’t belong. And, because the mind seeks to confirm our beliefs (through confirmation bias), would create situations and replicate behaviour to further consolidate that belief. He was very caught up in his story that he was an outsider.

A sense of belonging

To further compound this position, Tom was contracted as part of a large project and he felt like he didn’t fit in with the permanent employees, who had established themselves in the internal culture.

Forbes states that, ‘Employees who do not naturally fit into established corporate norms will often times try to assimilate to those norms – or put themselves “on guard” – in order to avoid potential biases or discrimination.’ This can take considerable effort and energy, which could be better spent on a person’s core duties.

A sense of belonging in the workplace contributes greatly to retention and attraction of high-quality candidates, which leads to better productivity, outcomes, creative solutions and more profit. It can also result in 75 per cent fewer sick days and avoid millions of dollars’ worth of lost productivity.

‘A sense of belonging in the workplace contributes greatly to retention and attraction of high quality candidates…’

Fostering this sense of belonging ‘in the workplace makes employees engaged and produce work that is elevated above the ordinary…’.

Once identified, the workplace wellbeing team worked with Tom and Rajiv with proven techniques that involved awareness, cultural changes and compassion and saw rapid improvement within weeks, thanks in part to the commitment of the people involved.

The change was so significant that Rajiv was enthusiastic and hungry to find more ways in which he could change the dynamics to bring out better and better results within his company. The company also extended Tom’s contract when the opportunity became available.

Welcome contract workers too

It can be really easy to forget that contract staff are an integral part of your team, even if they are only on staff for a limited time. And it shouldn’t be a last minute or token effort.

‘… there needs to be a culture and allowance for people to connect as human beings. We shouldn’t need bonding or team leadership days to actually connect with our colleagues and make meaningful relationships ,’ says Dr Michelle Lim, a loneliness researcher and senior lecturer in clinical psychology at Swinburne University.

Incorporating contract workers as genuinely part of the team and treating them as well as you treat all employees will only promote excellent benefits for the business and wider society as a whole and help contribute to preventing distressing issues such as high suicide rates in the engineering industry.

Can you relate in full or in part to these stories? Improve your wellbeing in your workplace today. Discover more about our for our contracting professionals.

*We’ve changed these names to provide privacy and protect the identity of these people.

Nukon is joint venture between the world of optimisation and automation. our parent company, SAGE Automation, is a leader in the operations market, while NUKON has fast established an outstanding reputation in the manufacturing data, intelligence andimprovement area.

This meeting of minds means we can now bridge the gaps between the different silos within our client businesses, bringing visibility, unity and breakthrough improvements right across our clients' businesses.

One Column Text

Enjoyed this post don't forget to share..

Embedded Expertise is a specialist consultancy that matches high calibre technical expertise with the agile clients who need them - fast.

Phone: 1300 050 557 Contact us

SAGE GROUP BRANDS

• SAGE Automation
• Embedded Expertise

QUICK LINKS

• Subscribe to our Newsletter

Culture Development

Workplace problem-solving examples: real scenarios, practical solutions.

• March 11, 2024

In today’s fast-paced and ever-changing work environment, problems are inevitable. From conflicts among employees to high levels of stress, workplace problems can significantly impact productivity and overall well-being. However, by developing the art of problem-solving and implementing practical solutions, organizations can effectively tackle these challenges and foster a positive work culture. In this article, we will delve into various workplace problem scenarios and explore strategies for resolution. By understanding common workplace problems and acquiring essential problem-solving skills, individuals and organizations can navigate these challenges with confidence and success.

Understanding Workplace Problems

Before we can effectively solve workplace problems , it is essential to gain a clear understanding of the issues at hand. Identifying common workplace problems is the first step toward finding practical solutions. By recognizing these challenges, organizations can develop targeted strategies and initiatives to address them.

Identifying Common Workplace Problems

One of the most common workplace problems is conflict. Whether it stems from differences in opinions, miscommunication, or personality clashes, conflict can disrupt collaboration and hinder productivity. It is important to note that conflict is a natural part of any workplace, as individuals with different backgrounds and perspectives come together to work towards a common goal. However, when conflict is not managed effectively, it can escalate and create a toxic work environment.

In addition to conflict, workplace stress and burnout pose significant challenges. High workloads, tight deadlines, and a lack of work-life balance can all contribute to employee stress and dissatisfaction. When employees are overwhelmed and exhausted, their performance and overall well-being are compromised. This not only affects the individuals directly, but it also has a ripple effect on the entire organization.

Another common workplace problem is poor communication. Ineffective communication can lead to misunderstandings, delays, and errors. It can also create a sense of confusion and frustration among employees. Clear and open communication is vital for successful collaboration and the smooth functioning of any organization.

The Impact of Workplace Problems on Productivity

Workplace problems can have a detrimental effect on productivity levels. When conflicts are left unresolved, they can create a tense work environment, leading to decreased employee motivation and engagement. The negative energy generated by unresolved conflicts can spread throughout the organization, affecting team dynamics and overall performance.

Similarly, high levels of stress and burnout can result in decreased productivity, as individuals may struggle to focus and perform optimally. When employees are constantly under pressure and overwhelmed, their ability to think creatively and problem-solve diminishes. This can lead to a decline in the quality of work produced and an increase in errors and inefficiencies.

Poor communication also hampers productivity. When information is not effectively shared or understood, it can lead to misunderstandings, delays, and rework. This not only wastes time and resources but also creates frustration and demotivation among employees.

Furthermore, workplace problems can negatively impact employee morale and job satisfaction. When individuals are constantly dealing with conflicts, stress, and poor communication, their overall job satisfaction and engagement suffer. This can result in higher turnover rates, as employees seek a healthier and more supportive work environment.

In conclusion, workplace problems such as conflict, stress, burnout, and poor communication can significantly hinder productivity and employee well-being. Organizations must address these issues promptly and proactively to create a positive and productive work atmosphere. By fostering open communication, providing support for stress management, and promoting conflict resolution strategies, organizations can create a work environment that encourages collaboration, innovation, and employee satisfaction.

The Art of Problem Solving in the Workplace

Now that we have a clear understanding of workplace problems, let’s explore the essential skills necessary for effective problem-solving in the workplace. By developing these skills and adopting a proactive approach, individuals can tackle problems head-on and find practical solutions.

Problem-solving in the workplace is a complex and multifaceted skill that requires a combination of analytical thinking, creativity, and effective communication. It goes beyond simply identifying problems and extends to finding innovative solutions that address the root causes.

Essential Problem-Solving Skills for the Workplace

To effectively solve workplace problems, individuals should possess a range of skills. These include strong analytical and critical thinking abilities, excellent communication and interpersonal skills, the ability to collaborate and work well in a team, and the capacity to adapt to change. By honing these skills, individuals can approach workplace problems with confidence and creativity.

Analytical and critical thinking skills are essential for problem-solving in the workplace. They involve the ability to gather and analyze relevant information, identify patterns and trends, and make logical connections. These skills enable individuals to break down complex problems into manageable components and develop effective strategies to solve them.

Effective communication and interpersonal skills are also crucial for problem-solving in the workplace. These skills enable individuals to clearly articulate their thoughts and ideas, actively listen to others, and collaborate effectively with colleagues. By fostering open and honest communication channels, individuals can better understand the root causes of problems and work towards finding practical solutions.

Collaboration and teamwork are essential for problem-solving in the workplace. By working together, individuals can leverage their diverse skills, knowledge, and perspectives to generate innovative solutions. Collaboration fosters a supportive and inclusive environment where everyone’s ideas are valued, leading to more effective problem-solving outcomes.

The ability to adapt to change is another important skill for problem-solving in the workplace. In today’s fast-paced and dynamic work environment, problems often arise due to changes in technology, processes, or market conditions. Individuals who can embrace change and adapt quickly are better equipped to find solutions that address the evolving needs of the organization.

The Role of Communication in Problem Solving

Communication is a key component of effective problem-solving in the workplace. By fostering open and honest communication channels, individuals can better understand the root causes of problems and work towards finding practical solutions. Active listening, clear and concise articulation of thoughts and ideas, and the ability to empathize are all valuable communication skills that facilitate problem-solving.

Active listening involves fully engaging with the speaker, paying attention to both verbal and non-verbal cues, and seeking clarification when necessary. By actively listening, individuals can gain a deeper understanding of the problem at hand and the perspectives of others involved. This understanding is crucial for developing comprehensive and effective solutions.

Clear and concise articulation of thoughts and ideas is essential for effective problem-solving communication. By expressing oneself clearly, individuals can ensure that their ideas are understood by others. This clarity helps to avoid misunderstandings and promotes effective collaboration.

Empathy is a valuable communication skill that plays a significant role in problem-solving. By putting oneself in the shoes of others and understanding their emotions and perspectives, individuals can build trust and rapport. This empathetic connection fosters a supportive and collaborative environment where everyone feels valued and motivated to contribute to finding solutions.

In conclusion, problem-solving in the workplace requires a combination of essential skills such as analytical thinking, effective communication, collaboration, and adaptability. By honing these skills and fostering open communication channels, individuals can approach workplace problems with confidence and creativity, leading to practical and innovative solutions.

Real Scenarios of Workplace Problems

Now, let’s explore some real scenarios of workplace problems and delve into strategies for resolution. By examining these practical examples, individuals can develop a deeper understanding of how to approach and solve workplace problems.

Conflict Resolution in the Workplace

Imagine a scenario where two team members have conflicting ideas on how to approach a project. The disagreement becomes heated, leading to a tense work environment. To resolve this conflict, it is crucial to encourage open dialogue between the team members. Facilitating a calm and respectful conversation can help uncover underlying concerns and find common ground. Collaboration and compromise are key in reaching a resolution that satisfies all parties involved.

In this particular scenario, let’s dive deeper into the dynamics between the team members. One team member, let’s call her Sarah, strongly believes that a more conservative and traditional approach is necessary for the project’s success. On the other hand, her colleague, John, advocates for a more innovative and out-of-the-box strategy. The clash between their perspectives arises from their different backgrounds and experiences.

As the conflict escalates, it is essential for a neutral party, such as a team leader or a mediator, to step in and facilitate the conversation. This person should create a safe space for both Sarah and John to express their ideas and concerns without fear of judgment or retribution. By actively listening to each other, they can gain a better understanding of the underlying motivations behind their respective approaches.

During the conversation, it may become apparent that Sarah’s conservative approach stems from a fear of taking risks and a desire for stability. On the other hand, John’s innovative mindset is driven by a passion for pushing boundaries and finding creative solutions. Recognizing these underlying motivations can help foster empathy and create a foundation for collaboration.

As the dialogue progresses, Sarah and John can begin to identify areas of overlap and potential compromise. They may realize that while Sarah’s conservative approach provides stability, John’s innovative ideas can inject fresh perspectives into the project. By combining their strengths and finding a middle ground, they can develop a hybrid strategy that incorporates both stability and innovation.

Ultimately, conflict resolution in the workplace requires effective communication, active listening, empathy, and a willingness to find common ground. By addressing conflicts head-on and fostering a collaborative environment, teams can overcome challenges and achieve their goals.

Dealing with Workplace Stress and Burnout

Workplace stress and burnout can be debilitating for individuals and organizations alike. In this scenario, an employee is consistently overwhelmed by their workload and experiencing signs of burnout. To address this issue, organizations should promote a healthy work-life balance and provide resources to manage stress effectively. Encouraging employees to take breaks, providing access to mental health support, and fostering a supportive work culture are all practical solutions to alleviate workplace stress.

In this particular scenario, let’s imagine that the employee facing stress and burnout is named Alex. Alex has been working long hours, often sacrificing personal time and rest to meet tight deadlines and demanding expectations. As a result, Alex is experiencing physical and mental exhaustion, reduced productivity, and a sense of detachment from work.

Recognizing the signs of burnout, Alex’s organization takes proactive measures to address the issue. They understand that employee well-being is crucial for maintaining a healthy and productive workforce. To promote a healthy work-life balance, the organization encourages employees to take regular breaks and prioritize self-care. They emphasize the importance of disconnecting from work during non-working hours and encourage employees to engage in activities that promote relaxation and rejuvenation.

Additionally, the organization provides access to mental health support services, such as counseling or therapy sessions. They recognize that stress and burnout can have a significant impact on an individual’s mental well-being and offer resources to help employees manage their stress effectively. By destigmatizing mental health and providing confidential support, the organization creates an environment where employees feel comfortable seeking help when needed.

Furthermore, the organization fosters a supportive work culture by promoting open communication and empathy. They encourage managers and colleagues to check in with each other regularly, offering support and understanding. Team members are encouraged to collaborate and share the workload, ensuring that no one person is overwhelmed with excessive responsibilities.

By implementing these strategies, Alex’s organization aims to alleviate workplace stress and prevent burnout. They understand that a healthy and balanced workforce is more likely to be engaged, productive, and satisfied. Through a combination of promoting work-life balance, providing mental health support, and fostering a supportive work culture, organizations can effectively address workplace stress and create an environment conducive to employee well-being.

Practical Solutions to Workplace Problems

Now that we have explored real scenarios, let’s discuss practical solutions that organizations can implement to address workplace problems. By adopting proactive strategies and establishing effective policies, organizations can create a positive work environment conducive to problem-solving and productivity.

Implementing Effective Policies for Problem Resolution

Organizations should have clear and well-defined policies in place to address workplace problems. These policies should outline procedures for conflict resolution, channels for reporting problems, and accountability measures. By ensuring that employees are aware of these policies and have easy access to them, organizations can facilitate problem-solving and prevent issues from escalating.

Promoting a Positive Workplace Culture

A positive workplace culture is vital for problem-solving. By fostering an environment of respect, collaboration, and open communication, organizations can create a space where individuals feel empowered to address and solve problems. Encouraging teamwork, recognizing and appreciating employees’ contributions, and promoting a healthy work-life balance are all ways to cultivate a positive workplace culture.

The Role of Leadership in Problem Solving

Leadership plays a crucial role in facilitating effective problem-solving within organizations. Different leadership styles can impact how problems are approached and resolved.

Leadership Styles and Their Impact on Problem-Solving

Leaders who adopt an autocratic leadership style may make decisions independently, potentially leaving their team members feeling excluded and undervalued. On the other hand, leaders who adopt a democratic leadership style involve their team members in the problem-solving process, fostering a sense of ownership and empowerment. By encouraging employee participation, organizations can leverage the diverse perspectives and expertise of their workforce to find innovative solutions to workplace problems.

Encouraging Employee Participation in Problem Solving

To harness the collective problem-solving abilities of an organization, it is crucial to encourage employee participation. Leaders can create opportunities for employees to contribute their ideas and perspectives through brainstorming sessions, team meetings, and collaborative projects. By valuing employee input and involving them in decision-making processes, organizations can foster a culture of inclusivity and drive innovative problem-solving efforts.

In today’s dynamic work environment, workplace problems are unavoidable. However, by understanding common workplace problems, developing essential problem-solving skills, and implementing practical solutions, individuals and organizations can navigate these challenges effectively. By fostering a positive work culture, implementing effective policies, and encouraging employee participation, organizations can create an environment conducive to problem-solving and productivity. With proactive problem-solving strategies in place, organizations can thrive and overcome obstacles, ensuring long-term success and growth.

Related Stories

• May 23, 2024

Software for Company Culture

Edgar schein models on organizational culture, best culture consulting firms, what can we help you find.

• Open access
• Published: 05 February 2022

Work environment risk factors causing day-to-day stress in occupational settings: a systematic review

• Junoš Lukan 1 , 2   na1 ,
• Larissa Bolliger 3   na1 ,
• Nele S. Pauwels 4 , 5 ,
• Mitja Luštrek 1 , 2 ,
• Dirk De Bacquer 3 &
• Els Clays 3  

BMC Public Health volume  22 , Article number:  240 ( 2022 ) Cite this article

11k Accesses

19 Citations

13 Altmetric

Metrics details

While chronic workplace stress is known to be associated with health-related outcomes like mental and cardiovascular diseases, research about day-to-day occupational stress is limited. This systematic review includes studies assessing stress exposures as work environment risk factors and stress outcomes, measured via self-perceived questionnaires and physiological stress detection. These measures needed to be assessed repeatedly or continuously via Ecological Momentary Assessment (EMA) or similar methods carried out in real-world work environments, to be included in this review. The objective was to identify work environment risk factors causing day-to-day stress.

The search strategies were applied in seven databases resulting in 11833 records after deduplication, of which 41 studies were included in a qualitative synthesis. Associations were evaluated by correlational analyses.

The most commonly measured work environment risk factor was work intensity, while stress was most often framed as an affective response. Measures from these two dimensions were also most frequently correlated with each other and most of their correlation coefficients were statistically significant, making work intensity a major risk factor for day-to-day workplace stress.

Conclusions

This review reveals a diversity in methodological approaches in data collection and data analysis. More studies combining self-perceived stress exposures and outcomes with physiological measures are warranted.

Peer Review reports

Over the past decades, substantial attention has been directed to research focusing on chronic exposure to stressors in occupational settings and the adverse impact of stress on chronic disease outcomes [ 1 , 2 ]. Psychosocial risk factors have been the last ones to be considered, but are now widely accepted to be as important as other factors like biological or chemical risks [ 3 ]. The influence on mental and cardiovascular health in particular has been confirmed and explained through frameworks at the forefront of stress research, such as the Job Demand-Control-Support model [ 4 – 6 ], the Effort-Reward Imbalance model [ 7 ], and the Job Demands-Resources model [ 8 ].

Evidence of chronic stressors influencing workers’ health and well-being is accumulating, and several systematic reviews and meta-analyses with a focus on studies investigating such relations are available. There is evidence that psychosocial stress is associated with cardiovascular morbidity and mortality [ 1 ], musculoskeletal disorders [ 9 ], mental health problems, such as depression and anxiety [ 2 ], and health risk behaviour, such as cigarette smoking, alcohol consumption, and overweight [ 10 ]. The most commonly studied workplace risk factors include job demand and job control (such as in the Job Demand-Control-Support model) [ 1 ], but several others have been studied, such as job insecurity, procedural (in)justice, workplace conflict or bullying [ 2 ], and workplace violence [ 11 ]. A lot of these risk factors are structural and as such measured at a single time point. On the other hand, a preliminary literature search revealed little information about how these structural risk factors manifest in daily work life and what the specific (if any) work environment risk factors causing day-to-day (i.e., non-chronic) stress are.

Understanding how day-to-day work situations lead to the experience of stress is important for several reasons. Stress measurement often relies on self-reports, which are subject to memory bias [ 12 ] and there are indications that chronic assessments are not simply the sum of multiple moment-to-moment ratings [ 13 ]. When stress is measured several times a day, these repeated measurements can instead capture stressful situations during or soon after they occur and the risk of memory bias is reduced. This relationship would also be important to understand since, in order to test hypotheses about how particular stressors lead to health outcomes, temporal relationships need to be explored [ 14 , 15 ]. Finally, the question of how to design stress management interventions is still open [ 16 ]. Broad constructs such as work demands and decision latitude are relatively stable aspects of a job and translating the findings from chronic stress research into stress management strategies applicable in every-day working life would require a better understanding of their day-to-day manifestations. To the best of our knowledge, no systematic review with a focus on day-to-day stress and related work environment risk factors has been performed so far.

We were interested in how various situations at work translate to an experience of stress and which situations are the most important for this experience. We named this relationship ‘day-to-day stress’, which differs from chronic stress in that it can entail daily situations in addition to structural characteristics of the workplace. Day-to-day stressors do not necessarily have long-lasting consequences but do influence the perception of work environment and elicit some kind of response from a person. We do not presume any conceptual difference between day-to-day stress and chronic stress or stressors, but rather differentiate them based on the methodology of stress measurement. As such, we did not restrain our selection of studies to review to any particular definition of (day-to-day or chronic) stress. To understand how exposures to work environment risk factors are related to daily variations of stress, we instead focused on the studies that measure these repeatedly with self-reports or continuously using physiological measurements and in real-world occupational settings.

The objective of this systematic review was to explore the onset of day-to-day stress by summarising evidence on potential day-to-day work environment risk factors (stressors), which have an immediate effect on self-perceived stress levels or physiological stress responses, and which may or may not cause chronic stress.

Materials and methods

We conducted this systematic review by following the Cochrane Handbook for Systematic Reviews [ 17 ] and the PRISMA 2009 Checklist [ 18 ] and registered it on PROSPERO under the ID: CRD42018105355 [ 19 ].

Eligibility criteria

We first settled on working definitions of the concepts of interest. Throughout this systematic review, we use the term work environment risk factors for stressors, which we defined more specifically as causes or predictors of stress, potentially occurring on a day-to-day basis within occupational settings . Furthermore, we defined self-perceived stress outcomes as consequences of such work environment risk factors which were measured with self-perception-based scales, questionnaires, or surveys .

As the main eligibility criterion, the studies needed to include work environment risk factors and either self-perceived stress outcomes or physiological stress detection or both. We looked for any (objective) descriptions of work situations and their consequences in terms of stress. We did not constrain the outcomes to any particular definition of stress as long as the authors of the original studies framed them as somehow related to the phenomenon of psychosocial stress.

Both, risk factors and outcomes, were required to be measured repeatedly, so methods capable of producing repeated or continuous measurements had to be used. One such method is Ecological Momentary Assessment [ 20, EMA ], which is a research method allowing participants to report their experiences in real-time and in real-world settings, in which data are collected repeatedly (i.e., more than two measurement points) over time and often through a digital platform such as a smartphone application [ 21 ]. Moreover, the phenomenon of interest was day-to-day stress, so studies focusing on chronic stress only were not considered.

We focused on studies set in a real-world working environment, and either the workplace setting or the occupational profile needed to be extractable. Healthy full-time and part-time workers of working age were chosen as the population of interest. Observational quantitative and mixed-methods studies (where only the quantitative part of the latter was of relevance) including at least two measurement points were included.

Strategies for database searching

We devised a search strategy according to the eligibility criteria described in the previous subsection. The main blocks of the search strategy require that 1) a study deals with stress (or synonymous concepts), which should furthermore be 2) day-to-day or episodic (or similar). We also set 3) the requirements for methods, which could be either ecological momentary assessments or other methods capable of producing repeated measures, and 4) that the setting of interest is the work setting. The full search strategies with indexing terms and free text words for all the databases can be found in Supplementary Figs. 1 to 7 [see Additional file  3 ].

We evaluated the search strategy with the PRESS checklist [ 22 ] before we applied it in the following databases: PubMed, Embase, Web of Science, Scopus, CINAHL, ERIC, and PsycArticles. We first carried out a search on 31 August 2018 and later did an update of the initial search on 3 July 2020. The only limitation we used at the time of the searches was “English language”.

Study selection process

The studies were selected based on the process described in the PRISMA statement [ 18 ]. After merging all the results and manually deduplicating them, we screened the titles and abstracts, and evaluated the full text of the remaining articles for eligibility.

Both title and abstract screening and full-text evaluation were done independently by two authors using the Rayyan software [ 23 ]. Conflicts after both screening phases were discussed until consensus was reached. We followed the same procedure when we updated our search.

Quality assessment strategy

The quality assessment in systematic reviews includes two phases: 1) evaluation of the quality at study level (each study separately) and 2) evaluation of the body of evidence (all included studies together) to give a thorough quality estimate of the evidence at hand.

For the quality assessment at study level, we used the QualSyst tool for quantitative research [ 24 ]. This tool offers ‘N/A’ grades for criteria that are inapplicable. Out of the 14 criteria in the tool, we omitted three—random allocation to treatment group (1) and blinding of investigators (2) and subjects (3)—since they are only applicable to intervention studies.

Consequently, each study was assessed according to 11 criteria (e.g., question or objective sufficiently described) on a three point scale. From these, the summary score is calculated, which is a number between 0 and 1, where 1 denotes complete satisfaction of all applicable criteria. This procedure was done independently by two authors and any conflicts were discussed until consensus was reached.

The quality assessment of the body of evidence was evaluated using the GRADE approach [ 25 ], including five criteria for downgrading (risk of bias, inconsistency, indirectness, imprecision, and publication bias) and two criteria for upgrading (large magnitude of effect and dose-response gradient) before an overall score was given.

Study selection

We applied the search strategy as discussed in Strategies for database searching and retrieved 15362 records. We removed duplicates first and then eliminated irrelevant studies by first screening their titles and abstracts and then considering the full text of a selected subset.

We followed the same procedure for the second search, in which we retrieved 18996 records. We excluded all the records already found in the first search as well as some duplicates from different databases, then repeated the same screening procedure. The whole process is illustrated in Fig.  1 .

Study selection presented with the PRISMA flow diagram [ 18 ]. The n 1 and n 2 refer to the first search we performed on 31 August 2018 and to the update search from 3 July 2020, respectively. Their sum is reported as n

As per recommendations in Moher et al. [ 18 ], we noted the exclusion reasons for all the publications we reviewed in full. 149 studies were excluded based on the main eligibility criterion: either the work environment risk factors or stress outcomes were missing, or they were not measured repeatedly. In 35 cases, neither the workplace setting nor the occupational profile was mentioned. In 26 cases, no work environment risk factor could be extracted. 19 publications turned out to be abstracts only. Four further studies were excluded because not all participants were described as healthy. Three studies were not accessible: two PhD theses [ 26 , 27 ], of which authors were contacted, but we got no response, and a report [ 28 ], the author of which is deceased. Two additional duplicates were found, one study only included observational methods (i.e., no self-reports), and one study was available in Korean only.

After this, we were left with 41 studies (34 from the first and 7 from the second search), which were included in the final review for a qualitative synthesis.

Study characteristics

Table  1 lists all the studies included in the final review and gives their most important characteristics. In addition to the number of subjects included ( N ) and the work setting of the study, it includes the study duration and assessment frequency. Added are the quality rating of the study and information about whether data analysis included multilevel analysis.

The studies included from N =14 to N =304 participants, with the median N median =83. The study duration also varied, usually together with the assessment frequency. Thus, some studies only looked at one day, but measured some parameters continuously (e.g., blood pressure in study ID 32), whereas others only sampled once a day for 60 days (study ID 26) or even once a week, but lasted for 182 days (study ID 37).

The average quality of the studies according to QualSyst was M QualSyst =0.86. Specifically, 10 out of the 41 studies were rated at the highest quality level, 28 studies were rated between 0.99 and 0.51, and 3 studies were rated as 0.50 or below. Points were most often deducted because recruitment methods were not clearly reported (‘Method of subject selection’ criterion) or when the authors only reported significance of the main results, but no estimate of variance, such as confidence intervals or standard errors (‘Some estimate of variance’ criterion).

The GRADE approach rates randomised trials as ‘high quality’, observational studies as ‘low quality’, and any other evidence as ‘very low quality’. Since all included studies of this review are observational studies, the quality of the body of evidence was consequently rated as low. Additionally, according to the criteria for downgrading or upgrading mentioned in Quality assessment strategy, no downgrading was required and no upgrading was feasible for our body of evidence, so ‘low’ was also the final score.

Work environment risk factors, self-perceived stress outcomes, and physiological measurements

We identified work environment risk factors, self-perceived stress outcomes, and physiological measurements measured in each study. We extracted all constructs that were measured more than twice (i.e., repeatedly or continuously), while one-time measurements (e.g., during initial baseline screening) were not considered. Since concepts like stress are defined in different ways across the studies, we also looked at the measurement instruments. The work environment risk factors and stress outcomes extracted in this way are published as Supplementary Tables 1 and 2 [see Additional file  1 ].

We classified these into broader categories, which were based on established frameworks. For work environment risk factors, we used the 6th European Working Conditions Survey classification of job quality indices [ 29 ] as the basis. These are objective features of a job which have been proven to have an impact on the health and well-being of workers. They are also only weakly correlated, so that they function as independent descriptions of job quality. Hence, these served well to get a higher level overview of work environment risk factors.

Similarly, stress outcomes were classified according to the stress model described by Ice and James [ 30 ]. They describe stress as a combination of affective, behavioural, and physiological responses, which impact mental health and can have physical health outcomes. These responses are consequences of a person’s appraisal of stressors (stimuli). While classifying the studies in our review, we also identified the need for two additional consequences of stress. First, stress can also affect a person’s cognition, not only at the stage of appraisal, but as its consequence; forgetting of intentions and cognitive failure are examples of this outcome. Second, we determined motivational responses, specifically work engagement, to be sufficiently distinct from affective responses to deserve its own category. This outcome involves not only emotions, but goal-directed behaviour closely related to affective responses.

The frequencies of different measures of work environment risk factors and stress outcomes are summarised in Table  2 . The risk factor most often measured in the included studies was work intensity, defined for example as time pressure or job demand. This was followed by social environment risk factors (such as co-worker and supervisor support) and ‘various’ factors (such as the number or type of stressful situations). On the other end, affective responses were by far the most often measured outcomes, especially as assessed by the Positive and Negative Affect Scale [ 31, PANAS ]. Some studies looked at physiological responses to stress as well, while other outcomes were rarely considered.

It is important to note that while all studies included at least one work environment risk factor and one stress outcome as a consequence of the design of our eligibility criteria, each study could measure more than one risk factor or outcome. This means that the total number of measurements is larger than the number of included studies.

Correlation coefficients

The variables of work environment risk factors, self-perceived stress outcomes, and physiological measurements were considered in the relation structure widely known as ‘exposure/predictor–outcome’ or ‘independent variable–dependent variable’.

As shown in Table  1 , 28 studies analysed their data by using multilevel models, while others resorted to other analyses, such as t -tests, correlational tables, and descriptive analysis. Since multilevel models control for dependencies between predictors (usually work environment risk factors) they give a more complete insight into relationships between all modelled variables. But for these studies direct comparison of coefficient estimates would not be appropriate since the models’ structure varied from study to study.

To produce a meaningful comparison, we therefore decided to focus on correlation coefficients in our synthesis. As these were available in the 28 studies as well as some others, they enabled us to compare more directly the results of more studies. It needs to be noted, however, that only bivariate relationships are reflected in these analyses, while more complex relationships between variables are omitted.

Accordingly, correlation coefficients between work environment risk factors (exposures) and self-perceived stress outcomes (outcomes), and work environment risk factors (exposures) and physiological measurements (outcomes) are available in Supplementary Table B [see Additional file  2 ].

For studies that did multilevel analysis, both within-person level and between-persons level results were extracted. But for other studies only a part of the results of interest were extractable. For example, only the results of between-persons level were reported in the study ID 37 or correlation coefficients were not reported for all variables included in the study ID 33 (e.g., no correlation coefficients between nursing tasks and heart rate).

Figure  2 shows the number of statistically significant and nonsignificant correlation coefficients for each pair of work environment risk factor and stress outcome. In this figure, we focused on within-subject correlations only as these were the ones that can capture day-to-day variation of stressors and responses.

The frequency of significant and nonsignificant correlation coefficients between categories of work environment risk factors and stress outcomes

As mentioned in Work environment risk factors, self-perceived stress outcomes, and physiological measurements (see Table  2 ), the most commonly measured risk factor and outcome were work intensity and affective response, respectively. Correspondingly, their relationship in the form of correlation was also the most commonly reported one. Note that the number of correlation coefficients does not directly follow from the number of studies studying a certain relationship, since Table  2 shows measures of all studies, regardless of whether they did multilevel analysis and whether within-subject correlations could be extracted. Additionally, a study looking at several measures of work environment risk factors or stress outcomes could report a correlation within each pair, so that the number of correlations can be even higher than the number of different measures.

Furthermore, most of the correlations between work intensity and affective response were statistically significant. Affective response was also commonly correlated with social environment and this relationship was more often statistically significant than not.

On the other hand commuting from and to the workplace was not significantly correlated with affective responses most of the time. Interestingly, the second most common type of outcomes, physiological responses, were mostly not significantly correlated with any of the risk factors.

In general, the correlations reported in the included studies were more often significant than not (110 significant vs. 80 nonsignificant correlations), but they were typically low. Only two of all the within-subject correlations exceeded 0.5 in their absolute magnitude.

Among the studies that included within-subject correlation coefficients in their results, the most commonly measured work environment risk factor was work intensity, and it was correlated most often with affective response. The high frequency can be to some extent explained by our search strategy. Both stress and demand were included as search terms and we categorised stress(fulness) as an affective response and work demand as work intensity. But since definitions of stress are diverse and often include concepts such as negative affect, our review captured many other stress responses as well as work environment risk factors (stressors).

Work intensity is often measured in epidemiological studies about health consequences of chronic stress, such as coronary heart disease [ 32 ] and depression [ 33 ]. This is reflected in the high number of studies that included it as the stressor of interest. However, since work intensity is most often paired with the control dimension to describe job strain, such as in the Job Demand-Control-Support model, the relative rarity of correlations between skills and discretion and stress outcomes is surprising. It seems that the control dimension of this model is relatively less well researched. However, it is still unclear whether demands and control are related to stress and its health consequences independently, or whether their interaction in the form of job strain is more important [ 34 ]. To settle this question, it would be crucial to explore the role of the control dimension more carefully.

The social environment (e.g., co-worker and supervisor support) has also been correlated with affective and other responses in the included studies. This should be beneficial for gathering more evidence for the relationship of the support dimension with health outcomes, for which only limited evidence has been available in existing reviews [ 33 ]. A similar statement could be made for the prospects category, which has found its place in the Effort-Reward Imbalance model [ 7 ].

Another surprising result was that physiological responses were generally not statistically significantly correlated with any of the work environment risk factors, despite the fact that stress is often predicted from physiological parameters [ 35 ]. This can be explained either with the studies’ analyses choices or complexity of their models. Some of the studies that measured physiological responses did not perform multilevel analysis, but simpler statistical analyses such as t -tests and analysis of variance (studies ID 17, 31, and 32). Others did perform regression analysis or multilevel analysis, but did not report within-subject correlation coefficients for physiological parameters (studies ID 14, 33, and 38). Only three studies reported within-subject correlation coefficients and were included in Fig.  2 , but the relationships between work environment risk factors were usually too complex to be captured by these simple coefficients. For example, co-worker support mediated the daily trajectory of some parameters of heart rate variability [ 36, study ID 8 ] and the relationship between work-to-family conflict and cortisol slope from dinner to bedtime was mediated by supervisor support [ 37, study ID 34 ].

This relative rarity of studies dealing with physiological aspects of stress compared to the field of chronic stress research can be put into a broader context with the help of the conceptual framework proposed by Martikainen et al. [ 38 ] and adapted by Rugulies [ 39 ]. This framework describes the connection between different levels of work environment and health outcomes. It starts with the broadest, (i) macro-level, economic, social, and political structures, and continues through (ii) meso-level workplace structures, (iii) meso-level psychosocial working conditions, to (iv) individual-level experience and cognitive and emotional processes. The latter elicit either (v) psycho-physiological changes or (vi) health-related behaviours, which in turn impact (vii) workers’ health and illness.

It is well established that meso-level workplace structures (ii), such as job insecurity [ 40 ], and meso-level psychosocial working conditions (iii), such as job strain [ 41 ], are related to the risk of diseases and disorders (vii). This has been observed both in immediate physiological responses to stress as well as sustained physiological and behaviour changes. For example, longer duration of work-related stress results in increased rise in morning cortisol level and reduced heart rate variability, and acute stress response involves elevated blood pressure [ 42 ]. On the other hand, job strain has been found to be linked to hypertension, atherosclerosis, and smoking intensity [ 43 ].

Some of the mechanisms of how this happens are also understood. First, pathophysiological effects of stress (v) have been detailed [ 44 ], such as neuroendocrine mechanisms of elevated cortisol and catecholamine (epinephrine) levels as well as inhibited anabolism. Second, stress is related to altered behaviour (vi), such as smoking and alcohol consumption [ 10 ], where this is seen as a second ‘indirect’ pathway of the link between stress and stress-related diseases.

A causal relationship between stress and cardiovascular diseases has still not been established, however, and the pathological mechanisms of chronic and acute stress may differ [ 41 ]. This evidence gap might be owed to a poor understanding of how psychological processes (iv) are involved in this pathway. Steptoe and Kivimäki [ 41 ] explicitly limit the focus of their review to ‘exposure to external stressors, rather than on psychological and biological factors affecting vulnerability to adversity’ (p. 360). And while they mention that ‘one reason for the weak relationship between physiological stress responses and future disease is that mental stress testing measures a propensity to high- or low-stress responsivity’ [ 42, p. 341 ], they only admit this role to biological stress reactivity.

But it might be precisely the psychosocial factors, which Martikainen et al. [ 38 ] see as ‘mediating the effects of social structural factors on individual health outcomes’ (p. 1091), that is, the pathway from (ii) and (iii) through (iv) to (vii), where the key to better understanding this causal relationship lies. It might be through perceptions and psychological processes at the individual level that these macro- and meso-level social processes lead to direct psychobiological processes or modified health-related behaviours and lifestyles and, in turn, influence health [ 38 ].

Some of the studies included in our review deal with the relationships in this pathway and more systematic research is needed. This also has implications for planning interventions better, since effects of stress and depression management techniques on cardiac outcomes are still uncertain [ 41 ]. While it is clear that occupational stress increases risk for coronary heart disease [ 45 ], more research is needed on how to lower this risk. For example, it is possible to modify work schedule to ameliorate exposure to job strain, but only a randomized clinical trial which would test this intervention could truly assess its effect [ 43 ].

Strengths and limitations

As illustrated, different methods of data collection (e.g., time span, number of measurement points) and a wide range of data analysis approaches (e.g., descriptive results, multilevel analysis) were used across the included studies. This heterogeneity led to a challenging data synthesis and study comparison, and restricted us to a qualitative (narrative) synthesis, rather than a quantitative synthesis in the form of a meta-analysis.

To enable a meaningful comparison of the studies’ results, we needed to introduce a rigorous approach to summarising them. First, we developed a working definition of the concepts explored in our research question. Despite widely acknowledged psychosocial stress models [ 4 , 46 ], definitions of psychosocial stress and job stressors are not used consistently in the literature. This diversity in terminology of ‘stressor’ and ‘stress’ was apparent during several steps, such as during the construction of the search strategies and during data extraction. By framing these phenomena—for the purpose of this systematic review—as ‘work environment risk factors’ and ‘self-perceived stress outcomes’, we attempted to harmonize these differences in terminology. To be able to study relationships between stressors and stress, we classified measured variables into one of these two categories according to our working definitions (see Background). This allowed us to compare different studies’ results.

As mentioned, we disregarded the original studies’ framing of independent and dependent variables and instead classified them according to our own criteria. While this enabled us to look at the studies from the point of view of our study question, it introduced the risk of misrepresenting the original findings.

This concern was alleviated by limiting our data extraction of study results to correlation coefficients, which helped us increase study comparability at the same time. The advantage of considering only correlational analyses is that the Pearson correlation coefficient is a symmetric statistic. This allowed us to sidestep the original authors’ hypotheses and models and frame their (partial) results in our work environment risk factors and stress outcomes research question. This had the effect of including studies from different fields and getting an overview of these relationships, which was as broad as possible.

On the other hand, considering only correlational analysis led to an incomplete representation of results of several included studies. This is especially true of the studies performing more extensive analyses, since correlational analysis was merely an intermediate step before final conclusions based on multilevel analysis or analyses focusing on moderating or mediating effects. This has already been illustrated with the case of physiological responses. With such a diverse set of predictors and outcomes, however, comparing the results of these more complex models proved to be problematic, since it is impossible to compare specific effects without considering the full model.

Another consideration is the focus on statistical significance of correlations. While a fixation on statistical significance has been widely criticised [ 47 ], it served as a good first step in comparisons of heterogeneous studies. Effect size examination made little sense as all the reported within-subject correlation coefficients were low (i.e., r <0.5). Noting the above points about simplification with regard to results reporting, the raw number of statistically significant and nonsignificant correlations should still serve as a first overview of the field.

While the field of chronic stress in the workplace is very well established, how daily work situations translate to day-to-day experience of stress and later to chronic conditions seems to be less understood.

We identified several high-quality studies dealing with this topic. The models they employ and the analytical methods they use are well developed. However, their research questions are particular and usually involve a somewhat narrow definition of stress. Instead of approaching stress outcomes as manifestations of a multifaceted response, only some types of responses are considered, most often affective responses. In our review, none of the studies approached this topic from a full-fledged stress model that would incorporate all the relevant aspects of the response to stressors.

Such a study would first require a combination of various data collection methods, such as ecological momentary assessment and continuous physiological monitoring. It would also call for a more complex analysis approach, such as combining multilevel modelling with structural equation modelling or other probabilistic graphical models. Finally, it would need to deal with the problem in the context of a well-established model of stress that lends itself well to such modelling.

Availability of data and materials

All data generated or analysed during this study are included in this published article and its Additional Files. Additional evaluations done by two reviewers independently are available from the corresponding author on reasonable request.

Abbreviations

Ecological momentary assessment

Positive affect negative affect scale

Fishta A, Backé E-M. Psychosocial stress at work and cardiovascular diseases: An overview of systematic reviews. Int Arch Occup Environ Health. 2015; 88(8):997–1014. doi:10.1007/s00420-015-1019-0.

Article   PubMed   PubMed Central   Google Scholar  

Harvey SB, Modini M, Joyce S, Milligan-Saville JS, Tan L, Mykletun A, Bryant RA, Christensen H, Mitchell PB. Can work make you mentally ill? a systematic meta-review of work-related risk factors for common mental health problems. Occup Environ Med. 2017; 74(4):301–10. doi:10.1136/oemed-2016-104015.

Article   Google Scholar  

Magnavita N, Chirico F. New and emerging risk factors in occupational health. Appl Sci. 2020; 10(24):8906. doi:10.3390/app10248906.

Article   CAS   Google Scholar  

Johnson JV, Hall EM. Job strain, work place social support, and cardiovascular disease: a cross-sectional study of a random sample of the Swedish working population. Am J Public Health. 1988; 78(10):1336–42. doi:10.2105/ajph.78.10.1336.

Article   CAS   PubMed   PubMed Central   Google Scholar  

Johnson JV, Hall EM, Theorell T. Combined effects of job strain and social isolation on cardiovascular disease morbidity and mortality in a random sample of the Swedish male working population. Scand J Work Environ Health. 1989; 15(4):271–79. doi:10.5271/sjweh.1852.

Article   CAS   PubMed   Google Scholar  

Karasek R, Theorell T. Healthy Work: Stress, Productivity and the Reconstruction of Working Life. New York: Basic books; 1990.

Google Scholar  

Siegrist J. Adverse health effects of high-effort/low-reward conditions. J Occup Health Psychol. 1996; 1(1):27–41. doi:10.1037/1076-8998.1.1.27.

Demerouti E, Bakker AB, Nachreiner F, Schaufeli WB. The job demands-resources model of burnout. J Appl Psychol. 2001; 86(3):499–512. doi:10.1037/0021-9010.86.3.499.

Hauke A, Flintrop J, Brun E, Rugulies R. The impact of work-related psychosocial stressors on the onset of musculoskeletal disorders in specific body regions: A review and meta-analysis of 54 longitudinal studies. Work Stress. 2011; 25(3):243–56. doi:10.1080/02678373.2011.614069.

Siegrist J, Rödel A. Work stress and health risk behavior. Scand J Work Environ Health. 2006; 32(6):473–81. doi:10.5271/sjweh.1052.

Article   PubMed   Google Scholar  

Magnavita N, Stasio ED, Capitanelli I, Lops EA, Chirico F, Garbarino S. Sleep problems and workplace violence: A systematic review and meta-analysis. Front Neurosci. 2019; 13(997):1–18. doi:10.3389/fnins.2019.00997.

Sato H, Kawahara J-i. Selective bias in retrospective self-reports of negative mood states. Anxiety Stress Coping. 2011; 24(4):359–67. doi:10.1080/10615806.2010.543132.

Bell C, Johnston D, Allan J, Johnston M, Pollard B. Repeated real time measures of work stress in nurses may not relate to questionnaire accounts. Psychol Health. 2013; 28(sup1 (EHPS 2013 Abstracts)):65–66. doi:10.1080/08870446.2013.810851.

Shiffman S, Stone AA. Introduction to the special section: Ecological momentary assessment in health psychology. Health Psychol. 1998; 17(1):3–5. doi:10.1037/h0092706.

Smyth JM, Stone AA. Ecological momentary assessment research in behavioral medicine. J Happiness Stud. 2003; 4(1):35–52. doi:10.1023/a:1023657221954.

Hurrell JJ. Organizational stress intervention In: Barling J., Kelloway E. K., Frone M. R., editors. Handbook of Work Stress. SAGE Publications, Inc.: 2005. p. 623–46. Chap. 27. http://dx.doi.org/10.4135/9781412975995.n27 .

Cochrane. Cochrane Handbook for Systematic Reviews of Interventions, 6.1 edn.: Cochrane; 2020.

Moher D, Liberati A, Tetzlaff J, Altman DG. Preferred reporting items for systematic reviews and meta-analyses: The PRISMA statement. PLoS Med. 2009; 6(7):1000097. doi:10.1371/journal.pmed.1000097.

Bolliger L, Lukan J, Pauwels NS, Luštrek M, De Bacquer D, Clays E. Work environment risk factors causing day-to-day stress in occupational settings: A systematic review. PROSPERO 2018 CRD42018105355. 2018. https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42018105355 .

Csikszentmihalyi M, Larson R, Prescott S. The ecology of adolescent activity and experience. J Youth Adolesc. 1977; 6(3):281–94. doi:10.1007/bf02138940.

Gibbons CJ. Turning the page on pen-and-paper questionnaires: Combining ecological momentary assessment and computer adaptive testing to transform psychological assessment in the 21st century. Front Psychol. 2017; 7. http://dx.doi.org/10.3389/fpsyg.2016.01933.

McGowan J, Sampson M, Salzwedel DM, Cogo E, Foerster V, Lefebvre C. PRESS – Peer Review of Electronic Search Strategies: 2015 Guideline Explanation and Elaboration (PRESS E&E). Ottawa: Elsevier BV; 2016.

Ouzzani M, Hammady H, Fedorowicz Z, Elmagarmid A. Rayyan—a web and mobile app for systematic reviews. Syst Rev. 2016; 5(1). http://dx.doi.org/10.1186/s13643-016-0384-4.

Kmet L, Lee R, Cook L. Standard Quality Assessment Criteria for Evaluating Primary Research Papers from a Variety of Fields. Edmonton, Alta: Institute of Health Economics; 2004.

Schünemann H, BroŻek J, Guyatt G, Oxman A. Handbook for Grading the Quality of Evidence and the Strength of Recommendations Using the GRADE Approach. London: Cochrane; 2013. Cochrane. Retrieved from https://training.cochrane.org/resource/grade-handbook .

Heeren JK. Stress, hardiness, and burnout among psychiatric nurses working in hospital settings. Phd thesis: University of Virginia; 1991.

Northrop LME. Stress, social support, and burnout in nursing home staff. Phd thesis: West Virginia University; 1996.

Johnstone M. Time and tasks: Teacher workload and stress. Research Report ED368700. 1993. Spotlights 44.

Eurofound. Sixth European Working Conditions Survey – Overview Report (2017 Update). Luxembourg: Publications Office of the European Union; 2017. doi:10.2806/422172.

Ice GH, James GD. Conducting a field study of stress In: Ice G. H., James G. D., editors. Measuring Stress in Humans. Cambridge: Cambridge University Press: 2006. p. 3–24. Chap. 1.

Chapter   Google Scholar  

Watson D, Clark LA, Tellegen A. Development and validation of brief measures of positive and negative affect. J Pers Soc Psychol. 1988; 54(6):1063–70. doi:10.1037/0022-3514.54.6.1063.

Pejtersen JH, Burr H, Hannerz H, Fishta A, Eller NH. Update on work-related psychosocial factors and the development of ischemic heart disease. Cardiol Rev. 2015; 23(2):94–98. doi:10.1097/crd.0000000000000033.

Theorell T, Hammarström A, Aronsson G, Bendz LT, Grape T, Hogstedt C, Marteinsdottir I, Skoog I, Hall C. A systematic review including meta-analysis of work environment and depressive symptoms. BMC Public Health. 2015; 15(738). http://dx.doi.org/10.1186/s12889-015-1954-4.

Burr H, Formazin M, Pohrt A. Methodological and conceptual issues regarding occupational psychosocial coronary heart disease epidemiology. Scand J Work Environ Health. 2016; 42(3):251–55. doi:10.5271/sjweh.3557.

PubMed   Google Scholar  

Alberdi A, Aztiria A, Basarab A. Towards an automatic early stress recognition system for office environments based on multimodal measurements. J Biomed Inform. 2016; 59:49–75. doi:10.1016/j.jbi.2015.11.007.

Baethge A, Vahle-Hinz T, Rigotti T. Coworker support and its relationship to allostasis during a workday: A diary study on trajectories of heart rate variability during work. J Appl Psychol. 2020; 105(5):506–26. doi:10.1037/apl0000445.

Almeida DM, Davis KD, Lee S, Lawson KM, Walter KN, Moen P. Supervisor support buffers daily psychological and physiological reactivity to work-to-family conflict. J Marriage Fam. 2016; 78(1):165–79. doi:10.1111/jomf.12252.

Martikainen P, Bartley M, Lahelma E. Psychosocial determinants of health in social epidemiology. Int J Epidemiol. 2002; 31(6):1091–93. doi:10.1093/ije/31.6.1091.

Rugulies R. What is a psychosocial work environment?. Scand J Work Environ Health. 2019; 45(1):1–6. doi:10.5271/sjweh.3792.

Kim TJ, von dem Knesebeck O. Is an insecure job better for health than having no job at all? a systematic review of studies investigating the health-related risks of both job insecurity and unemployment. BMC Public Health. 2015; 15(1). http://dx.doi.org/10.1186/s12889-015-2313-1.

Steptoe A, Kivimäki M. Stress and cardiovascular disease. Nat Rev Cardiol. 2012; 9(6):360–70. doi:10.1038/nrcardio.2012.45.

Steptoe A, Kivimäki M. Stress and cardiovascular disease: An update on current knowledge. Annu Rev Public Health. 2013; 34(1):337–54. doi:10.1146/annurev-publhealth-031912-114452.

Belkic K, Landsbergis PA, Schnall PL, Baker D. Is job strain a major source of cardiovascular disease risk?Scand J Work Environ Health. 2004; 30(2):85–128. doi:10.5271/sjweh.769.

Kivimäki M, Steptoe A. Effects of stress on the development and progression of cardiovascular disease. Nat Rev Cardiol. 2018; 15(4):215–29. doi:10.1038/nrcardio.2017.189.

Kivimäki M, Virtanen M, Elovainio M, Kouvonen A, Väänänen A, Vahtera J. Work stress in the etiology of coronary heart disease—a meta-analysis. Scand J Work Environ Health. 2006; 32(6):431–42. doi:10.5271/sjweh.1049.

Siegrist J, Li J. Associations of extrinsic and intrinsic components of work stress with health: A systematic review of evidence on the effort-reward imbalance model. Int J Environ Res Public Health. 2016; 13(4):432. doi:10.3390/ijerph13040432.

Wasserstein RL, Lazar NA. The ASA statement on p-values: Context, process, and purpose. Amer Statist. 2016; 70(2):129–33. doi:10.1080/00031305.2016.1154108.

Louch G, O’Hara J, Gardner P, O’Connor DB. A daily diary approach to the examination of chronic stress, daily hassles and safety perceptions in hospital nursing. Int J Behav Med. 2017; 24(6):946–56. doi:10.1007/s12529-017-9655-2.

Beckers DGJ, van Hooff MLM, van der Linden D, Kompier MAJ, Taris TW, Geurts SAE. A diary study to open up the black box of overtime work among university faculty members. Scand J Work Environ Health. 2008; 34(3):213–23. doi:10.5271/sjweh.1226.

Rutledge T, Stucky E, Dollarhide A, Shively M, Jain S, Wolfson T, Weinger MB, Dresselhaus T. A real-time assessment of work stress in physicians and nurses. Health Psychol. 2009; 28(2):194–200. doi:10.1037/a0013145.

Ilies R, Johnson MD, Judge TA, Keeney J. A within-individual study of interpersonal conflict as a work stressor: Dispositional and situational moderators. J Organ Behav. 2011; 32(1):44–64. doi:10.1002/job.677. First published: 22 December 2010.

Yeh Y-JY, Ma T-N, Pan S-Y, Chuang P-J, Jhuang Y-H. Assessing potential effects of daily cross-domain usage of information and communication technologies. J Soc Psychol. 2019; 160(4):465–78. doi:10.1080/00224545.2019.1680943.

Zhou L, Wang M, Chang C-H, Liu S, Zhan Y, Shi J. Commuting stress process and self-regulation at work: Moderating roles of daily task significance, family interference with work, and commuting means efficacy. Pers Psychol. 2017; 70(4):891–922. doi:10.1111/peps.12219.

Buunk BP, Verhoeven K. Companionship and support at work: A microanalysis of the stress-reducing features of social interaction. Basic Appl Soc Psych. 1991; 12(3):243–58. http://dx.doi.org/10.1207/s15324834basp1203_1.

Dudenhöffer S, Dormann C. Customer-related social stressors and service providers’ affective reactions. J Organ Behav. 2012; 34(4):520–39. doi:10.1002/job.1826.

Rodrigues S, Kaiseler M, Queirós C, Basto-Pereira M. Daily stress and coping among emergency response officers: a case study. Int J Emerg Serv. 2017; 6(2):122–33. doi:10.1108/ijes-10-2016-0019.

Beattie L, Griffin B. Day-level fluctuations in stress and engagement in response to workplace incivility: A diary study. Work Stress. 2014:1–19. doi:10.1080/02678373.2014.898712.

Diebig M, Bormann KC, Rowold J. Day-level transformational leadership and followers’ daily level of stress: A moderated mediation model of team cooperation, role conflict, and type of communication. Eur J Work Organ Psy. 2017; 26(2):234–49. doi:10.1080/1359432x.2016.1250741.

Webster JR, Adams GA, Maranto CL, Beehr TA. “dirty” workplace politics and well-being. Psychol Women Quart. 2018; 42(3):361–77. doi:10.1177/0361684318769909.

Kamarck TW, Shiffman SM, Smithline L, Goodie JL, Paty JA, Gnys M, Jong JY-K. Effects of task strain, social conflict, and emotional activation on ambulatory cardiovascular activity: Daily life consequences of recurring stress in a multiethnic adult sample. Health Psychol. 1998; 17(1):17–29. doi:10.1037/0278-6133.17.1.17.

Albrecht SL, Anglim J. Employee engagement and emotional exhaustion of fly-in-fly-out workers: A diary study. Aust J Psychol. 2018; 70(1):66–75. doi:10.1111/ajpy.12155.

Breevaart K, Bakker AB, Derks D, van Vuuren TCV. Engagement during demanding workdays: A diary study on energy gained from off-job activities. Int J Stress Manage. 2020; 27(1):45–52. doi:10.1037/str0000127.

Karlsson K, Niemelä P, Jonsson A. Heart rate as a marker of stress in ambulance personnel: A pilot study of the body’s response to the ambulance alarm. Prehospital Disaster Med. 2011; 26(1):21–26. doi:10.1017/s1049023x10000129.

Fernández-Castro J, Martínez-Zaragoza F, Rovira T, Edo S, Solanes-Puchol Á, Martín-del-Río B, García-Sierra R, Benavides-Gil G, Doval E. How does emotional exhaustion influence work stress? relationships between stressor appraisals, hedonic tone, and fatigue in nurses’ daily tasks: A longitudinal cohort study. Int J Nurs Stud. 2017; 75:43–50. doi:10.1016/j.ijnurstu.2017.07.002.

Klumb PL, Voelkle MC, Siegler S. How negative social interactions at work seep into the home: A prosocial and an antisocial pathway. J Organ Behav. 2017; 38(5):629–49. doi:10.1002/job.2154.

Pereira D, Semmer NK, Elfering A. Illegitimate tasks and sleep quality: An ambulatory study. Stress Health. 2014; 30(3):209–21. doi:10.1002/smi.2599.

Stucky ER, Dresselhaus TR, Dollarhide A, Shively M, Maynard G, Jain S, Wolfson T, Weinger MB, Rutledge T. Intern to attending: Assessing stress among physicians. Acad Med. 2009; 84(2):251–57. doi:10.1097/acm.0b013e3181938aad.

Baethge A, Rigotti T. Interruptions to workflow: Their relationship with irritation and satisfaction with performance, and the mediating roles of time pressure and mental demands. Work Stress. 2013; 27(1):43–63. doi:10.1080/02678373.2013.761783.

Ferdous R, Osmani V, Marquez JB, Mayora O. Investigating correlation between verbal interactions and perceived stress. In: 2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC). IEEE: 2015. p. 1612–15. doi:10.1109/embc.2015.7318683.

Matta FK, Scott BA, Colquitt JA, Koopman J, Passantino LG. Is consistently unfair better than sporadically fair? an investigation of justice variability and stress. Acad Manage J. 2017; 60(2):743–70. doi:10.5465/amj.2014.0455.

Reicherts M, Pihet S. Job newcomers coping with stressful situations: A micro-analysis of adequate coping and well-being. Swiss J Psychol. 2000; 59(4):303–16. doi:10.1024//1421-0185.59.4.303.

Gervais RL. Menstruation as a work stressor: Evidence and interventions In: Gervais R. L., Millear P. M., editors. Exploring Resources, Life-Balance and Well-Being of Women Who Work in a Global Context. Springer: 2016. p. 201–18. Chap. 12. http://dx.doi.org/10.1007/978-3-319-31736-6_1 .

Boudreaux E, Jones GN, Mandry C, Brantley PJ. Patient care and daily stress among emergency medical technicians. Prehospital Disaster Med. 1996; 11(3):188–93. doi:10.1017/s1049023x0004293x.

Shively M, Rutledge T, Rose BA, Graham P, Long R, Stucky E, Weinger MB, Dresselhaus T. Real-time assessment of nurse work environment and stress. J Healthc Qual. 2011; 33(1):39–48. doi:10.1111/j.1945-1474.2010.00093.x.

Baethge A, Deci N, Dettmers J, Rigotti T. “some days won’t end ever”: Working faster and longer as a boundary condition for challenge versus hindrance effects of time pressure. J Occup Health Psychol. 2019; 24(3):322–32. doi:10.1037/ocp0000121.

Buunk BP, Peeters MCW. Stress at work, social support and companionship: Towards an event-contingent recording approach. Work Stress. 1994; 8(2):177–90. doi:10.1080/02678379408259988.

Weenk M, Alken APB, Engelen LJLPG, Bredie SJH, van de Belt TH, van Goor H. Stress measurement in surgeons and residents using a smart patch. Am J Surg. 2018; 216(2):361–68. doi:10.1016/j.amjsurg.2017.05.015.

Steptoe A. Stress, social support and cardiovascular activity over the working day. Int J Psychophysiol. 2000; 37(3):299–308. doi:10.1016/s0167-8760(00)00109-4.

Johnston D, Bell C, Jones M, Farquharson B, Allan J, Schofield P, Ricketts I, Johnston M. Stressors, appraisal of stressors, experienced stress and cardiac response: A real-time, real-life investigation of work stress in nurses. Ann Behav Med. 2016; 50(2):187–97. doi:10.1007/s12160-015-9746-8.

van Hooff MLM. The daily commute from work to home: Examining employees’ experiences in relation to their recovery status. Stress Health. 2015; 31(2):124–37. doi:10.1002/smi.2534.

Diebig M, Bormann KC. The dynamic relationship between laissez-faire leadership and day-level stress: A role theory perspective. Ger J Hum Resour Manag. 2020; 34(3):324–44. doi:10.1177/2397002219900177.

Wood S, Michaelides G, Totterdell P. The impact of fluctuating workloads on well-being and the mediating role of work-nonwork interference in this relationship. J Occup Health Psychol. 2013; 18(1):106–19. doi:10.1037/a0031067.

Levin S, France DJ, Hemphill R, Jones I, Chen KY, Rickard D, Makowski R, Aronsky D. Tracking workload in the emergency department. Hum Factors. 2006; 48(3):526–39. doi:10.1518/001872006778606903.

Tadić M, Bakker AB, Oerlemans WGM. Work happiness among teachers: A day reconstruction study on the role of self-concordance. J School Psychol. 2013; 51(6):735–50. doi:10.1016/j.jsp.2013.07.002.

Elfering A, Semmer NK, Grebner S. Work stress and patient safety: Observer-rated work stressors as predictors of characteristics of safety-related events reported by young nurses. Ergonomics. 2006; 49(5-6):457–69. doi:10.1080/00140130600568451.

Almeida DM, Davis KD. Workplace flexibility and daily stress processes in hotel employees and their children. Ann Am Acad Politi Soc Sci. 2011; 638(1):123–40. doi:10.1177/0002716211415608.

Download references

Acknowledgments

Not applicable.

This work was supported by the Research Foundation – Flanders, Belgium (FWO) under Grant (project no. G.0318.18N); and the Slovenian Research Agency (ARRS) under Grant (project ref. N2-0081).

Author information

Junoš Lukan and Larissa Bolliger contributed equally to this work.

Authors and Affiliations

Department of Intelligent Systems, Jožef Stefan Institute, Jamova cesta 39, Ljubljana, 1000, Slovenia

Junoš Lukan & Mitja Luštrek

Jožef Stefan Postgraduate School, Jamova cesta 39, Ljubljana, 1000, Slovenia

Department of Public Health and Primary Care, Ghent University, C. Heymanslaan 10, Ghent, 9000, Belgium

Larissa Bolliger, Dirk De Bacquer & Els Clays

Knowledge Centre for Health Ghent, Ghent University, C. Heymanslaan 10, Ghent, 9000, Belgium

Nele S. Pauwels

Ghent University Hospital, C. Heymanslaan 10, Ghent, 9000, Belgium

You can also search for this author in PubMed   Google Scholar

Contributions

The following authors all contributed to this work: Junoš Lukan (JL), Larissa Bolliger (LB), Nele S. Pauwels (NP), Mitja Luštrek (ML), Dirk De Bacquer (DB), Els Clays (EC). The roles they shared according to the CRediT designations are as follows. Conceptualization: JL, LB, ML, EC Data curation: JL, LB Formal analysis: JL, LB Funding acquisition: ML, DB, EC Investigation: JL, LB Methodology: Not applicable Project administration: JL, LB, ML, EC Resources: NP Software: Not applicable Supervision: NP, ML, DB, EC Validation: Not applicable Visualization: JL Writing - original draft: JL, LB Writing - review & editing: JL, LB, NP, ML, EC. The authors read and approved the final manuscript.

Corresponding author

Correspondence to Larissa Bolliger .

Ethics declarations

Ethics approval and consent to participate, consent for publication, competing interests.

The authors declare that they have no competing interests.

Additional information

Publisher’s note.

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary Information

Additional file 1.

Tables 1 and 2 show work environment risk factors and stress outcomes, respectively, together with the tools used to measure them in original studies. They are ordered in broader categories according to the 6th European Working Conditions Survey [ 29 ] and with respect to the stress model of Ice and James [ 30 ].

Additional file 2

Correlations were extracted from studies that reported them. They are listed in a spreadsheet to enable replication of analyses. These correlations were counted to produce Fig.  2 in the main body of text.

Additional file 3

The full search strategies with indexing terms and free text words for all the databases searched: PubMed, Embase, Web of Science, Scopus, CINAHL, ERIC, and PsycArticles.

Additional file 4

The PRISMA Checklist noting the page numbers of all necessary review items.

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ . The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/ ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

Reprints and permissions

About this article

Cite this article.

Lukan, J., Bolliger, L., Pauwels, N.S. et al. Work environment risk factors causing day-to-day stress in occupational settings: a systematic review. BMC Public Health 22 , 240 (2022). https://doi.org/10.1186/s12889-021-12354-8

Download citation

Received : 09 April 2021

Accepted : 29 November 2021

Published : 05 February 2022

DOI : https://doi.org/10.1186/s12889-021-12354-8

Share this article

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

• Day-to-day stress
• Ecological Momentary Assessment (EMA)
• Work environment risk factors
• Stress outcomes
• Systematic literature review

BMC Public Health

ISSN: 1471-2458

• General enquiries: [email protected]

• +1 561-306-3576
• [email protected]

Creating a Work Environment that Inspires Employees to Stay

Claude werder.

• June 6, 2024

Current State

The evolving work environment is difficult to navigate for everyone. Few employers believe it will significantly improve in the near future. 92% of organizations are prioritizing investments to improve the employee work experience. At the same time, 92% of organizations also believe their top talent is at risk for leaving.

Complications

80% of organizations are operating under some form of hybrid work arrangement but leadership sentiments about this arrangement are mixed. About 35% of respondents to Brandon Hall Group™’s HCM Outlook 2024 study believe that as long as employees are meeting expectations, it doesn’t matter where they work from and an additional 35% believe that employees need to be in the office two to three days per week. Further complicating the work environment are 16% of organizations whose work or industry does not allow for hybrid work. Hybrid or remote work puts pressure on every aspect of the employee experience.

Consequences

As the graphic above illustrates, employers have many people priorities. As the saying goes, if everything is a priority, then nothing is a priority and employers can only pay attention to so many priorities at once. It is important to focus on a few critical objectives and assess progress over time before determining next steps.

Critical Question

• What are the key components that have the biggest impact on talent retention?

Brandon Hall Group ™ POV

Each employee is unique, which makes it difficult to focus on improving experiences because there are so many of them and employees value each experience to varying degrees. But one factor that our research reveals as critical to employee engagement and retention is providing an environment of psychological safety. If employers can provide that, they have a foundation for driving engagement and retaining talent.

Continuously Listen to Employees

Many employers still rely on annual employee surveys to understand the level of engagement. Technology enables you to connect with employees in a variety of sophisticated ways and target employee segments for deeper understanding of what motivates and demotivates and what they care about. Continuous listening is critical to understand your workforce and build an environment of psychological safety.

Act Quickly on Employee Feedback

Employees must feel heard. But, more importantly, they must believe you are taking what they say seriously. The only thing worse than not listening to your employees is to listen and do nothing — or listen, do something, but not communicate what you are doing.

Employers can’t address all concerns employees have, but they can analyze where the biggest problems are, address them, then design communication campaigns to inform the workforce. Even when you act, engage employees to be part of the solution and get their feedback so you can adjust as needed.

Recognize Employee Contributions More Frequently

Everyone likes — and many people crave — recognition. It’s human nature; we want to be appreciated. Brandon Hall Group ™ research indicates that recognition is important or critcal for driving business results.

Praising or providing positive reinforcement to an employee once a month does not seem like a high bar! With the aid of technology, there are countless ways for leaders and peers to praise, recognize and even reward employees for a job well done, making progress on a goal or overcoming a challenge.

About seven in 10 employers believe leadership development training is needed for the entire workforce, according to Brandon Hall Group’s study, Creating Leadership Development for Every Employee . But only about 40% do it.

There are significant benefits to leadership training for all:

• At least 80% of employers say it promotes a clear vision and direction, fosters collaboration and improves trust, coaching and emotional intelligence.
• Employees gain the opportunity to form good leadership habits early and become better decision-makers. It also demonstrates the organization’s commitment to employee and career development.

Empower Employees to Own their Career Development

Your employees want to know they can grow and prosper in your organization. If not, why stay? Historically, career development has been a blind spot for most employers. That is beginning to change as talent retention becomes a larger issue and organizations see the errors of their ways.

But busy managers and HR teams can only do so much. There have been great strides in technology that matches employees to opportunities (such as teams, projects, temporary assignments) to develop their capabilities in alignment with their aspirations. Invest in technology and other resources to give your employees more responsibility for career development. Empowerment provides a sense of belonging and feeling valued.

Like what you see? Share with a friend.

Resubscribe to our email distribution list.

Suggestions or feedback?

MIT News | Massachusetts Institute of Technology

• Machine learning
• Social justice
• Black holes
• Classes and programs

Departments

• Aeronautics and Astronautics
• Brain and Cognitive Sciences
• Architecture
• Political Science
• Mechanical Engineering

Centers, Labs, & Programs

• Abdul Latif Jameel Poverty Action Lab (J-PAL)
• Picower Institute for Learning and Memory
• Lincoln Laboratory
• School of Architecture + Planning
• School of Engineering
• School of Humanities, Arts, and Social Sciences
• Sloan School of Management
• School of Science
• MIT Schwarzman College of Computing

Improving working environments amid environmental distress

Press contact :, media download.

*Terms of Use:

Images for download on the MIT News office website are made available to non-commercial entities, press and the general public under a Creative Commons Attribution Non-Commercial No Derivatives license . You may not alter the images provided, other than to crop them to size. A credit line must be used when reproducing images; if one is not provided below, credit the images to "MIT."

Previous image Next image

In less than a decade, MIT economist Namrata Kala has produced a corpus of work too rich, inventive, and diverse to be easily summarized. Let’s try anyway.

Kala, an associate professor at the MIT Sloan School of Management, often studies environmental problems and their effects on workers and firms, with implications for government policy, corporate managers, and anyone concerned about climate change. She also examines the effects of innovation on productivity, from farms to factories, and scrutinizes firm organization in light of such major changes.

Kala has published papers on topics including the long-term effects of climate change on agriculture in Africa and India; the impact of mechanization on farmers’ incomes; the extent to which linguistic differences create barriers to trade; and even the impact of LED light bulbs on factory productivity. Characteristically, Kala looks at issues of global scale and pinpoints their effects at the level of individuals.

Consider one paper Kala and two colleagues published a couple of years ago, about the effects of air pollution on garment factory workers in India. The scholars examined patterns of particulate-matter pollution and linked that to detailed, worker-level data about how productive workers were along the production line. The study shows that air pollution damages sewing productivity, and that some managers (not all) are adept at recognizing which workers are most affected by it.

What emerges from much of this work is a real-time picture of human adaptation in a time of environmental distress.

“I feel like I’m part of a long tradition of trying to understand resilience and adaptation, but now in the face of a changing world,” Kala says. “Understanding interventions that are good for resilience while the world is changing is what motivates me, along with the fact that the vast majority of the world is vulnerable to events that may impact economic growth.”

For her research and teaching, Kala was awarded tenure at MIT last year.

Joining academia, then staying in it

Kala, who grew up in Punjab, India, was long mindful of big issues pertaining to society, the economy, and the environment.

“Growing up in India, it’s very difficult not to be interested in the some of the questions that are important for development and environmental economics,” Kala says.

However, Kala did not expect that interest to lead her into academia. She attended Delhi University as an undergraduate, earning her degree with honors in economics while expecting to find a job in the area of development. To help facilitate that, Kala enrolled in a one-year master’s program at Yale University, in international and development economics.

Before that year was out, Kala had a new realization: Studying development problems was integral to solving them. Academia is not on the sidelines when it comes to development, but helps generate crucial knowledge to foster better and smarter growth policies.

“I came to Yale for a one-year master’s because I didn’t know if I wanted to be in a university for another two years,” Kala says. “I wanted to work on problems in the world. And that’s when I became enthralled with research. It was this wonderful year where I could study anything, and it completely changed my perspective on what I could do next. So I did the PhD, and that’s how I became an economist.”

After receiving her PhD in 2015, Kala spent the next two years supported by a Prize Fellowship in Economics, History, and Politics at Harvard University and a postdoctoral fellowship at MIT’s own Abdul Latif Jameel Poverty Action Lab (J-PAL). In 2017, she joined the MIT faculty on a full-time basis, and has remained at the Institute since then.

The source material for Kala’s studies varies widely, though in all cases she is looking for ways to construct well-defined empirical studies tackling major questions, with key issues often revealed in policy or firm details.

“I find reading stuff about policy reform strangely interesting,” she quips.

Development, but with environmental quality

Indeed, sometimes the spark for Kala’s studies comes from her own broad knowledge of past policy reforms, combined with an ability to locate data that reveals their effects.

For instance, one working paper Kala and a colleague recently completed looks at an Indian policy to move industrial firms out of Delhi in order to help solve the city’s pollution problems; the policy randomly relocated companies in an industrial belt around the city. But what effect did this have on the firms? After examining the records of 20,000 companies, the researchers found these firms’ survival rate was 8 percent to 20 percent lower than if the policy called for them to be clustered more efficiently.

That finding suggests how related environmental policies can be designed in the future.

“This environmental policy was important in that it improved air quality in Delhi, but there’s a way to do that which also reduces the cost on firms,” Kala says.

Kala says she expects India to be the locus of many, though hardly all, of her future studies. The country provides a wide range of opportunities for research.

“India currently has both the largest number of poor people in the world as well as 21 of the 30 most polluted cities in the world,” Kala says. “Clearly, the tradeoff between development and environmental quality is extremely salient, and we need progress in understanding industrial policies that are at least environmentally neutral or improving environmental quality.”

Kala will continue to look for new ways to take pressing, large-scale issues and study their effects in daily life. But the fact that her work ranges so widely is not just due to the places she studies; it is also because of the place she studies them from. MIT, she believes, has provided her with an environment of its own, which in this case enhances her own productivity.

“One thing that helps a lot is having colleagues and co-authors to bounce ideas of off,” Kala says. “Sloan is the heart of so much interdisciplinary work. That is one big reason why I’ve had a broad set of interests and continue to work on many things.”

“At Sloan,” she adds, “there are people doing fascinating things that I’m happy to listen to, as well as people in different disciplines working on related things who have a perspective I find extremely enriching. There are excellent economists, but I also go into seminars about work or productivity or the environment and come away with a perspective I don’t think I could have come up with myself.”

Share this news article on:

Related links.

• Namrata Kala
• MIT Sloan School of Management
• Podcast: Curiosity Unbounded, episode 8 — Hard facts on soft skills

Related Topics

• Climate change
• School of Humanities Arts and Social Sciences

Related Articles

$25 million gift launches ambitious new effort tackling poverty and climate change

An experiment puts auditing under scrutiny

Previous item Next item

More MIT News

Through econometrics, Isaiah Andrews is making research more robust

Read full story →

Students research pathways for MIT to reach decarbonization goals

A data-driven approach to making better choices

Paying it forward

John Fucillo: Laying foundations for MIT’s Department of Biology

Researchers demonstrate the first chip-based 3D printer

• More news on MIT News homepage →

Massachusetts Institute of Technology 77 Massachusetts Avenue, Cambridge, MA, USA

• Map (opens in new window)
• Events (opens in new window)
• People (opens in new window)
• Careers (opens in new window)
• Accessibility
• Social Media Hub
• MIT on Facebook
• MIT on YouTube
• MIT on Instagram

ORIGINAL RESEARCH article

Impact of employees' workplace environment on employees' performance: a multi-mediation model.

• 1 Institute for Cultural Industries, Shenzhen University, Shenzhen, China
• 2 Department of Occupational Therapy, Faculty of Associated Medical Sciences, Chiang Mai University, Chiang Mai, Thailand
• 3 Program in Leisure Industry Management, Commercial College, Chinese Culture University, Taipei City, Taiwan
• 4 Department of Management, College of Business Administration, King Saud University, Riyadh, Saudi Arabia
• 5 Department of Management, Birmingham Business School, University of Birmingham, Birmingham, United Kingdom

This study examined the impact of workplace environment on employee task performance under the mediating role of employee commitment and achievement-striving ability. For this purpose, data were collected from the academic staff under a cross-sectional research design, and they were approached through convenience sampling technique. As per recommendations of established sample size criteria, we distributed a sum of 420 questionnaires among the respondents. Among these distributed questionnaires, only 330 were received back. The returned questionnaires were checked for missing and incomplete responses and after discarding the missing responses useable responses were 314 which were used for the data analysis. Data had been analyzed through structural equation modeling (SEM) by using Smart PLS 3. The SEM was done based on measurement models and structural models. The results indicated that a positive work environment had the power to improve employee performance. Similarly, a positive work environment also improved the employee commitment level and achievement-striving ability significantly. Both employee commitment and achievement-striving ability also improved employee performance. While in the case of mediation, it had also been observed that workplace environment triggered employee commitment and employee achievement-striving ability which further improved employee performance.

Introduction

According to the assumptions of human resource management (HRM), improved performance is accomplished through the employees of the organization. Employees are thus viewed as a valuable asset to every firm to improve performance ( 1 ). Before the last decades of the 20th century, the performance was viewed as the result of a mix of aptitude and motivation when given adequate resources, and therefore motivating people became an important aspect of most management. Whenever human resource (HR) is used to its greatest capacity, a business may attain limitless productivity, efficiency, and performance. All employees may not work in the same way since they have distinct working styles. Some personnel have the greatest potential regardless of the reward, whereas others benefit from a boost now and again ( 2 , 3 ). The employees' performances are determined by their willingness and openness to complete their jobs. Furthermore, if employees are willing and open to accomplish their jobs, it is possible that their productivity will grow, which will contribute to improved performance ( 4 ).

Employees, equipment, and supplies, on the other hand, must be provided with the required resources to perform, independent of their talents and expertise ( 5 ). “Performance appraisal impacts directly onto highly emotional tasks in professional life, judgment of a person's commitment, and competence,” ( 6 ). According to several academics, implementing a well-defined framework for analyzing employee performance is critical to a company's successful operation ( 7 ). The major difficulty for businesses, according to ( 8 ), has been focused on improving the performance of employees efficiently so that their authenticity remains on top. In other sense, how can businesses use performance evaluation procedures to increase their capacity to discern “excellent” employees (those who perform well) from “poor” employees? Furthermore, according to ( 9 ), many crucial variables in the study and implementation of a performance assessment model are still missed, which may explain why there is not currently an integrated approach for assessing employee performance.

The physical and behavioral aspects are the two facets of a healthy working climate. The prior refers to the factors which are linked with the ability of employees to remain physically associated to their workplaces. while the etiquettes of office bearers are influenced by the behavioral aspects of the environment, the workplace environment plays an important role in shaping behaviors of employees individually. Consequently, employees' motivation to work hard, their efficiency and performance are shaped by the influence of the quality of the workplace. Worker' levels of willingness to keep motivated, creative, engaged with colleagues, and loyal to job are all influenced by the factors of workplace environment ( 10 ). According to some researchers, this feature of relatedness with workplace environment have mixed beneficial and adverse impacts ( 11 ).

The majority of the workplace environments in developing countries are not up to the mark. Unfortunately, most firms consider a safe and healthy work environment to be an unnecessary expenditure and do not invest heavily in sustaining a comfortable working environment ( 12 ). For sustainable development, it is vital for any firm to have dedicated employees who are committed to their goals. When people work in groups, there is a possibility that they may behave as if they are entrepreneurs, so every group member engages in as many tasks as possible to demonstrate that he/she is the most promising person in the group. Employee commitment levels boost employee performance in firms which enhance their commitment levels. Previously, firms have given their employees job security to boost their dedication to the firm and efficiency ( 13 ). Employee performance is tied to employee commitment. Few academics have argued that each commitment element's psychological status varies from one worker to another ( 14 ).

It is supposed that affective commitment as well as employee performance have a positive relationship, suggesting that workers have a belief that their companies would be treating them positively (i.e., fair rehabilitation, involvement in choice determination) could boost interpersonal loyalty of them to the organization and, consequently, enhance their effectiveness ( 15 ). Moreover, the workers with a high sense of commitment to the company's goals feel a strong sense of ownership over their responsibilities, while the employees with a lower level of commitment to the company's targets feel no such obligation. Certain research indicates that normative commitment and performance of employees have a negative relationship ( 16 ). Employees who have a higher level of organizational commitment find themselves “stuck” in situations where they have little option to quit the organization even if they do not really want to stay. As a result, individuals take their jobs in a less serious manner, and their production suffers ( 16 ).

Eudemonia refers to working for and achieving job-related goals, as well as realizing one's maximum potential, and is based on the philosophy of eudemonia drive (i.e., achievement striving). Achievement striving, according to the notion, indicates employees' motivation to take action toward personal greatness ( 17 ). On the one hand, the social contact motivates accomplishment seeking by facilitating currently operating and combining for the purpose of fostering creativity and accomplishing work objectives. Achievement striving, on the other hand, is a performance-oriented aim that has a beneficial impact on staff performance ( 17 ). Employees are more likely to strive for an outstanding performance if they have a strong accomplishment drive. Employees who have meaningful social connections at work are more likely to be motivated to complete the assignments on time (i.e., achievement striving) ( 18 ).

Employees' performance has been evaluated before in different business sectors, leaving behind the gap for a specific sector's evaluation. Moreover, different firm level environmental factors along with job-related factors have been evaluated with specific mediation of employee-related factors such as motivation, adaptability, flexibility, proactivity, skill level, and commitment for evaluating the employees' performance ( 19 ). This kind of evaluation left a gap for assessing the specific mediating role of employees' commitment between their workplace environment and performance. Therefore, we utilized the employees' commitment as a potential mediator between employees' workplace environment and employees' performance. Similarly, the role of achievement-striving ability has been utilized as mediator previously along with occupational commitment between social interaction and job performance ( 18 ) leaving a gap for evaluating the impact of achievement-striving ability between workplace environment and employees' performance. Therefore, this study was designed to evaluate the mediating roles of employees' commitment and achievement-striving ability.

The impact of employee workplace environment has been studied previously for the evaluation of performance of the employees at different organizational levels but has not been studied among employees of the academic institutes therefore, it posed some questions to address whether it has any impact on the performance of employees of academic institutes or not. The question stated that what role could employee commitment and achievement striving ability of employees could play in the context of academic institute job performance of employees? To answer these questions, this study focused on evaluating the impact of the workplace environment of employees on their performance. The multi-mediation analysis was also carried out in this study to evaluate the aiding role of employees' commitment and achievement-striving ability of employees between workplace environment of employees and their performance.

Theoretical and Hypothesis Support

Employee performance is achieved through the organization's employees, according to HR management theory ( 20 ). To increase the performance, employees are thus considered as a vital asset in any company. Previous to the later decades of the 20th century, performance was considered as a combination of ability and motivation when given sufficient resources, and therefore motivating people, became a key element of the most of the management practices ( 21 ). When HR is employed to its full potential, a company may achieve unattainable levels of production, efficiency, as well as performance ( 22 ). So, this study gets motivation from HR management theory for evaluating the performance of employees.

The willingness as well as openness of employees to fulfill their work determines their performance. Furthermore, if employees are enthusiastic and motivated to accomplish their jobs, their performance is likely to improve, contributing to increased productivity ( 23 ). All this could be achieved under the premises of HRM theory. This study also gets a support from the theory of ecological systems. This theory is also known as “individual theory.” According to this theory, people in a specific environment have a dynamic relationship with their social, physiological, and physical environments. This theory also states that the workplace environments are inter-related in which the job settings are connected with each other and have an effect on activities at workplace in terms of context, time and processes ( 24 ). This theory underpins the importance of environment at workplace for the workers and individuals involved in organizational processes.

Once employees get a favorable working environment, then they become more dedicated to their assigned tasks which ultimately improves their performance. So, the ecological systems theory has a lot to offer to shape up the workplace environment. This study also gets support from social exchange theory in which favorable workplace environment provides a sort of motivation to the employees to work better. Such motivational activities in organizations take place having background support of some exchanges socially. The process of social exchange takes place between an organization and its workers indicating that the organization recognizes the contributions of its employees and ensures that they are well-cared for ( 25 ). This theory provided the basis for understanding the effect of employee performance in the context of the workplace environment.

Employees, in return, do their best to achieve the targets set by their organizations and they perform better in a given favorable working environment. Thus, a social exchange is in practice for this study. Social exchange theory also provides a basis for employees' commitment as if the workplace environment is favorable and suitable, it develops a sense of trust for the organization among the employees. The employees in exchange show more commitment toward the set targets of the organization. This trust is built as a consequence of management support, and as a result, employees are motivated, which aids in the development of a good attitude toward work, and employee commitment is increased, resulting in improved performance ( 26 ). A combination of these theories for evaluating the employees' performance has also been studied before and provided a basis for the conduct of this study.

Relationship of Employee Workplace Environment With Employees' Performance

Employees spend a major considerable amount of time at work, and their working environment has an impact on their performance in integrated ways ( 27 ). Employees who are satisfied with their work environment are more likely to have positive work output. A previous study has revealed that factors which shape up the workplace environment show their impact on the performance of employees ( 28 ). They also proposed that future studies on this kind of relationships referring to workplace environment and evaluation of performance could be conducted. A few scholars also encouraged future researchers to conduct comparison studies on private and public organizational levels for impact of workplace environments be on employee' performance ( 29 ). The researchers observed that the workplace environment is crucial since staff can work more efficiently doing their jobs in a nice workplace, which leads to higher employees' performance and organization output.

The terms “appealing climate” or “supportive atmosphere” refers to a situation which draws people and motivates them to work by giving them possibilities to accomplish ( 30 ). Workers are more willing to integrate their extraordinary use of skills, abilities, and knowledge to achieve success in a welcoming and supportive workplace environment. Employees will be motivated for a number of reasons to accomplish optimal performance and productivity inside a firm; such motivations could be endogenous or exogenous ( 31 ). Endogenous motivations help in accomplishing certain difficult tasks and exogenous motivations are the reward which are given in terms of the acknowledgments and the advanced salaries ( 31 ).

Another appropriate workplace strategy is to motivate employees to set their goals. Employees' performance improves as a result of this type of incentive program, and the productivity of the company rises ( 32 ). Goal setting serves two main functions as follows: First, to improve the behaviors of the individuals; second, to motivate them to work so that they can work effectively and efficiently ( 33 ). Generalized objectives are less successful than a particular aim. Furthermore, in contrast to an achievable objective, excellent performance is attained through hard goals. Based on the strategies of providing a better workplace environment to the employees, a few empirical investigations have been done in recent past in different contexts. These studies hinted to explore this kind of relationship even further for establishing this association as a set parameter in achieving improved employees' performance. Therefore, we suggested the hypothesis as given in the following:

H1: Employee workplace environment has positive and significant effect on employees' performance.

Impact of Employee Workplace Environment on Employees' Commitment

According to prior study, the employees' working atmosphere in the firm is vital and also has a significant impact on employees in a variety of aspects ( 34 ). If the working environment fails to attract employees and they have a bad perception of many workplace aspects such as sick leave, performance, mental illness, and performance, their demand will ultimately be lowered to a low level, impacting the institution's growth and productivity ( 35 ). Employee commitment to the workplace, innovation, efficiency, commitment, and financial wellbeing all benefit from a nice, secure, and reliable workplace, all of which affect the institution's development ( 36 ).

When employees work in groups, the individuals behave as if they are entrepreneurs, and every person in the group engages in as many events as possible to demonstrate how he or she is the brightest in the group. Worker level of commitment boost employee productivity in firms which improve their levels of commitment. Companies have traditionally offered job protection to the workers to boost their loyalty toward the company and performance. Employee performance is linked to employee commitment, which has three facets (affective commitment, continued commitment, and normative commitment). It was previously established that the office atmosphere had a favorable influence on workers' commitment to perform ( 37 ). As a result of this literature support, we hypothesized the following:

H2: Employee workplace environment significantly affects employees' commitment.

Impact of Employee Workplace Environment on Employees' Achievement-Striving Ability

One of the most critical factors influencing employee performance in an organization is the working environment. In today's competitive corporate world, monetary benefits are insufficient to motivate employees to reach better levels of performance levels ( 38 ). A mix of monetary and non-monetary rewards, on the other hand, is more effective better levels of employee performance, which results in increasing of achievement aims of the company for an instance, and it was observed that the employees of certain sector of companies wanted a pleasant, relaxing environment, and to achieve a higher degree of performance, a cooperative working atmosphere is required.

Billings noted that the employees are the focus of organizational decisions as they are present at their workplaces most of the day ( 39 ). In contemporary organizations, justice is not always administered through the equal distribution of employment resources as well as the provision of clear and acceptable explanations for choices taken, and employees are not always treated with dignity and respect throughout policy and procedure execution ( 40 ). This leads to a worse workplace environment while, it is proven that a better workplace environment is always suitable in achieving something good for the organizations. Achievement striving is totally the drive for achieving the targeted goals by the employees. The employees who are more targeted toward the goals are more productive in terms of their performance ( 18 ). In this way, if employees are given suitable workplace environment, then it could initiate achievement-striving ability in employees. So, based on this possible logic, we devised the following hypothesis:

H3: Employee workplace environment significantly affects employees' achievement-striving ability.

Mediation Between Workplace Environment and Employees' Performance

The performance of employees is a popular issue, and this is influenced in a range of ways by the workplace. Behavioral and physical features of a typical working environment are critical. All components which are linked to an employee's ability to physically engage with the workplace are referred to as the physical setting ( 41 ). While behavioral environmental components relate workplace occupants' etiquettes with one another. The workplace atmosphere has a positive impact on individual employee behavior ( 42 ). Consequently, workplace environment quality has a significant impact on workers and their motivation, enthusiasm, creativity, and efficiency. Work motivation, innovative behavior, attendance, colleagues' engagement, and career management are all influenced by how strongly they are connected to a company ( 43 ).

Depending on the physical circumstances in the workplace, it might have a beneficial or harmful impact. The majority of the working environment in underdeveloped nations is insecure and dangerous. However, most businesses consider a safe and healthy work atmosphere to be an absolute waste of money and therefore do not invest extensively in keeping it in good shape ( 44 ). Employees working in an unstable and unhealthy atmosphere, putting them at risk for occupational sickness related to the adverse effects of the environment on their productivity, which has an impact on the organization's total productivity ( 45 ). Employees are dealing with serious environmental issues at work, particularly in the software business, which makes it difficult to provide necessary amenities to improve their performance level ( 46 ).

Scholars recently examined software house workers' performance in the presence of physical and behavioral workplace ambient variables ( 47 ). As a result, this study's major goal is to analyze and evaluate the factors of the working as well as behavioral environment that influence employee performance. To accomplish the given task of evaluating the impact of the workplace environment of employees' performance, there was a dire need to find the facilitators who could boost the relationship of workplace environment and employees' performance. Based on this need, employee's commitment and achievement-striving ability of employees, which are discussed in previous section, are used as mediators of this study. So, we proposed the following hypothesis (see Figure 1 ).

Figure 1 . Conceptual framework.

H4: Employee commitment significantly mediates the relationship between employee workplace environment and employee performance.

H5: Achievement striving significantly mediates the relationship between employee workplace environment and employee performance.

Research Methods

This study used a cross-sectional research design to collect data from the participants. This research design was commonly used in survey research and previously the researchers have used cross-sectional research design in their studies ( 48 , 49 ). This study design was most suitable to our aim of the study which was to investigate the impact of the workplace environment on employee performance. So, we had obtained the perception of the respondents through a cross-sectional research design. In this regard, teachers from the academic institutes were approached. The respondents in this study were selected based on previous studies, where academic teaching staff were approached for data collection to study the impact of workplace environment ( 50 ). Before approaching the academic teaching staff for data collection, we sought formal approval from the administration.

After getting approval from the administration, we contacted the teaching staff according to the list provided by the academic institutes. Moreover, before asking the respondents to provide their feedback, we ensured them regarding data confidentiality and their written informed consent was obtained. Additionally, to increase their motivation in the study, we offered chocolates to the respondent with the questionnaire, so that they could fill out the survey questionnaire with motivation. Before distributing questionnaires to the respondents, a suitable sample size was determined and the criteria regarding setting a reasonable sample size were consulted. In this regard, the widely used and accepted criteria for sample size devised by the study in ( 51 ), and previously used by various researchers, were followed ( 52 ).

Thus, as per the recommendations of this sample size criteria, we distributed a sum of 420 questionnaires among the respondents and of these distributed questionnaires, only 330 were received back. The returned questionnaires were checked for missing and incomplete responses and after discarding the missing responses 314 were retained. Additionally, we have employed Smart PLS software, which handles the small sample size very comfortably, so the issue of sample size does not raise any question in this study ( 53 ).

Owing to the cross-sectional nature of the study, it was likely to encounter common method bias in this study. We employed several techniques to reduce the issue of common method bias, we interchanged the place of the scales and items in the questionnaires, so that respondents could not develop a correlation among the study constructs while reporting the responses. This helped us to reduce common method biases ( 54 , 55 ).

Demographic Characteristics

The first section of the questionnaires dealt with demographic characteristics related to qualification, gender, and teaching experience. From the perspective of qualification, respondents were mostly with 18 years of education and 16 years of education; however, the percentage of 18 years education among respondents was high (90%). Second, the distribution of the respondents according to gender's perspective was almost equal [i.e., 54% (male) and 46% (female)]. While most of the teaching staff were employed in service with experience of more than 3 years, very few have <1 year of experience.

Instrument Development

We followed a five-point Likert scale to collect the data for all exogenous and endogenous constructs ranging from five to one on a description of strongly agree to strongly disagree. The independent variable in this study (workplace environment) is measured through 10 items. The one-dimension of the environment (hedonic environment) is used in this study, which denotes the positive side of the workplace environment. Sample items for this scale include, “The transparency of rules in my institution is making my work easier,” and “My company is a positive workplace.” This scale is used in a recent study ( 50 ). This scale contains reverse coded questions, and we have also used these reverse coded questions to restrict the respondents from providing monotonic responses. The outcome variable in this study, employee performance is measured through six-items scale covering the perception of employees' task performance. This scale is developed by Koopmans et al. ( 56 ). The sample items for this scale include, “I kept in mind the results that I have to achieve in my work.” Although in previous studies ( 50 ), another dimension of employee performance has also been used such as contextual and counterproductive work behavior. However, we have used task performance as a measure to assess the response regarding employee performance which denotes it well.

Employee commitment is assessed based on six items-based scale of affective commitment developed by a research team ( 57 ) with sample item, “I would be happy to work at my organization until I retire.” While the second mediating variable, achievement-striving ability is assessed based on a scale developed by in a study ( 58 ) with five-items scale. A sample item for this scale, includes, “I am a very determined person when it comes to my job.”

Assessment of Measurement and Structural Model

We have employed a multi-variate data analysis tool in this study to test the hypotheses through structural equation modeling (SEM). For this purpose, the most commonly used partial least square (PLS) approach through Smart PLS was used ( 59 ). This software deals very well with the complex nature of research frameworks/models ( 60 ). In addition to this, smart PLS has good predicting capability even with a small sample size and it deals with small sample size very well. Lastly, it does deal better with the non-normal data and the issue of normality is handled by Smart PLS very well. Assessment of SEM is based on two approaches/methods, the first one is based on the measurement model while the second one is based on structural model ( 61 ).

Table 1 illustrates the reliability and validity of the study constructs, based on the assessment of the measurement model. At this stage of reliability and validity of the study, the model has been confirmed. For the issue of reliability, the first measure in this regard that is used is Cronbach Alpha or is termed as alpha. The minimum acceptable value for this indicator of reliability is 0.60 ( 60 , 62 ). Alpha statistics have been found statistically high above this benchmark; for instance, the alpha value for the construct, workplace environment is 0.929, for employee performance it is 0.745, for achievement-striving ability it is 0.839 and for employee commitment, it is 0.893. Thus, all the constructs possess good alpha reliability. Similarly, the second measure of reliability (rho-A) is also within the acceptable range (>0.60). The value of Rho-A for the workplace environment is 0.939, for the employee performance is 0.768, for the achievement-striving ability is 0.877, and for the employee commitment is 0.925. Thus, the second measure of reliability is also met. The third measure of reliability is based on composite reliability, which also shows a good level. The values for composite reliability are within a range of 0.830–0.941, illustrating good composite reliability.

Table 1 . Reliability and validity of the study constructs.

In the case of validity, it has been tested through average variance extracted (AVE) and it has been found that the AVE of the respective constructs is greater than the threshold limits of the acceptable range (≥0.50). All the study constructs possess greater AVE values (≥0.50) which indicate that the convergent validity has been established ( 63 ) as illustrated through Table 1 . The AVE values range between 0.551 and 0.663.

The second measure to assess the convergent validity is outer loadings ( Figure 2 ). At this stage, each indicator was checked for outer loadings, and it was observed that outer loadings are above the threshold value of 0.708. Table 2 illustrates the outer loadings of all study constructs. Two items have been dropped in this study due to weak or poor outer loadings. One item from the study constructs workplace environment (WE-10). Similarly, from employee performance, two items (ETP-3 and ETP-6) have been dropped due to poor outer loadings. One item from the construct achievement-striving ability (AS-4) was dropped. One item with slightly low outer loading (ETP-2) was retained in employee performance as the AVE of this construct was above the threshold value (≥0.50). Thus, all the indicators met with convergent validity criteria, and it can be referred that the model possesses convergent validity.

Figure 2 . Path estimates.

Table 2 . Outer loadings (convergent validity).

While testing the other side of validity (discriminant validity), we have followed two well-established criteria, the first one is Fornell and Larcker ( 64 ) and Heterotrait-monotrait (HTMT) ratio of correlations ratios ( 60 ). Tables 3 , 4 illustrate these two criteria. The first criteria in this regard indicates that the square root of the AVE of variables is higher than the correlations among them ( 52 , 65 ). For instance, the square root of AVE of achievement-striving ability is 0.814 which is higher than the correlations in that column (bold and underlined values in diagonal). Similarly, the square root of AVE of employee commitment is 0.808 which is also higher in that column. Same pattern is observed for employee performance and workplace environment.

Table 3 . Discriminant validity (Fornell–Larker-1981 criteria).

Table 4 . Discriminant validity (HTMT).

The HTMT ratio is used as the second measure to assess the discriminant validity. Two criteria were observed in this regard (liberal and conservative). Both criteria were met as the values of HTMT ratios in all columns are <0.90 and 0.85, describing that both liberal and conservative criteria are met. Liberal criteria HTMT ratio indicates that value of HTMT should not be higher than 0.90 while conservative criteria indicate that value of HTMT should not be higher than 0.85. Table 4 illustrates the discriminant validity through HTMT ratios.

Two criteria were used to assess the model fitness, namely, the coefficient of determination ( R 2 ) and effect size ( f 2 ). Table 5 illustrates the quality criteria based on coefficient of determination. Here, it has been observed that predictors (workplace environment) along with the mediators (achievement-striving ability and employee commitment) are explaining 63% variation in employee performance; thus, predicting a good and reasonable model fitness ( 52 , 66 ). Similarly, 10% change is observed in achievement-striving ability and 8% change in employee commitment as a result of the workplace environment. Figure 2 also illustrates the coefficient of determination, and it can be assumed that these values of coefficient of determination are satisfactory ( 60 ). Table 6 illustrates the effect size in terms of f 2 . All the effect sizes have been found satisfactory and depict good quality criteria ( 52 ). In addition to this, we have also tested the model predictive relevance based on Q 2 ( 67 ) and all the values of Q 2 have been found to be higher than zero, indicating model predictive relevance.

Table 5 . Coefficient of determination.

Table 6 . Effect size.

Hypotheses Testing

At the final stage, we tested hypotheses based on t - and p -statistics (See Figures 1 and 3 ). Direct hypotheses have been tested based on direct paths while hypotheses related to the mediation relations have been tested based on indirect paths (indirect effects). Table 7 illustrates direct, indirect, and total paths while Table 8 indicates hypotheses testing status. The first hypothesis of this study (H1) related to the relationship of the workplace environment and employee performance has been found statistically significant based on t - and p -statistics and it is accepted. The regression coefficient in this regard indicates that one unit change in the workplace environment will bring 0.55 unit change in employee performance. Moreover, this path also indicates that in the presence of positive workplace environment, employee performance (task performance) moves upward and positive change in task performance is observed.

Figure 3 . Path significance.

Table 7 . Direct, indirect, and total path estimates.

Table 8 . Hypotheses testing.

Similarly, the second hypothesis (H2) of this study which is based on the relationship of the workplace environment and employee commitment has also been found statistically significant as evident from the p - and t -statistics (H2 supported). This state of affairs indicates that with the upward change in the workplace environment there will be positive change in employee commitment. It can be safely assumed that a positive workplace environment tends to promote employee commitment. The third hypothesis of this study was based on the relationship of the workplace environment and achievement-striving ability, which has also been found statistically significant as illustrated in Table 8 (H3 is supported). Thus, a positive change in the workplace environment increases the achievement-striving ability of the employees at the workplace.

While talking to mediation hypotheses, these have been tested through the indirect effects as illustrated in Table 7 . Indirect effect for the path Workplace Environment → Employee Commitment → Employee Performance has been found statistically significant ( p < 0.005) which indicates that employee workplace environment positively increases the employee commitment level which further triggers employees to demonstrate a higher level of employee performance (H4 supported). Similarly, the indirect effect in H5, i.e., Workplace Environment → Achievement striving Ability → Employee Performance has also been found statistically significant ( p < 0.05) (H5 supported). This indicates that a positive workplace environment improves employees' achievement-striving ability which further enhances their ability to show a higher level of performance.

This study analyzed the impact of employee workplace environment on employee related factors including employee commitment and achievement-striving ability of the employees. The hypothesis of this research indicated that the workplace environment had a significant impact on shaping the performance of employees. A lot of research in the past had evaluated the similar kind of relationships in which changing environments and the factors of environments of workplace had significant contribution toward the job performance of employees ( 68 ). For instance, the work in ( 10 ) stated that with an increase in per unit variance for physical and behavioral environmental factors, employee's performance was increased which supported our argument. The possible reason behind this outcome was the psychological ability of employees which molded or reshaped the behaviors of employees in case of conducive and restrictive environments of workplace. All employees may not work in the same way since they have distinct working styles due to different workplace environments. Some personnel have the greatest potential regardless of the workplace conditions, whereas others benefit from a supportive environment of the workplace ( 2 ).

The direct effects of workplace environment of employees on employee commitment and achievement-striving ability were also evaluated in this study and found significant outcomes indicating that workplace environment influences the employee-based factors as well. The direct effects on employee commitment showed that if a conducive environment at the workplace was provided, then it could develop a stronger sense of commitment in the employees toward their job and organizations. Similar kind of results were also reported by some of the previous researchers ( 69 ). In exploration of the relationship between workplace environment with employee commitment, these researchers found that if environment of workplace is suitable then it could lead to wellbeing of employees which in turn improve commitment to work by the employees. Employee commitment levels boost employee performance in firms that increase their commitment levels. Previously, companies have given their employees job security to boost their dedication to the firm and performance ( 13 ).

Another dimension to this study was exploration of the relationship between workplace environment and achievement-striving ability of employees. The results indicated similarly the positive association between workplace environment and achievement-striving ability of employees. This kind of relationship evaluation was new as no one in past had evaluated the direct association of workplace environment of employees to achievement-striving ability of employees. The majority of the workplace environment in underdeveloped countries is not safe. Unfortunately, most firms consider a safe and healthy work environment to be an unnecessary expenditure and do not invest heavily in providing a comfortable working environment ( 12 ). The indirect effects of employee commitment and achievement-striving ability between workplace environment of employees and their performance are also evaluated in this study.

Both indirect effects of employee commitment and achievement-striving ability proved to be significantly mediating the relationship of workplace environment of employees and employee performance. This indicated that if employees were more committed to their work, then association of workplace environment and employee performance would be enhanced. Similarly, if employees had good ability of achievement striving then association of workplace environment with employees' performance would also be strengthened. Few researchers have claimed that the psychological status of every commitment element differs from one employee to the other ( 14 ). It is assumed that organizational commitment and employee performance have a positive relationship, implying that employees who perceive a firm's behavior toward companions is decent (i.e., humane treatment, involvement in judgment) might very well boost their sentimental commitment with the organization and their performance in the organization ( 15 ). The results of the this study are related to the work discussed in ( 18 ) but with a limitation that they evaluated the mediating link of employee commitment along with some moderators as well.

Theoretical and Practical Implications

From a theoretical perspective, this study tends to add to the existing body of knowledge by investigating the impact of a positive work environment on employee performance which is the contribution of the study. Moreover, this study has tested two mediating mechanisms and proved that achievement-striving ability and employee commitment as a mediator increase employee task performance, which is also a unique contribution. The perception of academic staff has been documented in this study which is the contribution of the study. From the practical point of view, this study advocates that organizations should focus on the creation and provision of a positive workplace environment at the workplace to improve the task performance of the employees. Similarly, a positive work environment promotes the achievement-striving ability of the employees, so organizations should also focus on improving the achievement-striving ability of the employees through a positive workplace environment.

Limitation of the Study

Just like other studies, this study has also some limitations. The first limitation is its cross-sectional nature, which does not allow us to assume cause and effect relationships. In the future, researchers should focus on other research designs in replicating this model, which might provide deeper insights into longitudinal research design. Second, only academic staff were approached for data collection; in the future, considering other sectors can provide useful insights. Particularly, banking sector employees can be approached in future studies. Third, we have anticipated only one side of a workplace environment, while in the future, other types of workplace environments should also be tested. Further, this study in future opting larger sample size can provide more detailed and deeper insights regarding the relationship between the workplace environment and employee performance. We have used two mediating mechanisms in this study, considering other mediating variables such as job satisfaction can also be a future avenue. This model can also be tested with the moderating phenomenon in the future such as leadership styles or cultural variables such as power distance and collectivism.

Conclusions

Based on the empirical findings of this study, it can be concluded that a positive work environment promotes employee performance within organizational circuits. More specifically, the workplace environment can improve the achievement-striving ability of the employees, and employees tend to bounce back in difficult situations. Similarly, a positive work environment provides a nurturing and pleasant work environment which promotes employee commitment and employees tend to be loyal to their organizations. In addition to this, it can also be concluded that the employee commitment has the potency to enhance the task performance of the employees; because employees show a higher level of task performance when they are committed to their employer or organization. Similarly, employees with higher achievement-striving ability tend to show a higher level of task performance even in difficult situations. Further it can be endorsed that motivational activities in organizational cultures are triggered under social exchanges, and positive behaviors at workplace are promoted in shape of employee commitment. This increased commitment can result in enhanced and improved individual and organizational performance.

Data Availability Statement

The original contributions presented in the study are included in the article/supplementary material, further inquiries can be directed to the corresponding author/s.

Author Contributions

GZ: initial and final draft. SC and KK: analysis and interpretation. AN and MH: proof read, revision, and data validation. All authors contributed to the article and approved the submitted version.

Researchers Supporting Project number (RSP-2022/87), King Saud University, Riyadh, Saudi Arabia.

Conflict of Interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Publisher's Note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

1. Nor AI. Enhancing employee performance through human resource management practices: a review of literature. Eur J Hum Resour Manag Stud. (2018). doi: 10.46827/ejhrms.v0i0.492 [Unpublished].

PubMed Abstract | CrossRef Full Text | Google Scholar

2. Meng J, Berger BK. The impact of organizational culture and leadership performance on PR professionals' job satisfaction: Testing the joint mediating effects of engagement and trust. Public Relat Rev. (2019) 45:64–75. doi: 10.1016/j.pubrev.2018.11.002

CrossRef Full Text | Google Scholar

3. Berberoglu A. Impact of organizational climate on organizational commitment and perceived organizational performance: empirical evidence from public hospitals. BMC Health Serv Res. (2018) 18:399. doi: 10.1186/s12913-018-3149-z

4. Raziq A, Maulabakhsh R. Impact of Working Environment on Job Satisfaction. Procedia Econ Financ. (2015) 23:717–25. doi: 10.1016/S2212-5671(15)00524-9

5. Kuruparensothynathan P, Vimalendran G, Maryselesteena V. Impact of Working Environment on Employees' Performance: An Emprial Study of Insurance Companies . (2016). doi: 10.13140/RG.2.2.12235.54563

CrossRef Full Text

6. Narcisse S, Harcourt M. Employee fairness perceptions of performance appraisal: a Saint Lucian case study. Int J Hum Resour Manag. (2008) 19:1152–69. doi: 10.1080/09585190802051451

7. Olson EM, Slater SF, Hult GTM, Olson KM. The application of human resource management policies within the marketing organization: the impact on business and marketing strategy implementation. Ind Mark Manag. (2018) 69:62–73. doi: 10.1016/j.indmarman.2018.01.029

8. Ho JL, Powell DM, Stanley DJ. The relation between deceptive impression management and employment interview ratings: a meta-analysis. Can J Behav Sci / Rev Can des Sci du Comport. (2021) 53:164–74. doi: 10.1037/cbs0000223

9. Moslemi S, Izadbakhsh H, Zarinbal M. A new reliable performance evaluation model: IFB-IER–DEA. OPSEARCH. (2019) 56:14–31. doi: 10.1007/s12597-019-00360-9

10. Hafeez I, Yingjun Z, Hafeez S, Mansoor R, Cheema K, ur R. Impact of workplace environment on employee performance: mediating role of employee health. Bus Manag Educ. (2019) 17:173–93. doi: 10.3846/bme.2019.10379

11. Purity M, Eilish M, Ogenna U, Honorati M, Henry M. The impact of supportive supervision on the implementation of HRM processes: A mixed-methods study in Tanzania. Health Syst Policy Res. (2017) 4:1–9. doi: 10.21767/2254-9137.100066

12. Aghaji A, Burchett HED, Oguego N, Hameed S, Gilbert C. Human resource and governance challenges in the delivery of primary eye care: a mixed methods feasibility study in Nigeria. BMC Health Serv Res. (2021) 21:1321. doi: 10.1186/s12913-021-07362-8

13. Mahmood A, Akhtar MN, Talat U, Shuai C, Hyatt JC. Specific HR practices and employee commitment: the mediating role of job satisfaction. Empl Relations Int J. (2019) 41:420–35. doi: 10.1108/ER-03-2018-0074

14. Yu Q, Yen DA, Barnes BR, Huang YA. Enhancing firm performance through internal market orientation and employee organizational commitment. Int J Hum Resour Manag. (2019) 30:964–87. doi: 10.1080/09585192.2017.1380059

15. Aziz H, Othman B, Gardi B, Ahmed S, Sabir B, Burhan Ismael N, et al. Employee commitment: the relationship between employee commitment and job satisfaction. J Humanit Educ Dev . (2021) 3:54–66. doi: 10.22161/jhed.3.3.6

16. van Rossenberg YGT, Klein HJ, Asplund K, Bentein K, Breitsohl H, Cohen A, et al. The future of workplace commitment: key questions and directions. Eur J Work Organ Psychol. (2018) 27:153–67. doi: 10.1080/1359432X.2018.1443914

17. Armbrecht J, Andersson TD. The event experience, hedonic and eudaimonic satisfaction and subjective well-being among sport event participants. J Policy Res Tour Leis Events. (2020) 12:457–77. doi: 10.1080/19407963.2019.1695346

18. Lin CP, Liu CM, Chan HT. Developing job performance: mediation of occupational commitment and achievement striving with competence enhancement as a moderator. Pers Rev . (2021) ahead-of-p: doi: 10.1108/PR-04-2020-0296

19. Diamantidis AD, Chatzoglou P. Factors affecting employee performance: an empirical approach. Int J Product Perform Manag. (2019) 68:171–193. doi: 10.1108/IJPPM-01-2018-0012

20. Alsafadi Y, Altahat S. Human resource management practices and employee performance: the role of job satisfaction. J Asian Financ Econ Bus. (2021) 8:519–29. doi: 10.13106/jafeb.2021.vol8.no1.519

21. Abbasi SG, Shabbir MS, Abbas M, Tahir MS. HPWS and knowledge sharing behavior: The role of psychological empowerment and organizational identification in public sector banks. J Public Aff. (2021) 21:e2512. doi: 10.1002/pa.2512

22. Gangi F, D'Angelo E, Daniele LM, Varrone N. Assessing the impact of socially responsible human resources management on company environmental performance and cost of debt. Corp Soc Responsib Environ Manag. (2021) 28:1511–27. doi: 10.1002/csr.2179

23. Leitão M, Correia RJ, Teixeira MS, Campos S. Effects of leadership and reward systems on employees' motivation and job satisfaction: an application to the Portuguese textile industry. J Strateg Manag . (2022). doi: 10.1108/JSMA-07-2021-0158 [Epub ahead of print].

24. Ferschmann L, Bos MGN, Herting MM, Mills KL, Tamnes CK. Contextualizing adolescent structural brain development: Environmental determinants and mental health outcomes. Curr Opin Psychol. (2022) 44:170–6. doi: 10.1016/j.copsyc.2021.09.014

25. Christensen-Salem A, Mesquita LF, Hashimoto M, Hom PW, Gomez-Mejia LR. Family firms are indeed better places to work than non-family firms! Socioemotional wealth and employees' perceived organizational caring. J Fam Bus Strateg. (2021) 12:100412. doi: 10.1016/j.jfbs.2020.100412

26. Casper Ferm LE, Thaichon P. Customer pre-participatory social media drivers and their influence on attitudinal loyalty within the retail banking industry: A multi-group analysis utilizing social exchange theory. J Retail Consum Serv. (2021) 61:102584. doi: 10.1016/j.jretconser.2021.102584

27. Wang X, Zhang Z, Chun D. How does mobile workplace stress affect employee innovative behavior? The role of Work–family conflict and employee engagement. Behav Sci . (2022) 12:2. doi: 10.3390/bs12010002

28. Awada M, Becerik-Gerber B, White E, Hoque S, O'Neill Z, Pedrielli G, et al. Occupant health in buildings: Impact of the COVID-19 pandemic on the opinions of building professionals and implications on research. Build Environ. (2022) 207:108440. doi: 10.1016/j.buildenv.2021.108440

29. Li X, Li H, Skitmore M, Wang F. Understanding the influence of safety climate and productivity pressure on non-helmet use behavior at construction sites: a case study. Eng Constr Archit Manag. (2022) 29:72–90. doi: 10.1108/ECAM-08-2020-0626

30. Ali G, Anbren S, Bashir MK. Climate mitigation, low-carbon society, and dynamism of educational institutes in a low-income country. Environ Sci Pollut Res. (2018) 25:3775–84. doi: 10.1007/s11356-017-0607-9

31. Song B, Tao W. Unpack the relational and behavioral outcomes of internal CSR: Highlighting dialogic communication and managerial facilitation. Public Relat Rev. (2022) 48:102153. doi: 10.1016/j.pubrev.2022.102153

32. Ahmed M, Guo Q, Qureshi MA, Raza SA, Khan KA, Salam J. Do green HR practices enhance green motivation and proactive environmental management maturity in hotel industry? Int J Hosp Manag. (2021) 94:102852. doi: 10.1016/j.ijhm.2020.102852

33. Martela F, Hankonen N, Ryan RM, Vansteenkiste M. Motivating voluntary compliance to behavioural restrictions: self-determination theory–based checklist of principles for COVID-19 and other emergency communications. Eur Rev Soc Psychol. (2021) 32:305–47. doi: 10.1080/10463283.2020.1857082

34. Li J, Bonn MA, Ye BH. Hotel employee's artificial intelligence and robotics awareness and its impact on turnover intention: the moderating roles of perceived organizational support and competitive psychological climate. Tour Manag. (2019) 73:172–81. doi: 10.1016/j.tourman.2019.02.006

35. Roslee NLB, Goh YS. Young adult's perception towards the formation of stigma on people experiencing mental health conditions: a descriptive qualitative study. Int J Ment Health Nurs. (2021) 30:148–57. doi: 10.1111/inm.12766

36. Ahakwa I, Yang J, Agba Tackie E, Atingabili S. The influence of employee engagement, work environment and job satisfaction on organizational commitment and performance of employees: a sampling weights in PLS path modelling. SEISENSE J Manag. (2021) 4:34–62. doi: 10.33215/sjom.v4i3.641

37. Faupel S, Helpap S. Top management's communication and employees' commitment to change: the role of perceived procedural fairness and past change experience. J Appl Behav Sci. (2020) 57:204–32. doi: 10.1177/0021886320979646

38. Torlak NG, Kuzey C. Leadership, job satisfaction and performance links in private education institutes of Pakistan. Int J Product Perform Manag. (2019) 68:276–95. doi: 10.1108/IJPPM-05-2018-0182

39. Billings J, Ching BCF, Gkofa V, Greene T, Bloomfield M. Experiences of frontline healthcare workers and their views about support during COVID-19 and previous pandemics: a systematic review and qualitative meta-synthesis. BMC Health Serv Res. (2021) 21:1–17. doi: 10.1186/s12913-021-06917-z

40. Sigahi TFAC, Kawasaki BC, Bolis I, Morioka SN. A systematic review on the impacts of Covid-19 on work: contributions and a path forward from the perspectives of ergonomics and psychodynamics of work. Hum Factors Ergon Manuf Serv Ind. (2021) 31:375–88. doi: 10.1002/hfm.20889

41. Scrima F, Mura AL, Nonnis M, Fornara F. The relation between workplace attachment style, design satisfaction, privacy and exhaustion in office employees: a moderated mediation model. J Environ Psychol. (2021) 78:101693. doi: 10.1016/j.jenvp.2021.101693

42. Zhang M, The Cong P, Sanyal S, Suksatan W, Maneengam A, Murtaza N. Insights into rising environmental concern: prompt corporate social responsibility to mediate green marketing perspective. Econ Res IstraŽivanja . (2022) 1−17. doi: 10.1080/1331677X.2021.2021966

43. Ozturk A, Karatepe OM, Okumus F. The effect of servant leadership on hotel employees' behavioral consequences: work engagement versus job satisfaction. Int J Hosp Manag. (2021) 97:102994. doi: 10.1016/j.ijhm.2021.102994

44. Hoque MZ, Cui S, Lilai X, Islam I, Ali G, Tang J. Resilience of coastal communities to climate change in Bangladesh: Research gaps and future directions. Watershed Ecol Environ. (2019) 1:42–56. doi: 10.1016/j.wsee.2019.10.001

45. Chen M, Ran B, Gao X, Yu G, Wang J, Jagannathan J. Evaluation of occupational stress management for improving performance and productivity at workplaces by monitoring the health, well-being of workers. Aggress Violent Behav . (2021) 101713. doi: 10.1016/j.avb.2021.101713

46. Kordsmeyer AC, Efimov I, Lengen JC, Flothow A, Nienhaus A, Harth V, et al. Balancing social and economic factors - explorative qualitative analysis of working conditions of supervisors in German social firms. J Occup Med Toxicol. (2022) 17:4. doi: 10.1186/s12995-021-00342-y

47. Di Blasio S, Shtrepi L, Puglisi GE, Astolfi A. A cross-sectional survey on the impact of irrelevant speech noise on annoyance, mental health and well-being, performance and occupants' behavior in shared and open-plan offices. Int J Environ Res Public Heal . (2019) 16:280. doi: 10.3390/ijerph16020280

48. Saqib S, Saleem S, Bashir M, Ali A. Workplace incivility, service spirit and gossips at workplace: perception of nurses working in public sector hospitals of Pakistan. J Manag Sci. (2017) 11:329–34. Available online at: https://qurtuba.edu.pk/jms/default_files/JMS/special_edition/3%20FMM/17%20(AIC-FMM%202017)%20319-334%20Shah%20Nazawz%20Saqib%20FMM-745.pdf

Google Scholar

49. Wu Q, Saqib S, Sun J, Xiao Y, Ma W. Incivility and knowledge hiding in. Academia: mediating role of interpersonal distrust and rumination. Front Psychol. (2022) 12:769282. doi: 10.3389/fpsyg.2021.769282

50. Abun D. Employees' Self-Efficacy and Work Performance of Employees as Mediated by Work Environment. Available SSRN 3958247 (2021).

51. Krejcie R V, Morgan DW. Determining sample size for research activities. Educ Psychol Meas. (1970) 30:607–10. doi: 10.1177/001316447003000308

52. Bashir M, Shabbir R, Saleem S, Abrar M, Saqib S, Gill SH. Job-related and nonjob-related gossips among low-ranked employees in unionized service organization. Front Psychol. (2020) 11:994. doi: 10.3389/fpsyg.2020.00994

53. Sarstedt M, Ringle CM, Smith D, Reams R, Hair JF Jr. Partial least squares structural equation modeling (PLS-SEM): a useful tool for family business researchers. J Fam Bus Strateg. (2014) 5:105–15. doi: 10.1016/j.jfbs.2014.01.002

54. Podsakoff PM, MacKenzie SB, Lee JY, Podsakoff NP. Common method biases in behavioral research: a critical review of the literature and recommended remedies. J Appl Psychol. (2003) 88:879. doi: 10.1037/0021-9010.88.5.879

55. Malhotra NK, Kim SS, Patil A. Common method variance in IS research: a comparison of alternative approaches and a reanalysis of past research. Manage Sci. (2006) 52:1865–83. doi: 10.1287/mnsc.1060.0597

56. Koopmans L, Bernaards CM, Hildebrandt VH, Van Buuren S, Van der Beek AJ, De Vet HCW. Improving the individual work performance questionnaire using rasch analysis. J Appl Meas. (2014) 15:160–75. doi: 10.1037/t35489-000

57. Rhoades L, Eisenberger R, Armeli S. Affective commitment to the organization: the contribution of perceived organizational support. J Appl Psychol. (2001) 86:825. doi: 10.1037/0021-9010.86.5.825

58. Jepsen DM. A Side By Side Comparison of Two Organizational Citizenship Behavior Models and Their Measures : Expanding the Construct Domain ' S Scope. In: 11th Annu Conf Asia Pacific Decis Sci Inst. Kowloon, Hong Kong (2006). pp. 670–4.

59. Ali F, Rasoolimanesh SM, Sarstedt M, Ringle CM, Ryu K. An assessment of the use of partial least squares structural equation modeling (PLS-SEM) in hospitality research. Int J Contemp Hosp Manag. (2018) 30:514–538. doi: 10.1108/IJCHM-10-2016-0568

60. Hair JFJ, Hult GTM, Ringle CM, Sarstedt M. A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM) Sage Publications (2021).

61. Hair JF, Sarstedt M, Ringle CM. Rethinking some of the rethinking of partial least squares. Eur J Mark . (2019) 53:566–584. doi: 10.1108/EJM-10-2018-0665

62. Hair Jr JF, Sarstedt M, Hopkins L, Kuppelwieser VG. Partial least squares structural equation modeling (PLS-SEM). Eur Bus Rev. (2014) 26:106–121. doi: 10.1108/EBR-10-2013-0128

63. Mela CF, Kopalle PK. The impact of collinearity on regression analysis: the asymmetric effect of negative and positive correlations. Appl Econ. (2002) 34:667–77. doi: 10.1080/00036840110058482

64. Fornell C, Larcker DF. Structural equation models with unobservable variables and measurement error: algebra and statistics. J Market Res. (1981) 18:382–8. doi: 10.2307/3150980

65. Hair JF, Ringle CM, Sarstedt M, PLS-SEM. Indeed a silver bullet. J Mark Theory Pract. (2011) 19:139–52. doi: 10.2753/MTP1069-6679190202

66. Hair JF, Black WC, Babin BJ, Anderson RE, Tatham RL. Multivariate data analysis (Vol. 6). (2006)

67. Geisser S. The predictive sample reuse method with applications. J Am Stat Assoc. (1975) 70:320–8. doi: 10.1080/01621459.1975.10479865

68. Saragih R, Warjio W, Susanti S. The effect of leadership style, work environment and performance benefits on employee performance in BP3TKI office, indonesia using statistical method. J Educ Hum Soc Sci (JEHSS). (2021) 4:1066–1074. doi: 10.34007/jehss.v4i2.801

69. Funminiyi AK. Impact of workplace environmental factors on employee commitment: evidence from North East Nigeria. Int J Sci Res Manag. (2018) 6:575–585. doi: 10.18535/ijsrm/v6i7.em08

Keywords: employee workplace environment, employees' performance, achievement-striving, striving for achievement, analysis

Citation: Zhenjing G, Chupradit S, Ku KY, Nassani AA and Haffar M (2022) Impact of Employees' Workplace Environment on Employees' Performance: A Multi-Mediation Model. Front. Public Health 10:890400. doi: 10.3389/fpubh.2022.890400

Received: 05 March 2022; Accepted: 08 April 2022; Published: 13 May 2022.

Reviewed by:

Copyright © 2022 Zhenjing, Chupradit, Ku, Nassani and Haffar. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Kuo Yen Ku, ykkuo@sce.pccu.edu.tw

Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.

• Open access
• Published: 03 June 2024

The influence of psychosocial work environment, personal perceived health and job crafting on nurses’ well-being: a cross-sectional survey study

• Xin Zhang 1 ,
• Chen Zhang 2 ,
• Jiayan Gou 1 &
• Shih-Yu Lee 3  

BMC Nursing volume  23 , Article number:  373 ( 2024 ) Cite this article

173 Accesses

Metrics details

The World Health Organization urged governments to prioritize the health and work well-being of nursing staff by promoting a positive working environment. A safe and healthy physical and psychosocial work environment is a basic human right for nurses. Job crafting is a necessary skill when facing challenging working conditions.

This cross-sectional correlational research based on the Job Demands-Resources Model aimed to explore the correlation between psychosocial work environment and work well-being among nurses working in the intensive care unit (ICU) and determine whether personal perceived health could mediate the relationship and whether job crafting can moderate the mediating effect. The study hypothesized that: 1. The psychosocial work environment would impact nurses' work well-being; 2. Personal perceived health would play a role as a mediator in the relationship between psychosocial work environment and work well‐being; 3. Job crafting would moderate the relationship between personal perceived health and work well‐being.

A total of 655 registered nurses (RNs) from 7 ICUs in a teaching hospital in Beijing participated in this study. The RNs completed a battery questionnaire measuring their health, psychosocial work environment, well-being, and job crafting. PROCESS macros analysis was used to test mediating and moderating effects.

Personal perceived health mediated the relationship between psychosocial work environment and work well-being (b = 0.012, 95% CI [0.008, 0.016]). The moderated mediated analysis revealed that job crafting moderated perceived health’s impact on work well-being (b = -0.007, 95% CI [− 0.010, − 0.003]).

A better psychosocial work environment with well-designed work organization and job content through job crafting could positively impact nurses’ health and work well-being.

Peer Review reports

Introduction

“A safe and healthy working environment is a fundamental right at work,” said Gilbert F. Houngbo, the International Labour Organization (ILO) Director-General [ 1 ]. The World Health Organization (WHO) has also urged governments to recognize the importance of creating a positive working environment and committing to promoting the health and work well-being of nursing practitioners [ 2 ]. A positive working environment encompasses reducing absenteeism and improving retention rates. It is essential to understand that motivation plays a significant role in determining the quality of care [ 3 ]. An individual's work well-being is their perception of cognitive, emotional, health, and social conditions related to their profession [ 4 ]. A demanding work environment can quickly increase work-related stress, reduce work well-being, negatively impact physical and mental health, and lead to burnout [ 5 , 6 , 7 ]. About the psychosocial work environment factors (job demands, job control, and social support), previous researches have highlighted that workplace social support (coworker and supervisor support) is positively related to well-being but negatively related to burnout (high job demand and low job control) on health among healthcare workers [ 8 , 9 ], In existing studies on nurses' well-being, the high-stress environment of the Intensive Care Unit (ICU) has been overlooked. However, study showed that ICU nurses often work extended hours and care for critically ill patients, which can result in physical and mental exhaustion, as well as burnout [ 10 ].

Over the past three years, most of the research on ICU nurses' struggles to adapt to challenging situations has been descriptive and primarily focused on external resources, revealing weaknesses in the healthcare systems in terms of staffing shortages, limited resources, lack of support, and access to training associated with pandemic [ 10 , 11 , 12 , 13 ]. Nursing staff in high-demand and low-resource work environments are particularly vulnerable to adverse impacts [ 14 , 15 ]. These effects can lead to nursing staff withdrawing from the workplace, which in turn results in poor quality of care and impaired clinical decision-making [ 11 , 13 , 16 ] and ultimately jeopardizes patient safety [ 10 ]. Recently, studies suggest that implementating organizational citizenship behaviour among nurses can inhibit negative occurrence that may impact patients' health and well-being [ 17 ]. Furthermore, nurse differentiation and job crafting are effective retention strategies [ 18 ]. Overall, ICU nurses worldwide are not adequately prepared to handle the job demands brought on by the crisis, significantly impacting their ability to provide optimal patient care [ 19 ].

Based on the job demands‐resources theory (JD‐R) [ 20 ], which defines working conditions (job characteristics) from the perspective of job demands and job resources and includes two processes: the health-impairment process and the work-related incentive process-related well-being (consisting of burnout and work engagement). For individuals, a positive work environment is achieved through balancing job demands and resources [ 21 ]. Previous studies indicate that ICU nurses successfully utilize internal psychological mechanisms to adapt to work demands, switch job resources to cope with the situation, and maintain work well-being [ 6 , 22 , 23 ]. Some nurses utilized problem-focused coping strategies, such as seeking information and social support; others used emotion-focused coping methods, such as positive thinking, relaxation techniques, and peer support, to cope with challenging situations [ 24 , 25 , 26 ]. It is important to consider individual needs and situational factors when examining nurses' ability to adapt to work demands, as the work environment can positively and negatively impact nurses.

Job crafting refers to an active process in which employees redefine and shape their roles to increase motivation and engagement in their tasks [ 27 ]. Job crafting involves employees proactively adjusting the demands and resources of their jobs to align with their preferences and strengths. Individuals and the work environment can influence job crafting as individuals modify their behaviors to balance work demands and resources [ 28 ]. Ensuring a healthy environment in the workplace can enhance productivity, safety, and comfort for employees [ 29 ]. Research confirmed that job crafting training is an effective method to assist employees in aligning job demands and resources. This can increase work engagement and performance, reduce fatigue, and improve health outcomes [ 30 ]. There has been an increase in ward-level crafting which is related to an individual-level increase in work engagement. Nursing managers who create an environment that encourages crafting task boundaries for team members’ growth are likely to contribute to increasing nurses' work engagement [ 31 ]. For ICU nurses, job crafting can be a valuable skill to help cope with workload and balance work and personal life in the workplace. According to recent studies, individuals who experience positive emotions, exhibit higher job satisfaction, and lower levels of burnout are more likely to thrive in their workplace [ 32 , 33 ]. Job crafting is a crucial factor that protects nurses from the adverse effects of work stress and burnout. It can significantly improve their well-being and create a positive psychosocial work environment. However, our understanding of job-crafting behaviors among ICU nurses is limited, and we still need to determine the individual and environmental factors that influence job crafting.

This study aimed to explore how personal perceived health (self-rated health, burnout, stress), as well as the psychosocial work environment (demands at work, work organization and job contents, interpersonal relations and leadership, and work-individual interface), relate to work well-being and job crafting among ICU nurses. Based on the JD‐R model [ 5 , 34 ], the secondary purpose was to explore the potential mechanism of this connection with personal perceived health as a mediator and job crafting as a moderator. We hypothesized that: 1. the psychosocial work environment would impact nurses' work well-being. 2. Nurses' personal perceived health would play a role as a mediator in the relationship between psychosocial work environment and work well‐being. 3. Job crafting would moderate the relationship between personal perceived health and work well‐being.

Study design and participants

This cross-sectional correlational exploratory study recruited participants from 7 ICUs of a medical center in Beijing with 12-h rotating shifts. The inclusion criteria were Registered Nurses (RN) providing direct patient care in the ICU and nurses who self-reported being pregnant with a history of mental illness were excluded. Based on the N:q rule [ 35 ] in the context of Structural Equation Modeling, it is appropriate to have N:q values ranging from 10:1 (10 observations per one estimated parameter) to even 20:1 seem appropriate. In this study, there are 12 estimated parameters (N:q values = 20:1), which means that 240 participants were needed. From May to August 2022, a convenient sample of 655 ICU RNs was recruited, and the study was completed. The Institutional Review Board approved the study at the research site (No. 2022030).

Sociodemographic

Sociodemographic data included age, gender, educational level, marital status, work hours, and length of time as a nurse and in the current ICU.

• Job crafting

The Job Crafting Scale (JCS) [ 36 ] was used to assess job crafting, with a 21-item, 5-point Likert-type scale (1 = never, 5 = very often), where a higher mean score indicates higher job crafting behaviors. The JCS comprises four subscales that measure four aspects of job crafting, including increasing structural work resources ( n  = 5), decreasing hindering job demands ( n  = 6), increasing social job resources ( n  = 5), and increasing challenging job demands ( n  = 5). The Cronbach's alpha of the JCS was 0.89 [ 36 ]. The Chinese version of the JCS was unavailable, so the first author (XZ) obtained permission from Tims and put together a team to translate the JCS. They followed the recommended procedures for cross-cultural research [ 37 ] and used forward- and backward-translate [ 38 ] methods to ensure that the original and target language conveyed the same meaning and content equivalence. The Cronbach's alpha of the Chinese JCS was 0.89 in the present study, and the four subscales ranged from 0.85 to 0.91.

Psychosocial work environment and personal perceived health

The Copenhagen Psychosocial Questionnaire (COPSOQ) II-short Chinese version [ 39 , 40 ] was utilized in this study as a 40-item Likert-type scale to evaluate the psychosocial work environment and personal health. The psychosocial work environment was assessed in Part 1 through four dimensions: (1) demands at work, (2) work organization and job contents, (3) interpersonal relations and leadership, and (4) work-individual interface. Personal perceived health was assessed in Part 2 through three dimensions: (1) self-rated health, (2) burnout, and (3) stress. The intensity or frequency of each question was measured on a score range of 0 to 100, where high scores in part 1 subscales indicate favorable psychosocial factors. In contrast, high scores in part 2 subscales suggest unfavorable factors. For example, a higher self-rated health indicates poor health conditions. The Cronbach's alpha of the COPSOQ was 0.83 in the current study [ 39 , 40 ].

Work well-being

The work well-being was measured by the Workplace Well-Being (WWB), a subscale of the Employ Well-being scale [ 41 ]. The WWB comprises six items scored on a 7-point Likert-type scale (1 = totally disagree, 7 = totally agree), with higher scores indicating higher levels of work well-being. The Cronbach's alpha of this subscale was 0.93 in the current study [ 41 ].

Data collection

The Nursing department at the research site used WeChat, a Chinese social media app, to send recruitment messages to ICU nurses. All the potential participants were informed that whether they participated in the study, they would not lose any benefits as an employee at the hospital, and completing the questionnaires was entirely voluntary. Nurses won't receive any benefit from their participation. Informed consent forms and completed questionnaires were submitted through a secure online platform ( www.wjx.cn ). All the contact information and questionnaire data were stored separately to ensure anonymity and confidentiality.

Data analysis

Data were analyzed using the SPSS 24.0 version. All data were evaluated to ensure statistical assumptions were met before substantive analysis. Before data analysis, all data were evaluated to ensure that all met statistical assumptions. Descriptive statistics were used to describe sample characteristics and the main variables, including mean ± standard deviation (SD), median (P 25 , P 75 ), range, and percentage. Pearson's correlation analyses explored the associations between the dependent variable (work well-being) and the independent variables. We utilized Hayes' PROCESS macro program [ 42 ] and bootstrapping to assess the significance of the moderated mediation model, which is a reliable method for evaluating the magnitude of conditional indirect effects [ 43 ]. According to our hypothesized model, we used Model 14 to examine the indirect effects of the psychosocial work environment on work well‐being through personal perceived health and job crafting. We used the bias-corrected bootstrapping method to generate 5000 random samples with a 95% bias corrected confidence interval (CI). Bootstrap CIs were used to determine the statistical significance of Model 14. If the CIs did not contain zero, the effect was considered significant.

Descriptive of the study participants and the variables

The mean age of the 655 study participants (Table  1 ) was 30.22 years old ( SD  = 5.48). The majority of them were female (92.5%), single (41.8%), and with a bachelor's or higher degree (72.4%). They had 7 (median) years of RN experience and 6 (median) years of current ICU experience. All study participants worked 12-h shifts (day and night within a week). Theoretically, education could impact an individual’s perceptions and behaviors. Therefore, the population was divided into two groups: diploma and at least college education. We compared the differences between the two groups to examine the potential impact of education on individuals' job crafting and perceived health (self-rated health, burnout, and stress). However, there is no significant difference ( p  > 0.05). Their perceptions of the psychosocial work environment (M = 65.05, SD  = 8.45) and personal perceived health (M = 45.31, SD  = 20.89) were moderate; however, their work well-being and job crafting scores were at a higher level (Table  2 ). Each variable’s skewness ranged from − 1.35 to 0.35, while kurtosis ranged from − 1.01 to 1.77. According to the reference values of an absolute skewness value ≤ 2 or an absolute kurtosis ≤ 4, the normality assumptions of the variables were met.

Linking personal perceived health, job crafting, and psychosocial work environment to work well-being: The moderated mediation model

Socidemographics were not significantly associated with the dependent and independent variables. The correlations between independent variables (personal perceived health, psychosocial work environment, job crafting), and dependent variable (work well-being) are detailed in Table  3 .

We aimed to determine whether the link between psychosocial work environment (COP subscale 1–4) and work well-being was mediated by personal perceived health (M) and whether job crafting (W) support influenced this relationship (Table  4 ). After controlling for the effect of mediator and moderator, it was found that a positive and significant relationship existed between the psychosocial work environment (including COP subscale 2 = work organizations and job contents and COP subscale 3 = interpersonal relations and leadership) and work well-being ( b  = 0.024, p  < 0.001). The findings support Hypothesis 1. The analysis showed that the poor psychosocial work environment was significantly associated with personal perceived health ( b  = -0.615, p  < 0.001). Furthermore, better personal perceived health (M) was linked to high levels of work well-being ( b  = 0.021, p  < 0.001). There was a positive indirect effect of the psychosocial work environment on work well-being through better personal perceived health (M) ( b  = 0.012, 95% CI [0.008, 0.016]). The findings support Hypothesis 2. The indexes of moderated mediation were found to be significant ( b  = -0.007, 95% CI [− 0.010, − 0.003]). This suggests that the effect of personal perceived health on work well-being varies with job crafting (W). In the moderated mediation model, the interaction between personal perceived health and job crafting was significant ( b  = 0.011, 95% CI [0.006, 0.015]). The findings support Hypothesis 3. The final moderated mediation model (R 2  = 0.41, F = 113.77, p  < 0.01) is presented in Fig.  1 .

The final moderated mediation model. Note. ** p  < 0.01. Psychosocial work environment: including COP subscale 2 = work organizations and job contents; COP subscale 3 = interpersonal relations and leadership. Path a = the effect of psychosocial work environment dependency on personal perceived poor health, path b = the effect of personal perceived poor health dependency on work well-being, path c = the effect of psychosocial work environment dependency on work well‐being, path d = the conditional effect of job crafting on personal perceived poor health to work well‐being

The study was conducted after the 3rd year of the COVID‐19 pandemic, capturing the effects of the context on ICU nurses' work well‐being. The findings revealed that a positive psychosocial work environment was associated with nurses' work well‐being (Hypothesis 1), and personal perceived health might mediate this association (Hypothesis 2). Moreover, job crafting could moderate the association between personal perceived health and work well‐being for ICU nurses (Hypothesis 3). This study's work well-being and job crafting level among ICU nurses is slightly higher than other studies [ 44 , 45 , 46 ]. The majority of the study participants were female, which is in line with the current nursing workforce in China. It has been identified that gender can influence thinking style [ 47 ]; therefore, conducting gender-specific studies could help prevent gender bias and lead to the development of tailored-made interventions to enhance work well-being. This finding suggests that the nurses in this study can redesign their work to better align with their skills and needs, enabling them to adapt and respond to changes and challenges in their work environment more effectively [ 48 ].

Encourage job crafting by recognizing personal successes and patient progress

The study’s findings have demonstrated that the psychosocial work environment significantly impacts the health and well-being of ICU nurses. The higher scores of increasing structural job resources and reduced job demands mean that ICU nurses can actively strive for work autonomy and have high expectations and requirements for reducing unnecessary duplication of work and excessive non-nursing work. This highlights the importance of nursing managers optimizing workflow to improve work efficiency and provide nurses with adequate resources [ 49 ]. Besides, the lowest score for increased job demands is consistent with findings from multiple studies [ 45 , 50 , 51 ], which may be related to a heavy ICU workload, critically ill patients, nurses tending to be stable and safe, and a lack of willingness to take the initiative to face challenges. ICU nurses may feel tired and stressed after encountering high job demands, requiring more interest and motivation for more challenging tasks.

The previous study showed that a structured psychosocial work environment with well-designed work organization and job content (WOJC) can improve psychological health and well-being, productivity, and retention [ 52 ]. The study showed that a WOJC that aligns with the workers' capabilities and skills can benefit both individuals and the organization [ 52 ]. According to the current study, the "work organizations and job contents" significantly positively impact work well-being (Fig.  1 ). Furthermore, most nurses believe that their professional identity comes from recognizing patients and their disease outcomes, which drives the redesigned behaviors of ICU nurses' work. Nursing managers should encourage their staff to achieve individual success and provide training on improving work efficiency by managing their time effectively and optimizing workflow. It is important for nurses to constantly learn new skills, knowledge, and techniques to cope with potential stress and challenges that may arise in their work. The findings of this study also suggest that "interpersonal relations and leadership" in the work environment positively affect ICU nurses' work well-being. Although work well-being is self-perceived by ICU nurses, its occurrence and mechanism of action are mainly influenced by the leadership style of nursing managers [ 46 ]. If the leadership style is more inclusive, open, and practical, it can improve job performance by increasing personal work engagement and work well-being.

Job crafting can decrease the adverse impact of the work environment on personal health

The results of this study suggest that ICU nurses’ personal perceived health can have a mediating effect on their psychological work environment and work well-being. That means nurses' work well-being can be indirectly improved by improving the work environment through enhancing personal resources. ICU nurses face numerous challenges, such as fast-paced nursing work, high pressure, frequent night shifts, prolonged standing, and managing critically ill patients with variable medical conditions. These challenges result in both physical and psychological stress [ 53 ]. Given the adverse impact of the work environment on nurses' health, we suggest setting up a proactive system that can promptly identify, report, and monitor health-related outcomes. To achieve this, a thorough and rigorous evaluation, efficient referral mechanisms, and conservative treatment options must be established to facilitate a safe return to work. Besides, it is imperative to have sufficient staffing and well-equipped facilities to ensure the health and safety of nurses in the workplace. Finally, according to a WHO global report, clear communication and leadership are also among the social determinants of health [ 54 ].

The results also show that job crafting moderates the relationship between personal perceived health and work well-being. Job crafting can moderate the mediated pathway between psychosocial work environment, personal perceived health, and work well-being. It can be understood that job crafting allows ICU nurses to make adaptive adjustments when facing different work environments. If the psychosocial work environment influences an individual's perceived health, job crafting can be considered an adaptive strategy to help individuals better acclimate to such environments. Due to positive individual factors, ICU nurses who engage in job crafting behaviors experience better-perceived health and increased ability to cope with stress and burnout. In the JD-R model, nurses can use their resources to acquire more work resources by actively participating in training and communicating with external parties [ 55 ]. Research showed that nurses with high levels of self-efficacy are confident, proactive, and utilize their strengths to conduct job crafting and seek resources at work [ 56 , 57 , 58 ]. Previous studies [ 59 , 60 ] have shown that intervention programs such as job-crafting diaries can effectively enhance ICU nurses' self-efficacy and improve their job-crafting behaviors. In addition, it is important to encourage ICU nurses to participate in the decision-making process. Enhancing their voice and sense of participation is essential for improving their work engagement.

Effective supervisor support create a conducive workplace

Research confirmed that transformational and servant leadership styles have a significant positive correlation with job crafting, while authoritarian leadership has a significant negative correlation [ 61 , 62 ]. Research also showed young nurses tend to score higher in job crafting, which suggests that they are more dedicated to their work [ 63 , 64 ]. This is particularly true for new nurses, who are often more curious and enthusiastic about their work environment and its content. They are likelier to maintain a positive attitude, actively seek new learning opportunities, and explore the workplace. It is recommended that nursing managers pay attention to individual nurse characteristics, encourage job crafting among young nurses, and provide personalized training and support to improve the alignment between individuals and the job roles. Senior ICU nurses have extensive clinical experience and are highly adaptable. Managers should provide more career development opportunities to stimulate their work enthusiasm and motivation. Nursing managers should adopt an effective leadership style and provide nurses with the necessary resources and conditions that create a conducive work environment. They should also demonstrate tolerance, support, and guidance toward nurses' job-crafting behaviors. By doing so, they can maximize the potential effectiveness of individual job crafting and achieve a win–win situation for both individuals and organizations. Ultimately, this will help to improve the quality of ICU nursing care and medical services.

Implications for practice

Based on our research findings, ICU nurses can adopt positive job crafting behaviors, such as flexibly adjusting work styles, organizing work tasks, and actively adapting to changes in the work environment to better maintain individual health perception and improve work well-being. In addition, we recommend that nursing managers prioritize and enhance the psychosocial work environment, transforming leadership styles to be more transformative and service-oriented. And we advocate for the encouragement and support of nurses in job crafting to make changes in their job, elevating their autonomy and adaptability through training and communication initiatives and make their jobs more meaningful. We propose establishing a health monitoring and support system coupled with timely health intervention measures to enhance individual perceived health. These suggestions are poised to assist in optimizing nurses' work experiences and improving their overall well-being in practice.

Limitations

Although this study provides valuable insights into the work well-being of ICU nurses, it’s important to note that the results are based on a single data collection time point, which may limit their internal validity and generalizability. Secondly, selection bias is a common limitation in cross-sectional studies that could affect the causality of observed relationships. Therefore, future longitudinal studies are needed to confirm the findings. Thirdly, there may be bias introduced by excluding nurses who are pregnant or have a history of mental illness. To enhance the robustness of the findings, it is recommended that future studies be conducted with multiple sites and longitudinal research.

The study found that nurses’ work well-being was positive influenced by the good psychosocial work environment, and negitive influenced by their poor health. Job crafting behaviors could also modulate the pathway from nurses' perceived health to work well-being. ICU nurses who engaged in job crafting behaviors were more likely to experience positive work well-being, which could help them proactively manage work stress and challenges. Further research is needed to identify effective strategies for promoting job-crafting behaviors among ICU nurses.

Availability of data and materials

The datasets generated and/or analysed during the present study are not publicly available due to the data being proprietary and confidential records of Chinese Academy of Medical Sciences & Peking Union Medical College, but are available from the corresponding author on reasonable request.

Working under the sun causes 1 in 3 deaths from non-melanoma skin cancer, say WHO and ILO. https://www.who.int/news/item/08-11-2023-working-under-the-sun-causes-1-in-3-deaths-from-non-melanoma-skin-cancer--say-who-and-ilo.Accessed 19 Apr, 2024.

WHO. Occupational health: health workers. https://www.who.int/news-room/fact-sheets/detail/occupational-health--health-workers.Accessed 20 Nov, 2023.

Achury Saldaña DM, Achury Beltrán LF, Rodríguez Colmenares SM, Alvarado Romero HR, Cavallo E, Ulloa AC, Merino V, da Silva BM, Andrade Fonseca D, Muñoz Acuña D, et al. Professional profile and work conditions of nurses working in intensive care units: A multicentre study. J Clin Nurs. 2022;31(11–12):1697–708. https://doi.org/10.1111/jocn.16026 .

Article   PubMed   Google Scholar  

Pan Y, Aisihaer N, Li Q, Jiao Y, Ren S. Work-Family Conflict, Happiness and Organizational Citizenship Behavior Among Professional Women: A Moderated Mediation Model. Front Psychol. 2022;13:923288. https://doi.org/10.3389/fpsyg.2022.923288 .

Article   PubMed   PubMed Central   Google Scholar  

Bakker AB, Demerouti E. Job demands–resources theory: Taking stock and looking forward. J occup health psychol. 2017;22(3):273.

Jarden RJ, Sandham M, Siegert RJ, Koziol-McLain J. Strengthening workplace well-being: perceptions of intensive care nurses. Nurs Crit Care. 2019;24(1):15–23.

Shin S-H, Lee E-H. Development and validation of a quality of healthy work environment instrument for shift nurses. BMC Nurs. 2024;23(1):37. https://doi.org/10.1186/s12912-023-01672-4 .

Gleason F, Malone E, Wood L, Baker SJ, Hollis RH, Richman JS, Chu DI, Lindeman B. The Job Demands-Resources Model as a Framework to Identify Factors Associated With Burnout in Surgical Residents. J Surg Res. 2020;247:121–7. https://doi.org/10.1016/j.jss.2019.10.034 .

Nordgren Selar A, Gagné M, Hellgren J, Falkenberg H, Sverke M. Compensation profiles among private sector employees in Sweden: Differences in work-related and health-related outcomes. Front Psychol. 2023;14:949711. https://doi.org/10.3389/fpsyg.2023.949711 .

Labrague LJ, de Los Santos JAA. Resilience as a mediator between compassion fatigue, nurses’ work outcomes, and quality of care during the COVID-19 pandemic. Appl nurs res. 2021;61:151476.

Gómez-Salgado J, Domínguez-Salas S, Romero-Martín M, Romero A, Coronado-Vázquez V, Ruiz-Frutos C. Work engagement and psychological distress of health professionals during the COVID-19 pandemic. J nurs manag. 2021;29(5):1016–25.

González-Gil MT, González-Blázquez C, Parro-Moreno AI, Pedraz-Marcos A, Palmar-Santos A, Otero-García L, Navarta-Sánchez MV, Alcolea-Cosín MT, Argüello-López MT, Canalejas-Pérez C. Nurses’ perceptions and demands regarding COVID-19 care delivery in critical care units and hospital emergency services. Intensive Crit Care Nurs. 2021;62:102966.

Lee H, Lee SE, Sang S, Morse B. The lived experience of nurses who volunteered to combat the COVID-19 pandemic in South Korea: A qualitative phenomenological study. J Nurs Manag. 2022;30(4):864–71.

LeGal P, Rhéaume A, Mullen J. The long-term effects of psychological demands on chronic fatigue. J nurs manag. 2019;27(8):1673–81.

Roelen CAM, van Hoffen MFA, Waage S, Schaufeli WB, Twisk JWR, Bjorvatn B, Moen BE, Pallesen S. Psychosocial work environment and mental health-related long-term sickness absence among nurses. Int Arch Occup Environ Health. 2018;91(2):195–203. https://doi.org/10.1007/s00420-017-1268-1 .

Labrague LJ, de Los Santos JAA. Fear of Covid-19, psychological distress, work satisfaction and turnover intention among frontline nurses. J nurs manag. 2021;29(3):395–403.

Mazzetti G, Sciolino L, Guglielmi D, Mongardi M, Nielsen K, Dawson J. Organizational citizenship behaviour as a protective factor against the occurrence of adverse nursing-sensitive outcomes: A multilevel investigation. J Nurs Manag. 2022;30(8):4294–303. https://doi.org/10.1111/jonm.13827 .

Felder M, Kuijper S, Allen D, Bal R, Wallenburg I. Job crafting as retention strategy: An ethnographic account of the challenges faced in crafting new nursing roles in care practice. Int J Health Plann Manage. 2024;39(3):722–39. https://doi.org/10.1002/hpm.3780 .

Gamble K, Murthy S, Silverberg SL, Gobat N, Puchalski Ritchie LM. Canadian critical care nurses experiences on the front lines of the COVID-19 pandemic: a qualitative descriptive study. BMC Nurs. 2022;21(1):330. https://doi.org/10.1186/s12912-022-01105-8 .

Bakker AB, Demerouti E. The job demands-resources model: State of the art. Journal of managerial psychology. 2007;22(3):309–28.

Article   Google Scholar  

Brauchli R, Jenny GJ, Füllemann D, Bauer GF. Towards a Job Demands-Resources Health Model: Empirical Testing with Generalizable Indicators of Job Demands, Job Resources, and Comprehensive Health Outcomes. Biomed Res Int. 2015;2015:959621. https://doi.org/10.1155/2015/959621 .

Jarden RJ, Sandham M, Siegert RJ, Koziol-McLain J. Intensive care nurse conceptions of well-being: a prototype analysis. Nurs Crit Care. 2018;23(6):324–31.

Peiró JM, Kozusznik MW, Soriano A.From Happiness Orientations to Work Performance: The Mediating Role of Hedonic and Eudaimonic Experiences. Int J Environ Res Public Health. 2019,16(24). https://doi.org/10.3390/ijerph16245002 .

Bianchi D, Baiocco R, Lonigro A, Pompili S, Zammuto M, Di Tata D, Morelli M, Chirumbolo A, Di Norcia A, Cannoni E, et al. Love in Quarantine: Sexting, Stress, and Coping During the COVID-19 Lockdown. Sex Res Social Policy. 2023;20(2):465–78. https://doi.org/10.1007/s13178-021-00645-z .

Mao A, Tam HL, Cheong PL, Van IK."You Need to Get Over the Difficulties and Stand Up Again"-A Qualitative Inquiry into Young Nurses' Coping with Lateral Violence from the Feminist Perspective. Int J Environ Res Public Health. 2021,18(13). https://doi.org/10.3390/ijerph18137167 .

Muazzam A, Naseem F, Shakil M, Visvizi A, Klemens J.Surviving COVID-19: Biopsychosocial Impacts, Death Anxiety, and Coping Strategies. Vaccines (Basel). 2023,11(3). https://doi.org/10.3390/vaccines11030705 .

Oubibi M, Fute A, Xiao W, Sun B, Zhou Y. Perceived organizational support and career satisfaction among Chinese teachers: the mediation effects of job crafting and work engagement during COVID-19. Sustainability. 2022;14(2):623.

Article   CAS   Google Scholar  

Jarden RJ, Sandham M, Siegert RJ, Koziol-McLain J. Conceptual model for intensive care nurse work well-being: a qualitative secondary analysis. Nurs Crit Care. 2020;25(2):74–83.

Stratton E, Lampit A, Choi I, Calvo RA, Harvey SB, Glozier N. Effectiveness of eHealth interventions for reducing mental health conditions in employees: A systematic review and meta-analysis. PLoS ONE. 2017;12(12):e0189904. https://doi.org/10.1371/journal.pone.0189904 .

Article   CAS   PubMed   PubMed Central   Google Scholar  

Shi Y, She Z, Li D, Zhang H, Niu K. Job crafting promotes internal recovery state, especially in jobs that demand self-control: a daily diary design. BMC Public Health. 2021;21(1):1889. https://doi.org/10.1186/s12889-021-11915-1 .

Iida M, Sakuraya A, Watanabe K, Imamura K, Sawada U, Akiyama H, Komase Y, Miyamoto Y, Kawakami N. The association between team job crafting and work engagement among nurses: a prospective cohort study. BMC Psychol. 2024;12(1):66. https://doi.org/10.1186/s40359-024-01538-7 .

Jing S, Li Z, Stanley DM, Guo X, Wenjing W. Work-family enrichment: influence of job autonomy on job satisfaction of knowledge employees. Front Psychol. 2021;12:726550.

Molero Jurado MDM, Pérez-Fuentes MDC, Barragán Martín AB, Gázquez Linares JJ, Oropesa Ruiz NF, Simón Márquez MDM. Emotional intelligence components as predictors of engagement in nursing professionals by sex. Healthcare (Basel). 2020;8(1):42. https://doi.org/10.3390/healthcare8010042 .

Bakker AB. Job crafting among health care professionals: The role of work engagement. J Nurs Manag. 2018;26(3):321–31. https://doi.org/10.1111/jonm.12551 .

Jackson DL. Revisiting sample size and number of parameter estimates: Some support for the N: q hypothesis. Structural equation modeling. 2003;10(1):128–41.

Tims M, Bakker AB, Derks D. Development and validation of the job crafting scale. Journal of vocational behavior. 2012;80(1):173–86.

Flaherty JA, Gaviria FM, Pathak D, Mitchell T, Wintrob R, Richman JA, Birz S. Developing instruments for cross-cultural psychiatric research. J Nerv Ment Dis. 1988;176(5):257–63.

Article   CAS   PubMed   Google Scholar  

Brislin RW. Back-translation for cross-cultural research. Journal of cross-cultural psychology. 1970;1(3):185–216.

Li J, Fu H, Hu Y, Shang L, Wu Y, Kristensen TS, Mueller BH, Hasselhorn HM. Psychosocial work environment and intention to leave the nursing profession: results from the longitudinal Chinese NEXT study. Scand J Public Health. 2010;38(3 Suppl):69–80. https://doi.org/10.1177/1403494809354361 .

Yeh WY, Cheng Y, Chen CJ, Hu PY, Kristensen TS. Psychometric properties of the Chinese version of Copenhagen burnout inventory among employees in two companies in Taiwan. Int J Behav Med. 2007;14(3):126–33. https://doi.org/10.1007/bf03000183 .

Zheng X, Zhu W, Zhao H, Zhang C. Employee well-being in organizations: Theoretical model, scale development, and cross-cultural validation. J Organ Behav. 2015;36(5):621–44.

Hayes AF. PROCESS: A versatile computational tool for observed variable mediation, moderation, and conditional process modeling. In.: University of Kansas, KS; 2012.

Google Scholar  

Field A. Discovering statistics using IBM SPSS statistics[M]. sage, 2013.

Baghdadi NA, Farghaly Abd-El Aliem SM, Alsayed SK.The relationship between nurses' job crafting behaviours and their work engagement. J Nurs Manag. 2021,29(2):214–219. https://doi.org/10.1111/jonm.13141 .

Cheng H, Ding Y, Wang B. A validation study of the Job Crafting Scale among nurses in public hospitals in China. J Nurs Manag. 2020;28(5):1021–9.

Işik MT, Özdemir RC. Intensive care nurses' fears about returning to work after recovering from COVID-19: A Qualitative Study. Indian J Crit Care Med. 2023;27(4):283–8. https://doi.org/10.5005/jp-journals-10071-24430 .

Rogers P, Hattersley M, French CC. Gender role orientation, thinking style preference and facets of adult paranormality: A mediation analysis. Conscious Cogn. 2019;76:102821. https://doi.org/10.1016/j.concog.2019.102821 .

Shen ZM, Wang YY, Cai YM, Li AQ, Zhang YX, Chen HJ, Jiang YY, Tan J. Thriving at work as a mediator of the relationship between psychological resilience and the work performance of clinical nurses. BMC Nurs. 2024;23(1):194. https://doi.org/10.1186/s12912-024-01705-6 .

Ferramosca FMP, De Maria M, Ivziku D, Raffaele B, Lommi M, Tolentino Diaz MY, Montini G, Porcelli B, De Benedictis A, Tartaglini D et al .Nurses' Organization of Work and Its Relation to Workload in Medical Surgical Units: A Cross-Sectional Observational Multi-Center Study. Healthcare (Basel).2023,11(2). https://doi.org/10.3390/healthcare11020156 .

Cheng H, Yang H, Ding Y, Wang B. Nurses’ mental health and patient safety: An extension of the Job Demands-Resources model. J Nurs Manag. 2020;28(3):653–63.

Dominguez LC, Stassen L, de Grave W, Sanabria A, Alfonso E, Dolmans D. Taking control: Is job crafting related to the intention to leave surgical training? PloS one. 2018;13(6):e0197276.

Javaid MU, Sohail M, Bano S, Ibrahim AM. Copenhagen psychosocial "Work organization and job content" as a higher-order construct in relation to workers' health: The Moderating Role of Leadership Quality. Risk Manag Healthc Policy. 2023;16:1721–30. https://doi.org/10.2147/RMHP.S419551 .

Xue X, Qiao J, Li Y, Zhang Q, Wang Y, Wang J, Xu C. Relationship between work engagement and healthy work environment among Chinese ICU nurses: The mediating role of psychological capital. Nurs Open. 2023;10(9):6248–57. https://doi.org/10.1002/nop2.1866 .

WHO. Social determinants of health: Report by the Director-General. https://apps.who.int/gb/ebwha/pdf_files/EB152/B152_22-en.pdf.Accessed 21 Nov, 2023.

Chu X, Zhang L, Li M. Nurses’ strengths use and turnover intention: The roles of job crafting and self-efficacy. J Adv Nurs. 2022;78(7):2075–84.

Durand F, Bourgeault IL, Hebert RL, Fleury M-J. The role of gender, profession and informational role self-efficacy in physician–nurse knowledge sharing and decision-making. J Interprof Care. 2022;36(1):34–43.

Harbridge R, Ivanitskaya L, Spreitzer G, Boscart V. Job crafting in registered nurses working in public health: A qualitative study. Appl Nurs Res. 2022;64:151556.

Roczniewska M, Bakker AB. Burnout and self-regulation failure: A diary study of self-undermining and job crafting among nurses. J Adv Nurs. 2021;77(8):3424–35. https://doi.org/10.1111/jan.14872 .

Hulshof IL, Demerouti E, Le Blanc PM. Providing services during times of change: Can employees maintain their levels of empowerment, work engagement and service quality through a job crafting intervention? Front Psychol. 2020;11:87.

Kassem AH, Ibrahim AAE. Effect of Job Crafting Training Program on Staff Nurses Work Involvement at Mansoura University Hospital. Tanta Scientific Nursing Journal. 2022;25(2):246–94.

HYUN M S. Structural relationship between nurses' occupational motivation and effectiveness based on the job crafting model[J]. J Korean Acad Nurs Adm. 2020:192–204.

Wang H, Li P, Chen S.The Impact of Social Factors on Job Crafting: A Meta-Analysis and Review. Int J Environ Res Public Health. 2020,17(21). https://doi.org/10.3390/ijerph17218016 .

Dilmaghani RB, Armoon B, Moghaddam LF. Work-family conflict and the professional quality of life and their sociodemographic characteristics among nurses: a cross-sectional study in Tehran. Iran BMC nursing. 2022;21(1):1–9.

Kim Y, Jang I. Moderating and mediating effects of social support in the relationship between work-family conflict, job satisfaction and turnover intention among married women nurses. Journal of Korean Academy of Nursing Administration. 2014;20(5):525–34.

Download references

Acknowledgements

Acknowledgment and sincere thanks to all participants for their cooperation.

Chinese National Natural Science Foundation [71603279] has supported this project.

Author information

Authors and affiliations.

School of Nursing, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China

Xin Zhang & Jiayan Gou

Department of Nursing, Chinese Academy of Medical Sciences & Fuwai Hospital, Beijing, China

School of Nursing, Hungkuang University, No. 1018, Sec. 6, Taiwan Boulevard, Taichung, 43302, Taiwan, China

Shih-Yu Lee

You can also search for this author in PubMed   Google Scholar

Contributions

Conceptualization, methodology, and formal analysis: Z.-X., L.-S.Y.; investigation: Z.-C., G.-J.Y.; writing—original draft: Z.-X., G.-J.Y.; writing—review and editing: Z.-X., L. -S.Y.; data curation: L.-S.Y. All authors have read and agreed to the published version of the manuscript.

Corresponding author

Correspondence to Shih-Yu Lee .

Ethics declarations

Ethics approval and consent to participate.

The study was approved by the Peking Union Medical College’s Institutional Review Board (No. 2022030). The study has been conducted in accordance with the principles outlined in the Declaration of Helsinki. Prior to participation, all participants were provided with detailed information about the study, including its purpose, procedures, potential risks, benefits, confidentiality measures, and the voluntary nature of participation. All subjects included in this study signed informed consent, and the investigation was conducted in accordance with relevant normative procedures.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.

Additional information

Publisher’s note.

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ . The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/ ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

Reprints and permissions

About this article

Cite this article.

Zhang, X., Zhang, C., Gou, J. et al. The influence of psychosocial work environment, personal perceived health and job crafting on nurses’ well-being: a cross-sectional survey study. BMC Nurs 23 , 373 (2024). https://doi.org/10.1186/s12912-024-02041-5

Download citation

Received : 01 February 2024

Accepted : 24 May 2024

Published : 03 June 2024

DOI : https://doi.org/10.1186/s12912-024-02041-5

Share this article

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

• Psychosocial work environment

BMC Nursing

ISSN: 1472-6955

• General enquiries: [email protected]

Your current User-Agent string appears to be from an automated process, if this is incorrect, please click this link:

An official website of the United States government

The .gov means it’s official. Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

The site is secure. The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

• Publications
• Account settings

Preview improvements coming to the PMC website in October 2024. Learn More or Try it out now .

• Advanced Search
• Journal List
• Int J Environ Res Public Health

An Empirical Study Analyzing Job Productivity in Toxic Workplace Environments

1 Glorious Sun School of Business and Management, Donghua University Shanghai, Shanghai 200051, China; nc.ude.uhd@meean

Ahmed Faisal Siddiqi

2 Business School, University of Central Punjab, Lahore 54600, Pakistan; moc.oohay@05pcusfa

Samma Faiz Rasool

3 School of Management, Shanghai University, Shanghai 200444, China

Purpose: This empirical study aims to determine the effects of a toxic workplace environment, which can negatively impact the job productivity of an employee. Methodology: Three hundred questionnaires were randomly distributed among the staff members of seven private universities in Pakistan with a final response rate of 89%. For analysis purposes, AMOS 22 was used to study the direct and indirect effects of the toxic workplace environment on job productivity. Confirmatory Factor Analysis (CFA) was conducted to ensure the convergent and discriminant validity of the factors, while the Hayes mediation approach was used to verify the mediating role of job burnout between the four dimensions of toxic workplace environment and job productivity. A toxic workplace with multiple dimensions, such as workplace ostracism, workplace incivility, workplace harassment, and workplace bullying, was used in this study. Findings: By using the multiple statistical tools and techniques, it has been proven that ostracism, incivility, harassment, and bullying have direct negative significant effects on job productivity, while job burnout was shown to be a statistical significant mediator between the dimensions of a toxic workplace environment and job productivity. Finally, we concluded that organizations need to eradicate the factors of toxic workplace environments to ensure their prosperity and success. Practical Implications: This study encourages managers, leaders, and top management to adopt appropriate policies for enhancing employees’ productivity. Limitations: This study was conducted by using a cross-sectional research design. Future research aims to expand the study by using a longitudinal research design.

1. Introduction

In the last few decades, organizations have had a single focus on “profit”, which was based solely on the stock prices. However, the outliers on the other side of the spectrum have been ignored, which are namely the “employees”, despite their established value as the most important assets of an organization [ 1 ]. An extensive review of the literature has determined that employees can be categorized as “stars”, who substantially increase organizational output and “toxic workers”, who simply are unsuitable for the organization [ 2 ]. Studies have shown that 80% of the issues and concerns regarding employees’ productivity are related to the type of work environment in which they operationalize their assigned tasks [ 3 ].

During different time periods, researchers tried to conceptualize the phrase “working environment”. In a simple form, the working environment is the totality of the systems, conditions and situations in which an employee performs his/her tasks [ 4 ]. A working environment can be classified into two major spectrums: collaborative workplace environment and toxic workplace environment [ 5 , 6 , 7 ]. On the positive end of the spectrum, collaborative workplace environments refer to the high-spirit workplace with a community-centered approach in which the employee and employer have an empathetic relationship that fosters the physical and psychological well-being of an employee. On the negative end of the spectrum, toxic workplace environments induce repulsive experiences, which lead to the negative, adverse and reduced outcomes of the employees [ 8 ]. A toxic environment is similar to a cancer that damages all the stakeholders of an organization as it creates toxic culture, toxic leaders, and toxic employees, which ultimately create a toxic organization [ 9 ]. Toxic behaviors in the workplace can increase the organizational cost due to the loss of a positive company image, low self-esteem, loss of employee morale, high turnover, work life conflict, high absenteeism, poor employee health, and lowered employee productivity [ 10 ]. Research has shown that a “toxic workplace environment” damages the organizational outcome. There is need for researchers to explore the root causes and potential consequences of the toxic workplace for both the employees and the whole organization [ 11 , 12 ]. Therefore, this study intends to highlight the different forms of toxic workplace environments and its consequences in the form of high job burnout and low productivity level. Job burnout is treated as a mediating variable between a toxic workplace environment and job productivity. The term ‘toxic workplace environment’ has multiple facets that include: workplace ostracism, workplace narcissism, workplace bullying, workplace incivility, aggressiveness, workplace harassment, workplace passivity, and others [ 13 ]. Ferris and Salzburg introduced the four dimensions that defines a toxic workplace, such as ostracism, bullying, incivility, and harassment [ 14 , 15 ]. To eradicate the toxic workplace environment, this study has the following two objectives:

• Determine the direct impact of the dimensions of toxic workplace environment on job productivity.
• Test the mediating role of job burnout between the multifaceted toxic workplace environment and job productivity.

Based on these objectives, the following hypotheses will be tested during this study:

There is a negative impact of workplace ostracism on job productivity .

There is a negative impact of workplace incivility on job productivity .

There is a negative impact of workplace harassment on job productivity .

There is a negative impact of workplace bullying on job productivity .

Job burnout mediates the relationship between workplace ostracism and job productivity .

Job burnout mediates the relationship between workplace incivility and job productivity .

Job burnout mediates the relationship between workplace harassment and job productivity .

Job burnout mediates the relationship between workplace bullying and job productivity .

2. Literature Review

2.1. toxic workplace environment.

The workplace environment is the totality of the interrelationships of individuals at the workplace, which can be technical, human, and organizational [ 16 , 17 , 18 ]. The workplace environment can be classified into two major categories: collaborative workplace environment and toxic workplace environment. The collaborative workplace environment yields a sense of happiness, joy, harmony, kindness, politeness, cooperation, and facilitation at the workplace [ 19 , 20 ]. The workplace is toxic when individuals in power are greedy and narcissistic and/or use unfair means to bully, harass, threat, and humiliate others. The toxic workplace can cause anxiety, stress, depression, health problems, absenteeism, job burnout, counterproductive work behavior, and ultimately degrade productivity [ 8 , 19 ].

2.2. Workplace Ostracism

Workplace ostracism is the perception of an individual regarding his/her social exclusion by his/her peers and supervisors at the workplace [ 15 , 21 , 22 , 23 , 24 , 25 , 26 ]. It creates a work environment with negative consequences for the employee in the form of high job dissatisfaction and high turnover intention [ 9 ]. Workplace ostracism includes the deliberate reduction in social networks that impact the physical and psychological health of an individual [ 14 , 22 , 25 , 26 ]. Ostracism is a painful experience that can result in negative and stressful outcomes [ 27 , 28 ]. Hobfoll recommended psychological capital as a combating agent to reduce the negative impact of workplace ostracism on an employee’s counter-productive work behavior [ 29 ]. In an organizational context, ostracism can create negative work behaviors, such as high anxiety, depression, emotional exhaustion, and lack of job productivity [ 30 ]. Overall, workplace ostracism is a stressor that stops an individual from performing their routine workplace activities, reduces their work motivation and adversely affects the productivity of both the individual and organization.

2.3. Workplace Incivility

Workplace incivility can be defined as the deliberate intention of one employee to violate the workplace norms by disrupting other employees for his/her personal gain [ 31 , 32 , 33 ]. Workplace incivility can be the verbal abuse or non-verbal actions of an individual that show disrespect towards colleagues or peers [ 34 ]. Due to the infancy of the term ‘incivility’ in the field of management as well as in the education and health sectors, researchers have focused on locating and eradicating its root causes, which negatively impact the employees’ self-esteem, respect, satisfaction, and productivity. Incivility causes physical, psychological and social harm to an individual through isolation, anxiety, depression, mental disability, and the development of low confidence [ 30 ]. It is a type of deviant and discourteous behavior with a low intensity that triggers an individual to undermine the image and performance of peers at the workplace. It includes expressing disgraceful, disrespectful, rude and harsh comments to an individual, who may be a peer, colleague or subordinate [ 35 , 36 , 37 , 38 , 39 ].

2.4. Workplace Bullying

Workplace bullying negatively impacts employees’ mental health [ 40 ]. Bullying includes criticism, blaming, social isolation, humiliation, joking, and excessive monitoring of an employee [ 36 , 41 , 42 ]. Bullying is a situational and contextual factor that is not only limited to bosses as it can also be exerted by supervisors, managers, peers, subordinates, colleagues and anyone in the workplace [ 43 , 44 , 45 , 46 ]. It can be entrenched into organizational settings and culture, which creates detrimental physical and mental health problems, emotional exhaustion and job burnout [ 47 ]. The term of ‘bullying’ can refer to individual or organizational bullying. Individual bullying comprises of dispute-related bullying, escalated bullying, complex bullying, delegated bullying, bystander bullying, merry-go-round bullying, gang bullying, good guy/bad guy bullying, subordinate bullying, and personality disorder bullying. Organizational bullying includes external pressure bullying, history and culture bullying, senior team tactic bullying, and process bullying [ 43 , 44 , 48 ]. Initially, this concept was introduced by Leymann Heinz in 1996 [ 49 ] and has been adopted in different organizations, industries, sectors, and countries [ 50 ]. As an indicator of a toxic workplace environment, bullying may result in job stressors, job burnout, buffering resources, negative work environment, work destruction, and low productivity [ 51 , 52 ].

2.5. Workplace Harassment

Harassment is unwanted conduct, which humiliates an individual; violates an individual’s dignity; or intimidates others [ 53 , 54 ]. Harassment may include unsolicited and explicit speech about race, sex, religion, belief, origin, age, genes, color or ethnicity as a part of a toxic workplace environment [ 55 , 56 ]. This concept was introduced by Farley in 1978 [ 57 ] and has gained a considerable amount of attention from researchers since the 1980′s as it is a significant source of stress at the workplace. In some Asian countries, there are limited efforts to investigate any potential harassment as it is considered to be disrespectful, disgraceful, and insulting for the victim [ 53 , 58 ]. Only a few individuals in Pakistan are willing to talk about workplace harassment [ 59 ]. Workplace harassment against women has been a frequent subject of studies, while workplace harassment against men rarely receives attention and is not frequently the subject of studies [ 60 ]. Males and females of all ages experience workplace harassment. Feminist scholars have linked this concept with gender discrimination, job threats, paradoxical power threat, stereotype thoughts, male dominant society, and illiteracy [ 61 ]. Workplace harassment not only negatively impacts the individual but also has the potential to affect the emotional well-being of an entire workplace. This leads to the loss of employee morale, which consequently reduces organizational productivity. Therefore, it is in the company’s best interest to ensure a safe workplace.

2.6. Job Burnout

Job burnout is one outcome of a toxic workplace environment that is defined by various dimensions: ostracism, narcissism, cynicism, aggressiveness, bullying, harassment, abusive supervisor, interpersonal conflict, and mistreatment [ 62 , 63 , 64 ]. This concept was first proposed by Freudenberger in 1975, which was characterized by emotional exhaustion, low motivation, and commitment that ultimately leads towards low productivity [ 41 , 65 ]. Job burnout refers to the emotional detachment of an employee from his/her task, which creates dissatisfaction with personal and professional life, achievements and work-life conflicts [ 66 , 67 ]. A burned-out employee manifests withdrawal behavior through absenteeism, increased leave and constantly being late. This will ultimately affect turnover. Employees who experience job burnout, usually suffer from mental and health problems, including depression, anxiety, tension, stress, work overload, sleeping problems, and muscle pain. This substantially reduces their ability to function in life [ 45 , 68 , 69 , 70 ]. Job burnout is basically a syndrome that can be created due to situational and individual factors. This syndrome causes depersonalization, poor self-assessment, self-underestimation, high stress, and negative job outcomes [ 71 , 72 , 73 , 74 ].

2.7. Job Productivity

The term of ‘productivity’ involves measuring the efforts of an individual to effectively and efficiently convert the input resources into output [ 75 ]. It basically refers to the time spent on the desired activity, which the employee is expected to perform within specific limited resources [ 76 ]. Scholars argued that the term of ‘productivity’ has no single operational definition as it can vary according to the context, culture, and type of the organization [ 41 ]. Job productivity integrates both the concepts of employee productivity and organizational productivity, which can be measured by quality considerations [ 77 ]. Job productivity depends upon multiple factors, including: individual ability, working environment, HR motivational policies, support from supervisors, and organizational standards. It can be measured in monetary terms, which has the attributes of financial, human, organizational, and social capital [ 59 , 78 ]. The level of productivity does not only depend upon the individual’s ability but also on his/her social network and work environment. Employees who enjoy their work environments are more engaged, more productive, happier, and healthier. Therefore, it makes perfect sense to generate a workplace that is conducive to the well-being of the workforce and organizations should make efforts to provide a better environment for employees so that they may feel comfortable and committed to their jobs in order to increase productivity.

3. Data and Methodology

3.1. sample and procedure.

A survey design was used to collect quantitative data, before rigorous data analytical techniques were applied to test the nature of the relationships among the selected variables. This study aimed to determine the impact of different dimensions of a toxic workplace environment, including ostracism, incivility, harassment, and bullying, on job productivity. Furthermore, we wanted to test the mediation of job burnout between toxic workplace environments and job productivity. A positivism paradigm was favored to test these relationships by using a survey questionnaire design recommended by Robson & McCartan [ 79 ]. A systematic sampling technique was used to select seven private universities in the city of Lahore, Pakistan [ 80 ]. Employees were the unit of analysis for this study. A total of 300 questionnaires were randomly distributed among staff members and 267 responses were received back. Thus, the response rate was 89%. For analysis purposes, AMOS 22 was used to conduct CFA and to verify the direct and indirect effect of variables. SPSS was used for descriptive statistics, while the Hayes mediation [ 81 ] approach was used to verify the mediating role of job burnout between toxic workplace environments and job productivity.

3.2. Measurements

A toxic workplace environment consists of four sub-constructs: ostracism, incivility, harassment, and bullying. All these constructs were measured on a five-point Likert scale adapted from the ostracism scale [ 82 ], incivility scale [ 83 ], harassment scale [ 84 ], bullying scale [ 85 ], job burnout scale [ 86 ], and job productivity scale [ 87 ].

4. Empirical Findings/Analysis

4.1. confirmatory factor analysis (measurement model).

Confirmatory factor analysis (CFA) was conducted to judge the convergent and discriminant validity of each construct and to determine the fitness of the overall measurement model. AMOS 22 was used to conduct CFA. Table 1 revealed the results of convergent validity, which showed that all factor loadings were greater than 0.60 and the composite construct reliability was also greater than the threshold value of 0.70. The average variance extracted (AVE) of all constructs was also greater than the minimum recommended value of 0.50, which indicated that our six-factor CFA, met the standards of convergent validity. Table 2 presented the overall fitness of the six factor CFA which indicated a moderate fit of the indices with the data for direct effects (GFI = 0.937, AGFI = 0.861, NFI = 0.930, TLI = 0.910, CFI = 0.966, & RMSEA = 0.031) and for indirect effects or the mediation model. The discriminate validity was estimated by using the typologies mentioned in literature by Fornell and Hair et al. [ 88 , 89 ]. Table 3 shows the results of the discriminant validity in which the AVE of all conducts were greater than maximum shared square variance (MSV) and average shared square variance (ASV). The square root of AVE of each construct was also greater than its correlation, thus supporting our measurement model of discriminant validity.

Results of confirmatory factor analysis and Convergent validity and construct reliability.

Variables	Measurement Items	Standard Loadings	AVE	CCR	Cronbach Alpha
Ostracism	Ost1 Ost2	0.823 0.914	0.786	0.802	0.908
Incivility	Inc1 Inc2	0.692 0.721	0.531	0.715	0.912
Harassment	Har1 Har2	0.827 0.912	0.623	0.818	0.904
Bullying	Bully1 Bully2	0.835 0.916	0.623	0.721	0.834
Job burnout	Burnout	0.935	0.521	0.857	0.949
Job productivity	Prod1 Prod2	0.898 0.689	0.518	0.597	0.872

Model Fitness.

	Direct Effect	Indirect Affect
GFI	0.937	0.941
AGFI	0.861	0.893
NFI	00.930	0.925
TLI	0.910	0.931
CFI	0.966	0.955
RMSEA	0.031	0.049

Discriminant Reliability.

	AVE	MSV	ASV	Ost_all	Inc_all	Har_all	Bully_all	Burnout_all	Prod_all
Ostracism_all	0.528	0.524	0.222	0.773
Incivility_all	0.701	0.214	0.186	0.376	0.849
Harassment_all	0.521	0.381	0.392	0.554	0.542	0.707
Bullying_all	0.623	0.331	0.218	0.307	0.497	0.609	0.808
Job burnout_all	0.664	0.318	0.252	0.460	0.361	0.572	0.536	0.784
Job productivity_all	0.526	0.514	0.265	0.710	0.257	0.609	0.199	0.453	0.766

Note: Diagonal value: Square root of AVE and Non-diagonal value: correlation.

4.2. Descriptive Statistics

From our total sample (267 cases), 211 (79%) were males, and 56 (21%) were females. In terms of age, 158 (59%) were under 30 years, 52 (19.4%) were 30–39 years old, 36 (13.5%) were 40–49 years old, and 21 (8.1%) were 50–59 years old. This showed that most of the respondents were under the age of 30 years. In terms of qualification, 28 (10.8%) respondents had a PhD degree, 102 (38.9%) respondents had a Master of Philosophy degree, 62 (23.5%) had a Master degree, 70 (26.5%) had a Bachelor degree and 5 (1.9%) had intermediate degrees. Among 267 respondents, 243 (89%) were full-time employees and only 24 (11%) were contractual employees. For salary, 61.2% of the respondents had a salary less than 30,000 PKR (Pakistani Rupee), 18% had a salary range of 30,000–50,000 PKR, 11.1% had a salary range of 51,000–80,000 PKR, and only 9.7% had a salary over 80,000 PKR.

Table 4 shows the results of the minimum, maximum, means, and standard deviations of the data. In this research study, a survey of 38 items was used and the response rate of all items vary from 1 to 5. The results showed that the mean values of different items were 3.34–3.64 and the standard deviation was 0.889–1.064.

Results of Descriptive Statistics.

Name of Variables	N	Min.	Max.	Mean	Std. D.
Ostracism	267	1	5	3.42	1.026
Incivility	267	1	5	3.40	1.064
Harassment	267	1	5	3.34	0.944
Bullying	267	1	5	3.40	0.889
Job burnout	267	1	5	3.64	1.024
Job productivity	267	1	5	3.47	0.999

4.3. Regression Analysis

The direct and indirect effects were tested by using the structural equation modeling technique (SEM). Table 5 displayed the results of the direct effects of four constructs of toxic workplace environments (ostracism, incivility, harassment, and bullying) on job productivity.

Results of Direct Effects.

Hypothesis Tested	Independent Variables	Dependent Variables (Job Productivity)		Remarks
		Coefficients	-Value
H1	Ostracism	−0.884	0.000	Significant
H2	Incivility	−0.274	0.010	Significant
H3	Harassment	−0.783	0.002	Significant
H4	Bullying	−0.696	0.031	Significant

Note: All values were significant at 0.05 significance level (two-tailed).

The regression coefficient of ostracism was -0.884. Since the regression coefficient was negative with significant at the 0.05 level, this supported our hypothesis H1, which stated that there is a negative significant impact of work-place ostracism on job productivity. Our results showed that greater ostracism resulted in less job productivity.

Similarly, the regression coefficient of incivility was −0.274 and was significant at the 0.05 level. This also supported our hypothesis H2, which stated that there is a negative significant impact of workplace incivility on job productivity.

Furthermore, the regression coefficient of harassment was also negative (−0.783), which was significant at the 0.05 level. Therefore, we can conclude that there is a negative significant impact of workplace harassment on job productivity, which supports our hypothesis H3.

Likewise, the regression coefficient of bullying was −0.696, which was also significant at the 0.05 level. Therefore, it supported our hypothesis H4, which stated that there is a negative significant impact of workplace bullying on job productivity. Thus, job productivity will decrease if workplace bullying exists.

We employed the Bootstrapping technique to test the indirect effects among variables. Table 6 shows the results of the indirect effects.

Results of Indirect Effects.

Hypothesis Tested	Independent Variables	Dependent Variable (Job Productivity)		Remarks
		β Coefficients	-Value
H5	Ost  →  Burnout  →  Prod	0.229	0.0	Significant
H6	Inc  →  Burnout  →  Prod	0.271	0.0	Significant
H7	Har  →  Burnout  →  Prod	0.314	0.0	Significant
H8	Bully  →  Burnout  →  Prod	0.329	0.0	Significant

As the indirect effect of ostracism on job productivity through job burnout was 0.229, which was significant at 0.05 level, this supported our hypothesis H5, which stated that job burnout mediates the relationship between workplace ostracism and job productivity.

Similarly, the indirect effect of incivility on job productivity through job burnout was 0.271, which was significant at the 0.05 level. This supported our hypothesis H6, which stated that job burnout mediates the relationship between workplace incivility and job productivity.

In the same way, the indirect effect of harassment on job productivity through job burnout was 0.314, which was significant at the 0.05 level. This supported our hypothesis H7, which stated that job burnout mediates the relationship between workplace harassment and job productivity.

Finally, the indirect effect of bullying on job productivity through job burnout was 0.329, which was significant at the 0.05 level. This supported our hypothesis H8, which stated that burnout mediates the relationship between workplace bullying and job productivity.

Path Analysis-I ( Figure 1 ) was conducted to evaluate the overall goodness of fit. A Chi-square value that is close to zero indicates little difference between the expected and observed covariance matrices with a probability level greater than 0.05, justifying the absence of meaningful unexplained variance. Moreover, to estimate a better goodness of fit, due to the fact that Chi-square is sensitive to sample size, we calculated the ratio of Chi-square to degrees of freedom, which should be less than three in an acceptable data-model fit. In addition, we utilized the Comparative Fit Index (CFI) [ 90 ], the Tucker–Lewis Index (TLI) [ 91 ], the Root Mean Square Error of Approximation (RMSEA) [ 92 ], and the Standardized Root Mean Square Residual (SRMR) [ 93 ]. The indicators of a well-fitting model are evidenced by CFI and TLI that are greater than 0.95, RMSEA that is less than 0.06, and SRMR that is less than 0.08 [ 9 ]. The mediated regression in the Path Analysis-II also confirms all the above mentioned calculations, thus providing good evidence about the good fit of the model ( Figure 2 ).

Path Analysis-I.

Path Analysis-II.

4.4. Mediation Analysis

The Hayes mediation [ 81 ] approach was used to check the mediating role of job burnout between the four dimensions of a toxic workplace environment and job productivity. The dimensions of toxic workplace environments were ostracism, incivility, harassment, and bullying, while job productivity was a dependent variable. For mediation, we had to ensure three conditions: whether mediation existed or not (checked by p -value); the effect of mediation (by value of effect); and whether mediation was statistically significant or not. From the output in Table 7 , it could be observed that job burnout acted as a mediator between ostracism and job productivity (H5: effect = 0.240); incivility and job productivity (H6: effect = 0.601); harassment and job productivity (H7: effect = 0.415); and also served as a mediator between bullying and job productivity (H8: effect = 0.112). As the values of the effects are greater than zero for all four combinations of variables and the p-values were also less than 0.05 (standard sig. value), we concluded that the mediation of job burnout existed between the variables. The values of both BootLLCI and BootULCI had negative signs, which proved that job burnout acted as a statistically significant mediator between all four dimensions of toxic workplace environment and job productivity.

Results of Indirect Effect (Mediation Effect).

Hypothesis Tested	Paths	Effect	-Value	Boot LLCI	Boot ULCI	Remarks
H5	Ost  →  Burnout  →  Prod	0.240	0.000	−0.1093	−0.0084	Statistically significant mediation
H6	Inc  →  Burnout  →  Prod	0.601	0.001	−0.0752	−0.0078	Statistically significant mediation
H7	Har  →  Burnout  →  Prod	0.415	0.031	−0.0548	−0.0281	Statistically significant mediation
H8	Bully  →  Burnout  →  Prod	0.112	0.000	−0.0266	−0.1435	Statistically significant mediation

5. Discussion

A toxic workplace environment can create difficulty in an employee’s work life and can reduce his/her job performance. This present study aimed to determine the direct influence of ostracism, incivility, harassment, and bullying (dimensions of toxic workplace environment) on job productivity and also tried to analyze the indirect effects of these variables with job burnout being a mediator. By using the multiple statistical tools and techniques, it has been proven that ostracism, incivility, harassment, and bullying have direct significant negative effects on job productivity, which was shown by the negative coefficients of −0.884, −0.274, −0.783, −0.696 respectively, ( p < 0.05). For indirect effects, job burnout was shown to be a statistically significant mediator between the four dimensions of toxic workplace environment and job productivity, which was confirmed by the validation of the hypotheses. Our results clearly justify that a toxic workplace has direct significant negative effect on the job productivity of an employee. Consistent with prior research, this study also shows that workplace ostracism [ 94 ], workplace incivility [ 34 ], workplace harassment [ 53 , 58 ], and workplace bullying [ 43 , 44 , 46 ] reduce job productivity. Previous studies also indicated that a toxic workplace increased job burnout [ 24 , 95 ].

Unfortunately, toxic workplaces exist in many organizations and are generally characterized by a culture of dysfunctional interpersonal dynamics despite of the awareness that human capital is the contributing factor for any organization’s sustainable growth and innovation. Mostly, organizational or corporate culture is driven from the top-down approach, and if the leadership is not concerned about the toxic environment, it can be difficult to shift the culture. There are several approaches to address this issue. One of them is for the organization leaders to demonstrate their support to employees by acknowledging their difficulties at work and providing necessary support, especially for the tasks that have more demanding requirements. When the employees have a sense of social support, appreciation, and a positive work environment, they perform better.

We have included a few suggestions for minimizing if not eradicating the toxic culture in a work environment:

• One can do a self-assessment: “Are my actions or performances contributing towards a positive environment?”
• Actively disengage from negative interactions.
• Try to focus on turning a bad situation into a good learning experience. Frequently, the strongest personal growth comes from thriving on the most difficult situations. When an employee is working in a toxic environment, he/she should try to pay close attention to the lessons he/she can take away from the experiences. In every adversary, there is positive insight that one can learn to become a better person.
• Communicate positive messages to others. Employees should share appreciation for peers, team members, subordinates, and also for the work they do. Recognize that people like to feel appreciated in different ways.
• Establish and implement clear policies and communication procedures that address toxic factors, such as harassment and bullying. Most companies have a code of conduct policies, but many of those policies are general or solely address unethical and financial misconduct. Companies rarely maintain policies with specific language that adequately defines a range of prohibited behaviors. A sound policy should be established with clear and multiple reporting mechanisms in place.
• Once the policy has been established, the leaders must ensure all managers and employees receive the training on how to identify, respond, and report these toxic behaviors. Training must also highlight the challenges and fears of employees who struggle to report these types of behaviors.
• Even though one may work in a really toxic environment, an individual should try to not add to the toxicity of the work environment and instead should try to be of benefit in removing the toxic factors from the workplace.

6. Conclusions

Productivity enhancement is a major apprehension of every organization across the globe irrespective of the organization’s nature, operations, functions, area, and sector. However, the meaning and sense of the term ‘productivity’ vary according to the vision and objectives of the organization. Furthermore, there are factors that play an important role in cultivating the productivity in different organizations according to their internal cultures and environments. From an extensive review of the academic literature available on the topic, it has been identified that organizational productivity is conditional on the level of their employee’s productivity. The researchers attempted to explore factors that could affect the intensity of productivity. As evident from the results, a toxic work environment significantly impacts the job productivity and the job burnout. Thus, we concluded that the toxic workplace increases the job burnout level of an employee. When an employee feels negatively about the organization, he/she tends to compromise the productivity level of his/her performance, which could also increase the stress level of an employee. This study recommends that in every organization, HR departments and policy makers should develop and implement strict policies for eradicating a toxic workplace environment to make it collaborative and conducive for the employees.

Acknowledgments

All the authors are grateful to English editing services of MDPI, which helped us to meet the high requirement of the MDPI Journals. We are also thankful to Andrew Alexander for providing help in proof-reading of this article. Andrew is from America who is an English language teacher in Shanghai.

Author Contributions

First author (A.A.) conducted the whole research over all. She collected the data, performed statistical tests, analyzed results, and wrote the discussion part of this study. Second author (X.M.) is the supervisor of the first author. Third author (A.F.S.) guided in statistical analysis of this article and fourth author (S.F.R.) wrote the literature review.

This research received no external funding.

Conflicts of Interest

The authors declare no conflict of interest.

Environment Variables: What They Are and How To Use Them

If you’ve worked on any form of application development , you must have already heard of the term “environment variables.” Environment variables are used to store app secrets and configuration data, which are retrieved by your running app when needed.

Environment variables add dynamicity to your static code base; you can switch between internal/external resources based on the value of the environment variable passed to your app.

This article will break down environment variables for you. You will learn some popular ways to create and manage environment variables and understand when to use them. By the end of this article, you’ll be able to effectively and confidently use environment variables in your applications.

Without further ado, let’s begin!

What Is an Environment Variable?

Reiterating the explanation above, environment variables are variables available to your program/application dynamically during runtime. The value of these variables can come from a range of sources — text files, third-party secret managers, calling scripts, etc.

What’s important here is the fact that the value of these environment variables is not hardcoded in your program. These are truly dynamic and can be changed based on the environment that your program is running in.

Types of Environment Variables

There are three prominent types of environment variables in a Windows-based computer system, and each of them has its use cases. Let’s discuss them one by one.

1. System Environment Variables

System environment variables reside on the topmost root of the system and are the same for all processes running in a system under all the user profiles of the system. Your operating system/system administrator usually sets these, and you’re rarely required to fiddle with them.

One of the most common uses of a system environment variable is setting up a PATH variable to a global package/library to be used by all users in the system.

2. User Environment Variables

User environment variables are those that are local to a user profile in Windows systems. These variables are used to store user-specific information such as the path to a local installation of libraries that are not to be used by all users, values specific to programs installed only for specific users, etc.

You do not need the system administrator to make changes to these variables; you can do that yourself as a user. These variables are helpful when implementing local changes in your system without affecting other users.

3. Runtime/Process Environment Variables

Runtime environment variables are further narrowed down only to the runtime or the process that they are associated with. These are usually set by the parent process that creates the new process and is accompanied by the system and user environment variables as well.

You can use terminal scripting to create and store these variables on the fly. Runtime variables are usually not permanent unless scripted, and you need to define them whenever you start a new process.

Environment Variables in Unix-based Systems

Unlike Windows systems, Unix-based systems do not have three layers of environment variable types. In such systems, everything is stored under a var object and can be accessed/modified by the running program.

If you need to set some environment variables as default to be loaded each time any program runs on your system, you need to define them in files such as .~/bashrc or ~.profile that are loaded when the system boots up.

Environment Variables vs Pseudo-environment Variables

A separate line of dynamic environment variables is available in Windows and DOS-based systems, known as pseudo environment variables. These are not statically assigned pairs of keys and values, but rather dynamic references that return various values when queried.

While you can assign a value to an environment variable manually by using the SET command or its equivalent, you can not assign values to pseudo environment variables. There is a fixed list of such variables, and you can use them in your code to make your job easier. Some popular use cases include %CD% for the current directory and %TIME% for the current time.

Why Should You Use Environment Variables?

Now that you understand what an environment variable is and its various types, it’s time to know why you should extensively use it in your apps.

Separation of Concerns

One of the most important reasons why you should use environment variables in your applications is to adhere to a popular and useful design principle — separation of concern. The design principle states that computer programs should be divided into distinct sections to manage them efficiently. Each section should be based on one of the program’s primary concerns, and there should be minimal coupling between such sections.

You can consider application configuration as one of such concerns; hence it needs to be separated from the main program. One of the best ways to do it is to store it in an external file and inject it as and when needed. Environment variables help you isolate critical application configuration data using env files or remote variable stores. This way, your developers are only provided with the information they need.

Maintaining Independent Configuration Sets Across Environments

Apart from isolating app configurations from your source code, you also need to be able to switch between sets of configuration data easily. If you choose to hard-code your app configuration values in your source code, it can become almost impossible to replace those values based on external conditions such as deployment environments.

The usage of environment variables helps you decouple your configuration data from your code and standardize the way this information is provided to your app, which enables you to modify/exchange the information being provided on the fly.

Securing Secrets

Your app secrets fall under sensitive information. If wrong people get their hands on them, they can access your app’s internal architecture and third-party resources. Common examples include AWS keys and system account details. Unauthorized access to these keys can lead to loss of money and application data. Hackers can even go so far as to restrict your app from working normally.

Therefore it is vital that you protect these secrets. Leaving them lying around in your codebase can result in all of your developers gaining access to them. If you do not follow proper code obfuscation methods, your apps can be reverse engineered to retrieve the keys lying among your code. Isolating these secrets via environment variables can prevent such scenarios from happening.

Example Use Cases of Environment Variables

Now that you have a clear idea of how environment variables work and how you should use them effectively, here are some common scenarios where you can use environment variables:

• Environment Type : Environment variables are often used to store the name of the environment in which the app is currently running. The app’s logic can use this value to access the right set of resources or enable/disable certain features or sections of the app.
• Domain Name : The domain name of an application can vary based on its environment. Isolating it also helps you easily make changes to your app’s domain name without searching for its occurrences throughout the codebase.
• API URLs : Each environment of your app can have APIs deployed in different environments as well.
• Private Keys : Keys to paid services and resources need to be isolated from the app’s source code so that they do not accidentally fall into the wrong hands.
• Service Account Numbers, etc. : You can vary other system-specific information, such as service account numbers, keytabs, etc., based on the app’s environment for resource management and monitoring.

How To Store Environment Variables

Now that you understand why environment variables are important, it is time to look at how you can store and access them in your application. Discussed below are three different yet popular ways of managing environment variables in an application.

Using .env Files

.env files are undoubtedly the easiest and most popular ways of managing environment variables. The idea here is simple—you store your environment variables in a file named .env at the root of your project. The application queries for the variables in this file and loads them for use during runtime. Here’s what a typical .env file looks like:

.env files also enable you to define sets of environment variables and access them based on your app’s runtime environment or other factors. Instead of saving the file as simply .env , you can make more than one file and keep them as .env.dev and .env.prod . Inside these files, you can define the same sets of variables but with varying values, depending on the environment.

Example Template

When working with .env files, it is not recommended to add them to your version control system (more on this later). Therefore you should define a “.env.template” in your project so that developers can follow the template and create a .env file for themselves locally.

Here’s what a .env.template file would look like:

It doesn’t have to follow any conventions as long as it is self-explanatory for your development team. To simplify this process, you could also use packages such as env-template .

Here are some reasons you should consider using .env files to manage environment variables in your app.

Simple To Use

This method is the simplest in the line of environment variable management techniques. All you need to do is create a plain text file that contains your secrets and store it at the root of your project.

Switching environments is as simple as changing the env file itself. You can store multiple files by the names .env.dev , .env.prod , .env.uat , etc., and configure your source code to access these files based on the environment that it is being run under.

Local Access

You can easily set up .env files in a local development environment. Unlike platform-native variable managers, you do not need to deploy your app to leverage the environment variables functionality. Compared to secret managers, .env files are easier to set up locally, and there is no network dependency for accessing your app secrets.

Open Source Support

There are numerous open-source packages to help you load and manage app secrets from env files. You do not need to depend on paid services, nor are your options limited when it comes to app secret management. There is a wide range of third-party open-source libraries to help you manage your env files. Some popular/useful examples are dotenv , env-template , and cross-env .

Here are some disadvantages of env files you should know before using them in your projects.

.env files store your app secrets in the form of key-value pairs. The usual format for storing environment variables in a .env file is:

You need to strictly stick to this format for your app to be able to read your app secrets successfully. If you make one small mistake somewhere between tens or hundreds of lines of environment variables, the entire file might not be parsed, and your program will throw unrelated errors throughout. The fact that there is a parsing error with your .env file might not even be highlighted. This is why you need to be careful while using .env files.

Prone to Accidental Secret Leakage While Sharing/Storage

Since .env files are plain text files, they are vulnerable to accidental exposure when stored on a shared hard drive or sent over via an unsecured network. Therefore you need to take special care to not leak out your app secrets when you’ve stored them using .env files.

Using Platform-Native Variable Storage

Another popular option for storing environment variables is to rely on your deployment platform’s variable storage. Most deployment environments, such as Heroku, AWS , Netlify, etc., provide a space for users to upload secrets which are later injected into the runtime of your application. You can check your deployment platform’s documentation to know if they support it and how to get started with it.

Here’s a quick look at Netlify’s environment variable manager:

Here’s why you should consider using platform-native variable storage solutions.

Highly Secure

Since this option is managed entirely by your deployment platform, it is bound to be more secure than storing your secrets in a plain text file . You can control who gets access to the variables manager, and you can rest assured that the secrets will never get accidentally pushed to your VCS.

Easy To Update

Updating the environment variables when they’re stored independently is simpler—you do not need to edit your source code and make a new release for it. You can simply change the values in the platform and rebuild your project. It will receive the new values the next time it is started.

Formatting woes are gone, too, since most platform-specific deployment managers lint the keys as you enter them. In cases such as Netlify’s, you get to enter the secrets in a pre-formatted form, eliminating the chances of making a formatting mistake.

Enables Collaboration

Since deployment platforms can be accessed by your entire team, you can easily share the secrets with the right people without having to send over text files via the internet. You can control who gets to access the variable manager (in most cases) and use it as a central repository for your app secrets.

While platform-native variable managers seem to be just the solution you need, there are a few issues you should keep in mind before opting for them.

Platform-Dependent

As their name goes, they are highly specific to the platform you’re using. In some cases, your deployment platform might not even offer such a service. Changing your deployment platform for getting access to such a service might not seem to be the best decision.

Non-Uniform

Since they are offered and managed completely by the deployment platform, such services can be highly non-uniform. Moving variables from one platform to another can be problematic. You can not even assume that every deployment platform would provide the options of importing/exporting environment variables. While most do, it is entirely in the hands of the platform. There are high chances of running into a small-scale vendor lock-in if you have a long list of environment variables.

No Local Support

While such services are great for accessing environment variables in your app’s deployments, there’s rarely a chance that you can use these while developing your app locally. In most cases, you’ll have to resort to managing local .env files. While it fulfills the purpose, it complicates the whole setup unnecessarily.

Using Secret Managers

The third option which is currently quite young in its development stages is to use dedicated secret managers. Secret managers are third-party services that enable you to isolate your app secrets completely from your source code/deployment and fetch them as and when needed over secure network connections.

Here are some of the advantages that secret managers offer over other methods of secret management.

Since your secrets are stored in a completely isolated service, you can be assured that you’ll most likely never leak them out accidentally while sharing them with your colleagues or via version control commits. The third-party platform takes care of keeping your secrets safe, and they usually have quite strict SLAs when it comes to data security.

Even when accessing the secrets from inside of your application, most secret managers provide their own client code that can securely fetch and allow access to the secrets wherever needed.

Uniform Across Environments

Since the secrets are now independent of your codebase and deployment environments, you can now enjoy uniformity across environments. You do not need to make special arrangements for onboarding new developers or take special steps before pushing your app to production — most of these aspects are simplified or taken care of by your secrets manager.

While secret managers appear to be the best possible solution at hand for managing environment variables, they have their own share of caveats.

Managing environment variables has been an internal activity within projects for a long time. Even most deployment platforms provide this feature free of cost since they do not incur any additional costs for it.

However, since secret managers are completely independent services, they have their own cost of operations. Hence, users have to bear this cost while using these services.

Early Stages of Technology

Since the technology is fairly new, you can never be sure of how well it is going to be adopted by the industry in the coming days. While secret managers show great promise in terms of security and ease of management, the cost factor and data handling concerns might result in rather slow adoption of the technology.

How To Work With Environment Variables

Now that you understand the concept of environment variables and the available ways to implement them in an app, let’s look at how you can work with them via the terminal and in Node.js-based apps .

Environment Variables in the Terminal

Since environment variables are specific to processes, you can set and delete them via the terminal so that they are passed down to the processes that your terminal spawns.

Finding Variable Values

To view the list of environment variables in your terminal, you can run the following commands specific to your operating system.

On Windows:

On Linux or MacOS:

This will print a list of all available environment variables to your running terminal.

Setting New Variables

To set new variables via the terminal, you can run the following commands.

Deleting Variables

To delete an environment variable, you need to run the following commands.

Please note that the methods discussed above are only for creating/deleting environment variables for the current session of the terminal.

Environment Variables in Node.js

JavaScript is one of the most popular programming languages right now. It is widely used in building backend as well as front-end applications , making it one of the most versatile programming languages.

Node.js is among the most widely used JS frameworks for building backend applications. Let’s take a look at how you can handle environment variables in Node.js-based apps easily.

Accessing Environment Variables Directly

Node.js provides you with a reference to your current process’ environment variables via process.env . You can view the available environment variables by printing this object to the console.

This object will contain variables available to the running Node process. You can add new variables to it by declaring them before running your app, similar to this:

As you can see, the new variable gets added to your process.env object. However, you can not access any variables defined under a .env file via this method. To do that, you need to use a package like dotenv to load the .env file on runtime.

Using dotenv Package to Access .env Files

The dotenv package helps you to load environment variables stored in .env files at the root of your project. Its usage is simple, you need to install it by running the following command:

Next, you need to add the following line of code in the beginning of your app’s code to initialize the package:

That’s it! Now the secrets that you store in a .env file at the root of your project will be loaded in your process.env object as soon as the app starts. We will see this method in action later in the following tutorial.

Environment Variable Tutorial

The best way to understand a technical concept is to watch it in action. Here’s a quick tutorial to help you get started with environment variables and learn their usage in detail.

In the following guide, we will demonstrate how to use environment variables via all of the three ways that we mentioned above— .env files, platform-native variable managers, and secret managers. All of these ways will require a common step, which is to set up a basic Node.js project.

First: Create a Node.js Project

To begin, ensure that you have Node.js installed on your system. Once you have it set up on your system, you’ll have access to npm (short for Node Package Manager). npm helps you to install node packages from the global npm registry via the command line. It will come in handy when installing packages related to our test project.

Next, open up a terminal and create a new directory. Initialize a fresh Node project in it:

Keep pressing enter through the incoming questions to accept the default options. Once done, your terminal would look something like this:

Now you can open up this project using an IDE such as Visual Studio Code or IntelliJ IDEA.

Create a new file in the root of your project folder and save it with the name index.js . This will be the starting point for your application. Next, install Express for quickly creating and testing REST servers:

Once you have Express installed, paste the following piece of code in your index.js file:

This is a starter snippet for a basic “Hello World” endpoint using Node.js and Express. Run the following on your command line:

This will start your node + express app. If you navigate to http://localhost:8080 on your web browser, you’ll receive a similar output:

This indicates that you’ve set up your app properly! The next step is to update your app to use environment variables. Update the code in index.js to match the following snippet:

Instead of sending a “Hello world!” message in the response, we will now be sending a JSON object that carries two pieces of information:

• environment : Indicates the current environment in which the app is deployed
• apiBaseUrl : Carries the base URL for a hypothetical API. We will change the value of this URL based on the environment that the app is deployed in.

In case of not being able to access the environment variables, the object will contain “Not found” as the values for the two keys described above. Before moving ahead, rerun the node index.js command and you’ll receive the following output:

This indicates that your app is currently unable to access the environment variables. On top of that, we have not even defined the values for these variables. Let’s take a look at the various ways available to do that in the next sections.

Type 1: Add Environment Variables Via env Files

Let’s begin with the most basic way of adding environment variables — env files. In your project root, create a new file called .env and store the following code in it:

Next, restart your app by running the node index.js command again and check for the output:

You will find that the output still remains the same. This is because even though you’ve defined the value of the environment variables, you’ve not really instructed your app on where to find them. This is where packages such as dotenv come handy in.

Run the following command to install dotenv :

To begin using dotenv in your code, add the following code on line number 2 of your index.js:

Next, restart the app and check for the output:

As you can see, the values for the environment variables have been loaded from your .env file!

Now, to spice things up, let’s rename our .env file to .env.dev and create another file by the name .env.staging . Paste the following piece of code into the new file:

Once you’re done with, replace line number 2 of your index.js file with the following piece of code:

What’s changed here is that we’re now instructing the dotenv package to fetch the contents of the environment variables from one of the two available files based on another environment variable called NODE_ENV . Where does the value of this environment variable come from? Your terminal.

To test out this setup, run your app using the following command:

If you go to localhost:8080 now, you’ll notice the following response:

Now, kill the running app and run it again using the following command:

Going to localhost:8080 will now lead you to the following response:

This is how you can use .env files to access different sets of variables based on external conditions. The external condition here is the external environment variable NODE_ENV which is essentially a user environment variable while environment and apiBaseUrl were runtime environment variables. The calling user profile supplies the value of the NODE_ENV variable and the app utilizes it to make internal decisions.

In case you are on Windows, you might face difficulties while running the previous two commands. The Windows terminal might not allow you to assign user environment variables on the fly using the KEY=VALUE syntax (unless it is Bash on Windows).

A quick solution in that case is to make use of scripts and cross-env .

Install cross-env by running the following command:

Next, go to your package.json file and update the scripts key to match this:

Now you can run the following commands to run your app with two different sets of environment variables:

This is a universal fix and you can use these scripts on bash/zsh as well.

Next, let’s take a look at how to use a third-party variable manager.

Type 2: Use Heroku’s Native Environment Variable Manager

To be able to follow along during this part of the tutorial, you’ll need a Heroku account. Go ahead and create it before moving ahead.

Before deploying the app on Heroku, there are a few changes that you’ll need to make to your code. First of all, add a new script in your package.json called start:

This script will be used by Heroku to run your app once deployed. Also, go to the last line of your index.js file and update it to the following:

This will ensure that the app is deployed on the port specified by Heroku.

Next, you need to install the Heroku CLI locally to be able to access your Heroku apps from your command line. For this tutorial, you can use the following command to install the CLI:

However, Heroku docs recommend installing it via one of the other ways listed in the link mentioned above for better support. Once installed, run the following command to log in to your Heroku account:

Once done there, go to dashboard.heroku.com and log into your account. Next, create a new app by clicking on New > Create new app .

On the next page, click on the Create App button without entering any details. This will create a new heroku app for you with a random name.

Here’s what your app’s dashboard would look like:

This page also contains instructions on how to deploy your app to Heroku via the CLI. Here is the list of commands you have to run to deploy your app to Heroku:

Once the deploy is completed successfully, you can view the deployed app via the dashboard by clicking on the Open App button

If you’ve done everything right, you’ll see the following response:

Why does this happen, you may think? This is because we haven’t provided the environment variables to our app in any form yet. If you check the commands that you used to deploy the app, you’ll notice that we haven’t pushed the .env files to our version control. We have also not defined the NODE_ENV value in the start script.

To inject environment variables into your app now, you need to navigate to Settings > Config Vars on your Heroku Dashboard. Upon clicking Reveal Config Vars , you’ll see a similar screen:

You can now enter the contents of your .env file here:

If you go back and refresh your app’s URL, you’ll notice that the values have been updated:

This is how you can make use of a deployment platform’s secrets manager to manage your environment variables. However, this requires you to manually manage the environment variables via the platform’s dashboard. As you can see for Heroku, there is no option to import a large dump of environment variables from a file, forcing you to enter each of them one by one. This can get quite troublesome at times.

The next section features a more efficient method of managing app secrets — secret managers.

Type 3: Use Doppler to Manage Environment Variables

The methods discussed above do not provide uniformity across platforms. You would usually not rely on env files when deploying to production, and it is not possible to make use of platform-native variable managers when working locally. Secret managers like Doppler fill this gap.

To try it out for yourself, you need to first create a free account on Doppler .

Once done, you can follow along. It will most probably create a sample project for you automatically by the name example-project. For simplicity, let’s keep it aside and create a fresh project for our use case.

Go to the dashboard and click on the plus icon next to Projects.

Enter its name as “my-app” and proceed. Here’s what the project should look like once it is ready:

Click on the dev config list item. Click on Add New Secret and add two secrets as follows:

Click on the Save button to save your changes. Note that Doppler does not support camel casing when naming your secrets. While it is generally preferred to keep the secret names in all caps, using Doppler does not leave you with any other options. To identify the secrets being fetched from Doppler, we’ve prefixed them with DP_

Now that the variables are created and stored in Doppler, let’s integrate them into our codebase. You need to set up the Doppler CLI to do so. Here’s a quick gist of what you need to do.

First of all, install the CLI locally by following the instructions specific to your operating system . Next, login into the Doppler CLI with your newly created account using the following command:

Once logged in, run the following command to connect to your remote Doppler project from your CLI:

Once you’ve connected to the right project, you’ll be able to access your secrets via the following command:

However, we will not run this command directly. Instead, we will append this to one of our run scripts so that it gets run automatically whenever the app starts. Let’s update the package.json file with the new run script for the dev environment:

Also, remember that we created new variable names in Doppler that started with DP_ . So we’ll need to update our index.js file to display this variable as well:

To see things in action, run the following command:

This is what http://localhost:3000 should look like now:

The third variable in the list ( DP_ENVIRONMENT ) is being fetched from Doppler directly.

Next, you can connect Doppler with your deployment platform to access these secrets via your deployed app. To do that, let’s begin by creating a new environment in Doppler for a new set of deployment secrets.

Go back to the home page for your project my-app. Click on the only list item in the Staging list:

You will notice that the two secret variables that you’ve defined in the dev environment are already available here but they’re missing values:

Add the following values and click on Save :

Once done here, click on the Integrations tab and Add Sync on this page to begin connecting to your deployment platform. You will receive a list of platforms that Doppler can integrate with:

Since our app is deployed on Heroku, let’s click on Heroku. Follow the on-screen steps to connect your Heroku account to Doppler and provide the required access roles. Once it’s connected, you’ll reach a similar screen:

Select the Project Type as App , choose your Heroku app in the list of available apps, choose stg as the Config to sync , and Do Not Import in Import Options , since we do not want to import any secrets from Heroku to Doppler.

Click on Set Up Integration when done. You will reach a similar screen when the integration is made successfully:

Now if you check the Config Vars section in your Heroku app’s dashboard, you’ll notice that the variables from Doppler have been added automatically to your Heroku deployment’s config vars:

You’ll also notice that the two original environment variables ( environment and apiBaseUrl ) have been removed. This happened because we chose Do Not Import under Import Options . You can go ahead and add these again in Heroku if needed.

While the presence of the new environment variables in Heroku’s Config Vars section demonstrates that you’ve successfully set up Doppler to manage secrets both locally in your development environment and in your deployment environment as well, you can go ahead and deploy the updated code to Heroku to view the changes in the deployed app. Here’s what it’ll look like when done:

This completes the tutorial to set up environment variables in a Node.js project using three popular methods. Next, let’s take a look at some ways in which you can ensure that your environment variables and their files are secure while they’re in use.

How To Keep Environment Variable Files Secure

While environment variables are a useful resource in modern DevOps practices, you need to be aware of the security implications that they can cause. Here are some tips you can use to keep your environment variable files secure and away from prying eyes.

Keep env Files Out of Version Control

One of the most important things you should keep in mind when handling any secrets is to keep them out of version control. Version control is meant solely for tracking changes across your application’s source code. Everything that goes in a version control system stays in it until deleted explicitly, and most of your team has access to this historical data for reference purposes.

If you’ve stored the keys to your AWS storage bucket or a paid API service in an env file for use in your application, you do not want to share it with your entire development team unless they are required to have access to it. If your project is open-sourced on a platform like GitHub , adding env files to your VCS could mean sharing it with the whole world! Env files are intended to be stored locally. You can provide each deployment environment with relevant env files via dedicated methods.

Always add the env file to your .gitignore file (assuming you use git for version control) or employ any other way to have your VCS skip the env files when committing changes. You can consider adding a template env file to your VCS so that any other team member may use it as a reference to create their env files locally.

Check Package Name Before Installation

Since you’d usually install most packages from NPM when working with a Node.js application, you should take extra care while doing so. It is well known that anybody can create and deploy an NPM package. And it’s also unsurprising that people often make mistakes when typing the name of a package that they want to install.

Multiple cases have been noted where malicious packages with names similar to some popular packages have been accidentally installed by users due to typing errors. Such packages are designed to gain access to your app’s environment variables and send them via the internet to their creators.

The only way to save yourself is to be alert whenever installing new packages from the internet.

Prefer Secret Managers Over env Files

With issues like accidental leakage while sharing and formatting errors, env files certainly aren’t the best option available for secret management. Enter secret managers. Secret managers such as Doppler enable you to isolate your app secrets completely from your source code and manage them in a dedicated platform.

You can grant your team access to these secrets directly on the platform, and your app can access these via encrypted connections over the internet. It solves all the woes associated with env files while allowing you the flexibility to maintain sets of secrets based on the environments of your application.

However, there are caveats here too. Secret managers are in a very early stage of their technological development. On top of that, secret managers are third-party platforms that are subject to their own set of security issues. Therefore careful evaluation and selection of the right secret manager are important. Moreover, if your application, its development team, or the number of app’s secrets isn’t large enough, secret managers might be overkill for you.

Environment Variable Reference Table

Here’s a quick cheat sheet to help you get up to speed with environment variables and their usage quickly:

Definition of environment variables	Variables supplied to processes by their calling processes
Purpose
Types	For Windows only:
Popular example use cases
How to implement these in your app?

Environment variables are important for isolating sensitive data from your application. They help to secure your app’s secrets as well as enable you to switch between sets of secrets easily depending on the app’s environment. However, managing them adds another task to your plate.

There are multiple ways to secure and environment variables, as we discussed above. Explore them all and find which ones will fit and speed up your project the best.

Related Articles

How to Debug Node.js Code Using Multiple Tools

What’s the Average Node.js Developer Salary?

10 Most Popular Types of Node.js Apps

• SUGGESTED TOPICS
• The Magazine
• Newsletters
• Managing Yourself
• Managing Teams
• Work-life Balance
• The Big Idea
• Data & Visuals
• Reading Lists
• Case Selections
• HBR Learning
• Topic Feeds
• Account Settings
• Email Preferences

Time’s Up for Toxic Workplaces

• Manuela Priesemuth

Three ways to create an environment that doesn’t tolerate abuse.

Direct interactions with “bad bosses” can be traumatic, but the problem often goes further than a single individual. Research has shown that abusive behavior, especially when displayed by leaders, can spread throughout the organization, creating entire climates of abuse. But organizations also can also structure work environments that combat abuse by: 1) educating managers about all costs associated with abusive conduct; 2) strengthening anonymous feedback channels where employees can report their experience without fear of retribution; and 3) upholding and enforcing fair and equitable norms throughout the organization.

Millions of people face abusive supervisors and bullies at work . These employees are targets of ridicule, threats, or demeaning comments by their manager on a daily basis, which results in decreased satisfaction, productivity, and commitment to the job as well as the organization at large.

• MP Manuela Priesemuth is the Megan ’07 and Matthew ’06 Baldwin Assistant Professor of Management at Villanova University. Her research focuses on destructive leadership, workplace aggression, organizational fairness, and behavioral ethics.

Partner Center

• Skip to main content
• Skip to search
• Skip to footer

Products and Services

Live stream splunk's user conference for free.

Global broadcast | June 11–12, 2024

Making AI work for you

Cisco AI is where the AI hype ends and meaningful help begins.

Certifications

Cisco Validated

Announced at Cisco Live

Cisco XDR with AI Assistant

Remediate the highest-priority incidents with an AI-first XDR solution.

Cisco Networking Cloud 

One platform experience. Assured, secured, and simplified.

Secure Firewall 1200 Series

Compact, all-in-one SD-WAN firewall for your distributed enterprise branch.

Catch up on what you missed

Keynote: Vision for the Future

CEO Chuck Robbins addresses how to connect and protect your business in the AI era.

Keynote: Go Beyond

Learn about Cisco, Splunk, and reaping the benefits of the AI revolution.

Deep dive sessions

See tech announcements and strategic direction from Cisco's senior tech leaders.

View keynotes and tech sessions in the on-demand library.

Press release

Cisco Live puts AI center stage and more. 

Cisco launches $1B global AI investment fund.

Validate your AI skills with certifications

Join all Cisco U. Theater sessions live and direct from Cisco Live or replay them, access learning promos, and more. It's time to Go Beyond the basics and level up your learning.

Identity is the new perimeter

Stop identity-based attacks while providing a seamless authentication experience with Cisco Duo's new Continuous Identity Security. 

Inside Cisco

• More events

Cisco reveals Nexus HyperFabric

Cisco Nexus HyperFabric makes it easy for customers to deploy, manage, and monitor generative AI models and inference applications without deep IT knowledge and skills.

Cisco and Splunk launch integrated Full-Stack Observability experience

Using Cisco and Splunk observability solutions, customers can build an observability practice that meets their IT environment needs for on-premises, hybrid, and multicloud.

ThousandEyes Digital Experience Assurance shifts IT operations

New Cisco ThousandEyes capabilities and AI-native workflows in Cisco Networking Cloud will deliver Digital Experience Assurance, transforming IT operations.

Improving code-mixed hate detection by native sample mixing: A case study for Hindi-English code-mixed scenario

• Mazumder, Debajyoti
• Kumar, Aakash
• Patro, Jasabanta

Hate detection has long been a challenging task for the NLP community. The task becomes complex in a code-mixed environment because the models must understand the context and the hate expressed through language alteration. Compared to the monolingual setup, we see very less work on code-mixed hate as large-scale annotated hate corpora are unavailable to make the study. To overcome this bottleneck, we propose using native language hate samples. We hypothesise that in the era of multilingual language models (MLMs), hate in code-mixed settings can be detected by majorly relying on the native language samples. Even though the NLP literature reports the effectiveness of MLMs on hate detection in many cross-lingual settings, their extensive evaluation in a code-mixed scenario is yet to be done. This paper attempts to fill this gap through rigorous empirical experiments. We considered the Hindi-English code-mixed setup as a case study as we have the linguistic expertise for the same. Some of the interesting observations we got are: (i) adding native hate samples in the code-mixed training set, even in small quantity, improved the performance of MLMs for code-mixed hate detection, (ii) MLMs trained with native samples alone observed to be detecting code-mixed hate to a large extent, (iii) The visualisation of attention scores revealed that, when native samples were included in training, MLMs could better focus on the hate emitting words in the code-mixed context, and (iv) finally, when hate is subjective or sarcastic, naively mixing native samples doesn't help much to detect code-mixed hate. We will release the data and code repository to reproduce the reported results.

• Computer Science - Computation and Language