strengths of qualitative research in nursing

• Open access
• Published: 22 July 2024

Characteristics and quality of reporting qualitative nursing research related to the COVID-19 pandemic: a systematic search and critical review

• Ian-In Vong 1 ,
• Monique Rothan-Tondeur 1 , 2 &
• Rita Georges Nohra 1  

BMC Nursing volume  23 , Article number:  498 ( 2024 ) Cite this article

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The COVID-19 (Coronavirus disease of 2019) pandemic caused major disruption to nursing research, especially qualitative research. Researchers had to overcome numerous challenges that potentially impacted the quality of the studies carried out.

The aim of this study is to assess the characteristics and quality of reporting qualitative nursing articles on the COVID-19 pandemic.

A systematic search and critical review using content analysis was conducted on published nurse-led articles using a qualitative approach related to the COVID-19 pandemic. A combination of the Consolidated Criteria for Reporting Qualitative Research (COREQ) and Standards for Reporting Qualitative Research (SRQR) checklists and additional items identified from the literature were used to assess the characteristics and overall quality of reporting of qualitative research.

Out of 63,494 articles screened, 444 met the inclusion criteria. Most studies were published in high-impact, Quartile 1 journals, with the majority originating from the USA. Common themes included workforce experiences and the impact of pandemic restrictions. Methodological quality varied, with a notable underuse of standardized reporting checklists. Despite pandemic-induced challenges in data collection, interviews remained the predominant method. However, the adoption of remote research methods and analysis software was limited.

The findings underscore the resilience and adaptability of nursing researchers during the pandemic. High-quality publications in top-tier journals indicate rigorous academic standards. However, the low utilization of reporting checklists suggests a need for greater emphasis on methodological transparency and adherence to established quality guidelines. This review highlights the importance of enhancing qualitative research practices to improve the rigor and reliability of studies, particularly in crisis contexts.

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Introduction

The COVID-19 pandemic has threatened the health and well-being of global citizens which has led to a significant change in the attitude, lifestyle, and behavior of people from diverse professions [ 1 ]. Nurses have been and remain central to the pandemic––nurses are central to preventative, curative and palliative activities associated with COVID-19, and have taken these roles on in addition to their usual roles [ 2 ]. Nurses reported low job satisfaction, high levels of burnout, stress, and anxiety [ 3 ]. Researchers have experienced a decline in research motivation [ 4 ]. Scientific productivity, particularly among female academics, has suffered due to increased childcare responsibilities and psychological distress [ 5 ]. And parent researchers struggled to balance work and family responsibilities during the pandemic [ 6 ].

On the other hand, the travel restrictions and lockdown during the pandemic have undoubtedly affected all aspects of research, including qualitative research [ 7 , 8 ]. Qualitative nursing research is essential and important for understanding patient experiences, exploring complex healthcare phenomena, and guiding patient-centered care [ 9 ]. It provides insights into the subjective experiences, perceptions, and emotions of patients, families, and providers [ 10 ], bringing a holistic perspective to understanding the phenomena under study [ 11 ]. With qualitative methodologies, insight can be gained regarding the social responses to this pandemic, they are also the best methods to help explain, address, and plan for emergencies and pandemics, such as COVID-19 [ 7 , 12 , 13 ]. Restrictions during the pandemics made traditional data collection methods challenging [ 1 , 14 ]. Nurse researchers had to adapt to perform data collection in a virtual environment, shifting from face-to-face interviews to telephone or online meetings [ 1 ]; research participants were unwilling to show their faces at virtual meetings, and face-to-face interviews were only allowed with masks on [ 7 , 8 ]. These changes affected the quality and richness of data collection, missing important non-verbal elements such as attitude, gesture, and context [ 15 , 16 ].

Given the disruptive impact of the COVID-19 pandemic on nursing qualitative research activities, and deleterious effects on nurses, like emotional exhaustion [ 17 ], psychological distress [ 18 ], and burnout [ 3 , 19 ], but nurse researchers have also been very responsive to the pandemic, the Journal of Advanced Nursing has received hundreds of manuscripts focused on the pandemic, and more than 200 papers published on the COVID-19 pandemic in 2 years [ 2 ]. We doubted the quality of the publication. Scholarly journals are the most important media source for the dissemination of such research findings and information related to connecting this new evidence to practice [ 20 ] and nursing publication plays an essential role in improving nurses’ knowledge of new information and interesting this knowledge into nursing practice [ 21 ]. Together these phenomena might run the risk of producing poor quality qualitative research. Current literature provides two bibliometric analyses of COVID-19 research published in nursing journal, these provide the readers with only objective information on nursing publication related to COVID-19. The existing literature lacks comprehensive reviews that specifically focus on the characteristics and reporting quality of qualitative nursing research related to COVID-19. This study addresses this gap by providing a thorough analysis, which is crucial for guiding future research efforts and improving the overall quality of qualitative studies in nursing. By emphasizing the importance of maintaining high research quality, this study aims to contribute valuable insights that can inform future research, policymaking, and practice in nursing.

Providing a critical review of COVID-19 qualitative nursing research is an unmet need. To achieve this goal, we designed a systematic literature search including all available COVID-19 nursing qualitative articles using a large task force dedicated to the analysis of high-volume articles. We aimed at investigating the characteristics and the methodological quality assessment of reporting COVID-19 qualitative nursing publications.

We conducted a systematic literature search and a critical review using content analysis. This type of content analysis was to enable the production of measurements, occurrences, or comparisons through statistical or quantitative methods [ 22 ]. This review builds upon the methods utilized in two similar reviews [ 23 , 24 ], which assessed the characteristics of articles and described the methodological quality of the articles by presenting the percentage of compliance with each item of a standardized methodological reporting quality checklist. Our study adopted a pre-established checklist which was designed based on the Consolidated Criteria for Reporting Qualitative Research (COREQ) [ 25 ] and the Standards for Reporting Qualitative Research (SRQR) [ 26 ], along with other items identified in the literature to examine the quality of reporting in qualitative research.

This study is an ancillary study that extracted articles related to COVID-19 from the database of a large study aims to assess the characteristics and reporting quality using a qualitative approach in the field of nursing from 2012 to January 2023.

Search strategy

Several databases were consulted to ensure the inclusion of relevant studies in the field of nursing. The main databases are academic and medical databases, such as PubMed, CINAHL (Cumulative Index to Nursing and Allied Health Literature), Cairn, Embase, Web of science and Scopus. Document search strategies are developed using the MeSH thesaurus (Medical subject headings) and related keywords. The MEDLINE strategy has been developed and tested by the research team: “nursing research“[MH] OR “nursing research“[TW] OR (“nursing research“[Title/Abstract:~2]) OR nurs*[affiliation]) AND (“qualitative research“[MH] OR “qualitative research“[TIAB] OR “qualitative study“[TIAB] OR “qualitative studies“[TIAB] OR “grounded theory“[TIAB] OR “phenomenology“[TIAB] OR “ethnography“[TIAB] OR (“qualitative study“[Title/Abstract:~2] OR “qualitative studies“[Title/Abstract:~2] OR “qualitative research“[Title/Abstract:~2] OR “qualitative theory“[Title/Abstract:~2] OR “qualitative theories“[Title/Abstract:~2] OR “grounded study“[Title/Abstract:~2] OR “grounded studies“[Title/Abstract:~2] OR “grounded theory“[Title/Abstract:~2] OR “grounded theories“[Title/Abstract:~2] OR “grounded research“[Title/Abstract:~2] OR “ethnological study“[Title/Abstract:~2] OR “ethnological studies“[Title/Abstract:~2] OR “ethnological theory“[Title/Abstract:~2] OR “ethnological theories“[Title/Abstract:~2] OR “ethnological research“[Title/Abstract:~2] OR “phenomenological study“[Title/Abstract:~2] OR “phenomenological studies“[Title/Abstract:~2] OR “phenomenological theory“[Title/Abstract:~2] OR “phenomenological theories“[Title/Abstract:~2] OR “phenomenological research“[Title/Abstract:~2]. Then, a hand search was conducted to identified articles related to COVID-19. The literature search was performed between June 2023 to August 2023.

Inclusion and exclusion criteria

Any qualitative nursing research related to COVID-19 was included. The first authors must be nurses. The language was limited to English and French. Both peer-reviewed and pre-prints articles were included.

Articles related to non-human samples and full-text unavailable were excluded.

Article screening

We followed the PRISMA 2020 (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) for article selection. All articles yielded through an initial search from the databases were exported into Rayyan Software, a web-based tool designed to conduct and coordinate systematic literature reviews. Hand search was performed to identify articles related to COVID-19, and duplicates were removed. Next, affiliations were examined to determine if the first author was a nurse, and then titles and abstracts were reviewed to determine if the publication met inclusion and exclusion criteria. Two researchers finished the screening independently. Any discrepant result was discussed by the two reviewers and resolved by consensus, or where necessary, a third researcher was involved. Finally, the articles that met the inclusion and exclusion criteria were selected for full-text reading.

Data extraction and data analysis

We used the pre-established checklist combining items from the SRQR and COREQ checklists and adding other items identified in the literature to answer the objective of this study. The checklist included 33 items seen in Tables  1 and 9 items regarding characteristics of the articles, and 24 items regarding methodological quality assessment. The checklist was pilot-tested and revised. Revisions were made after discussion among the researchers and included clarification of checklist items and the response of researchers to each item. For items of the characteristics of the articles, data were extracted to Excel (Excel 2020, Microsoft Excel, Redmond, WA, USA) for categorization. For items of methodological quality assessment, ATLAS.ti software (version 23.2.1) was used. All identified articles were imported into the software for content analysis with the use of a coding function, codes were created according to the items on the data extraction checklist, researcher read the content of the full-text articles one by one, then identified and coded the phrases according to the codes. For example, the code “field note” was created, and the researcher identified and coded the content if it is mentioned in the article. The frequency of each code was calculated to identify the methodological quality of the included articles.

Ethical considerations

This study is a review based on published articles; ethical approval was not required.

A total of 63,494 articles were registered in Rayyan software. Of these, 918 articles (1.44%) were related to COVID-19. After the exclusion of 56 articles due to duplication, the titles, and abstracts of all the articles were examined and 393 articles were excluded due to affiliations in which the first author was not a nurse. The remaining studies were reviewed in full-text. There were 20 articles excluded due to articles with a non-qualitative approach, 4 articles written in a foreign language were excluded, and 1 article was excluded because of full-texted unavailable. A total of 444 full-text articles related to COVID-19 were analyzed. The flowchart is presented in Fig.  1 .

Flowchart of articles screening

Characteristics of the COVID-19 qualitative nursing research

The 444 included articles were published in 196 different journals, one of which was published on MedRxiv, an online pre-print platform for non-peer-reviewed research, with the most articles being published in the International Journal of Environmental Research and Public Health ( n  = 28, 14.3%).

Table  2 shows the most productive journals in terms of COVID-19 nursing qualitative publications. With regard to the quartile of the journals, the studies were published most frequently in Q1 journals ( n  = 260, 58.6%), followed by Q2 ( n  = 118, 26.6%), Q3 ( n  = 49, 11.0%), Q4 ( n  = 12, 2.7%). The impact factors for each journal are grouped into 6 categories: Of the 444 articles, impact factor below 1 ( n  = 54, 12.2%), impact factor between 1 and 1.999 ( n  = 72, 16.2%). In addition, impact factor between 2 and 2.999 ( n  = 107, 24.1%), impact factor between 3 and 3.999 ( n  = 92, 20.7%), impact factor between 4 and 4.999 ( n  = 87, 19.6%), and impact factor of 5 or higher ( n  = 29, 6.5%). And 3 articles published in journals with an impact factor which is not applicable.

We then assessed the distribution of countries among all the included publications. The top 10 publishing countries were the United States ( n  = 64, 14.4%), Iran ( n  = 57, 12.8%), China ( n  = 35, 7.9%), Turkey ( n  = 33, 7.4%), Spain ( n  = 32, 7.2%), Canada ( n  = 22, 5.0%), Indonesia ( n  = 19, 4.3%), Italy ( n  = 16, 3.6%) and the United Kingdom ( n  = 16, 3.6%) respectively, and South Korea ( n  = 14, 3.2%), see Fig.  2 . Regarding the year of publication, 27 articles (6.1%) were published in 2020, 170 articles (38.3%) in 2021, and 240 articles (54.1%) in 2022.

Distribution of countries of COVID-19 related qualitative nursing research published

The academic qualifications of the first authors were reported in 150 (33.8%) of the 444 articles. Of these, 113 (75.3%) first authors have a Ph.D degree ( n  = 113, 75.3%), Ph.D. candidates ( n  = 3, 2.0%), Ph.D. students ( n  = 7, 4.7%), Master degree ( n  = 23, 15.3%), Master students ( n  = 2, 1.3%), and Bachelor degree ( n  = 2, 1.3%). The affiliations of the first author were the universities ( n  = 395, 89.7%), the hospitals ( n  = 34, 7.7%), research centers ( n  = 12, 2.7%), and independent researchers ( n  = 1, 0.2%).

The focuses on COVID-19 qualitative nursing publications were categorized into 7 groups: workforce experience ( n  = 213, 48.0%), pandemic restrictions experience ( n  = 100, 22.5%), learning experience ( n  = 44, 9.9%), infected COVID-19 experience ( n  = 32, 7.2%), hospitalized experience ( n  = 30, 6.8%), psychological perception ( n  = 24, 5.4%), and guideline analysis ( n  = 1, 0.2%) during the COVID-19 pandemic, see Fig.  3 . The population was mainly clinical nurses ( n  = 197, 44.4%), nursing managers ( n  = 15, 3.4%), nurse educators ( n  = 5, 1.1%), nursing students ( n  = 50, 11.3%), other healthcare professionals ( n  = 18, 4.1%), COVID-19 patients ( n  = 31, 7.0%), other patients ( n  = 36, 8.1%), family members / caregivers ( n  = 24, 5.4%), and public ( n  = 68, 15.3%). Figures  4 and 5 shows the population distribution of the included articles.

Focuses of COVID-19 qualitative nursing research

Target population of COVID-19 qualitative nursing research

Distribution of clinical nurses

Methodological quality assessment of COVID-19 qualitative nursing research

Table  3 shows the prevalence of the items for reporting the methodological quality assessment of the included articles.

Methodological orientation

Of the 444 articles, the most adopted approach was the descriptive approach ( n  = 165, 37.1%), Fig.  6 shows the types of approach adopted. Additionally, 84 (18.9%) of the articles only mentioned “qualitative study” without specifying which approach was being adopted.

Types of approach adopted

Only one-third of the analyzed articles ( n  = 135, 30.4%) mentioned employing standardized reporting quality checklists. Among these, the COREQ checklist was the most utilized ( n  = 119, 26.8%), followed by the SRQR checklist ( n  = 16, 3.6%).

Data collection

Among the articles included, 382 (86%) used interviews/discussions as a data collection method, 20 articles (4.5%) used mixed methods for data collection, and 42 articles (9.5%) that used methods other than interviews/discussions, 2.7% used surveys with open questions, 2.03% carried out document analysis, 1.8% examined diaries, 1.6% analyzed comments on social media, 0.5% used the photovoice method, and finally 0.2% carried out an analysis of audio-newspapers, an analysis of video diaries, an analysis of media interviews, only 1 article used observation as data collection method.

With the articles using interview/discussion methods, 261 articles (64.9%) specified who conducted the interviews. And 78 of them (19.4%) provided detailed information on their professional profiles. Most articles ( n  = 327, 81.3%) mentioned the setting of data collection, with 65.4% ( n  = 214) conducted remotely, 28.4% ( n  = 93) conducted face-to-face, and 6.1% ( n  = 20) indicated that the interviews were conducted whether remotely or face-to-face depending on participants’ wishes. The remoted interviews were conducted by teleconference ( n  = 134, 57.3%), by telephone ( n  = 66, 28.2%), and by teleconference or telephone ( n  = 34, 14.5%), depending on the choice of participants. The software commonly used for teleconferencing was Zoom (44.5%), WhatsApp (11%), and Microsoft Teams (9.2%), while 35% did not mention which software was used, Fig.  7 shows the characteristics of data collection. Most articles ( n  = 340, 84.8%) specified the duration of the interviews, they were described in two ways: mean duration ( n  = 87, 25.6) or minimum and maximum duration ( n  = 253, 74.4%). Audio recording was most used (86.7%), followed by visual recording (13.0%), and a few (0.3%) mentioned whether audio/visual recording was used. Most articles ( n  = 351, 87.3%) provided interview guidelines, while only 16.9% ( n  = 68) pre-tested them.

Characteristics of data collection

Participants

Most articles ( n  = 434, 97.7%) mentioned the number of samples. Almost all the articles ( n  = 443, 99.9%) provided a detailed description of the samples. The most common sampling method was purposive sampling ( n  = 244, 66.8%), followed by convenience sampling ( n  = 34, 9.3%) and snowball sampling ( n  = 33, 9.0%). Some articles ( n  = 54, 14.8%) used mixed sampling methods.

Data analysis

The commonly used methods of analysis were content analysis ( n  = 149, 36.0%) and thematic analysis ( n  = 143, 34.4%) (Fig.  8 ). And some articles did not specify which method was used ( n  = 14, 3.4%). And the most common software chosen by the authors were NVivo (46.9%), MAXQDA (26.7%), and ATLAS.ti (16.0%).

Methods of data analysis

Presentation of results

All the articles (100%) presented their results in narrative form. The majority (90.3%) presented quotations in their results. Only 4.7% presented code recurrence. 18.7% used graphics to present their results, and 9.2% mentioned participants checking reports.

This study focused on the identification of the characteristics and reporting quality of qualitative nursing published research related to COVID-19 pandemic. We used a systematic search approach to identify qualitative nursing studies published related to the COVID-19 and then carried out a critical review with the use of content analysis of the identified articles, relying on a checklist created based on two standardized checklists (SRQR and COREQ). A total of 444 published studies were included and critically reviewed. The most productive country was the USA, which corresponds with a bibliometric analysis of COVID-19 research published in a nursing journal. This can be explained by the fact that the USA is one of the most impacted countries by COVID-19 [ 27 ] and is one of the most prolific countries regarding nursing research [ 28 ]. A significant finding of our study is that the majority of articles were published in journals ranked within Quartile 1. This suggests that the research produced during this period not only addressed urgent topics but also met high academic standards.

In addition, the findings revealed that the most represented topics and target population were related to the workforce experience and clinical nurses respectively, this is consistent with an article that focused on the reflections on nursing research during the pandemic COVID-19 [ 2 ]. Interestingly, clinical nurses were the predominant target population of the articles reviewed, this is possibly attributable to the challenge of conducting research with patients and the public due to pandemic-related restrictions. This thematic focus is likely driven by the critical challenge and changes by clinical nurses during the pandemic, highlighting their significant role in the frontline response and the need to understand and support them.

It was surprising to see that the use of standardized checklists to guide research studies by the researchers was notably low, with only 30.4% mentioning the use of standardized checklists. This finding is particularly noteworthy in the context of qualitative nursing research during the COVID-19 pandemic, a period that demanded high-quality evidence to inform rapidly changing clinical practices. The low adoption rate of standardized checklists may reflect gaps in researchers’ awareness or accessibility to these tools, or perhaps a broader issue in the research culture that undervalues structured guidance in study design and reporting, as these checklists aim to improve the quality of reporting these study types and allow readers to better understand the design, conduct, analysis and findings of published studies [ 25 ].

Traditional qualitative research data collection methods like interviews and discussions were supposed to be most impacted by the pandemic. Surprisingly, 86% ( n  = 382) of the included articles used interviews or discussions as the data collection methods, and 28% of the researchers remained choosing the face-to-face interview method. We questioned how communication and facial expression were observed if facemasks were worn during the interview. Among the included studies that used the interview method in data collection, a significant proportion with 66% of these interviews were conducted remotely, either by telephone or online. These findings align with the literature reviewed, where nursing researchers in the USA reported an increase in the use of online platforms, as well as sending emails and phone calls for data collection, a trend which has seen a significant increase [ 8 ]. Researchers in Japan also reported having to adapt their research methods according to changes in the research environment, moving from in-person interviews to remote telephone interviews, collecting data while maintaining the social distancing, and online data collection [ 8 ]. A randomized research study comparing online interviews to in-person interviews person to assess health conditions was conducted in Australia. The results of this study showed that online interviews were preferred by a greater proportion of participants than in-person interviews, and then those assigned to the online group had a lower dropout rate. Additionally, the use of online interviews did not result in a loss of data quality [ 29 ]. Another study also indicated that online modalities for conducting qualitative research did not lead to substantially different thematic findings than in-person data collection [ 30 ]. These suggest that remote data collection methods would be a good choice for researchers, especially in situations where face-to-face interactions are challenging or not possible. The success of remote interviews in maintaining data quality, participant engagement, and lower dropout rates indicates their viability as a robust alternative to traditional methods. This shift not only ensures the continuity of research during crises like the COVID-19 pandemic but also offers a flexible and efficient approach for future qualitative studies. Embracing remote data collection can enhance the adaptability of research designs and potentially broaden the reach and inclusivity of participant recruitment, making it a valuable methodological option for qualitative nursing researchers.

The adoption of software tools in data analysis was surprisingly low, with only 37% of studies utilizing such resources. This finding suggests a potential area for further development in qualitative research practices, particularly to enhance efficiency and collaboration, especially in scenarios necessitating remote work and data sharing, especially during the pandemic when social contact was limited. In addition, there are other benefits of using qualitative data analysis software, including freedom from manual and administrative tasks, saving time, greater flexibility, and improved validity and reliability, and traceability of qualitative research [ 31 ].

In summary, this study carried out an in-depth analysis of data relating to the journals, articles, researchers, and methods used, identifying both strengths and areas requiring improvement. It highlighted the editorial quality of the publications and the methodological diversity observed in qualitative nursing studies linked to the COVID-19 pandemic. We found that many articles demonstrated commendable transparency in explicitly detailing their research approach, data collection processes, sampling methods, and data analysis techniques. However, some areas need improvement. A key aspect is the insufficient representation of strategies to ensure study rigor, such as triangulation and validation by respondents. It is essential to include critical reflection on the role of researchers, potential biases and their influence during the analysis and selection of data for presentation. Additionally, discussions about data saturation and sequential analysis can significantly strengthen the quality of qualitative research reporting. It is important that authors not only explain the methods or techniques they used but also provide clear and detailed justifications for their choices.

The effective translation of nursing research into clinical practice is critical, especially as healthcare professionals heavily depend on the latest research to guide their practices and decisions. The variability in the quality and reliability of research articles can lead to the adoption of clinical practices that may not be supported by strong evidence, potentially affecting patient care and hindering the advancement of nursing practice [ 32 ]. Therefore, improving the transparency and rigor of research methodology reporting is essential to ensure that clinical practices are based on reliable and robust evidence. Our study highlights the importance of methodological clarity and the use of standardized checklists in guiding research, This is increasingly relevant as nursing research evolves to meet global health challenges. By ensuring the high quality of reporting qualitative research, we can better bridge the gap between research and clinical practice, leading to improved patient outcomes and more effective healthcare delivery.

Limitations

It is also essential to recognize that our research method may have some limitations. The diversity of qualitative research methods restricted our assessment to an overview of overall research reporting quality. Additionally, our inclusion criterion based on the first author as a nurse may have excluded studies conducted by nurse-led teams, but where academic conventions led to a different first author. The time limit of the database prevented us from including articles published after January 2023. Finally, we excluded articles not published in English or French, meaning that relevant articles in other languages may have been omitted.

Conclusions

In conclusion, we urge researchers to provide detailed information in their articles, thereby allowing audiences to carefully evaluate the effectiveness and adequacy of the methods and materials used to produce credible and useful results. We also recommend researchers to adopt validated critical appraisal checklists when conducting their studies. This study highlights the importance of continued reflection on qualitative research practices with a view to improving the reporting quality of future studies in the field of nursing, especially during the special period of a pandemic. Additionally, we plan to compare these results with ancillary studies to assess the characteristics and reporting quality of qualitative nursing research before the COVID-19 pandemic. In the future, we wish to open the way for future studies aimed at exploring the relationships between the different criteria identified and each qualitative approach.

Data availability

The data as well as detailed descriptions of the literature search and search outcome (including excluded articles) are available from the corresponding author upon request.

Abbreviations

Coronavirus disease of 2019

Consolidated Criteria for Reporting Qualitative Research

Standards for Reporting Qualitative Research

Medical Subject Heading

Cumulative Index to Nursing and Allied Health Literature

Preferred Reporting Items for Systematic Reviews and Meta-Analyses

United States of America

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Giménez-Espert MDC, Prado-Gascó V, Soto-Rubio A, Psychosocial, Risks. Work Engagement, and job satisfaction of nurses during COVID-19 pandemic. Front Public Health. 2020. https://doi.org/10.3389/fpubh.2020.566896 . 8;566896.

Peasgood T, Bourke M, Devlin N, Yang Y, Dalziel K. Randomised comparison of online interviews versus face-to-face interviews to value health states. Soc Sci Med. 2023. https://doi.org/10.1016/j.socscimed.2023.115818 . 1982(323);115818.

Guest G, Namey E, Chen M. A simple method to assess and report thematic saturation in qualitative research. PLoS ONE. 2020;15(5):e0232076. https://doi.org/10.1371/journal.pone.0232076 .

Cypress BS. Qualitative research: challenges and dilemmas. Dimens Crit Care Nurs. 2019;38(5):264–70. https://doi.org/10.1097/DCC.0000000000000374 .

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Vong, II., Rothan-Tondeur, M. & Nohra, R.G. Characteristics and quality of reporting qualitative nursing research related to the COVID-19 pandemic: a systematic search and critical review. BMC Nurs 23 , 498 (2024). https://doi.org/10.1186/s12912-024-02138-x

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Qualitative research and its role in nursing knowledge

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There are several reasons why qualitative research is a suitable means to answer a number of relevant nursing research issues. However, as a research methodology it is not without its critics. This article debates the importance of qualitative research to nursing knowledge and uses the literature and practice experience to evaluate its contribution.

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• Mixed methods research: expanding the evidence base
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• Allison Shorten 1 ,
• Joanna Smith 2
• 1 School of Nursing , University of Alabama at Birmingham , USA
• 2 Children's Nursing, School of Healthcare , University of Leeds , UK
• Correspondence to Dr Allison Shorten, School of Nursing, University of Alabama at Birmingham, 1720 2nd Ave South, Birmingham, AL, 35294, USA; [email protected]; ashorten{at}uab.edu

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Introduction

‘Mixed methods’ is a research approach whereby researchers collect and analyse both quantitative and qualitative data within the same study. 1 2 Growth of mixed methods research in nursing and healthcare has occurred at a time of internationally increasing complexity in healthcare delivery. Mixed methods research draws on potential strengths of both qualitative and quantitative methods, 3 allowing researchers to explore diverse perspectives and uncover relationships that exist between the intricate layers of our multifaceted research questions. As providers and policy makers strive to ensure quality and safety for patients and families, researchers can use mixed methods to explore contemporary healthcare trends and practices across increasingly diverse practice settings.

What is mixed methods research?

Mixed methods research requires a purposeful mixing of methods in data collection, data analysis and interpretation of the evidence. The key word is ‘mixed’, as an essential step in the mixed methods approach is data linkage, or integration at an appropriate stage in the research process. 4 Purposeful data integration enables researchers to seek a more panoramic view of their research landscape, viewing phenomena from different viewpoints and through diverse research lenses. For example, in a randomised controlled trial (RCT) evaluating a decision aid for women making choices about birth after caesarean, quantitative data were collected to assess knowledge change, levels of decisional conflict, birth choices and outcomes. 5 Qualitative narrative data were collected to gain insight into women’s decision-making experiences and factors that influenced their choices for mode of birth. 5

In contrast, multimethod research uses a single research paradigm, either quantitative or qualitative. Data are collected and analysed using different methods within the same paradigm. 6 7 For example, in a multimethods qualitative study investigating parent–professional shared decision-making regarding diagnosis of suspected shunt malfunction in children, data collection included audio recordings of admission consultations and interviews 1 week post consultation, with interactions analysed using conversational analysis and the framework approach for the interview data. 8

What are the strengths and challenges in using mixed methods?

Selecting the right research method starts with identifying the research question and study aims. A mixed methods design is appropriate for answering research questions that neither quantitative nor qualitative methods could answer alone. 4 9–11 Mixed methods can be used to gain a better understanding of connections or contradictions between qualitative and quantitative data; they can provide opportunities for participants to have a strong voice and share their experiences across the research process, and they can facilitate different avenues of exploration that enrich the evidence and enable questions to be answered more deeply. 11 Mixed methods can facilitate greater scholarly interaction and enrich the experiences of researchers as different perspectives illuminate the issues being studied. 11

The process of mixing methods within one study, however, can add to the complexity of conducting research. It often requires more resources (time and personnel) and additional research training, as multidisciplinary research teams need to become conversant with alternative research paradigms and different approaches to sample selection, data collection, data analysis and data synthesis or integration. 11

What are the different types of mixed methods designs?

Mixed methods research comprises different types of design categories, including explanatory, exploratory, parallel and nested (embedded) designs. 2   Table 1 summarises the characteristics of each design, the process used and models of connecting or integrating data. For each type of research, an example was created to illustrate how each study design might be applied to address similar but different nursing research aims within the same general nursing research area.

• View inline

Types of mixed methods designs*

What should be considered when evaluating mixed methods research?

When reading mixed methods research or writing a proposal using mixed methods to answer a research question, the six questions below are a useful guide 12 :

Does the research question justify the use of mixed methods?

Is the method sequence clearly described, logical in flow and well aligned with study aims?

Is data collection and analysis clearly described and well aligned with study aims?

Does one method dominate the other or are they equally important?

Did the use of one method limit or confound the other method?

When, how and by whom is data integration (mixing) achieved?

For more detail of the evaluation guide, refer to the McMaster University Mixed Methods Appraisal Tool. 12 The quality checklist for appraising published mixed methods research could also be used as a design checklist when planning mixed methods studies.

• Elliot AE , et al
• Creswell JW ,
• Plano ClarkV L
• Greene JC ,
• Caracelli VJ ,
• Ivankova NV
• Shorten A ,
• Shorten B ,
• Halcomb E ,
• Cheater F ,
• Bekker H , et al
• Tashakkori A ,
• Creswell JW
• 12. ↵ National Collaborating Centre for Methods and Tools . Appraising qualitative, quantitative, and mixed methods studies included in mixed studies reviews: the MMAT . Hamilton, ON : BMJ Publishing Group , 2015 . http://www.nccmt.ca/resources/search/232 (accessed May 2017) .

Competing interests None declared.

Provenance and peer review Commissioned; internally peer reviewed.

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eTable 1. Contextual Data for Participating Trusts (2019)

eTable 2. Diagnostic Groups in Sample (Main Diagnostic Group and Comorbidities)

eFigure 1. Low Staffing Effects Using Alternate Thresholds for Low Staffing

eTable 3. Sensitivity Analysis: Different Exposure Windows for Low Staffing

eTable 4. Effects of Low Staffing and Staff-Mix on Mortality - Survival Models With Single Staff-Mix Factors

eFigure 2 . Nonlinear Relationship: Support Staff-Mix and Hazard of Death

eTable 5. Combined Model for Associations Between Staff-Mix and Mortality (Linear and Nonlinear)

eFigure 3. Interaction Between Low Staffing and Staff-Mix

eAppendix. Estimating the Effects of Eliminating Low Staffing With Temporary Staff

eTable 6. Data Used to Estimate Net Effects of Averting Low Staffing Using Temporary Staff

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Griffiths P , Saville C , Ball J, et al. Nursing Team Composition and Mortality Following Acute Hospital Admission. JAMA Netw Open. 2024;7(8):e2428769. doi:10.1001/jamanetworkopen.2024.28769

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Nursing Team Composition and Mortality Following Acute Hospital Admission

• 1 School of Health Sciences, University of Southampton, Southampton, United Kingdom
• 2 Portsmouth Hospitals University Trust, Portsmouth, United Kingdom
• 3 National Institute for Health Research Applied Research Collaboration, Wessex, United Kingdom
• 4 Statistical Sciences Research Institute, University of Southampton, Southampton, United Kingdom

Question   Is variation in the composition of the nursing team on a hospital inpatient unit associated with risk of patient death?

Findings   In this longitudinal cohort study of 626 313 patient admissions in 4 centers, there was a statistically significant increase in the risk of death among patients exposed to days of low nurse staffing or high proportions of temporary staff. When low staffing was averted using temporary staff, the risk was reduced but remained elevated compared with the baseline.

Meaning   These findings suggest that the risk of death associated with low nurse staffing is only partly mitigated by using temporary staff to remedy shortfalls.

Importance   Many studies show the adverse consequences of insufficient nurse staffing in hospitals, but safe and effective staffing is unlikely to be just about staff numbers. There are considerable areas of uncertainty, including whether temporary staff can safely make up shortfalls in permanent staff and whether using experienced staff can mitigate the effect of staff shortages.

Objective   To explore the association of the composition of the nursing team with the risk of patient deaths.

Design, Setting, and Participants   This patient-level longitudinal observational study was conducted in 185 wards in 4 acute hospital trusts in England between April 2015 and March 2020. Eligible participants were patients with an overnight stay and nursing staff on adult inpatient wards. Data analysis was conducted from month April 2022 to June 2023.

Exposure   Naturally occurring variation during the first 5 days of hospital admission in exposure to days of low staffing from registered nurses (RNs) and nursing support (NS) staff, the proportion of RNs, proportion of senior staff, and proportion of hospital-employed (bank) and agency temporary staff.

Main Outcomes and Measures   The primary outcome was death within 30 days of admission. Mixed-effect Cox proportional hazards survival models were used.

Results   Data from 626 313 admissions (319 518 aged ≥65 years [51.0%]; 348 464 female [55.6%]) were included. Risk of death was increased when patients were exposed to low staffing from RNs (adjusted hazard ratio [aHR], 1.08; 95% CI 1.07-1.09) and NS staff (aHR, 1.07; 95% CI, 1.06-1.08). A 10% increase in the proportion of temporary RNs was associated with a 2.3% increase in the risk of death, with no difference between agency (aHR, 1.023; 95% CI, 1.01-1.04) and bank staff (aHR, 1.02; 95% CI, 1.01-1.04). A 10% increase in the proportion of agency NS was associated with a 4% increase in risk of death (aHR, 1.04; 95% CI, 1.02-1.06). Evidence on the seniority of staff was mixed. Model coefficients were used to estimate the association of using temporary staff to avoid low staffing and found that risk was reduced but remained elevated compared with baseline.

Conclusions and Relevance   This cohort study found that having senior nurses in the nursing team did not mitigate the adverse outcomes associated with low nurse staffing. These findings indicate that while the benefits of avoiding low staffing may be greater than the harms associated with using temporary staff, particularly for RNs, risk remains elevated if temporary staff are used to fill staffing shortages, which challenges the assumption that temporary staff are a cost-effective long-term solution to maintaining patient safety.

Many studies and inquiries into poor care have demonstrated the adverse consequences of inadequate nurse staffing on acute hospital wards, including increased risk of patient death and suboptimal experiences for both patients and staff. 1 - 3 While existing evidence can be used to make a compelling case for avoiding low staffing and increasing the availability of registered nurses (RNs), safe and effective staffing is not solely determined by the number of staff, but involves many factors including the composition, skill, and experience of the nursing team. 4 , 5 Although some consideration has been given to the mix of staff between RNs and nursing support (NS) staff, much less attention has been given to other aspects of the mix of staff.

Studies on nursing skill-mix in acute care hospitals typically define skill-mix as the proportion of RNs among all those delivering hands-on nursing care. 6 The wider team includes NS staff who work under the supervision of RNs, including nursing assistants, who are not professionally registered, and nurses with lower-level qualifications such as licensed practical nurses and nursing associates, a role recently introduced in the UK to support RNs. 6 Most findings suggest that a skill-mix with a lower proportion of RNs is associated with more adverse outcomes 6 and either unchanged or increased net costs. 7 However, there is ongoing interest in modifying skill-mix to contain costs and alleviate the effects of RN shortages. 8

Temporary staff are often used to compensate for staff shortages or as a potentially efficient way of responding to variations in demand. Some studies have found a higher risk of adverse events with high levels of temporary staff. Unfamiliarity with the care setting is hypothesized to lead to inefficiency, reduced continuity, and, hence, increased risk to patients. 9 - 11 However, other studies have found no adverse outcomes from using temporary staff to maintain staffing levels. 12 , 13 Recent research highlights differences in the impact of external agency nurses and temporary staff directly employed by hospitals. 14 The same study also identified that more senior RNs were more productive, thus raising the possibility that more senior staff could partially mitigate the adverse effects of low staffing. 14 Within England, recent changes have focused on improving the skills of staff who provide support to nurses by introducing a new role, the RN associate, 15 but no research has thus far explored the effect of staff-mix among support staff.

In this article, we aim to fill the gaps and uncertainties in existing literature by presenting findings from a multisite study in England. We investigated the association of the risk of death following an acute admission with nursing team composition. Specifically, we examined the impact of low staffing, the proportion of RNs, the seniority of both RNs and NS staff, as well as the proportion of temporary staff.

This cohort study was approved by the Health Research Authority and the University of Southampton Ethics Committee. The research was conducted in accordance with the Declaration of Helsinki 16 ; written informed consent was not required because data was deidentified with no reasonable possibility of identifying any living person. Patients in the National Health Service have the option of opting out of use of their data in this fashion for research purposes. Reporting followed the Strengthening the Reporting of Observational Studies in Epidemiology ( STROBE ) reporting guideline. We used anonymized patient records and nurse roster data from 4 acute hospital trusts in England from April 2015 to March 2020 to explore longitudinal associations of staffing levels and staff-mix with outcomes. The trusts were diverse in many respects, including size and teaching status (and eTable 1 and eTable 2 in Supplement 1 ). Eligible patients were those with elective and emergency admissions with an overnight stay in an adult medical, surgical, or intensive care ward.

The primary outcome was death from all causes within 30 days of admission (including death after discharge). We used details in the patient record to calculate an estimated risk of death using the published Summary Hospital Mortality Indicator (SHMI) model, 17 , 18 based on age, diagnosis ( International Statistical Classification of Diseases and Related Health Problems, Tenth Revision [ ICD-10 ]), method of admission (emergency vs elective) and comorbidities. We applied the April 2019 model, developed from national data for the previous 3 years, which coincided with the study period.

Staffing data consisted of worked shifts from ward rosters. Nursing staff were identified as RN or NS from their pay band, using the national grading system. 19 Jobs in the English National Health Service are evaluated and allocated into 1 of 9 major bands based on criteria including the levels of judgement, knowledge, and skills required, with band 5 and above used for RNs and 4 or lower for NS staff. 20 We calculated the number of hours provided by each of these staff groups and divided these by patient-days to calculate hours per patient-day (HPPD) for both RNs and NS staff. We identified temporary staff employed directly by the hospital (ie, bank) or hired through an external agency and calculated the hours worked within each staff group. These data were used to calculate variables to indicate understaffing and the mix of staff for each day of each patient’s stay.

We estimated the expected staffing for both RN and NS staff using the mean staffing levels (in HPPD) for each ward. Where we identified sustained change in the most frequent diagnostic categories, main specialty, sex, modal age group, mix of elective vs emergency admissions, proportion of overnight stays, or patient occupancy, we divided the time series and calculated the expected staffing level for each period. We identified days when a patient experienced staffing below expected, using days below the mean HPPD as the primary threshold, with other thresholds above and below the mean tested in a sensitivity analysis. We focused analysis on exposures that occurred during the first 5 days of the hospital stay, accounting for the majority of the stay for most patients, although we assessed the sensitivity of results using longer and shorter exposure periods.

We identified the daily proportion of hours worked by RNs and considered the mix of grades within the RN and NS staff groups as a proxy for experience and seniority. We calculated the percentage of senior RNs based on proportion of RN hours delivered by band 6 and above. Band 5 is used for the majority of staff nurses, with band 6 and above used for senior staff nurses, ward managers, charge nurses, and their deputies.

We calculated the percentage of senior NS staff based on the proportion of NS hours delivered by band 4 staff. Whereas there are no formal training requirements for NS staff as a whole, band 4 is generally used for those with extensive formal training and experience including RN associates, a relatively new role with apprenticeship training leading to a foundation degree. 15 We calculated the percentage of RN hours from temporary staff, separating hours staff employed through the hospital’s own bank and from an external agency. Similarly, we calculated the percentage of temporary NS hours.

We linked staffing levels and the mix of staff for each day of each patient’s stay to the patient records. Patient-days not matched to RN staffing were treated as missing, although patient-days where NS hours were 0 were retained because wards can operate without support staff. The previous day’s staffing values were carried forward in the case of missing values.

We used mixed-effect Cox proportional hazards survival models to handle time-varying covariates because patients experience daily variations in staffing during their hospital stay. 21 In all models, patient case-mix adjustment was undertaken using the SHMI risk score (range 0%-100% indicating estimated risk of death), with ward included as a random effect to account for unmeasured ward-level factors. Models without staffing factors gave good concordance (C-index = 0.854). The assumption of proportional hazards was examined by graphing scaled Schoenfeld residuals and was reasonable for the staffing variables.

We first assessed the association of exposure with low staffing. Because detrimental understaffing effects may accumulate over time, we modeled days of low staffing as a cumulative time-dependent covariate. We then assessed the association of staff-mix with outcomes. Initially, we estimated models including low staffing and one staff-mix factor, comparing model fit to the model with low staffing only. Staff-mix factors that improved model fit were then included in a combined multivariable model, after which we assessed interactions between staff-mix and low staffing and nonlinear associations. We used the Akaike information criterion and the Bayesian information criterion to assess model fit, preferring models that minimized the values of both. 22

Dataset construction and analysis was undertaken using R version 4.3.0 (R Project for Statistical Computing) with Rstudio (Posit), 23 , 24 data wrangling and descriptive statistics used the packages tidyverse 2.0.0 and finalfit 1.0.6. 25 , 26 Survival dataset construction and analysis used survival 3.5-5 and coxme 2.2-18.1 packages. 27 , 28 Significance was considered a 2-sided P  < .05. Data analysis was conducted from April 2022 to June 2023.

We linked data for 626 313 admissions (319 518 aged 65 years or older [51.0%]; 348 464 female [55.6%]) to 185 inpatient units across 4 trusts ( Table 1 ). Of all admissions, 502 717 (80.3%) were emergencies and 412 403 (65.8%) were to medical specialties. See eTable 2 in Supplement 1 for diagnostic groups. The median (IQR) hospital stay was 3.63 (1.77-8.28) days. Most admissions had at least 1 comorbidity with 279 415 (44.6%) having a Charlson Comorbidity Index score greater than 5. Mortality within 30 days of admission was 5.1% (31 885 admissions).

Mean (SD) staffing over the first 5 days was 5.29 (4.22) RN HPPD and 2.93 (1.37) NS HPPD ( Table 2 ). Low staffing (below the ward mean) occurred on 1 116 749 of 2 468 860 patient days (45.2%). The mean (SD) RN proportion was 61.50% (0.12%). Mean (SD) RN hours included 25.44% (0.18%) from senior staff (band 6 and above), 5.20% (0.10%) from temporary bank staff, and 4.84% (0.10%) from temporary agency staff. Of NS hours, a mean (SD) 1.97% (0.06%) were provided by senior staff (band 4). Nearly 14% of NS hours were provided by temporary staff, mostly bank (mean [SD], 12.28% [0.19%]).

Of the 514 899 patients exposed to days of low RN staffing, 27 397 (5.3%) died, whereas 4488 of 111 414 (4.0%) who were not exposed died. Results were similar for patients exposed to days of low NS staffing. In the multivariable model, each day of low RN staffing was associated with a 7.9% increase in risk of death (adjusted hazard ratio [aHR], 1.08; 95% CI, 1.07-1.09; P  < .001) and each day of low NS staffing was associated with a 7.2% increase in risk (aHR, 1.07; 95% CI, 1.06-1.08; P  < .001) ( Table 3 ).

Results were similar when low staffing was defined at different thresholds below the mean, while the estimated adverse effects of low RN staffing increased with thresholds above the mean (eFigure 1 in Supplement 1 ). Models using the first 3 and 10 days of staffing gave similar results to those using 5 days (eTable 3 in Supplement 1 ). Models with ward as a fixed effect gave similar estimates for staffing effects, as did models including weekend admission as a factor.

Adding single staff-mix factors to the low staffing model improved model fit, except for the proportion of RNs. A higher proportion of senior RNs was associated with a lower risk of death (aHR, 0.99; 95% CI, 0.97-1.00; P  = .005) whereas higher proportions of temporary staff were associated with a higher risk of death (eTable 4 in Supplement 1 ). Staff-mix factors leading to improved model fit were then included in a combined multivariable model ( Table 3 ).

Every 10% increase in the proportion of temporary RNs (bank and agency) was associated with a 2.3% increase in risk of death for both bank temporary staff (aHR, 1.02; 95% CI, 1.01-1.04; P  = .005) and agency temporary staff (aHR, 1.02; 95% CI, 1.01-1.04; P  < .001). Increases in bank assistants had a similar association (aHR, 1.02; 95% CI, 1.01-1.03; P  < .001), but every 10% increase in the proportion of agency assistants was associated with a 4% increase in risk (aHR, 1.04; 95% CI, 1.02-1.06). Small reductions in risk were observed with increased proportions of senior RN and NS staff, but they were not statistically significant. If the senior RN was defined as band 7 and above, the conclusion was unaltered.

We tested for nonlinear associations, adding polynomial terms for staffing variables. The marginal effect of understaffing increased when patients were exposed to more days of understaffing while the marginal effect of a higher proportion of bank assistants and senior NS staff reduced as levels approached 20% (eFigure 2 in Supplement 1 ); however, model fit was not improved (increased bayesian information criterion) (eTable 5 in Supplement 1 ). We tested for interactions between low staffing and the staff-mix variables of grade-mix and temporary staffing. While some interactions were statistically significant, plots suggested trivial effects (see eFigure 3 in Supplement 1 for examples) and overall model fit was worse.

We estimated the net effects of rectifying low staffing using temporary staff. We used hazard ratio estimates from Table 3 (model 2) and applied them to the mean staffing levels and shortfalls in Table 2 , assuming that observed shortfalls were removed by temporary staff, thus increasing the proportion of temporary staff (eAppendix and eTable 6 in Supplement 1 ). If using temporary staff to avoid shortfalls, the resulting increase in temporary staff partially offsets the benefit from avoiding low staffing, leading to an estimated net reduction in the risk of death of 4.1% for low staffing averted using temporary RNs (bank or agency) or bank NS, compared with a decrease of 7.7% associated with rectifying low staffing with permanent RNs. When agency NS staff were used to address shortfalls of support staff, the reduction in risk of death was 1.2%.

In this cohort study, when patients were exposed to days of low nurse staffing, the risk of death was substantially increased. The mix of staff was associated with variation in the risk of death, but there was no evidence that more senior staff or temporary staff could fully compensate for the effect of low staffing. There was some evidence that having more senior staff within the RN and NS staff groups was associated with reduced risk of death, but results were inconsistent. Higher proportions of temporary staff were associated with an increased risk of death. Agency NS staff had a larger adverse association than those employed through the hospital bank. To our knowledge, this is the first study to explore the offsets between low staffing and temporary staff use. While the benefits of avoiding low staffing were greater than the harms associated with temporary staff, net benefits from more staff were diminished, and, in the case of agency-employed NS staff, negligible.

Our findings on the adverse outcomes of low RN staffing are consistent with a growing body of evidence, which includes an increasing number of longitudinal studies examining individual patient exposures to low staffing levels. 3 The adverse association of low RN staffing was greater than that of NS staffing, but low NS staffing was still associated with increased risk of death. We found no evidence that the proportion of RNs was associated with increased mortality. This finding seems to go against a considerable body of prior research, which has mostly found that a greater presence of RNs in the skill-mix is associated with a reduction in adverse events. 6 , 7 Other studies using methods similar to those of this study have concluded that having adequate support staff is important for patient safety, 29 but the preponderance of evidence, including some pointing to adverse effects arising from both high and low support staffing levels 30 should caution against a simplistic interpretation of this evidence as supporting substitution. Rather, we interpret this finding as indicating that adequate staffing of the nursing team, including support staff, is important for maintaining patient safety.

Previous studies support a beneficial effect from the use of more senior staff within the nursing team although these studies have not considered the mix of the support team. 14 Our finding is consistent with some benefits from the relatively new RN associate role, which will increase the proportion of senior support staff. The possibility of a nonlinear association in our findings suggests a diminishing return and even adverse effects at higher levels, but conclusions must be tentative because model fit was not improved. Evidence that more senior RNs reduced the risk of death was mixed in that the effect was reduced and not statistically significant in models that included all staff-mix factors.

Previous research on the use of temporary staff has led to mixed conclusions. Aiken and colleagues 12 , 13 concluded that an apparent association of high use of temporary staffing and adverse staff with patient outcomes could be attributed to poor work environments and lower staffing levels in hospitals using more temporary staff. Hurst et al 31 concluded that wards using temporary staff were more expensive to run but could deliver similar quality of care. On the other hand, a UK study 11 found that days with high use of temporary staffing were associated with increased risk of death independently of low staffing. Our study also found that higher proportions of temporary staff were associated with increased risk, irrespective of low staffing, with no important interaction between the two. We were able to assess the possible impact of trade-offs between risks from low staffing and risks from using temporary staff. The harm associated with low staffing was greater than that associated with using temporary staff to rectify any shortfall. While this finding is reassuring, use of temporary staff to rectify shortfalls is unlikely to be cost-effective because outcomes are worse with likely higher costs. 32 We did not observe any difference for temporary RNs employed through the hospital bank compared with an agency, but agency support staff had little, if any, contribution to maintaining patient safety.

Our research has several strengths. We were able to use objective longitudinal data to explore the association of variation in staffing over time with the risk of death. We included many inpatient units, and the trusts were diverse. However, this study also has limitations. The study was observational, so cause cannot be established. We used mean observed staffing as a reference point for expected staffing to account for different staffing requirements in different wards; however, mean staffing is influenced by factors other than patient need. We considered the grade of staff within RN and NS staff groups as a proxy for skills and experience. Although the bands are based on assessments of the knowledge skills and judgement required to perform a role, we had no direct measure nor could we assess variation within grades. We focused on only a single outcome, but low staffing is known to have adverse effects on a range of outcomes for patients, quality of care, and staff. The effects of staff-mix on these outcomes may differ. Further qualitative and quantitative research to understand the work of temporary staff would be of value. We used model coefficients to estimate the trade-offs between risks from low staffing and risks from using temporary staff, but this assumes the associations were causal and the estimates were unbiased.

In this cohort study, low levels of nurse staffing in hospital wards were associated with an increased risk of death. Having sufficient seniority and experience within the nursing team was important, but it did not provide a strategy to mitigate the adverse effects of staff shortfalls. While the benefits of avoiding low staffing were greater than the harms associated with using temporary staff, particularly for RNs, risk remained elevated if temporary staff were used to fill staffing shortages. While our findings show the importance of considering the mix of staff as well as absolute numbers, the largest effect sizes observed were those associated with low staffing. This finding challenges the assumption that temporary staff are a cost-effective long-term solution to maintaining patient safety.

Accepted for Publication: June 24, 2024.

Published: August 19, 2024. doi:10.1001/jamanetworkopen.2024.28769

Open Access: This is an open access article distributed under the terms of the CC-BY License . © 2024 Griffiths P et al. JAMA Network Open .

Corresponding Author: Peter Griffiths, RN, PhD, School of Health Sciences, University of Southampton, Southampton SO17 1BJ, United Kingdom ( [email protected] ).

Author Contributions: Drs Griffiths and Meredith had full access to all of the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis.

Concept and design: Griffiths, Ball, Culliford, Jones, Lambert, Dall'Ora.

Acquisition, analysis, or interpretation of data: All authors.

Drafting of the manuscript: Griffiths, Ball, Rubbo.

Critical review of the manuscript for important intellectual content: All authors.

Statistical analysis: Griffiths, Meredith, Rubbo.

Obtained funding: Griffiths, Jones, Dall'Ora.

Administrative, technical, or material support: Lambert.

Supervision: Griffiths, Ball, Jones.

Conflict of Interest Disclosures: None reported.

Funding/Support: This project was funded by the National Institute for Health and Care Research (NIHR) Health Services and Delivery Research Programme (award No. NIHR128056) and the NIHR Applied Research Collaboration (Wessex).

Role of the Funder/Sponsor: The funder agreed to the protocol but had no part in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.

Disclaimer: This paper presents independent research commissioned by the NIHR. The views and opinions expressed by authors in this publication are those of the authors and do not necessarily reflect those of the National Health Service, the NIHR Coordinating Centre, the Health and Social Care Delivery Research Programme or the Department of Health and Social Care.

Group Information: A full list of the Workforce Health Outcomes Study Group appears in Supplement 2 .

Data Sharing Statement: See Supplement 3 .

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Qualitative Research and its Uses in Health Care

Although relatively uncommon in health care research, qualitative research is now receiving recognition and is increasingly used in health care research with social and cultural dimensions. Unlike quantitative research, which is deductive and tends to analyze phenomena in terms of trends and frequencies, qualitative research seeks to determine the meaning of a phenomenon through description. It aims to develop concepts that aid in the understanding of natural phenomena with emphasis on the meaning, experiences and views of the participants. Differences among qualitative researchers exist on matters of ontology, epistemology, data collection methods and methods of evaluation. The aim of this article is not to act as a practical guide on how to conduct qualitative research, but is an attempt to give an introduction to qualitative research methods and their use in health-related research.

Q ualitative research is defined as an umbrella term covering an array of interpretative techniques which seek to describe, decode, translate and otherwise come to terms with the meaning, not the frequency, of certain more or less naturally occurring phenomena in the social world. 1 , 2

As a method of inquiry, it was first used by sociologists and anthropologists in the early twentieth century, although it existed much earlier than that in its non-structural form. Researchers studied cultures and groups in their own and foreign settings and told stories of their experience long before then. In the 1920s and 1930s, social anthropologists and sociologists implemented a more focused approach compared to the old unsystematic and journalistic style used in those days. Since the 1960s, qualitative research has experienced a steady growth starting with the development of grounded theory and new publications in ethnography. 3 , 4 The number of books, articles and papers related to qualitative research has increased tremendously during the past 20 years and more researchers, including health-related professionals, have moved to a more qualitative paradigm adapting and modifying these approaches to the study needs of their own areas. 4

Since qualitative research does not aim to enumerate, it is sometimes viewed as the exact opposite to quantitative methods and the two methods are frequently presented as antagonists. Quantitative research is based on structure and uses experiments and surveys as methods. In addition, it is deductive in nature and uses statistical sampling methods. In contrast, qualitative research is described as an action research using observation and interview methods. It is inductive in nature and depends on the purposeful selection of participants. Whereas quantitative researchers use reliability as a way of verification, qualitative researchers use validity. Recently, there has been a growing recognition that the quantitative-qualitative debate and distinction is unnecessary and that it would be more fruitful for the relation between the two methods to be complementary and overlapping rather than exclusive. 6 In fact, neither qualitative nor quantitative research is superior to the other; there are weaknesses and strengths in each method. Qualitative and quantitative research methods can indeed be seen as complementary and both are necessary to provide an understanding of a phenomenon.

Several researchers have argued that the research questions and the phenomenon under investigation should determine the methodology to used. 7 , 8 , 9 The crucial question, therefore, is not “what is the best research method?” but “what is the best research method for answering this question most effectively and efficiently?” 10 So, while qualitative and quantitative research may well investigate similar topics, each will address a different type of question. Holman sums up this position: “true understanding in medicine cannot be achieved without adding qualitative methods to the research arsenal”. 11

Traditional quantitative methods, such as randomised controlled trials, are the appropriate means of testing, for example, the effect of an intervention or a treatment, while a qualitative exploration of beliefs and understandings is needed to find out why the results of research are often not implemented in clinical practice. The aim of qualitative research is to develop concepts that can help us understand social phenomena in natural settings, giving emphasis on the meanings, experiences and views of the participants. 10

Qualitative research methods are the most suitable for this approach because of their emphasis on people’s lived experience. They are considered to be well suited for locating the meanings that people place on the events, processes, and structures of their lives and their perceptions, presuppositions and assumptions. 5 In his advice to graduate students, Patton lists a number of conditions that are suitable for a qualitative study. These include: questions about people’s experiences; inquiry into the meanings people make of their experiences; studying a person in the context of her or his social/interpersonal environment and research where it is difficult to develop a standardised instrument due to the lack of knowledge on the phenomenon. 12

ARGUMENTS FOR AND AGAINST QUALITATIVE METHODS

There are major differences of opinions among qualitative researchers on matters of ontology and epistemology as well as the methods to be used and criteria of evaluation. There are also disagreements about the nature, purpose, status and practice of its methods. A large number of authors take a predominantly method-based approach; authors such as Miles and Huberman 5 and Patton 12 put emphasis on data collection techniques. Another approach is to classify qualitative research according to research traditions, i.e. whether phenomenological, grounded theory or ethnography, amongst others. Authors such as Creswel 9 and Denzin and Lincolin 3 prefer this approach, which has the advantage of being based on systematisation of knowledge providing a sense of order and orientation. On the other hand, it has the disadvantage of oversimplification, ignoring the issues of the research question and conceptual frameworks used and the way these issues can shape the research process and the findings. 13 In addition, some researchers have decided to classify qualitative research according to the research question or the method of analysis.

Although the majority of qualitative researchers stress that qualitative research is inductive in nature, in contrast to quantitative research which is deductive, there are qualitative researchers who argue that both can be used for different purposes and at different times, and that qualitative research can be done in a deductive way where prior assumptions are tested on new cases. 14 Retroduction, which is defined as the movement backward and forward between theory and data or the combination of deduction and induction, is said to be a characteristic of qualitative research. 11 The degree of deduction or induction and which one follows the other depends on the research question. 12 .

Guba and Lincoln 15 used the term “emergent design” to describe a qualitative study design that emerges as the study progresses in response to the researcher’s early observations. There are also qualitative studies in health care that base their research questions on the results of prior literature of quantitative studies on the subject. 16 , 17 While the research questions in these studies were relatively precise, the method used was flexible.

Miles and Huberman 5 state that no study conforms exactly to a standard methodology and that the researcher bends the methodology to the peculiarities of the study. According to Creswell, 9 traditions of inquiry used “need not be pure, and one might mix procedures from several”. Mixing approaches and procedures is encouraged by some authors and regarded as a creative approach to qualitative research. 12

Studies using qualitative research in health care have been criticised for the misguided separation of method from theory and of technique from the conceptual underpinnings. 18 However, qualitative health researchers respond by stating that the choice of method and how it is used can perfectly well be matched to what is being studied rather than to the methodological leanings of the researcher. 10 It has been suggested that incorporating qualitative research method experts into health research teams enriches research and ensures that the right methodology is used for answering the right questions. Finally, using qualitative methods in health-related research has resulted in more insight into health professionals’ perceptions of lay participation in care and identification of barriers to changing healthcare practice.

QUALITATIVE RESEARCH APPROACHES

Grounded theory, phenomenology and ethnography are three approaches used in qualitative research. Grounded theory approach is a commonly used qualitative method in the social sciences to inductively generate or discover a theory out of the data. 9 Phenomenology and ethnography are more commonly used qualitative approaches in health care and will be highlighted below.

PHENOMENOLOGY

One of the major strengths of qualitative research is its emphasis upon understanding the phenomenon of interest holistically and in its context. The term phenomenology is popular and widely embraced, but its meaning has become confusing and faint. Different researchers refer to phenomenology differently. It can refer to an inquiry paradigm, an interpretive theory, a philosophy, an analytical perspective, a major qualitative research tradition or a research method framework. 12

In spite of the differences, all of these approaches share the focus of phenomenology, which is exploring how human beings make sense of experience and the meaning they give to these experiences. Phenomenology is being used in the social and human sciences including sociology, education, psychology, nursing and health sciences. 9

Phenomenologists are interested in how people put together the phenomena they experience in such a way as to make sense of the world and develop a worldview. They assume commonality in human experience and focus on meaning-making as the essence of human experience. The essence is the core meaning mutually understood through a phenomenon commonly experienced. 12 The phenomenon under study may be emotions, relationships, a programme, an organisation or a culture. 12 Bracketing is one of the central ideas in phenomenology. It means that the researcher has to set aside all of his prejudgments and his previous experience about the phenomena and approach the field with an open mind, imagination and intuition. Although important, bracketing is often said to be a difficult task. 9

Patton 12 describes the difference between conducting a phenomenological study and using a phenomenological perspective to a study. He argues that, “one can employ a general phenomenological perspective to elucidate the importance of using methods that capture people’s experience of the world without conducting a phenomenological study that focuses on the essence of shared experience”.

ETHNOGRAPHY

In ethnography, the researcher studies the structure and function of a group of people. An example of a structure or configuration is the kinship, while the function refers to patterns of relationships affecting and regulating behaviour. 9 The aim of ethnographic studies is to give a holistic picture of the social group studied, attempting to describe aspects of the cultural and social system of that particular group. These aspects could be the group history, religion, economy, politics or environment.

Data collection methods vary in ethnographic studies with observation and interviews being the most popular methods. Although some authors expressed concern that anthropological methods may be misused or applied superficially by the medical profession, 19 others, however, expressed the need for acknowledging and incorporating ethnographic methods in health care research. 20 Savage 19 explains that today the term ethnography can be applied to any small-scale social research carried out in everyday settings and uses several methods evolving in design and focusing on an individual’s meanings and explanations. In health care, ethnography has been used in topics related to health beliefs and practices, allowing these issues to be viewed in the context in which they occur and therefore helping broaden the understanding of behaviours related to health and illness. 20

In addition, there has been an increase in the amount of cross-cultural research and a change in the form of this research. Recently, more short-term ethnographic and cross-cultural studies have been undertaken, for example, studies sponsored by international development agencies or student exchange projects. 12

QUALITATIVE RESEARCH INSTRUMENTS

Qualitative research instruments used for data collection include interviews, observations, and analysis of documents. Interviews are the most common techniques used to gather research information. There are three types of interviews: structured, semi-structured and unstructured, described in some books as structured, informed and guided, respectively. 13

The semi-structured interview is more commonly used in health care-related qualitative research. Such an interview is characteristically based on a flexible topic guide that provides a loose structure of open-ended questions to explore experiences and attitudes. It has the advantage of great flexibility, enabling the researcher to enter new areas and produce richer data. In addition, it helps the researcher to develop a rapport with the informants. Semi-structured interviews elicit people’s own views and descriptions and have the benefit of uncovering issues or concerns that have not been anticipated by the researcher. 6 They are commonly used when the aim is to gain information on the perspectives, understandings and meanings constructed by people regarding the events and experiences of their lives. However, this type of interviewing is claimed to reduce the researcher’s control over the interview situation and take a longer time to conduct and analyse, in addition to the difficulties of the analysis process. 21

In health care, interviews are the appropriate tool to be used if the research is concerned with interpersonal aspects of care or if the available evidence is limited. 6

Another qualitative research instrument that can be used in health care research is the focus group. Focus group interviews have the advantage of being more time efficient as more people can be interviewed for the same amount of time. They also provide a richer source of data. On the other hand, focus group interviews tend to document the ‘public’ rather than the ‘private’ views of the individuals. In addition some people do not interview well in-group situations. 13

THE USE OF THE INTERVIEW GUIDE

Some qualitative researchers are reluctant to plan a design of their study in advance of the data collection. They argue that the phenomenon studied must first be discovered and they describe their design as emergent. However, increasingly more qualitative researchers appear ready to define a research question and develop an interview guide prior to starting the data collection. 11 Patton defines an interview guide as a series of topics or broad interview questions which the researcher is free to explore and probe with the interviewee. 12 The advantage of an interview guide is that it helps the interviewer pursue the same basic lines of inquiry with each person interviewed and manage the interviews in a more systematic and comprehensive way. The findings of earlier work are increasingly being used as a facilitator for further research. However, concepts drawn from earlier work are supposed to be held lightly and to be subject to reformulation or rejection by the researcher especially as the study goes on and the research progresses. 11 The extent to which such a flexibility of design is important will vary depending on the topic and the aim of the study.

Sampling strategies in qualitative research are largely determined by the purpose of the study. Statistical representativeness is not considered as a prime requirement in qualitative research and is not normally sought. Furthermore, qualitative data collection is more time consuming and expensive, which makes the use of a probability sample impractical. 6 The aim of sampling in qualitative research is to identify specific groups of people who hold characteristics or live in circumstances relevant to the phenomena being studied. In this way, identified informants are expected to enable enriched exploration of attitudes and aspects of behaviour relevant to the research. 10 Two types of samples used in qualitative research, maximum variation and homogenous samples, are explained below.

According to Patton, 12 maximum variation sampling is where the researcher attempts to study a phenomenon by seeking out settings or persons that represent the greatest differences in that phenomenon. A maximum variation sample documents diverse variations and identifies important common patterns by representing diverse cases to develop fully multiple perspectives about the cases. 9 This means that the participants are sampled based on particular predetermined criteria in order to cover a range of constituencies, such as different age, cultural background or class. 6

Similarly, the researcher can select the setting of the data collection on the basis that it is sufficiently similar to other settings in which generalisation is sought. This way the researcher is demonstrating the possibility that the setting studied is representative of the population studied. 2

In homogeneous sampling, the researcher chooses a small homogenous sample with the purpose of describing some particular subgroups in depth. 12

The sample size in qualitative research is not determined by fixed rules, but by factors such as the depth and duration of the interview and what is feasible for a single interviewer. 22 Although it is theoretically possible to carry out qualitative research on large samples, qualitative researchers find themselves obliged by time and resource limits to trade breadth for depth. 11 The sample size for interview studies is usually much smaller than those of a quantitative research, usually not exceeding 50 participants, although this can vary with the research question asked. 6 Patton 12 states, “there are no rules for sample size in qualitative inquiry”. In other words, sample size depends on the aim of the study and what is possible, given the time and resources available.

ANALYSING QUALITATIVE RESEARCH

Although there are plenty of guidelines for analysing qualitative research, applying these guidelines requires judgment and creativity because each qualitative study is unique. 12 A researcher might also be confused by the different terms used by qualitative researchers when describing analysis. Analysis might be described as interpretation, making sense of data, or transforming data. Analysis is sometimes presented to indicate different procedures based on language, theory or what is described as interpretive/descriptive analysis. 11 However, overlap can take place between these different methods and a researcher might decide to use a method of analysis that is based on language, such as symbolic interactionist, while using grounded theory to develop a theory at the same time. Most of the analytical approaches to qualitative research in health care are ‘generic’ and are not labelled within one of the specific traditions of qualitative research. A common approach in most of these studies is general and inductive in nature, but does not comply with the very systematic and rigorous inductive approach of grounded theory. In addition, it has been described that many researchers use a simple two-level analysis scheme followed by a more specific level. This means that the researcher can initiate the analysis based on the conceptual framework used in order to produce more inductive data, and the coding moves from the descriptive to the more interpretative and inferential codes. 5

COMPUTER USE IN QUALITATIVE DATA ANALYSIS

Qualitative research studies typically produce very large amount of data that needs to be managed efficiently. Computer packages can improve the efficiency of data management. 11 Computer programs provide a way of storing and retrieving material. They are therefore useful in locating cases, statements, phrases or even words, thereby replacing the tedious and time-consuming process of “cutting and pasting” and “colour coding”. The use of computer packages, however, is claimed to distance the analyst from the data, 11 and may take the place of a close and careful analysis. Using a computer programme can lead to quantitative analysis instead of qualitative, for example, counting occurrences, giving more weight to more frequent events, and ignoring isolated incidences. 23 In addition, computer programmes are said to fix and label categories during the analysis process and the researcher may be reluctant to change these categories. 9 Furthermore, the researcher is required to learn the computer programme, which may add to the time and effort he or she will need to spend on the research project. The researcher also has to be aware of the limitations of computer programmes. While computer packages can help with the intensive process of analysis and the management of large data sets, they are not a substitute for “immersion” in the data, and thorough knowledge that can enable the researcher to make comparisons, identify patterns and develop interpretations. 6 There are different packages available: Ethnograph, Atlas and NUD.IST are the mostly used. QSR NVivo is a new product developed by the makers of NUD.IST and is user-friendlier, more suitable for individual research projects and more visually attractive than previous packages.

THE ROLE OF THE RESEARCHER IN QUALITATIVE RESEARCH

Patton 12 states that, “the human element in qualitative research is both its strength and weakness”. It is considered a point of strength because it allows human insight and experience to develop new understandings of the world, and a point of weakness because it depends heavily on the researcher’s skills, creativity, training and intellect. Qualitative methods depend on both critical and creative thinking and the balance between the two in conducting the study and interpreting its results. The role of the researcher is approached differently according to the type of research tradition used. A phenomenologist researcher is required to bracket his/her own assumptions when collecting data. On the other hand, in an ethnographic study, the effect of the researcher on the interview and the interaction is seen as inevitable and important in shaping the results of the study.

Although practising clinicians routinely interview patients during their clinical work, interviewing is a well-established technique in sociology and related disciplines. One of the differences between clinical and research-aimed interviews lies in their different purposes. The usual aim of the clinical interview is to fit the patient’s problem into the appropriate medical category for diagnosis and management. On the other hand, the aim of a qualitative research interview is to discover the interviewee’s own meaning and avoid prior assumptions and preset categories. 22 Having said that, there are general skills in clinical interviewing that can be useful, such as listening and observation. A good level of self-awareness is necessary in the researcher in order to reduce possible biases.

Researchers in qualitative research need to consider how they are perceived by interviewees and the effect of features related to the researcher, such as class, race, and sex on the interview. This question is more important if the interviewee knows that the interviewer is a doctor. It has been described that a patient, or someone who is likely to be become one, may give what he or she thinks is a desirable response, thinking that the doctor will be pleased.

RIGOUR IN QUALITATIVE RESEARCH

Health field research is generally quantitative and based on biomedical traditions and experimental methods. In this field, qualitative research is criticized for being subject to researcher bias and for lacking reproducibility and generalisability. 10 Researchers presenting their qualitative work in health-related research are partly responsible for this view. Many qualitative researchers neglect the importance of giving an adequate description of their theoretical concepts and methods used in their research. A systematic research method is also essential when conducting qualitative research. Rigour in qualitative research includes procedures taken at different stages of the research process including during data collection and analysis. Several procedures have been described to increase rigour in qualitative research. For example, triangulation is commonly used as a way of validating of data.

TRIANGULATION

In triangulation, the researcher uses multiple methods, sources, researchers or theories to provide evidence that strengthens his or her study. Triangulation provides different ways of looking at the same phenomenon and adds credibility and confidence in the conclusions drawn from the study. There are two main types of triangulation, triangulation of sources and analyst triangulation. Patton 12 defines triangulation of sources as “checking out the consistency of different data sources within the same method”. When using this type of triangulation, the researcher compares the perspectives of people from different points of view. For example, studies in programme evaluation might compare the views of staff, clients or funding bodies. 12 Studies in health care have used this method of verification to study the accounts of doctors, patients, and managers in order to identify similarities and differences in views. An example is the study of patients’ versus doctors’ agendas in general practice. 23 Both similarities and differences from different sources, when given reasonable explanation, could contribute significantly to the credibility of the findings. Triangulation with multiple analysts can also be used as a method of verification. It is defined as “having two or more persons independently analyse the same qualitative data and compare their findings”. 12

QUALITATIVE RESEARCH IN HEALTH CARE MANAGEMENT

Recently, there has been a greater acceptance of the qualitative approach, even as a stand-alone method, in health care research. Institutions that control funding for medical research have developed ethical guidelines for assessing qualitative studies which indicates formal acceptance of this form of research within an area previously dominated by quantitative methods. 13 More qualitative research articles are published in health-related journals, in addition to a new qualitative research journal (Qualitative Health Research).

Quality of health care is one of the areas where qualitative methods can be used. The concept of quality in health care is multidimensional and multifaceted and some of the questions asked related to the quality of care or services may not be acquiescent to quantitative methods. 6 Qualitative research offers a variety of methods to be used for identifying what is really important to both patients and carers. It can also be used to identify and detect obstacles to change and the reasons why improvement does not occur. 6 It is therefore an essential component of health services research because it enables us to reach areas not amenable to quantitative research, for example, lay and professional health beliefs. In addition, qualitative description can be a prerequisite of quantitative research, particularly in areas that have received little previous investigation.

Qualitative research is widely used to study issues related to doctor-patient interaction especially in general practice. Studies concerning patients’ versus doctors’ agendas in general practice and general practitioners perceptions of effective health care are examples. 23 , 24 Recently there have been more studies concentrating on patients’ own perceptions and views regarding their health and health care services, for example a study on women’s views on the impact of operative delivery in the second stage of labour. 25 Another example is the study on middle-aged person’s experience of living with severe heart failure. 26

Another area where qualitative research is being used in health care is to identify obstacles and barriers to practice change by exploring the reasons behind certain behaviours. A good example of this is the study of patients’ decisions about whether or not to take anti-hypertensive drugs. 27 There are similar studies on issues such as the use of antibiotics in general practice and patient compliance.

In addition to issues related to the patients’ perception, some qualitative studies concentrated on factors fostering the doctor’s motivation and the effect of doctors’ social life and culture, in addition to issues related to the doctor’s own health. Examples are the study by Dumelow et al. 28 on the relation between a career and family life for English hospital consultants. Another example is a study aimed at exploring general practitioners’ perceptions of the effects of their profession and training on their attitudes to illness in themselves and colleagues. 29

Qualitative work can help in identifying cultural and social factors that affect health care positively or negatively. Such information can be helpful in improving service delivery. 6 Studies on patients from ethnic minorities have identified administrative and language barriers that affected health care and shed light on some of the beliefs and behaviours of these patients that might have affected help seeking and compliance. Good examples are the studies by Bush et al. 30 exploring the influences on smoking in Bangladeshi and Pakistani adults in the UK, and the multi-centre cross-cultural postnatal depression study. 31

There has been an increasing interest and use of qualitative research methods in primary health care and general practice articles. Britten 32 states that “the nature of general practice is such that a variety of research methods are needed to explore all its intricacies” He adds that qualitative methods can enrich research in general practice by opening up areas not amenable to quantitative methods, topics such as patient satisfaction, doctor-patient interaction, in addition to identifying and explaining attitudes, beliefs and behaviour. In addition, qualitative research has been used in the assessment of new technology methods used in health care. For example, the studies on the implementation of the National Health System information technology programme in the UK. 11 , 33

Qualitative research methods are receiving an increasing recognition in health care related research. The use of qualitative research in health care enables researchers to answer questions that may not be easily answered by quantitative methods. Moreover, it seeks to understand the phenomenon under study in the context of the culture or the setting in which it has been studied, therefore, aiding in the development of new research instruments, such as questionnaires that are more culturally acceptable. However, because health care related research has, for decades, been based on quantitative methods, the introduction of a new method requires researchers in health care who attempt to use it, to have a thorough understanding of its theoretical basis, methodology and evaluation techniques.

Acknowledgments

I would like to thank Sultan Qaboos University, Oman, for granting me a scholarship to do my PhD at the University of Nottingham, UK. I am also grateful to my PhD supervisor, Dr Margaret Oates, for her guidance and support.

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Progress in remote sensing and gis-based fdi research based on quantitative and qualitative analysis.

1. Introduction

2. research methods and data, 2.1. research methods, 2.2. data sources and screening, 2.3. data processing, 3. subject categories and publication trends, 3.1. subject evolution, 3.2. trends in the number and cited times of published papers, 4. the intellectual structure, 4.1. quantitative analysis, 4.2. qualitative analysis, 4.2.1. macro-environmental research at national, regional, and city scales, 4.2.2. global industrial development and layout, 4.2.3. research on global value chains, 4.2.4. micro-information geography of tncs, 4.2.5. internationalization and commercialization of geo-information industry, 4.2.6. multiple data and interdisciplinary approaches, 5. discussions and conclusions, data availability statement, acknowledgments, conflicts of interest.

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Li, Z. Progress in Remote Sensing and GIS-Based FDI Research Based on Quantitative and Qualitative Analysis. Land 2024 , 13 , 1313. https://doi.org/10.3390/land13081313

Li Z. Progress in Remote Sensing and GIS-Based FDI Research Based on Quantitative and Qualitative Analysis. Land . 2024; 13(8):1313. https://doi.org/10.3390/land13081313

Li, Zifeng. 2024. "Progress in Remote Sensing and GIS-Based FDI Research Based on Quantitative and Qualitative Analysis" Land 13, no. 8: 1313. https://doi.org/10.3390/land13081313

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