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How to Write the Dissertation Findings or Results – Steps & Tips

Published by Grace Graffin at August 11th, 2021 , Revised On October 9, 2023

Each  part of the dissertation is unique, and some general and specific rules must be followed. The dissertation’s findings section presents the key results of your research without interpreting their meaning .

Theoretically, this is an exciting section of a dissertation because it involves writing what you have observed and found. However, it can be a little tricky if there is too much information to confuse the readers.

The goal is to include only the essential and relevant findings in this section. The results must be presented in an orderly sequence to provide clarity to the readers.

This section of the dissertation should be easy for the readers to follow, so you should avoid going into a lengthy debate over the interpretation of the results.

It is vitally important to focus only on clear and precise observations. The findings chapter of the  dissertation  is theoretically the easiest to write.

It includes  statistical analysis and a brief write-up about whether or not the results emerging from the analysis are significant. This segment should be written in the past sentence as you describe what you have done in the past.

This article will provide detailed information about  how to   write the findings of a dissertation .

When to Write Dissertation Findings Chapter

As soon as you have gathered and analysed your data, you can start to write up the findings chapter of your dissertation paper. Remember that it is your chance to report the most notable findings of your research work and relate them to the research hypothesis  or  research questions set out in  the introduction chapter of the dissertation .

You will be required to separately report your study’s findings before moving on to the discussion chapter  if your dissertation is based on the  collection of primary data  or experimental work.

However, you may not be required to have an independent findings chapter if your dissertation is purely descriptive and focuses on the analysis of case studies or interpretation of texts.

• Always report the findings of your research in the past tense.
• The dissertation findings chapter varies from one project to another, depending on the data collected and analyzed.
• Avoid reporting results that are not relevant to your research questions or research hypothesis.

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1. Reporting Quantitative Findings

The best way to present your quantitative findings is to structure them around the research  hypothesis or  questions you intend to address as part of your dissertation project.

Report the relevant findings for each research question or hypothesis, focusing on how you analyzed them.

Analysis of your findings will help you determine how they relate to the different research questions and whether they support the hypothesis you formulated.

While you must highlight meaningful relationships, variances, and tendencies, it is important not to guess their interpretations and implications because this is something to save for the discussion  and  conclusion  chapters.

Any findings not directly relevant to your research questions or explanations concerning the data collection process  should be added to the dissertation paper’s appendix section.

Use of Figures and Tables in Dissertation Findings

Suppose your dissertation is based on quantitative research. In that case, it is important to include charts, graphs, tables, and other visual elements to help your readers understand the emerging trends and relationships in your findings.

Repeating information will give the impression that you are short on ideas. Refer to all charts, illustrations, and tables in your writing but avoid recurrence.

The text should be used only to elaborate and summarize certain parts of your results. On the other hand, illustrations and tables are used to present multifaceted data.

It is recommended to give descriptive labels and captions to all illustrations used so the readers can figure out what each refers to.

How to Report Quantitative Findings

Here is an example of how to report quantitative results in your dissertation findings chapter;

Two hundred seventeen participants completed both the pretest and post-test and a Pairwise T-test was used for the analysis. The quantitative data analysis reveals a statistically significant difference between the mean scores of the pretest and posttest scales from the Teachers Discovering Computers course. The pretest mean was 29.00 with a standard deviation of 7.65, while the posttest mean was 26.50 with a standard deviation of 9.74 (Table 1). These results yield a significance level of .000, indicating a strong treatment effect (see Table 3). With the correlation between the scores being .448, the little relationship is seen between the pretest and posttest scores (Table 2). This leads the researcher to conclude that the impact of the course on the educators’ perception and integration of technology into the curriculum is dramatic.

Paired Samples

Paired Samples Correlation

Paired Samples Test

Also Read: How to Write the Abstract for the Dissertation.

2. Reporting Qualitative Findings

A notable issue with reporting qualitative findings is that not all results directly relate to your research questions or hypothesis.

The best way to present the results of qualitative research is to frame your findings around the most critical areas or themes you obtained after you examined the data.

In-depth data analysis will help you observe what the data shows for each theme. Any developments, relationships, patterns, and independent responses directly relevant to your research question or hypothesis should be mentioned to the readers.

Additional information not directly relevant to your research can be included in the appendix .

How to Report Qualitative Findings

Here is an example of how to report qualitative results in your dissertation findings chapter;

How do I report quantitative findings?

The best way to present your quantitative findings is to structure them around the  research hypothesis  or  research questions  you intended to address as part of your dissertation project. Report the relevant findings for each of the research questions or hypotheses, focusing on how you analyzed them.

How do I report qualitative findings?

The best way to present the  qualitative research  results is to frame your findings around the most important areas or themes that you obtained after examining the data.

An in-depth analysis of the data will help you observe what the data is showing for each theme. Any developments, relationships, patterns, and independent responses that are directly relevant to your  research question  or  hypothesis  should be clearly mentioned for the readers.

Can I use interpretive phrases like ‘it confirms’ in the finding chapter?

No, It is highly advisable to avoid using interpretive and subjective phrases in the finding chapter. These terms are more suitable for the  discussion chapter , where you will be expected to provide your interpretation of the results in detail.

Can I report the results from other research papers in my findings chapter?

NO, you must not be presenting results from other research studies in your findings.

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How to Write an Impressive Thesis Results Section

After collecting and analyzing your research data, it’s time to write the results section. This article explains how to write and organize the thesis results section, the differences in reporting qualitative and quantitative data, the differences in the thesis results section across different fields, and the best practices for tables and figures.

What is the thesis results section?

The thesis results section factually and concisely describes what was observed and measured during the study but does not interpret the findings. It presents the findings in a logical order.

What should the thesis results section include?

• Include all relevant results as text, tables, or figures
• Report the results of subject recruitment and data collection
• For qualitative research, present the data from all statistical analyses, whether or not the results are significant
• For quantitative research, present the data by coding or categorizing themes and topics
• Present all secondary findings (e.g., subgroup analyses)
• Include all results, even if they do not fit in with your assumptions or support your hypothesis

What should the thesis results section not include?

• If the study involves the thematic analysis of an interview, don’t include complete transcripts of all interviews. Instead, add these as appendices
• Don’t present raw data. These may be included in appendices
• Don’t include background information (this should be in the introduction section )
• Don’t speculate on the meaning of results that do not support your hypothesis. This will be addressed later in the discussion and conclusion sections.
• Don’t repeat results that have been presented in tables and figures. Only highlight the pertinent points or elaborate on specific aspects

How should the thesis results section be organized?

The opening paragraph of the thesis results section should briefly restate the thesis question. Then, present the results objectively as text, figures, or tables.

Quantitative research presents the results from experiments and  statistical tests , usually in the form of tables and figures (graphs, diagrams, and images), with any pertinent findings emphasized in the text. The results are structured around the thesis question. Demographic data are usually presented first in this section.

For each statistical test used, the following information must be mentioned:

• The type of analysis used (e.g., Mann–Whitney U test or multiple regression analysis)
• A concise summary of each result, including  descriptive statistics   (e.g., means, medians, and modes) and  inferential statistics   (e.g., correlation, regression, and  p  values) and whether the results are significant
• Any trends or differences identified through comparisons
• How the findings relate to your research and if they support or contradict your hypothesis

Qualitative research   presents results around key themes or topics identified from your data analysis and explains how these themes evolved. The data are usually presented as text because it is hard to present the findings as figures.

For each theme presented, describe:

• General trends or patterns observed
• Significant or representative responses
• Relevant quotations from your study subjects

Relevant characteristics about your study subjects

Differences among the results section in different fields of research

Nevertheless, results should be presented logically across all disciplines and reflect the thesis question and any hypotheses that were tested.

The presentation of results varies considerably across disciplines. For example, a thesis documenting how a particular population interprets a specific event and a thesis investigating customer service may both have collected data using interviews and analyzed it using similar methods. Still, the presentation of the results will vastly differ because they are answering different thesis questions. A science thesis may have used experiments to generate data, and these would be presented differently again, probably involving statistics. Nevertheless, results should be presented logically across all disciplines and reflect the thesis question and any  hypotheses that were tested.

Differences between reporting thesis results in the Sciences and the Humanities and Social Sciences (HSS) domains

In the Sciences domain (qualitative and experimental research), the results and discussion sections are considered separate entities, and the results from experiments and statistical tests are presented. In the HSS domain (qualitative research), the results and discussion sections may be combined.

There are two approaches to presenting results in the HSS field:

• If you want to highlight important findings, first present a synopsis of the results and then explain the key findings.
• If you have multiple results of equal significance, present one result and explain it. Then present another result and explain that, and so on. Conclude with an overall synopsis.

Best practices for using tables and figures

The use of figures and tables is highly encouraged because they provide a standalone overview of the research findings that are much easier to understand than wading through dry text mentioning one result after another. The text in the results section should not repeat the information presented in figures and tables. Instead, it should focus on the pertinent findings or elaborate on specific points.

Some popular software programs that can be used for the analysis and presentation of statistical data include  Statistical Package for the Social Sciences (SPSS ) ,  R software ,  MATLAB , Microsoft Excel,  Statistical Analysis Software (SAS) ,  GraphPad Prism , and  Minitab .

The easiest way to construct tables is to use the  Table function in Microsoft Word . Microsoft Excel can also be used; however, Word is the easier option.

General guidelines for figures and tables

• Figures and tables must be interpretable independent from the text
• Number tables and figures consecutively (in separate lists) in the order in which they are mentioned in the text
• All tables and figures must be cited in the text
• Provide clear, descriptive titles for all figures and tables
• Include a legend to concisely describe what is presented in the figure or table

Figure guidelines

• Label figures so that the reader can easily understand what is being shown
• Use a consistent font type and font size for all labels in figure panels
• All abbreviations used in the figure artwork should be defined in the figure legend

Table guidelines

• All table columns should have a heading abbreviation used in tables should be defined in the table footnotes
• All numbers and text presented in tables must correlate with the data presented in the manuscript body

Quantitative results example : Figure 3 presents the characteristics of unemployed subjects and their rate of criminal convictions. A statistically significant association was observed between unemployed people <20 years old, the male sex, and no household income.

Qualitative results example: Table 5 shows the themes identified during the face-to-face interviews about the application that we developed to anonymously report corruption in the workplace. There was positive feedback on the app layout and ease of use. Concerns that emerged from the interviews included breaches of confidentiality and the inability to report incidents because of unstable cellphone network coverage.

Table 5. Themes and selected quotes from the evaluation of our app designed to anonymously report workplace corruption.

Tips for writing the thesis results section

• Do not state that a difference was present between the two groups unless this can be supported by a significant  p-value .
• Present the findings only . Do not comment or speculate on their interpretation.
• Every result included  must have a corresponding method in the methods section. Conversely, all methods  must have associated results presented in the results section.
• Do not explain commonly used methods. Instead, cite a reference.
• Be consistent with the units of measurement used in your thesis study. If you start with kg, then use the same unit all throughout your thesis. Also, be consistent with the capitalization of units of measurement. For example, use either “ml” or “mL” for milliliters, but not both.
• Never manipulate measurement outcomes, even if the result is unexpected. Remain objective.

Results vs. discussion vs. conclusion

Results are presented in three sections of your thesis: the results, discussion, and conclusion.

• In the results section, the data are presented simply and objectively. No speculation or interpretation is given.
• In the discussion section, the meaning of the results is interpreted and put into context (e.g., compared with other findings in the literature ), and its importance is assigned.
• In the conclusion section, the results and the main conclusions are summarized.

A thesis is the most crucial document that you will write during your academic studies. For professional thesis editing and thesis proofreading services , visit Enago Thesis Editing for more information.

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Have you  completed all data collection procedures and analyzed all results ?

Have you  included all results relevant to your thesis question, even if they do not support your hypothesis?

Have you reported the results  objectively , with no interpretation or speculation?

For quantitative research, have you included both  descriptive and  inferential statistical results and stated whether they support or contradict your hypothesis?

Have you used  tables and figures to present all results?

In your thesis body, have you presented only the pertinent results and elaborated on specific aspects that were presented in the tables and figures?

Are all tables and figures  correctly labeled and cited in numerical order in the text?

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Writing your Dissertation:  Results and Discussion

When writing a dissertation or thesis, the results and discussion sections can be both the most interesting as well as the most challenging sections to write.

You may choose to write these sections separately, or combine them into a single chapter, depending on your university’s guidelines and your own preferences.

There are advantages to both approaches.

Writing the results and discussion as separate sections allows you to focus first on what results you obtained and set out clearly what happened in your experiments and/or investigations without worrying about their implications.This can focus your mind on what the results actually show and help you to sort them in your head.

However, many people find it easier to combine the results with their implications as the two are closely connected.

Check your university’s requirements carefully before combining the results and discussions sections as some specify that they must be kept separate.

Results Section

The Results section should set out your key experimental results, including any statistical analysis and whether or not the results of these are significant.

You should cover any literature supporting your interpretation of significance. It does not have to include everything you did, particularly for a doctorate dissertation. However, for an undergraduate or master's thesis, you will probably find that you need to include most of your work.

You should write your results section in the past tense: you are describing what you have done in the past.

Every result included MUST have a method set out in the methods section. Check back to make sure that you have included all the relevant methods.

Conversely, every method should also have some results given so, if you choose to exclude certain experiments from the results, make sure that you remove mention of the method as well.

If you are unsure whether to include certain results, go back to your research questions and decide whether the results are relevant to them. It doesn’t matter whether they are supportive or not, it’s about relevance. If they are relevant, you should include them.

Having decided what to include, next decide what order to use. You could choose chronological, which should follow the methods, or in order from most to least important in the answering of your research questions, or by research question and/or hypothesis.

You also need to consider how best to present your results: tables, figures, graphs, or text. Try to use a variety of different methods of presentation, and consider your reader: 20 pages of dense tables are hard to understand, as are five pages of graphs, but a single table and well-chosen graph that illustrate your overall findings will make things much clearer.

Make sure that each table and figure has a number and a title. Number tables and figures in separate lists, but consecutively by the order in which you mention them in the text. If you have more than about two or three, it’s often helpful to provide lists of tables and figures alongside the table of contents at the start of your dissertation.

Summarise your results in the text, drawing on the figures and tables to illustrate your points.

The text and figures should be complementary, not repeat the same information. You should refer to every table or figure in the text. Any that you don’t feel the need to refer to can safely be moved to an appendix, or even removed.

Make sure that you including information about the size and direction of any changes, including percentage change if appropriate. Statistical tests should include details of p values or confidence intervals and limits.

While you don’t need to include all your primary evidence in this section, you should as a matter of good practice make it available in an appendix, to which you should refer at the relevant point.

For example:

Details of all the interview participants can be found in Appendix A, with transcripts of each interview in Appendix B.

You will, almost inevitably, find that you need to include some slight discussion of your results during this section. This discussion should evaluate the quality of the results and their reliability, but not stray too far into discussion of how far your results support your hypothesis and/or answer your research questions, as that is for the discussion section.

See our pages: Analysing Qualitative Data and Simple Statistical Analysis for more information on analysing your results.

Discussion Section

This section has four purposes, it should:

• Interpret and explain your results
• Answer your research question
• Justify your approach
• Critically evaluate your study

The discussion section therefore needs to review your findings in the context of the literature and the existing knowledge about the subject.

You also need to demonstrate that you understand the limitations of your research and the implications of your findings for policy and practice. This section should be written in the present tense.

The Discussion section needs to follow from your results and relate back to your literature review . Make sure that everything you discuss is covered in the results section.

Some universities require a separate section on recommendations for policy and practice and/or for future research, while others allow you to include this in your discussion, so check the guidelines carefully.

Starting the Task

Most people are likely to write this section best by preparing an outline, setting out the broad thrust of the argument, and how your results support it.

You may find techniques like mind mapping are helpful in making a first outline; check out our page: Creative Thinking for some ideas about how to think through your ideas. You should start by referring back to your research questions, discuss your results, then set them into the context of the literature, and then into broader theory.

This is likely to be one of the longest sections of your dissertation, and it’s a good idea to break it down into chunks with sub-headings to help your reader to navigate through the detail.

Fleshing Out the Detail

Once you have your outline in front of you, you can start to map out how your results fit into the outline.

This will help you to see whether your results are over-focused in one area, which is why writing up your research as you go along can be a helpful process. For each theme or area, you should discuss how the results help to answer your research question, and whether the results are consistent with your expectations and the literature.

The Importance of Understanding Differences

If your results are controversial and/or unexpected, you should set them fully in context and explain why you think that you obtained them.

Your explanations may include issues such as a non-representative sample for convenience purposes, a response rate skewed towards those with a particular experience, or your own involvement as a participant for sociological research.

You do not need to be apologetic about these, because you made a choice about them, which you should have justified in the methodology section. However, you do need to evaluate your own results against others’ findings, especially if they are different. A full understanding of the limitations of your research is part of a good discussion section.

At this stage, you may want to revisit your literature review, unless you submitted it as a separate submission earlier, and revise it to draw out those studies which have proven more relevant.

Conclude by summarising the implications of your findings in brief, and explain why they are important for researchers and in practice, and provide some suggestions for further work.

You may also wish to make some recommendations for practice. As before, this may be a separate section, or included in your discussion.

The results and discussion, including conclusion and recommendations, are probably the most substantial sections of your dissertation. Once completed, you can begin to relax slightly: you are on to the last stages of writing!

Continue to: Dissertation: Conclusion and Extras Writing your Methodology

See also: Writing a Literature Review Writing a Research Proposal Academic Referencing What Is the Importance of Using a Plagiarism Checker to Check Your Thesis?

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The main purpose of a dissertation is to contribute knowledge to your field of study. So it goes without saying that a dissertation is rather pointless if you don’t document the results of your research clearly! This is where you document the findings of your research, where you make sense of what you have discovered throughout the research process and explain its relevance to the research question or problem. Let’s explore how to write the results section of your dissertation.

What goes in the results section

Conventionally, the results section is the fourth chapter of your dissertation, written after you present your method of study . How exactly you present your findings differs from study to study, depending on the topic and discipline your research is situated in, the methods you used, and what kind of data you are presenting. 

Here’s what you’ll cover in the results chapter: 

• A brief reminder of the research question and the purpose of your research  
• The results of your experiment or study and what they mean 
• The data that you’ve collected in sentence form, accompanied by visual elements such as tables, graphs, charts, etc. 
• A critical analysis of how they relate to your research question 

Pro-tip: Always check your university’s guidelines for specific details on what you are required to write about in this section.

Results vs discussion

It’s important to note that the results chapter is usually not the same as the discussion . The purpose of the results section is to present findings in a logical, objective, and impartial manner. At this stage, you do not include your interpretation as a researcher or discuss the implications of the research. Observations that you make, as a researcher, are better suited for the next few chapters. In other words, you simply present the data in the results chapter, and you interpret it in the discussion chapter. 

Although, in some cases (for instance, if your university tells you to), you may be asked to combine the two sections. In this case, you’ll have to weave your interpretation and analysis into the segments where you’re presenting data. 

How to write and structure the results section

Regardless of whether your dissertation is qualitative or quantitative in nature, there are certain aspects common to this chapter. It has an introduction that reiterates the aims and purpose of the research, a body that deconstructs the results obtained during the research process, and a conclusion that summarizes the study’s findings and sets the stage for a discussion about its implications for your research area. 

This chapter is written in the simple past tense, as you are reporting a study that has been conducted in the past. 

Reporting qualitative research 

The purpose of qualitative research is to explore the depth and nuances of a particular topic. So you’ll be engaged with uncovering it through words and detailed descriptions, rather than hard numbers. A qualitative study sees data being presented primarily in the form of words , often supplemented with quantitative data that supports relevant claims. You’re likely to resort to this kind of analysis if you’re working in humanities and social sciences. 

The first decision you’ll need to make at this moment is whether you’ll be structuring your data chronologically (in order of how you conducted the research) or thematically (in terms of patterns and trends that you see in your data). 

Ensure that each finding you highlight is directly relevant to your research question. You may have made many discoveries over the course of your research, but your chapter has to be concise and report findings that either support or contradict your hypothesis. There is a lot of raw data that you will need to sift through to decide what’s important. 

Include excerpts and quotations from appropriate sources such as interviews, discussion transcripts, supporting literature, and so on, to back each of your findings. 

Although your chapter is mostly just a barrage of words, it’s useful to have graphs, tables, charts, and other visual elements that illustrate what you’re saying in text. Having such quantitative parameters within the chapter is not mandatory (and may not even apply to certain types of research, like a literary analysis), but is often helpful with establishing a story for your research. 

Commonly used qualitative research methods: in-depth interviews, case studies, focus group discussions, theoretical research , literary analysis, and so forth. 

Reporting quantitative research

Quantitative research, as the name suggests, focuses on studying data through statistical and mathematical techniques. If you’re doing this type of research for your dissertation, your results chapter will be dominated by statistics and numbers (represented through graphs, tables, charts, etc.), explained succinctly through text. 

Here’s what you have to include in the chapter: 

• Statistical analysis, their relevance and relationship with the research question 
• Observations about whether data supports or rejects the hypothesis 
• Trends, patterns, and relationships that can be understood from the data 

Since numerical data can be dense and difficult to understand at the first glance, it’s always advised that you articulate them visually, through graphs, tables, charts, and perhaps even relevant figures. Not only does this allow you to deconstruct data in a more appealing way, but it also allows you to spell out a narrative for your data, which you will support with text that explains your findings. 

Commonly used quantitative research methods: Surveys, polls, simulations and modeling of data 

Tips to write a good results section

• Include tables, figures, and other visual elements to present complex data in a more accessible way. These elements should supplement the words rather than be repetitive. 
• Use a variety of visual elements to illustrate data that might be difficult to interpret solely with words. 
• Be honest in your reporting. This may seem obvious, but it’s easy to forget that results always don’t need to corroborate your hypothesis. In fact, it’s perfectly acceptable for the opposite to happen; this is useful in telling the research community that something doesn’t work! What matters in this section is relevance.
• Be concise and precise in your reporting. You don’t need to delve into every little detail about your data. Simply present data and information that is relevant to your research question. 

Frequently Asked Questions

Are the results and discussion sections the same, do i have to combine the results and discussions sections, where can i document raw data i haven’t been able to include in the chapter, how long should the results section of a dissertation be, what can i include in an appendix.

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How to Write the Results Section of your Dissertation or Thesis?

Introduction

Organizing your results, providing context, presenting the data in results section, describing statistical analysis, reporting the findings in results section, supporting the findings, visual representation in results section.

As you progress on your journey towards completing your PhD or Post Graduate dissertation, one of the most critical sections that holds immense significance is the results section.

Results section serves as the pinnacle of your research, where you unveil the outcomes of your exhaustive efforts and shed light on the answers to your research questions. In this blog post, we will delve into the intricacies of the results section and explore how to effectively present and interpret your findings to leave a lasting impact.

Whether you’re conducting research in the field of biology, psychology, computer science, or any other discipline, the results section is where your data takes center stage. It is a space where you showcase your meticulous analysis, statistical methods, and the discoveries you’ve made along the way. By understanding the key components and best practices for constructing a compelling results section, you can present your findings in a manner that resonates with both your academic peers and the wider research community.

In this comprehensive guide, we will walk you through the fundamental elements of the results section, from organizing your data to choosing the appropriate visual representations. We will explore the importance of clear and concise reporting, emphasizing the significance of providing contextual information and highlighting any unexpected or groundbreaking discoveries.

Furthermore, we will discuss strategies for effectively interpreting your results, discussing their implications, and connecting them back to your research objectives. By mastering these skills, you will be able to demonstrate the significance of your work, contribute to the existing body of knowledge, and potentially pave the way for further research in your field.

Throughout the blog post, I will provide concrete examples from various disciplines to illustrate the implementation of these techniques. Additionally, I will offer valuable tips on avoiding common pitfalls, ensuring the accuracy and reliability of your results, and seeking feedback from your advisors or peers to enhance the quality of your analysis.

If you are in paucity of time, not confident of your writing skills and in a hurry to complete the writing task then you can think of hiring a research consultant that solves all your problems. Please visit my article on Hiring a Research consultant for your PhD tasks for further details.

Organizing the results of your study in a logical and coherent manner is crucial for effectively communicating your findings. By presenting your results in an organized structure, you enhance the clarity and readability of your dissertation. Here are some key considerations for organizing your results:

• Research studies often involve complex algorithms, software implementations, experimental data, and performance metrics. It is essential to organize these diverse elements in a cohesive manner to make it easier for readers to follow your research. A well-structured results section enables readers to understand the progression of your experiments and the relationship between different findings.
• Begin by reminding readers of the research questions or hypotheses that guided your study. This alignment helps establish a clear connection between the objectives of your research and the subsequent presentation of results. For example, if your research question focuses on evaluating the efficiency of a new sorting algorithm, you would present the experimental data, performance metrics, and comparative analyses specific to that algorithm in relation to the research question.
• Subsubsection 1.1: Experimental Setup
• Subsubsection 1.2: Experimental Results and Analysis
• Subsubsection 2.1: Performance Metrics
• Subsubsection 2.2: Comparative Results and Discussion

Remember to tailor the organization of your results section to the specific requirements of your research. The key is to provide a logical flow and structure that enables readers to easily comprehend and interpret your findings.

Providing context for the results of your study is essential to help readers understand the significance and implications of your findings. By offering background information and study design details, you establish a foundation upon which the results can be properly interpreted. Here are some key considerations for providing context:

• Before delving into the results, it is important to provide readers with relevant background information about the topic or problem being addressed. This may include a literature review of existing research, theories, or methodologies in the field. By doing so, you situate your work within the broader landscape of and demonstrate its relevance. Additionally, explain the design of your study, such as the specific algorithms, software frameworks, datasets, or hardware setups used. This ensures that readers understand the context in which your results were obtained.
• Provide a brief overview of the current state-of-the-art in image recognition algorithms and their limitations.
• Explain the specific challenges or gaps in the existing methods that motivated your research.
• Describe the design of your study, including the choice of machine learning techniques, datasets used for training and evaluation, preprocessing steps, and any hardware or software configurations.

By providing context, you allow readers to understand the background, motivation, and methodology behind your research. This sets the stage for better comprehension and interpretation of your results. Contextualizing your findings, as it helps establish the relevance, novelty, and potential impact of your research within the larger field.

Presenting data in a clear and organized manner is crucial for effectively communicating your results. The way you present your data can greatly impact the reader’s understanding and interpretation of your findings. Here are some key considerations for presenting data:

• Presenting performance metrics of different algorithms using a table to allow for easy comparison.
• Using a line graph to depict the improvement in accuracy over training iterations in a machine learning model.
• Employing a bar chart to compare the execution times of different algorithms on a specific dataset.
• Clear labelling and formatting of your data ensure that readers can easily understand and interpret the information presented. Label each table, figure, chart, or graph with a concise and descriptive title. Ensure that axes, legends, and labels are clearly labelled and units of measurement are specified. Use appropriate fonts, colours, and styles to enhance readability. Consider providing captions or footnotes to provide additional context or explanations where necessary.
• In the text, refer to a specific table presenting the accuracy results of different algorithms and explain how these results support your research hypothesis or contribute to the field.
• Discuss a figure showing the relationship between the number of training examples and the performance of a machine learning model, emphasizing its implications for scalability and generalization.

By presenting data in a visually appealing and well-organized manner, you enhance the clarity and accessibility of your results. Proper labelling, formatting, and referring to each table or figure in the text help readers navigate the information and grasp its significance. Remember to choose the most appropriate format for your data and use visuals to support and reinforce your findings.

The inclusion of statistical analyses in the results section is crucial for providing objective and quantitative evidence to support your findings. Statistical analyses help you draw meaningful conclusions from your data and determine the significance of observed results. Here are some key considerations for describing statistical analyses:

• Statistical analyses play a vital role in determining the reliability and significance of your findings. They provide a systematic and objective framework for interpreting the data and testing hypotheses. Discuss the importance of including statistical analyses in the results section to demonstrate the rigour and validity of your research.
• Describe using a t-test to compare the means of two groups in a user study, as it is appropriate for assessing the statistical significance of differences.
• Explain employing logistic regression to model the relationship between independent variables and a binary outcome in a predictive analytics study.
• Report the p-value as 0.032, indicating a statistically significant difference between the two groups at the 0.05 significance level.
• Interpret an effect size of 0.40 as a medium-sized effect, highlighting its practical importance in the context of the research.

By describing the statistical analyses conducted, explaining the rationale behind the chosen tests, and accurately presenting the statistical values and interpretations, you strengthen the validity and reliability of your findings. Statistical analyses provide an objective framework for drawing conclusions from your data and lend credibility to your research in the computer science domain.

Reporting the findings of your research in an objective, concise, and clear manner is essential for effectively communicating your results. Here are some key considerations for reporting the findings:

• Summarize the key findings of a machine learning study by stating that “the proposed algorithm achieved an average accuracy of 85% on the test dataset, outperforming existing state-of-the-art methods by 10%.”
• For a research question about the impact of different programming languages on software performance, present specific metrics such as execution time or memory usage for each language, along with a comparison and interpretation of the results.
• Instead of using overly technical language, communicate the results in a more accessible way: “The experimental results showed a significant correlation between the number of training samples and the accuracy of the model, indicating that a larger training dataset leads to improved prediction performance.”

By guiding readers on summarizing the results objectively and concisely, addressing each research question or hypothesis, and using clear and concise language, you ensure that your findings are communicated effectively. This approach allows readers to understand the core contributions of your research and how they align with the research questions or hypotheses you set out to investigate.

Providing strong evidence from the data to support your findings, addressing unexpected or contradictory results, and discussing limitations and potential explanations are essential components of reporting research findings. Here are some key considerations for supporting the findings:

• Present empirical evidence from a user study, such as participant feedback or performance metrics, to support the usability and effectiveness of a proposed user interface design.
• If a software system performed unexpectedly poorly in certain scenarios, discuss potential factors such as data bias, implementation issues, or limitations of the evaluation methodology that could have influenced the results.
• Acknowledge limitations such as a small sample size, limited dataset availability, or computational constraints that might affect the generalizability or robustness of the results.
• Discuss potential explanations for unexpected results, such as issues with data quality, algorithmic complexity, or model assumptions.

By providing evidence from the data to support the findings, addressing unexpected or contradictory results, and discussing limitations and potential explanations, you demonstrate a rigorous and reflective approach to your research in the computer science domain. This allows readers to assess the strength and reliability of your findings and gain a deeper understanding of the nuances and implications of your work.

Using visual representations, such as tables, graphs, and figures, alongside the text can greatly enhance the understanding and impact of your findings. Here are some key considerations for visual representation:

Visual representations offer several benefits in presenting research findings. They provide a concise and intuitive way to convey complex information, trends, and patterns. Visuals can help readers grasp key insights at a glance, enhance the overall readability of the document, and make the findings more memorable. Visual representations also facilitate effective comparisons, highlight important relationships, and aid in storytelling. Example:

When creating visual representations, consider the following tips to ensure clarity and effectiveness: a. Choose the appropriate visual format: Select the most suitable format, such as tables, line graphs, scatter plots, or heatmaps, based on the nature of the data and the message you want to convey.

b. Simplify and declutter: Avoid overwhelming the visuals with excessive data points, labels, or unnecessary decorations. Keep the design clean and focused on conveying the essential information.

c. Label and title clearly: Provide descriptive and informative titles for tables, graphs, and figures. Label the axes, data points, or components clearly to facilitate understanding.

d. Use colors and visual cues purposefully: Utilize colors and visual cues to highlight important information or differentiate between categories. Ensure that the chosen colors are distinguishable and accessible. e. Provide legends and captions: Include legends to explain symbols, colors, or abbreviations used in the visuals. Provide informative captions or annotations to guide readers in interpreting the visuals accurately. Example:

By incorporating clear and effective visual representations alongside the text, you enhance the presentation and understanding of your research findings in the computer science domain. Well-designed tables, graphs, and figures can simplify complex information, facilitate comparisons, and enhance the visual appeal of your dissertation. Remember to choose appropriate formats, keep the visuals uncluttered, label clearly, and use colors and visual cues purposefully to maximize their impact.

Writing the results section of a dissertation or thesis is a critical task that requires careful attention to detail, organization, and effective communication. Throughout this blog post, we have explored key elements to consider when crafting this section.

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How to Write a Results Section for a Dissertation or Research Paper: Guide & Examples

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A results section is a crucial part of a research paper or dissertation, where you analyze your major findings. This section goes beyond simply presenting study outcomes. You should also include a comprehensive statistical analysis and interpret the collected data in detail.

Without dissertation research results, it is impossible to imagine a scientific work. Your task here is to present your study findings. What are qualitative or quantitative indicators? How to use tables and diagrams? How to describe data? Our article answers all these questions and many more. So, read further to discover how to analyze and describe your research indexes or contact or professionals for dissertation help from StudyCrumb.

What Is a Results Section of Dissertation?

The results section of a dissertation is a data statement from your research. Here you should present the main findings of your study to your readers. This section aims to show information objectively, systematically, concisely. It is allowed using text supplemented with illustrations.  In general, this section's length is not limited but should include all necessary data. Interpretations or conclusions should not be included in this section. Therefore, in theory, this is one of your shortest sections. But it can also be one of the most challenging sections.  The introduction presents a research topic and answers the question "why?". The Methods section explains the data collection process and answers "how?". Meanwhile, the result section shows actual data gained from experiments and tells "what?" Thus, this part plays a critical role in highlighting study's relevance. This chapter gives reader study relevance with novelty. So, you should figure out how to write it correctly. Here are main tasks that you should keep in mind while writing:

• Results answer the question "What was found in your research?"
• Results contain only your study's outcome. They do not include comments or interpretations.
• Results must always be presented accurately & objectively.
• Tables & figures are used to draw readers' attention. But the same data should never be presented in the form of a table and a figure. Don't repeat anything from a table also in text.

Dissertation: Results vs Discussion vs Conclusion

Results and discussion sections of a dissertation are often confused among researchers. Sometimes both these parts are mixed up with a conclusion for thesis . Figured out what is covered in each of these important chapters. Your readers should see that you notice how different they are. A clear understanding of differences will help you write your dissertation more effectively. 5 differences between Results VS Discussion VS Conclusion:

Wanna figure out the actual difference between discussion vs conclusion? Check out our helpful articles about Dissertation Discussion or Dissertation Conclusion.

Present Your Findings When Writing Results Section of Dissertation

Now it's time to understand how to arrange the results section of the dissertation. First, present most general findings, then narrow it down to a more specific one. Describe both qualitative & quantitative results. For example, imagine you are comparing the behavior of hamsters and mice. First, say a few words about the behavioral type of mammals that you studied. Then, mention rodents in general. At end, describe specific species of animals you carried out an experiment on.

Qualitative Results Section in Dissertation

In your dissertation results section, qualitative data may not be directly related to specific sub-questions or hypotheses. You can structure this chapter around main issues that arise when analyzing data. For each question, make a general observation of what data show. For example, you may recall recurring agreements or differences, patterns, trends. Personal answers are the basis of your research. Clarify and support these views with direct quotes. Add more information to the thesis appendix if it's needed.

Quantitative Results Section in a Dissertation

The easiest way to write a quantitative dissertation results section is to build it around a sub-question or hypothesis of your research. For each subquery, provide relevant results and include statistical analysis . Then briefly evaluate importance & reliability. Notice how each result relates to the problem or whether it supports the hypothesis. Focus on key trends, differences, and relationships between data. But don't speculate about their meaning or consequences. This should be put in the discussion vs conclusion section. Suppose your results are not directly related to answering your questions. Maybe there is additional information that helps readers understand how you collect data. In that case, you can include them in the appendix. It is often helpful to include visual elements such as graphs, charts, and tables. But only if they accurately support your results and add value.

Tables and Figures in Results Section in Dissertation

We recommend you use tables or figures in the dissertation results section correctly. Such interpretation can effectively present complex data concisely and visually. It allows readers to quickly gain a statistical overview. On the contrary, poorly designed graphs can confuse readers. That will reduce the effectiveness of your article.  Here are our recommendations that help you understand how to use tables and figures:

• Make sure tables and figures are self-explanatory. Sometimes, your readers may look at tables and figures before reading the entire text. So they should make sense as separate elements.
• Do not repeat the content of tables and figures in text. Text can be used to highlight key points from tables and figures. But do not repeat every element.
• Make sure that values ​​or information in tables and text are consistent. Make sure that abbreviations, group names, interpretations are the same as in text.
• Use clear, informative titles for tables and figures. Do not leave any table or figure without a title or legend. Otherwise, readers will not be able to understand data's meaning. Also, make sure column names, labels, figures are understandable.
• Check accuracy of data presented in tables and figures. Always double-check tables and figures to make sure numbers converge.
• Tables should not contain redundant information. Make sure tables in the article are not too crowded. If you need to provide extensive data, use Appendixes.
• Make sure images are clear. Make sure images and all parts of drawings are precise. Lettering should be in a standard font and legible against the background of the picture.
• Ask for permission to use illustrations. If you use illustrations, be sure to ask copyright holders and indicate them.

Tips on How to Write a Results Section

We have prepared several tips on how to write the results section of the dissertation!  Present data collected during study objectively, logically, and concisely. Highlight most important results and organize them into specific sections. It is an excellent way to show that you have covered all the descriptive information you need. Correct usage of visual elements effectively helps your readers with understanding. So, follow main 3 rules for writing this part:

• State only actual results. Leave explanations and comments for Discussion.
• Use text, tables, and pictures to orderly highlight key results.
• Make sure that contents of tables and figures are not repeated in text.

In case you have questions about a  conceptual framework in research , you will find a blog dedicated to this issue in our database.

What to Avoid When Writing the Results Section of a Dissertation

Here we will discuss how NOT to write the results section of a dissertation. Or simply, what points to avoid:

• Do not make your research too complicated. Your paper, tables, and graphs should be clearly marked and follow order. So that they can exist independently without further explanation.
• Do not include raw data. Remember, you are summarizing relevant results, not reporting them in detail. This chapter should briefly summarize your findings. Avoid complete introduction to each number and calculation.
• Do not contradict errors or false results. Explain these errors and contradictions in conclusions. This often happens when different research methods have been used.
• Do not write a conclusion or discussion. Instead, this part should contain summaries of findings.
• Do not tend to include explanations and inferences from results. Such an approach can make this chapter subjective, unclear, and confusing to the reader.
• Do not forget about novelty. Its lack is one of the main reasons for the paper's rejection.

Dissertation Results Section Example

Let's take a look at some good results section of dissertation examples. Remember that this part shows fundamental research you've done in detail. So, it has to be clear and concise, as you can see in the sample.

Final Thoughts on Writing Results Section of Dissertation

When writing a results section of a dissertation, highlight your achievements by data. The main chapter's task is to convince the reader of conclusions' validity of your research. You should not overload text with too detailed information. Never use words whose meanings you do not understand. Also, oversimplification may seem unconvincing for readers. But on the other hand, writing this part can even be fun. You can directly see your study results, which you'll interpret later. So keep going, and we wish you courage!

Writing any academic paper is long and thorough work. But StudyCrumb got you back! Our professional writers will deliver any type of work quickly and excellently! 

Joe Eckel is an expert on Dissertations writing. He makes sure that each student gets precious insights on composing A-grade academic writing.

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How to Write an APA Results Section

Kendra Cherry, MS, is a psychosocial rehabilitation specialist, psychology educator, and author of the "Everything Psychology Book."

Emily is a board-certified science editor who has worked with top digital publishing brands like Voices for Biodiversity, Study.com, GoodTherapy, Vox, and Verywell.

Verywell / Nusha Ashjaee 

What to Include in an APA Results Section

• Justify Claims
• Summarize Results

Report All Relevant Results

• Report Statistical Findings

Include Tables and Figures

What not to include in an apa results section.

Psychology papers generally follow a specific structure. One important section of a paper is known as the results section. An APA results section of a psychology paper summarizes the data that was collected and the statistical analyses that were performed. The goal of this section is to report the results of your study or experiment without any type of subjective interpretation.

At a Glance

The results section is a vital part of an APA paper that summarizes a study's findings and statistical analysis. This section often includes descriptive text, tables, and figures to help summarize the findings. The focus is purely on summarizing and presenting the findings and should not include any interpretation, since you'll cover that in the subsequent discussion section.

This article covers how to write an APA results section, including what to include and what to avoid.

The results section is the third section of a psychology paper. It will appear after the introduction and methods sections and before the discussion section.

The results section should include:

• A summary of the research findings.
• Information about participant flow, recruitment, retention, and attrition. If some participants started the study and later left or failed to complete the study, then this should be described. 
• Information about any reasons why some data might have been excluded from the study. 
• Statistical information including samples sizes and statistical tests that were used. It should report standard deviations, p-values, and other measures of interest.

Results Should Justify Your Claims

Report data in order to sufficiently justify your conclusions. Since you'll be talking about your own interpretation of the results in the discussion section, you need to be sure that the information reported in the results section justifies your claims.

When you start writing your discussion section, you can then look back on your results to ensure that all the data you need are there to fully support your conclusions. Be sure not to make claims in your discussion section that are not supported by the findings described in your results section.

Summarize Your Results

Remember, you are summarizing the results of your psychological study, not reporting them in full detail. The results section should be a relatively brief overview of your findings, not a complete presentation of every single number and calculation.

If you choose, you can create a supplemental online archive where other researchers can access the raw data if they choose.

How long should a results section be?

The length of your results section will vary depending on the nature of your paper and the complexity of your research. In most cases, this will be the shortest section of your paper.

Just as the results section of your psychology paper should sufficiently justify your claims, it should also provide an accurate look at what you found in your study. Be sure to mention all relevant information.

Don't omit findings simply because they failed to support your predictions.

Your hypothesis may have expected more statistically significant results or your study didn't support your hypothesis , but that doesn't mean that the conclusions you reach are not useful. Provide data about what you found in your results section, then save your interpretation for what the results might mean in the discussion section.

While your study might not have supported your original predictions, your finding can provide important inspiration for future explorations into a topic.

How is the results section different from the discussion section?

The results section provides the results of your study or experiment. The goal of the section is to report what happened and the statistical analyses you performed. The discussion section is where you will examine what these results mean and whether they support or fail to support your hypothesis.

Report Your Statistical Findings

Always assume that your readers have a solid understanding of statistical concepts. There's no need to explain what a t-test is or how a one-way ANOVA works. Your responsibility is to report the results of your study, not to teach your readers how to analyze or interpret statistics.

Include Effect Sizes

The Publication Manual of the American Psychological Association recommends including effect sizes in your results section so that readers can appreciate the importance of your study's findings.

Your results section should include both text and illustrations. Presenting data in this way makes it easier for readers to quickly look at your results.

Structure your results section around tables or figures that summarize the results of your statistical analysis. In many cases, the easiest way to accomplish this is to first create your tables and figures and then organize them in a logical way. Next, write the summary text to support your illustrative materials.

Only include tables and figures if you are going to talk about them in the body text of your results section.

In addition to knowing what you should include in the results section of your psychology paper, it's also important to be aware of things that you should avoid putting in this section:

Cause-and-Effect Conclusions

Don't draw cause-effect conclusions. Avoid making any claims suggesting that your result "proves" that something is true. 

Interpretations

Present the data without editorializing it. Save your comments and interpretations for the discussion section of your paper. 

Statistics Without Context

Don't include statistics without narration. The results section should not be a numbers dump. Instead, you should sequentially narrate what these numbers mean.

Don't include the raw data in the results section. The results section should be a concise presentation of the results. If there is raw data that would be useful, include it in the appendix .

Don't only rely on descriptive text. Use tables and figures to present these findings when appropriate. This makes the results section easier to read and can convey a great deal of information quickly.

Repeated Data

Don't present the same data twice in your illustrative materials. If you have already presented some data in a table, don't present it again in a figure. If you have presented data in a figure, don't present it again in a table.

All of Your Findings

Don't feel like you have to include everything. If data is irrelevant to the research question, don't include it in the results section.

But Don't Skip Relevant Data

Don't leave out results because they don't support your claims. Even if your data does not support your hypothesis, including it in your findings is essential if it's relevant.

More Tips for Writing a Results Section

If you are struggling, there are a few things to remember that might help:

• Use the past tense . The results section should be written in the past tense.
• Be concise and objective . You will have the opportunity to give your own interpretations of the results in the discussion section.
• Use APA format . As you are writing your results section, keep a style guide on hand. The Publication Manual of the American Psychological Association is the official source for APA style.
• Visit your library . Read some journal articles that are on your topic. Pay attention to how the authors present the results of their research.
• Get a second opinion . If possible, take your paper to your school's writing lab for additional assistance.

What This Means For You

Remember, the results section of your paper is all about providing the data from your study. This section is often the shortest part of your paper, and in most cases, the most clinical.

Be sure not to include any subjective interpretation of the results. Simply relay the data in the most objective and straightforward way possible. You can then provide your own analysis of what these results mean in the discussion section of your paper.

Bavdekar SB, Chandak S. Results: Unraveling the findings . J Assoc Physicians India . 2015 Sep;63(9):44-6. PMID:27608866.

Snyder N, Foltz C, Lendner M, Vaccaro AR. How to write an effective results section .  Clin Spine Surg . 2019;32(7):295-296. doi:10.1097/BSD.0000000000000845

American Psychological Association.  Publication Manual of the American Psychological Association  (7th ed.). Washington DC: The American Psychological Association; 2019.

Purdue Online Writing Lab. APA sample paper: Experimental psychology .

Berkeley University. Reviewing test results .

Tuncel A, Atan A. How to clearly articulate results and construct tables and figures in a scientific paper ? Turk J Urol . 2013;39(Suppl 1):16-19. doi:10.5152/tud.2013.048

By Kendra Cherry, MSEd Kendra Cherry, MS, is a psychosocial rehabilitation specialist, psychology educator, and author of the "Everything Psychology Book."

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How to Write the Results/Findings Section in Research

What is the research paper Results section and what does it do?

The Results section of a scientific research paper represents the core findings of a study derived from the methods applied to gather and analyze information. It presents these findings in a logical sequence without bias or interpretation from the author, setting up the reader for later interpretation and evaluation in the Discussion section. A major purpose of the Results section is to break down the data into sentences that show its significance to the research question(s).

The Results section appears third in the section sequence in most scientific papers. It follows the presentation of the Methods and Materials and is presented before the Discussion section —although the Results and Discussion are presented together in many journals. This section answers the basic question “What did you find in your research?”

What is included in the Results section?

The Results section should include the findings of your study and ONLY the findings of your study. The findings include:

• Data presented in tables, charts, graphs, and other figures (may be placed into the text or on separate pages at the end of the manuscript)
• A contextual analysis of this data explaining its meaning in sentence form
• All data that corresponds to the central research question(s)
• All secondary findings (secondary outcomes, subgroup analyses, etc.)

If the scope of the study is broad, or if you studied a variety of variables, or if the methodology used yields a wide range of different results, the author should present only those results that are most relevant to the research question stated in the Introduction section .

As a general rule, any information that does not present the direct findings or outcome of the study should be left out of this section. Unless the journal requests that authors combine the Results and Discussion sections, explanations and interpretations should be omitted from the Results.

How are the results organized?

The best way to organize your Results section is “logically.” One logical and clear method of organizing research results is to provide them alongside the research questions—within each research question, present the type of data that addresses that research question.

Let’s look at an example. Your research question is based on a survey among patients who were treated at a hospital and received postoperative care. Let’s say your first research question is:

“What do hospital patients over age 55 think about postoperative care?”

This can actually be represented as a heading within your Results section, though it might be presented as a statement rather than a question:

Attitudes towards postoperative care in patients over the age of 55

Now present the results that address this specific research question first. In this case, perhaps a table illustrating data from a survey. Likert items can be included in this example. Tables can also present standard deviations, probabilities, correlation matrices, etc.

Following this, present a content analysis, in words, of one end of the spectrum of the survey or data table. In our example case, start with the POSITIVE survey responses regarding postoperative care, using descriptive phrases. For example:

“Sixty-five percent of patients over 55 responded positively to the question “ Are you satisfied with your hospital’s postoperative care ?” (Fig. 2)

Include other results such as subcategory analyses. The amount of textual description used will depend on how much interpretation of tables and figures is necessary and how many examples the reader needs in order to understand the significance of your research findings.

Next, present a content analysis of another part of the spectrum of the same research question, perhaps the NEGATIVE or NEUTRAL responses to the survey. For instance:

  “As Figure 1 shows, 15 out of 60 patients in Group A responded negatively to Question 2.”

After you have assessed the data in one figure and explained it sufficiently, move on to your next research question. For example:

  “How does patient satisfaction correspond to in-hospital improvements made to postoperative care?”

This kind of data may be presented through a figure or set of figures (for instance, a paired T-test table).

Explain the data you present, here in a table, with a concise content analysis:

“The p-value for the comparison between the before and after groups of patients was .03% (Fig. 2), indicating that the greater the dissatisfaction among patients, the more frequent the improvements that were made to postoperative care.”

Let’s examine another example of a Results section from a study on plant tolerance to heavy metal stress . In the Introduction section, the aims of the study are presented as “determining the physiological and morphological responses of Allium cepa L. towards increased cadmium toxicity” and “evaluating its potential to accumulate the metal and its associated environmental consequences.” The Results section presents data showing how these aims are achieved in tables alongside a content analysis, beginning with an overview of the findings:

“Cadmium caused inhibition of root and leave elongation, with increasing effects at higher exposure doses (Fig. 1a-c).”

The figure containing this data is cited in parentheses. Note that this author has combined three graphs into one single figure. Separating the data into separate graphs focusing on specific aspects makes it easier for the reader to assess the findings, and consolidating this information into one figure saves space and makes it easy to locate the most relevant results.

Following this overall summary, the relevant data in the tables is broken down into greater detail in text form in the Results section.

• “Results on the bio-accumulation of cadmium were found to be the highest (17.5 mg kgG1) in the bulb, when the concentration of cadmium in the solution was 1×10G2 M and lowest (0.11 mg kgG1) in the leaves when the concentration was 1×10G3 M.”

Captioning and Referencing Tables and Figures

Tables and figures are central components of your Results section and you need to carefully think about the most effective way to use graphs and tables to present your findings . Therefore, it is crucial to know how to write strong figure captions and to refer to them within the text of the Results section.

The most important advice one can give here as well as throughout the paper is to check the requirements and standards of the journal to which you are submitting your work. Every journal has its own design and layout standards, which you can find in the author instructions on the target journal’s website. Perusing a journal’s published articles will also give you an idea of the proper number, size, and complexity of your figures.

Regardless of which format you use, the figures should be placed in the order they are referenced in the Results section and be as clear and easy to understand as possible. If there are multiple variables being considered (within one or more research questions), it can be a good idea to split these up into separate figures. Subsequently, these can be referenced and analyzed under separate headings and paragraphs in the text.

To create a caption, consider the research question being asked and change it into a phrase. For instance, if one question is “Which color did participants choose?”, the caption might be “Color choice by participant group.” Or in our last research paper example, where the question was “What is the concentration of cadmium in different parts of the onion after 14 days?” the caption reads:

 “Fig. 1(a-c): Mean concentration of Cd determined in (a) bulbs, (b) leaves, and (c) roots of onions after a 14-day period.”

Steps for Composing the Results Section

Because each study is unique, there is no one-size-fits-all approach when it comes to designing a strategy for structuring and writing the section of a research paper where findings are presented. The content and layout of this section will be determined by the specific area of research, the design of the study and its particular methodologies, and the guidelines of the target journal and its editors. However, the following steps can be used to compose the results of most scientific research studies and are essential for researchers who are new to preparing a manuscript for publication or who need a reminder of how to construct the Results section.

Step 1 : Consult the guidelines or instructions that the target journal or publisher provides authors and read research papers it has published, especially those with similar topics, methods, or results to your study.

• The guidelines will generally outline specific requirements for the results or findings section, and the published articles will provide sound examples of successful approaches.
• Note length limitations on restrictions on content. For instance, while many journals require the Results and Discussion sections to be separate, others do not—qualitative research papers often include results and interpretations in the same section (“Results and Discussion”).
• Reading the aims and scope in the journal’s “ guide for authors ” section and understanding the interests of its readers will be invaluable in preparing to write the Results section.

Step 2 : Consider your research results in relation to the journal’s requirements and catalogue your results.

• Focus on experimental results and other findings that are especially relevant to your research questions and objectives and include them even if they are unexpected or do not support your ideas and hypotheses.
• Catalogue your findings—use subheadings to streamline and clarify your report. This will help you avoid excessive and peripheral details as you write and also help your reader understand and remember your findings. Create appendices that might interest specialists but prove too long or distracting for other readers.
• Decide how you will structure of your results. You might match the order of the research questions and hypotheses to your results, or you could arrange them according to the order presented in the Methods section. A chronological order or even a hierarchy of importance or meaningful grouping of main themes or categories might prove effective. Consider your audience, evidence, and most importantly, the objectives of your research when choosing a structure for presenting your findings.

Step 3 : Design figures and tables to present and illustrate your data.

• Tables and figures should be numbered according to the order in which they are mentioned in the main text of the paper.
• Information in figures should be relatively self-explanatory (with the aid of captions), and their design should include all definitions and other information necessary for readers to understand the findings without reading all of the text.
• Use tables and figures as a focal point to tell a clear and informative story about your research and avoid repeating information. But remember that while figures clarify and enhance the text, they cannot replace it.

Step 4 : Draft your Results section using the findings and figures you have organized.

• The goal is to communicate this complex information as clearly and precisely as possible; precise and compact phrases and sentences are most effective.
• In the opening paragraph of this section, restate your research questions or aims to focus the reader’s attention to what the results are trying to show. It is also a good idea to summarize key findings at the end of this section to create a logical transition to the interpretation and discussion that follows.
• Try to write in the past tense and the active voice to relay the findings since the research has already been done and the agent is usually clear. This will ensure that your explanations are also clear and logical.
• Make sure that any specialized terminology or abbreviation you have used here has been defined and clarified in the  Introduction section .

Step 5 : Review your draft; edit and revise until it reports results exactly as you would like to have them reported to your readers.

• Double-check the accuracy and consistency of all the data, as well as all of the visual elements included.
• Read your draft aloud to catch language errors (grammar, spelling, and mechanics), awkward phrases, and missing transitions.
• Ensure that your results are presented in the best order to focus on objectives and prepare readers for interpretations, valuations, and recommendations in the Discussion section . Look back over the paper’s Introduction and background while anticipating the Discussion and Conclusion sections to ensure that the presentation of your results is consistent and effective.
• Consider seeking additional guidance on your paper. Find additional readers to look over your Results section and see if it can be improved in any way. Peers, professors, or qualified experts can provide valuable insights.

One excellent option is to use a professional English proofreading and editing service  such as Wordvice, including our paper editing service . With hundreds of qualified editors from dozens of scientific fields, Wordvice has helped thousands of authors revise their manuscripts and get accepted into their target journals. Read more about the  proofreading and editing process  before proceeding with getting academic editing services and manuscript editing services for your manuscript.

As the representation of your study’s data output, the Results section presents the core information in your research paper. By writing with clarity and conciseness and by highlighting and explaining the crucial findings of their study, authors increase the impact and effectiveness of their research manuscripts.

For more articles and videos on writing your research manuscript, visit Wordvice’s Resources page.

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Writing up the results section of your dissertation

(Last updated: 12 May 2021)

Since 2006, Oxbridge Essays has been the UK’s leading paid essay-writing and dissertation service

We have helped 10,000s of undergraduate, Masters and PhD students to maximise their grades in essays, dissertations, model-exam answers, applications and other materials. If you would like a free chat about your project with one of our UK staff, then please just reach out on one of the methods below.

When asked why doing a dissertation can be such a headache, the typical student usually replies with one of two answers. Either, they simply don't like writing enormous volumes of text, or – and you may relate here – they categorically do not enjoy analysing data. "It's so long and boring!", the typical student wails.

Well, students wail, and we answer. We have put together this very comprehensive, very useful guide on how to write up the results section of your dissertation. To help you further, we've broken the information down into both quantitative and qualitative results, so you can focus on what applies to you most.

Writing up your quantitative results

Understanding the basics of your research.

First, you need to recall what you have assessed – or what your main variables are.

All quantitative research has at least one independent and one dependent variable, and, at this point, you should define them explicitly. An independent variable is one that you control to test its effects on the dependent variable. A dependent variable is thus your outcome variable.

Second, you need to determine if your variables were categorical or continuous.

A categorical variable is one with a fixed number of possible values, and a continuous variable is one where final scores have a wide range. Finally, you need to recall if you have used a so-called covariate or confounder variable. This is a variable that could have influenced the relationship between your independent and dependent variable, and that you controlled in order to accurately estimate the relationship between your main variables.

Let’s explain all this with an example. Suppose that your research was to assess whether height is associated with self-esteem. Here, participants’ height is an independent variable and self-esteem is a dependent variable. Because both height and scores on a measure of self-esteem can have a wide range, you have two continuous variables. You might have also wanted to see if the relationship between height and self-esteem exists after controlling for participants’ weight. In this case, weight is a confounding variable that you need to control for.

Here is another example. You might have assessed whether more females than males want to read a specific romantic novel. Here, your independent variable is gender and your dependent variable is the determination to read the book. Since gender has categories (male and female), this is a categorical variable. If you have assessed the determination to read the book on a scale from 1 to 10 (e.g. 1 = no determination at all to read the book, all the way to 10 = extremely strong determination to read it), then this is a continuous variable; however, if you have asked your participants to say whether they do or do not want to read the book, then this is a categorical variable (since there are two categories: “yes” and “no”).

Lastly, you might have wanted to see if the link between gender and the determination to read the book exists after controlling for participants’ current relationship status. Here, relationship status is your confounding variable.

We will return to these examples throughout this blog post. At this point, it is important to remember that outlining your research in this way helps you to write up your results section in the easiest way possible.

Let’s move on to the next step.

Outlining descriptive and frequencies statistics

In order to report descriptive and/or frequencies statistics, you need to outline all variables that you have used in your research and note whether those variables are continuous or categorical.

For continuous variables, you are using descriptive statistics and reporting the measures of central tendency (mean) and measures of variability or spread (standard deviation). For categorical variables, you are using frequencies statistics and reporting the number (or frequency) of participants per category and associated percentages. Both these statistics require you to make a table, and in both cases you also need to comment upon the statistics.

How does all of this look in practice? Recall the two examples that were outlined above. If you have assessed the association between participants’ height and self-esteem, while controlling for participants’ weight, then your research consists of three continuous variables. You need to make a table, as in TABLE 1 below, which identifies means and standard deviations for all these variables. When commenting upon the results, you can say:

Participants were on average 173.50 cm tall (SD = 5.81) and their mean weight was 65.31 kg (SD = 4.44). On average, participants had moderate levels of self-esteem (M = 5.55, SD = 2.67).

Note that, in this example, you are concluding that participants had moderate self-esteem levels if their self-esteem was assessed on a 1 to 10 scale. Since the value of 5 falls within the middle of this range, you are concluding that the mean value of self-esteem is moderate. If the mean value was higher (e.g., M = 8.33), you would conclude that participants’ self-esteem was, on average, high; and if the mean value was lower (e.g., M = 2.44), you would conclude that average self-esteem scores were low.

Let’s now return to our second research example and say that you want to report the degree to which males and females want to read a romantic novel, where this determination was assessed on a 1-10 (continuous) scale. This would look as shown in TABLE 2.

We can see how to report frequencies statistics for different groups by referring to our second example about gender, determination to read a romantic novel, and participants’ relationship status.

Here, you have three categorical variables (if determination to read the novel was assessed by having participants reply with “yes” or “no”). Thus, you are not reporting means and standard deviations, but frequencies and percentages.

To put this another way, you are noting how many males versus females wanted to read the book and how many of them were in a relationship, as shown in TABLE 3. You can report these statistics in this way:

Twenty (40%) male participants wanted to read the book and 35 (70%) female participants wanted to read the book. Moreover, 22 (44%) males and 26 (52%) females indicated that they are currently in a relationship.

Reporting the results of a correlation analysis

The first of these is correlation, which you use when you want to establish if one or more (continuous, independent) variables relate to another (continuous, dependent) variable. For instance, you may want to see if participants’ height correlates with their self-esteem levels.

The first step here is to report whether your variables are normally distributed. You do this by looking at a histogram that describes your data. If the histogram has a bell-shaped curve (see purple graph below), your data is normally distributed and you need to rely on a Pearson correlation analysis. Here, you need to report the obtained r value (correlation coefficient) and p value (which needs to be lower than .05 in order to establish significance). If you find a correlation, you need to say something like:

One final thing to note, which is important for all analyses, is that when your p value is indicated to be .000, you never report it by saying “ p = .000”, but by noting “ p p = .011”.

If your data is skewed rather than normally distributed (see red graphs), then you need to rely on a Spearman correlation analysis. Here, you report the results by saying:

Spearman correlation analysis revealed a positive relationship between people’s height and their self-esteem (r s = .44, p There has been a significant positive correlation between height and self-esteem after controlling for participants’ weight ( r = .39, p = .034).

You also need to make a table that will summarise your main results. If you didn’t use a covariate, you will have a fairly simple table, such as that shown in TABLE 4. If you have used a covariate, your table is slightly more complex, such as that shown in TABLE 5. Note that both tables use “-” to indicate correlations that have already been noted within the table. Also note how “*”, “**”, and “***” are used to annotate correlations that are significant at different levels.

Reporting the results of a regression

These are the specific points that you need to address in order to make sure that all assumptions have been met:

(1) for the assumption of no multicollinearity (i.e., a lack of high correlation between your independent variables), you need to establish that none of your Tolerance statistics are below .01 and none of the VIF statistics are above 10;

(2) for the assumption of no autocorrelation of residuals (i.e., a lack of correlation between the residuals of two observations), you need to look at this table and see whether your Durbin-Watson statistic falls within a desirable range, depending on your number of participants and the number of predictors (independent variables); and,

(3) for the assumptions of linearity (i.e., a linear relationship between independent and dependent variables) and homoscedasticity (i.e., a variance of error terms that should be similar across the independent variables), you need to look at the scatterplot of standardised residual on standardised predicted value and conclude that your graph doesn’t funnel out or curve.

All of this may sound quite complex. But in reality it is not: you just need to look at your results output to note the Tolerance and VIF values, Durbin-Watson value, and the scatterplot. Once you conclude that your assumptions have been met, you write something like:

Since none of the VIF values were below 0.1 and none of the Tolerance values were above 10, the assumption of no multicollinearity has been met. Durbin-Watson statistics fell within an expected range, thus indicating that the assumption of no autocorrelation of residuals has been met as well. Finally, the scatterplot of standardised residual on standardised predicted value did not funnel out or curve, and thus the assumptions of linearity and homoscedasticity have been met as well.

If your assumptions have not been met, you need to dig a bit deeper and understand what this means. A good idea would be to read the chapter on regression (and especially the part about assumptions) written by Andy Field. You can access his book here . This will help you understand all you need to know about the assumptions of a regression analysis, how to test them, and what to do if they have not been met.

Now let’s focus on reporting the results of the actual regression analysis. Let’s say that you wanted to see if participants’ height predicts their self-esteem, after controlling for participants’ weight. You have entered height and weight as predictors in the model and self-esteem as a dependent variable.

First, you need to report whether the model reached significance in predicting self-esteem scores. Look at the results of an ANOVA analysis in your output and note the F value, degrees of freedom for the model and for residuals, and significance level. These values are shown in PICTURE 2.

Significance value tells you if your predictor reached significance – such as whether participants’ height predicted self-esteem scores. You also need to comment upon the β value. This value represents the change in the outcome associated with a unit change in the predictor . Thus, if your β value is .351 for participants’ height (predictor/independent variable), then this means that for every increase in height by 1 cm, self-esteem increases by .35. You need to report the same thing for your other predictor – that is, participants’ weight.

Finally, since your model included both height and weight as predictors, and height acted as a significant predictor, you can conclude that participants’ height influences their self-esteem after controlling for weight.

Reporting the results of a chi-square analysis

For instance, you would do a chi-square analysis when you want to see whether gender (categorical independent variable with two levels: males/females) affects the determination to read a book, when this variable is measured with yes/no answers (categorical dependent variable with two levels: yes/no).

When reporting your results, you should first make a table as shown in TABLE 3 above. Then you need to report the results of a chi-square test, by noting the Pearson chi-square value, degrees of freedom, and significance value. You can see all these in your output.

Finally, you need to report the strength of the association, for which you need to look at the Phi and Cramer’s V values. When each of your variables has only two categories, as in the present example, Phi and Cramer’s V values are identical and it doesn’t matter which one you will report. However, when one of your variables has more than two categories, it is better to report the Cramer’s V value. You report these values by indicating the actual value and the associated significance level.

Note that Cramer’s V value can range from 0 to 1. The closer the value is to 1, the higher the strength of the association. You can report the results of the chi-square analysis in the following way:

Reporting the results of a t-test analysis

Recall that you have previously outlined descriptive statistics for these variables, where you have noted means and standard deviations for males’ and females’ scores on the determination to read the novel (see TABLE 2 above). Now you need to report the obtained t value, degrees of freedom, and significance level – all of which you can see in your results output.

You can say something like:

Reporting the results of one-way ANOVA

In the t-test example, you had two conditions of a categorical independent variable, which corresponded to whether a participant was male or female. You would have three conditions of an independent variable when assessing whether relationship status (independent variable with three levels: single, in a relationship, and divorced) affects the determination to read a romantic novel (as assessed on a 1-10 scale).

Here, you would report the results in a similar manner to that of a t -test. You first report the means and standard deviations on the determination to read the book for all three groups of participants, by saying who had the highest and lowest mean. Then you report the results of the ANOVA test by reporting the F value, degrees of freedom (for within-subjects and between-subjects comparisons), and the significance value.

There are two things to note here. First, before reporting your results, you need to look at your output to see whether the so-called Levene’s test is significant. This test assesses the homogeneity of variance – the assumption being that all comparison groups should have the same variance. If the test is non-significant, the assumption has been met and you are reporting the standard F value.

However, if the test is significant, the assumption has been violated and you need to report instead the Welch statistic, associated degrees of freedom, and significance value (which you will see in your output; for example, see PICTURE 3 above).

The second thing to note is that ANOVA tells you only whether there were significant differences between groups – but if there are differences, it doesn’t tell you where these differences lie. For this, you need to conduct a post-hoc comparison (Tukey’s HSD test). The output will tell you which comparisons are significant.

You can report your results in the following manner:

Reporting the results of ANCOVA

For instance, you will use ANCOVA when you want to test whether relationship status (categorical independent variable with three levels: single, in a relationship, divorced) affects the determination to read a romantic novel (continuous dependent variable, assessed on a 1-10 scale) after controlling for participants’ general interest in books (continuous covariate, assessed on a 1-10 scale).

To report the results, you need to look at the “test of between-subjects effects” table in your output. You need to report the F values, degrees of freedom (for each variable and error), and significance values for both the covariate and the main independent variable. As with ANOVA, a significant ANCOVA doesn’t tell you where the differences lie. For this, you need to conduct planned contrasts and report the associated significance values for different comparisons.

You can report the results in the following manner:

Reporting the results of MANOVA

For instance, you would use MANOVA when testing whether male versus female participants (independent variable) show a different determination to read a romantic novel (dependent variable) and a determination to read a crime novel (dependent variable).

When reporting the results, you first need to notice whether the so-called Box’s test and Levene’s test are significant. These tests assess two assumptions: that there is an equality of covariance matrices (Box’s test) and that there is an equality of variances for each dependent variable (Levene’s test).

Both tests need to be non-significant in order to assess whether your assumptions are met. If the tests are significant, you need to dig deeper and understand what this means. Once again, you may find it helpful to read the chapter by Andy Field on MANOVA, which can be accessed here .

Following this, you need to report your descriptive statistics, as outlined previously. Here, you are reporting the means and standard deviations for each dependent variable, separately for each group of participants. Then you need to look at the results of “multivariate analyses”.

You will notice that you are presented with four statistic values and associated F and significance values. These are labelled as Pillai’s Trace, Wilks’ Lambda, Hotelling’s Trace, and Roy’s Largest Root. These statistics test whether your independent variable has an effect on the dependent variables. The most common practice is to report only the Pillai’s Trace. You report the results in the same manner as reporting ANOVA, by noting the F value, degrees of freedom (for hypothesis and error), and significance value.

However, you also need to report the statistic value of one of the four statistics mentioned above. You can label the Pillai’s Trace statistic with V, the Wilks’ Lambda statistic with A, the Hotelling’s Trace statistic with T, and Roy’s Largest Root statistic with Θ (but you need report only one of them).

Finally, you need to look at the results of the Tests of Between-Subjects Effects (which you will see in your output). These tests tell you how your independent variable affected each dependent variable separately. You report these results in exactly the same way as in ANOVA.

Here’s how you can report all results from MANOVA:

Writing up your qualitative results

Before reporting the results of your qualitative research, you need to recall what type of research you have conducted. The most common types of qualitative research are interviews, observations, and focus groups – and your research is likely to fall into one of these types.

All three types of research are reported in a similar manner. Still, it may be useful if we focus on each of them separately.

Reporting the results of interviews

For example, let’s say that your qualitative research focused on young people’s reasons for smoking. You have asked your participants questions that explored why they started smoking, why they continue to smoke, and why they wish to quit smoking. Since your research was organised in this manner, you already have three major themes: (1) reasons for starting to smoke, (2) reasons for continuing to smoke, and (3) reasons for quitting smoking. You then explore particular reasons why your participants started to smoke, why they continue to smoke, and why they want to quit. Each reason that you identify will act as a subtheme.

When reporting the results, you should organise your text in subsections. Each section should refer to one theme. Then, within each section, you need to discuss the subthemes that you discovered in your data.

Let’s say that you found that young people started smoking because: (1) they thought smoking was cool, (2) they experienced peer pressure, (3) their parents modelled smoking behaviour, (4) they thought smoking reduces stress, and (5) they wanted to try something new. Now you have five subthemes within your “reasons for starting to smoke” theme. What you need to do now is to present the findings for each subtheme, while also reporting quotes that best describe your subtheme. You do that for each theme and subtheme.

It is also good practice to make a table that lists all your themes, subthemes, and associated quotes.

Here’s an example of how to report a quote within a text:

Reporting the results of observations

For instance, you might have noticed that the therapist finds it important to discuss: (1) the origin of the problem, (2) the lack of a patient’s medical difficulties, (3) the experience of stress, (4) the link of stress to the problem, and (5) the new understanding of the problem. You can consider these as themes in your observations.

Accordingly, you will want to report each theme separately. You do this by outlining your observation first (this can be a conversation or a behaviour that you observed), and then commenting upon it.

Here’s an example:

Therapist: Was there something that stressed you out during the last few months?

Patient: Yes, of course. I thought I would lose my job, but that passed. After that, I was breaking up with my girlfriend. But between those things, I was fine.

Therapist: And was there any difference in your symptoms while you were and while you were not stressed?

Patient: Hmmm. Actually yes. Now that I think of it, they were mostly present when I went through those periods.

Therapist: Could it be that stress intensifies your symptoms?

Patient: I never thought of it. I guess it seems logical. Is it?

Reporting the results of focus groups

As an example, let’s say that your focus group dealt with identifying reasons why some people prefer Coca-Cola over Schweppes, and vice versa. You have transcribed your focus group sessions and have extracted themes from the data. You have discovered a wide variety of reasons why people prefer one of the two drinks.

When reporting your results, you should have two sections: one listing reasons for favouring Coca-Cola, and the other listing reasons for favouring Schweppes. Within each section, you need to identify specific reasons for these preferences. You should connect these specific reasons to particular quotes.

Here’s an example of how this may look:

In conclusion…

As we have seen, writing up qualitative results is easier than writing quantitative results. Yet, even reporting statistics is not that hard, especially if you have a good guide to help you.

Hopefully, this guide has reduced your worries and increased your confidence that you can write up the results section of your dissertation without too many difficulties.

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Honors student produces prize-winning research on loneliness

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In her honors thesis, recent graduate Amber Duffy describes how loneliness influences a person’s ability to respond to stress

Amber Duffy, who graduated last semester magna cum laude , didn’t always plan to write an honor’s thesis.

She came to the University of Colorado Boulder on a pre-med track, studying neuroscience, but an introductory psychology class knocked her off that path and inspired her to change her major.  

“I really liked the behavioral aspect of psychology,” she says.

She liked psychology so much, in fact, that she wasn’t content simply to study it. She wanted to contribute to it. “If I’m not going to do medical school anymore,” she remembers thinking, “I should delve into research.”

Recent psychology and neuroscience graduate Amber Duffy won the the Outstanding Poster Presentation Talk award at the Society for Personality and Social Psychology’s Annual Convention in San Diego, recognizing her research on loneliness.

She contacted Erik Knight , a CU Boulder assistant professor of psychology and neuroscience, with whom she’d taken a class her sophomore year, and he invited her to join his lab . She ended up working there for two years, during which time she decided to write an honor’s thesis.

The topic? Loneliness and its effect on young adults’ stress responses.

Why loneliness?  

Duffy’s interest in loneliness isn’t purely academic. Many of her friends and family have struggled with it for years, even before the pandemic, she says. And she herself, the daughter of a Taiwanese mother and a Pennsylvanian father, has often felt its sting.  

“Growing up in a multicultural family in my predominantly white town”—Castle Rock, Colorado—“it was hard for me to connect with people sometimes,” she says. “I would learn about my mom’s culture at home and then go to school or talk with friends, and they just didn’t understand how I lived.”

Her concerns over loneliness only increased when she learned of Surgeon General Dr. Vivek H. Murthy’s warning that the United States is suffering from a loneliness epidemic.

“The mortality impact of being socially disconnected is similar to that caused by smoking up to 15 cigarettes a day,” Murthy states.  

Hearing this spurred Duffy to action. She wanted to contribute to the fight against loneliness and its potentially negative consequences.

“If we expand our knowledge of loneliness,” she says, “maybe there’s a way we can come up with a more substantial treatment.”

More gas, less brakes

For her honors experiment, Duffy gathered 51 CU Boulder undergraduates between the ages of 18 and 34 and divided them randomly into a control condition and an experimental condition. Those in the former provided a low-stress comparison to those in the latter, who were put through the wringer.

First, the subjects in the experimental condition had to interview for a high-stakes job Duffy and Knight had concocted specifically for the study.

“We told them, in the moment, ‘You have five minutes to prepare a five-minute speech on why you’re the perfect applicant,’” says Duffy.

Immediately following that, subjects had to solve subtraction problems for five minutes, out loud, perfectly, starting at 6,233 and going down from there in increments of 13. “If they made a mistake,” says Duffy, “they had to start over.”

While the subjects ran these gauntlets, Duffy monitored their heart-rate variability (HRV), or the change in interval between heartbeats, and their pre-ejection period (PEP), or the time it takes for a heart to prepare to push blood to the rest of the body. Both serve as indicators of how a person’s stress-response system is functioning, Duffy explains. 

Finally, when the stress tests were done, the subjects completed the UCLA Loneliness Scale Version 3 questionnaire, which research has found to be a reliable means of measuring loneliness.

Duffy had hypothesized that lonelier subjects would have more pronounced stress responses than less lonely subjects, and indeed that’s what her data revealed.

Lonelier subjects had higher heartrates, stronger responses from their sympathetic nervous systems (SNS) and weaker responses from their parasympathetic nervous systems (PNS). Duffy likens the SNS, which controls the fight-or-flight response, to a car’s gas pedal and the PNS, which counterbalances the SNS, to a car’s brakes.

When met with stressful situations, then, lonelier individuals had more gas and less brakes, which Duffy says could have long-term health implications.

Yet she is also quick to point out that more research needs to be done, preferably with more subjects.

If we expand our knowledge of loneliness, maybe there’s a way we can come up with a more substantial treatment.”

“We only had 51 people. An increase in sample size would help with more reliable data,” she says. “It’s also important to look at more clinical and diverse populations because there are other factors that could affect loneliness levels.” 

Posters, prizes and professorships

Duffy submitted an abstract of her research to The Society for Personality and Social Psychology’s Annual Convention in San Diego, where she hoped to present a poster, thinking this would be a nice, low-key way of getting some conference experience under her belt.

Her abstract was accepted. But then a conference organizer asked her if, in addition to presenting a poster, she could also give a fifteen-minute talk. She would be the only undergraduate at the conference to do so.

Duffy balked. The thought of speaking to a roomful of PhDs intimidated her. “Most of my life I’ve heard how cutthroat academia is,” she says. But she ultimately agreed, and she was glad she did.

Her talk and poster presentation went so well that not only did she receive interest and encouragement from several doctoral programs, but she also won an award that she didn’t even know existed: the Outstanding Poster Presentation Talk award.

“In the middle of my poster presentation, a woman came up to me—I didn’t know who she was—and said, ‘I have a check here for you for $500.’ I didn’t know that was supposed to happen, but it was great!”

Now graduated, Duffy isn’t 100% sure what her next steps will be, but she’s leaning toward one day pursuing a PhD. 

“When you get a PhD, you get to do research and also work with students,” she says. “I think it would be fun to be a professor and give back in that way.”

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Writing an Abstract

What is an abstract.

An abstract is a 150- to 250-word paragraph that provides readers with a quick overview of your essay or report and its organization. It should express your thesis (or central idea) and your key points; it should also suggest any implications or applications of the research you discuss in the paper.

According to Carole Slade, an abstract is “a concise summary of the entire paper.”

The function of an abstract is to describe, not to evaluate or defend, the paper.

The abstract should begin with a brief but precise statement of the problem or issue, followed by a description of the research method and design, the major findings, and the conclusions reached.

The abstract should contain the most important key words referring to method and content: these facilitate access to the abstract by computer search and enable a reader to decide whether to read the entire dissertation.

Note: Your abstract should read like an overview of your paper, not a proposal for what you intended to study or accomplish. Avoid beginning your sentences with phrases like, “This essay will examine...” or “In this research paper I will attempt to prove...”  

(The examples above are taken from Form and Style (10th ed.), by Carole Slade; The Scott, Foresman Handbook for Writers (5th ed.); and the Publication Manual of the American Psychological Association (5th ed.).)

Note: The following are specifications for an abstract in APA style, used in the social sciences, such as psychology or anthropology. If you are in another discipline, check with your professor about the format for the abstract.

Writing an Abstract for an IMRaD Paper

Many papers in the social sciences, natural sciences, and engineering sciences follow IMRaD structure: their main sections are entitled Introduction, Methods, Results, and Discussion. People use the abstract to decide whether to read the rest of the paper, so the abstract for such a paper is important.

Because the abstract provides the highlights of the paper, you should draft your abstract after you have written a full draft of the paper. Doing so, you can summarize what you’ve already written in the paper as you compose the abstract.

Typically, an abstract for an IMRaD paper or presentation is one or two paragraphs long (120 – 500 words). Abstracts usually spend

25% of their space on the purpose and importance of the research (Introduction)

25% of their space on what you did (Methods)

35% of their space on what you found (Results)

15% of their space on the implications of the research

Try to avoid these common problems in IMRaD abstracts:

1. The abstract provides a statement of what the paper will ask or explore rather than what it found:

X This report examines the causes of oversleeping. (What did it find out about these causes?) √ Individuals oversleep because they go to bed too late, forget to set their alarms, and keep their rooms dark.

2. The abstract provides general categories rather than specific details in the findings:

X The study draws conclusions about which variables are most important in choosing a movie theater. (What, specifically, are these variables?)

√ The study concludes that the most important variables in choosing a movie theater are comfortable seats and high-quality popcorn.

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2024 Theses Doctoral

Social Network Effects on Health and Emotional Wellbeing

Stanoi, Ovidia Andreea

Humans’ social relationships determine to a large degree their trajectories in life. Despite strong evidence for the impact of interpersonal relations on wellbeing, the causal links between the two are not yet fully understood. This dissertation offers a new perspective on the mechanisms through which social ties influence negative (excessive drinking) and positive (participation in recreational activities) health behaviors. In three studies employing a unique combination of social network, fMRI, and experience-sampling methods, we propose that health decisions are the result of complex computations involving prior social experiences, perceived social norms, social comparison processes, and current feelings of connections. Each chapter of this dissertation discusses one of these three studies. Chapter 1 provides evidence that past social experiences shape valuations of new information by showing that pairs of students that drink often together tend to have more similar neural responses to novel alcohol cues in regions associated with affective self-generated thought. In addition, this Chapter suggests that researchers must consider the intricate interplay between individuals’ personal goals and their communities’ norms to understand the influence of social environments on neural representations. The degree to which students aligned their neural response patterns to alcohol with those of their peers depended on interactions between their individual motives for drinking and their group’s approval of this behavior. Chapter 2 presents novel findings that people spontaneously represent social information from multiple networks (e.g., popularity and leadership) at a neural level in social cognition (right TPJ, dmPFC) and valuation (vmPFC) regions. Importantly, individuals who display higher neural sensitivity to status differences are also more likely to align their drinking behavior with their group norms in daily life. Together, our results provide insight into the neural mechanisms through which social comparison processes shape conformity and suggest social cognition and valuation regions as important hubs orchestrating this process. While Chapter 1 and Chapter 2 focus on the influence of social ties on drinking, Chapter 3 discusses the protective role of close relations during difficult times. We provide evidence that close college friendships, even if afar, helped young adults cope with the stress of the COVID-19 pandemic. Follow-up between- and within-individual analyses reveal that this buffering effect could be explained by differences in the quality of online interactions (e.g., via phone, text messaging), instances of personal disclosure, and participation in enjoyable activities. All in all, this dissertation advances our understanding of why measures of social wellbeing are the best predictor of health trajectories in life, by highlighting the important role social ties play in shaping valuation of new information, guiding behavior to meet social goals, and protecting against stress by allowing people to engage in recreational activities.

• Social networks--Health aspects
• Drinking of alcoholic beverages--Social aspects
• COVID-19 (Disease)--Social aspects
• Health--Decision making
• Social status
• Cognition--Social aspects
• Mental health--Social aspects

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UNLV Theses, Dissertations, Professional Papers, and Capstones

Fear of recurrence as a mediator of illness perception and perceived stress in acute myocardial infarction survivors.

Sarah E. Zvonar Follow

Degree Type

Dissertation

Degree Name

Doctor of Philosophy (PhD)

First Committee Member

Reimund Serafica

Second Committee Member

Jennifer Kawi

Third Committee Member

Andrew Reyes

Fourth Committee Member

Stephen Benning

Number of Pages

Purpose: The primary objective of this study is to evaluate fear of recurrence as a mediator of illness perception and perceived stress. This research will determine how illness perceptions and fear of recurrence affect perceived stress in the acute myocardial infarction (AMI) population. Other aims will observe how demographics predict patients who may experience increased fear of recurrence and stress in the AMI population, how the variables of fear of recurrence change over time, and if fear of recurrence is still a significant mediator after controlling for depression and anxiety.Rational/ Conceptual Basis/ Background: Acute myocardial infarctions (AMIs) are often accompanied by psychological sequelae that may interfere with survivors' physical, cognitive, and emotional recovery. Post-myocardial infarction patients are taught to take proactive measures toward preventing future cardiac events, including decreasing overall stress. Theoretical models suggest that illness perception, fear of recurrence, and stress can all influence health outcomes. The relationships between these variables have little empirical data within the AMI population. Utilizing Leventhal's common-sense method of self-regulation, this study will identify how fear of recurrence (or progression) mediates illness perception and perceived stress. Methods: In this repeated measures, descriptive design, adult AMI (n=171) survivors at a Level 1 trauma center, identified from hospital admissions between November 2021 and December 2022, as well as AMI survivors from Facebook recruitment methods, will respond to self-reported surveys measuring illness perception (Brief Illness Perceptions Questionnaire [BIPQ] Appendix B), fear of recurrence (Fear of Progression Questionnaire [FoP-Q] Appendix C), and perceived stress (Perceived Stress Scale [PSS-10] Appendix D). Demographics will be collected from patient-reported variables of concurrent health conditions and modifiable risk factors such as diet, exercise, and smoking. This data was collected two times at baseline and six weeks follow-up to identify changes over time. Results: Fear of recurrence mediated the relationship between illness perceptions and perceived stress in acute myocardial infarction (AMI) survivors [F (2,168) =43.31, R²=0.34, p<0.001]. Predictors of fear of recurrence include alcohol intake. The paired t-tests comparing fear of recurrence were not significantly different at baseline (M=68.45, SD=21.72) and six weeks follow-up (M=69.43, SD=21.40); [t (159) =1.64, p=0.10]. After controlling depression and anxiety, fear of recurrence was still a significant mediator of illness perceptions and perceived stress [B = 0.09, SE = 0.05, t (166) = 2.03, p = 0.044]. Conclusion: These results suggest that fear of recurrence is a significant predictor of perceived stress in AMI survivors, meaning that practitioners should discuss the possibility of reoccurrence with survivors and assess fear of recurrence. The level of alcohol intake may indicate those who are negatively coping with the fear of recurrence after an AMI. Time since AMI is not a factor in fear of recurrence, but more research should be done to make this conclusion. Depression and anxiety are independent of the fear of recurrence and may not capture those who fear another AMI.

acute myocardial infarction; fear of progression; fear of recurrence; illness perception; leventhal; perceived stress

• Disciplines

Health and Medical Administration | Nursing | Psychology

File Format

Degree grantor.

University of Nevada, Las Vegas

Repository Citation

Zvonar, Sarah E., "Fear of Recurrence as a Mediator of Illness Perception and Perceived Stress in Acute Myocardial Infarction Survivors" (2023). UNLV Theses, Dissertations, Professional Papers, and Capstones . 4810. http://dx.doi.org/10.34917/36114835

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Reference Examples

More than 100 reference examples and their corresponding in-text citations are presented in the seventh edition Publication Manual . Examples of the most common works that writers cite are provided on this page; additional examples are available in the Publication Manual .

To find the reference example you need, first select a category (e.g., periodicals) and then choose the appropriate type of work (e.g., journal article ) and follow the relevant example.

When selecting a category, use the webpages and websites category only when a work does not fit better within another category. For example, a report from a government website would use the reports category, whereas a page on a government website that is not a report or other work would use the webpages and websites category.

Also note that print and electronic references are largely the same. For example, to cite both print books and ebooks, use the books and reference works category and then choose the appropriate type of work (i.e., book ) and follow the relevant example (e.g., whole authored book ).

Examples on these pages illustrate the details of reference formats. We make every attempt to show examples that are in keeping with APA Style’s guiding principles of inclusivity and bias-free language. These examples are presented out of context only to demonstrate formatting issues (e.g., which elements to italicize, where punctuation is needed, placement of parentheses). References, including these examples, are not inherently endorsements for the ideas or content of the works themselves. An author may cite a work to support a statement or an idea, to critique that work, or for many other reasons. For more examples, see our sample papers .

Reference examples are covered in the seventh edition APA Style manuals in the Publication Manual Chapter 10 and the Concise Guide Chapter 10

Related handouts

• Common Reference Examples Guide (PDF, 147KB)
• Reference Quick Guide (PDF, 225KB)

Textual Works

Textual works are covered in Sections 10.1–10.8 of the Publication Manual . The most common categories and examples are presented here. For the reviews of other works category, see Section 10.7.

• Journal Article References
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Data and Assessments

Data sets are covered in Section 10.9 of the Publication Manual . For the software and tests categories, see Sections 10.10 and 10.11.

• Data Set References
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Audiovisual Media

Audiovisual media are covered in Sections 10.12–10.14 of the Publication Manual . The most common examples are presented together here. In the manual, these examples and more are separated into categories for audiovisual, audio, and visual media.

• Artwork References
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• Film and Television References
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• Podcast References
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Online Media

Online media are covered in Sections 10.15 and 10.16 of the Publication Manual . Please note that blog posts are part of the periodicals category.

• Facebook References
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How To Write The Discussion Chapter

A Simple Explainer With Examples + Free Template

By: Jenna Crossley (PhD) | Reviewed By: Dr. Eunice Rautenbach | August 2021

If you’re reading this, chances are you’ve reached the discussion chapter of your thesis or dissertation and are looking for a bit of guidance. Well, you’ve come to the right place ! In this post, we’ll unpack and demystify the typical discussion chapter in straightforward, easy to understand language, with loads of examples .

Overview: The Discussion Chapter

• What  the discussion chapter is
• What to include in your discussion
• How to write up your discussion
• A few tips and tricks to help you along the way
• Free discussion template

What (exactly) is the discussion chapter?

The discussion chapter is where you interpret and explain your results within your thesis or dissertation. This contrasts with the results chapter, where you merely present and describe the analysis findings (whether qualitative or quantitative ). In the discussion chapter, you elaborate on and evaluate your research findings, and discuss the significance and implications of your results .

In this chapter, you’ll situate your research findings in terms of your research questions or hypotheses and tie them back to previous studies and literature (which you would have covered in your literature review chapter). You’ll also have a look at how relevant and/or significant your findings are to your field of research, and you’ll argue for the conclusions that you draw from your analysis. Simply put, the discussion chapter is there for you to interact with and explain your research findings in a thorough and coherent manner.

What should I include in the discussion chapter?

First things first: in some studies, the results and discussion chapter are combined into one chapter .  This depends on the type of study you conducted (i.e., the nature of the study and methodology adopted), as well as the standards set by the university.  So, check in with your university regarding their norms and expectations before getting started. In this post, we’ll treat the two chapters as separate, as this is most common.

Basically, your discussion chapter should analyse , explore the meaning and identify the importance of the data you presented in your results chapter. In the discussion chapter, you’ll give your results some form of meaning by evaluating and interpreting them. This will help answer your research questions, achieve your research aims and support your overall conclusion (s). Therefore, you discussion chapter should focus on findings that are directly connected to your research aims and questions. Don’t waste precious time and word count on findings that are not central to the purpose of your research project.

As this chapter is a reflection of your results chapter, it’s vital that you don’t report any new findings . In other words, you can’t present claims here if you didn’t present the relevant data in the results chapter first.  So, make sure that for every discussion point you raise in this chapter, you’ve covered the respective data analysis in the results chapter. If you haven’t, you’ll need to go back and adjust your results chapter accordingly.

If you’re struggling to get started, try writing down a bullet point list everything you found in your results chapter. From this, you can make a list of everything you need to cover in your discussion chapter. Also, make sure you revisit your research questions or hypotheses and incorporate the relevant discussion to address these.  This will also help you to see how you can structure your chapter logically.

Need a helping hand?

How to write the discussion chapter

Now that you’ve got a clear idea of what the discussion chapter is and what it needs to include, let’s look at how you can go about structuring this critically important chapter. Broadly speaking, there are six core components that need to be included, and these can be treated as steps in the chapter writing process.

Step 1: Restate your research problem and research questions

The first step in writing up your discussion chapter is to remind your reader of your research problem , as well as your research aim(s) and research questions . If you have hypotheses, you can also briefly mention these. This “reminder” is very important because, after reading dozens of pages, the reader may have forgotten the original point of your research or been swayed in another direction. It’s also likely that some readers skip straight to your discussion chapter from the introduction chapter , so make sure that your research aims and research questions are clear.

Step 2: Summarise your key findings

Next, you’ll want to summarise your key findings from your results chapter. This may look different for qualitative and quantitative research , where qualitative research may report on themes and relationships, whereas quantitative research may touch on correlations and causal relationships. Regardless of the methodology, in this section you need to highlight the overall key findings in relation to your research questions.

Typically, this section only requires one or two paragraphs , depending on how many research questions you have. Aim to be concise here, as you will unpack these findings in more detail later in the chapter. For now, a few lines that directly address your research questions are all that you need.

Some examples of the kind of language you’d use here include:

• The data suggest that…
• The data support/oppose the theory that…
• The analysis identifies…

These are purely examples. What you present here will be completely dependent on your original research questions, so make sure that you are led by them .

Step 3: Interpret your results

Once you’ve restated your research problem and research question(s) and briefly presented your key findings, you can unpack your findings by interpreting your results. Remember: only include what you reported in your results section – don’t introduce new information.

From a structural perspective, it can be a wise approach to follow a similar structure in this chapter as you did in your results chapter. This would help improve readability and make it easier for your reader to follow your arguments. For example, if you structured you results discussion by qualitative themes, it may make sense to do the same here.

Alternatively, you may structure this chapter by research questions, or based on an overarching theoretical framework that your study revolved around. Every study is different, so you’ll need to assess what structure works best for you.

When interpreting your results, you’ll want to assess how your findings compare to those of the existing research (from your literature review chapter). Even if your findings contrast with the existing research, you need to include these in your discussion. In fact, those contrasts are often the most interesting findings . In this case, you’d want to think about why you didn’t find what you were expecting in your data and what the significance of this contrast is.

Here are a few questions to help guide your discussion:

• How do your results relate with those of previous studies ?
• If you get results that differ from those of previous studies, why may this be the case?
• What do your results contribute to your field of research?
• What other explanations could there be for your findings?

When interpreting your findings, be careful not to draw conclusions that aren’t substantiated . Every claim you make needs to be backed up with evidence or findings from the data (and that data needs to be presented in the previous chapter – results). This can look different for different studies; qualitative data may require quotes as evidence, whereas quantitative data would use statistical methods and tests. Whatever the case, every claim you make needs to be strongly backed up.

Step 4: Acknowledge the limitations of your study

The fourth step in writing up your discussion chapter is to acknowledge the limitations of the study. These limitations can cover any part of your study , from the scope or theoretical basis to the analysis method(s) or sample. For example, you may find that you collected data from a very small sample with unique characteristics, which would mean that you are unable to generalise your results to the broader population.

For some students, discussing the limitations of their work can feel a little bit self-defeating . This is a misconception, as a core indicator of high-quality research is its ability to accurately identify its weaknesses. In other words, accurately stating the limitations of your work is a strength, not a weakness . All that said, be careful not to undermine your own research. Tell the reader what limitations exist and what improvements could be made, but also remind them of the value of your study despite its limitations.

Step 5: Make recommendations for implementation and future research

Now that you’ve unpacked your findings and acknowledge the limitations thereof, the next thing you’ll need to do is reflect on your study in terms of two factors:

• The practical application of your findings
• Suggestions for future research

The first thing to discuss is how your findings can be used in the real world – in other words, what contribution can they make to the field or industry? Where are these contributions applicable, how and why? For example, if your research is on communication in health settings, in what ways can your findings be applied to the context of a hospital or medical clinic? Make sure that you spell this out for your reader in practical terms, but also be realistic and make sure that any applications are feasible.

The next discussion point is the opportunity for future research . In other words, how can other studies build on what you’ve found and also improve the findings by overcoming some of the limitations in your study (which you discussed a little earlier). In doing this, you’ll want to investigate whether your results fit in with findings of previous research, and if not, why this may be the case. For example, are there any factors that you didn’t consider in your study? What future research can be done to remedy this? When you write up your suggestions, make sure that you don’t just say that more research is needed on the topic, also comment on how the research can build on your study.

Step 6: Provide a concluding summary

Finally, you’ve reached your final stretch. In this section, you’ll want to provide a brief recap of the key findings – in other words, the findings that directly address your research questions . Basically, your conclusion should tell the reader what your study has found, and what they need to take away from reading your report.

When writing up your concluding summary, bear in mind that some readers may skip straight to this section from the beginning of the chapter.  So, make sure that this section flows well from and has a strong connection to the opening section of the chapter.

Tips and tricks for an A-grade discussion chapter

Now that you know what the discussion chapter is , what to include and exclude , and how to structure it , here are some tips and suggestions to help you craft a quality discussion chapter.

• When you write up your discussion chapter, make sure that you keep it consistent with your introduction chapter , as some readers will skip from the introduction chapter directly to the discussion chapter. Your discussion should use the same tense as your introduction, and it should also make use of the same key terms.
• Don’t make assumptions about your readers. As a writer, you have hands-on experience with the data and so it can be easy to present it in an over-simplified manner. Make sure that you spell out your findings and interpretations for the intelligent layman.
• Have a look at other theses and dissertations from your institution, especially the discussion sections. This will help you to understand the standards and conventions of your university, and you’ll also get a good idea of how others have structured their discussion chapters. You can also check out our chapter template .
• Avoid using absolute terms such as “These results prove that…”, rather make use of terms such as “suggest” or “indicate”, where you could say, “These results suggest that…” or “These results indicate…”. It is highly unlikely that a dissertation or thesis will scientifically prove something (due to a variety of resource constraints), so be humble in your language.
• Use well-structured and consistently formatted headings to ensure that your reader can easily navigate between sections, and so that your chapter flows logically and coherently.

If you have any questions or thoughts regarding this post, feel free to leave a comment below. Also, if you’re looking for one-on-one help with your discussion chapter (or thesis in general), consider booking a free consultation with one of our highly experienced Grad Coaches to discuss how we can help you.

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This post was based on one of our popular Research Bootcamps . If you're working on a research project, you'll definitely want to check this out ...

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36 Comments

Thank you this is helpful!

This is very helpful to me… Thanks a lot for sharing this with us 😊

This has been very helpful indeed. Thank you.

This is actually really helpful, I just stumbled upon it. Very happy that I found it, thank you.

Me too! I was kinda lost on how to approach my discussion chapter. How helpful! Thanks a lot!

This is really good and explicit. Thanks

Thank you, this blog has been such a help.

Thank you. This is very helpful.

Dear sir/madame

Thanks a lot for this helpful blog. Really, it supported me in writing my discussion chapter while I was totally unaware about its structure and method of writing.

With regards

Syed Firoz Ahmad PhD, Research Scholar

I agree so much. This blog was god sent. It assisted me so much while I was totally clueless about the context and the know-how. Now I am fully aware of what I am to do and how I am to do it.

Thanks! This is helpful!

thanks alot for this informative website

Dear Sir/Madam,

Truly, your article was much benefited when i structured my discussion chapter.

Thank you very much!!!

This is helpful for me in writing my research discussion component. I have to copy this text on Microsoft word cause of my weakness that I cannot be able to read the text on screen a long time. So many thanks for this articles.

This was helpful

Thanks Jenna, well explained.

Thank you! This is super helpful.

Thanks very much. I have appreciated the six steps on writing the Discussion chapter which are (i) Restating the research problem and questions (ii) Summarising the key findings (iii) Interpreting the results linked to relating to previous results in positive and negative ways; explaining whay different or same and contribution to field of research and expalnation of findings (iv) Acknowledgeing limitations (v) Recommendations for implementation and future resaerch and finally (vi) Providing a conscluding summary

My two questions are: 1. On step 1 and 2 can it be the overall or you restate and sumamrise on each findings based on the reaerch question? 2. On 4 and 5 do you do the acknowlledgement , recommendations on each research finding or overall. This is not clear from your expalanattion.

Please respond.

This post is very useful. I’m wondering whether practical implications must be introduced in the Discussion section or in the Conclusion section?

Sigh, I never knew a 20 min video could have literally save my life like this. I found this at the right time!!!! Everything I need to know in one video thanks a mil ! OMGG and that 6 step!!!!!! was the cherry on top the cake!!!!!!!!!

Thanks alot.., I have gained much

This piece is very helpful on how to go about my discussion section. I can always recommend GradCoach research guides for colleagues.

Many thanks for this resource. It has been very helpful to me. I was finding it hard to even write the first sentence. Much appreciated.

Thanks so much. Very helpful to know what is included in the discussion section

this was a very helpful and useful information

This is very helpful. Very very helpful. Thanks for sharing this online!

it is very helpfull article, and i will recommend it to my fellow students. Thank you.

Superlative! More grease to your elbows.

Powerful, thank you for sharing.

Wow! Just wow! God bless the day I stumbled upon you guys’ YouTube videos! It’s been truly life changing and anxiety about my report that is due in less than a month has subsided significantly!

Simplified explanation. Well done.

The presentation is enlightening. Thank you very much.

Thanks for the support and guidance

This has been a great help to me and thank you do much

I second that “it is highly unlikely that a dissertation or thesis will scientifically prove something”; although, could you enlighten us on that comment and elaborate more please?

Sure, no problem.

Scientific proof is generally considered a very strong assertion that something is definitively and universally true. In most scientific disciplines, especially within the realms of natural and social sciences, absolute proof is very rare. Instead, researchers aim to provide evidence that supports or rejects hypotheses. This evidence increases or decreases the likelihood that a particular theory is correct, but it rarely proves something in the absolute sense.

Dissertations and theses, as substantial as they are, typically focus on exploring a specific question or problem within a larger field of study. They contribute to a broader conversation and body of knowledge. The aim is often to provide detailed insight, extend understanding, and suggest directions for further research rather than to offer definitive proof. These academic works are part of a cumulative process of knowledge building where each piece of research connects with others to gradually enhance our understanding of complex phenomena.

Furthermore, the rigorous nature of scientific inquiry involves continuous testing, validation, and potential refutation of ideas. What might be considered a “proof” at one point can later be challenged by new evidence or alternative interpretations. Therefore, the language of “proof” is cautiously used in academic circles to maintain scientific integrity and humility.

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June 5, 2024

Thesis Gold Receives Positive Metallurgical Tests Results for Lawyers-Ranch Project: Achieves Average Precious Metal Recovery of 95% for Gold and 92% for Silver

Vancouver, British Columbia–(Newsfile Corp. – June 5, 2024) – Thesis Gold Inc. (TSXV: TAU) (WKN: A3EP87) (OTCQX: THSGF) (“ Thesis ” or the “ Company “) is pleased to announce the successful completion of preliminary metallurgical testing at the Company’s 100% owned Lawyers-Ranch Project. This testing aims to assess the economics of an expanded project that integrates high-grade feed from Ranch and higher-grade underground material to a processing site at Lawyers. The program was designed based on the updated Mineral Resource Estimate from May 1, 2024 ( link to news release ). The Project is road-accessible and forms a contiguous, 495 km 2 land package in the prolific Toodoggone Mining District in northern British Columbia.

The testing, completed by SGS Canada, focused on evaluation of the project’s metallurgical response to a variety of flowsheets investigating gravity, flotation, and cyanidation methods. The comprehensive laboratory study concluded with the full treatment circuit evaluation including locked cycle flotation by testing of three separate master composites. These composites were from blended feed samples of known resources from both the Lawyers and Ranch properties that had variations in gold, silver, and sulphur head grade. The laboratory full circuit evaluation demonstrated a recovery range of 93% to 96% for gold and 86% to 96% for silver. This included producing a primary precious metal flotation concentrate with gold grades exceeding 160 g/t, indicating a marketable precious metal concentrate with favorable payables. The metallurgical results will be used as part of an updated preliminary economic assessment of the project, scheduled for Q3-2024.

Metallurgical Testing Highlights :

• Process Flowsheet Development : with gravity pretreatment, flotation, and leaching of secondary concentrate and float tails. The overall recovery range was 93% to 96% for gold and 86% to 96% for silver, demonstrating excellent extraction potential.
• Gravity Pretreatment: Recovery ranged from 20 to 38% for gold, and 2 to 10% of silver at grades exceeding 360 g/t Au and 1190 g/t Ag, which is suitable for onsite doré production.
• Primary Flotation Concentrate: Recovery ranging from 40% to 65% of gold producing a concentrate grade exceeding 160 g/t Au and 55% to 78% recovery for silver with a concentrate grade of over 5,000 g/t Ag.
• Leaching: of a secondary float concentrate and the float tailing, scavenged an additional 8-20% of gold and 12-24% of silver.

Dr. Ewan Webster, President and CEO, commented “The excellent metallurgical results from the combined Lawyers-Ranch project highlight not only the high recoveries of 95% for gold and 92% for silver but also the marketable concentrate grades. These findings, based on blended composites from potential mining areas, provide a strong foundation for the upcoming preliminary economic assessment. Given the strength of these results, our continued efforts will be directed towards optimizing capital costs, operating costs, and maximizing payables, rather than addressing fundamental process challenges.”

Flowsheet Development

The metallurgical testing initially involved variations to gravity separation, flotation, and cyanidation procedures for process optimization. The study concluded with a locked cycle flotation test on each of three master composites, with separate cyanidation of the scavenger concentrate. This was then combined with the leaching of the float tailing. The data compared well to open cycle float tests.

Each of the three master composites were to represent various mineral zones from both properties. This includes potential underground and open pit material from Lawyers and newly identified mineral zones at Ranch (see Table 1). Each zone composite was typically formed from 2 to 7 drill hole intervals averaging approximately 10 metres, with varying precious metal and sulphur (S) grades. These master composites therefore provide good confidence in the flowsheet response to the varying mineralogy of the project.

Table 1: Master Composite Blend

The flotation flowsheet for the locked cycle tests following gravity pretreatment are illustrated in Figure 1.

Figure 1: Flotation Flowsheet

Following laboratory test work optimization, the metallurgical response was confirmed by using locked cycle testing (see Figure 1 above) on three master composites representing blends from both Ranch and Lawyers. The test conditions consisted of grinding to an 80% particle passing size (P80) of 125 microns and subjecting the ground product to gravity treatment by centrifugal concentration. The centrifugal concentrate was cleaned by panning. Gravity tailing was sent to a differential flotation circuit with the primary (rougher) concentrate cleaned with a selective collector in three stages, while depressing pyrite with elevated slurry pH using lime. This generated a cleaned primary flotation concentrate accounting for approximately 2 wt.% of the feed mass having a high precious metal grades suitable for sale (see Table 2 below). A lower grade secondary scavenger flotation concentrate representing less than 3 wt.% of the mill throughput was pulled using a strong collector (potassium amyl xanthate). This material was then sent for aggressive leaching for 36 hours using high cyanide concentration. This residue was then combined with the flotation tailing for a final stage leach maintaining 1 g/L NaCN for 24 hours.

Overall, the combined testing showed that gravity pretreatment yielded a gold recoveries ranging from 17% to 38%. The silver recoveries were typically lower, ranging from 2% to 10%. When considering the combined processes of gravity and primary (rougher) flotation, the gold recoveries were notably high, with 86% for Composite M1(HG), 87% for Composite M2 (MG), and 77% for Composite M3 (LG). The combined silver recoveries were also substantial, achieving 81%, 85%, and 65% for the respective composites. The gravity and flotation concentrates demonstrated high grades and efficient recovery rates, for some zones. Stability in the locked cycle tests was generally good, with consistent mass, gold, and silver recoveries observed in the final three cycles. However, adjustments may be necessary in future test work, particularly to manage the re-floating of pyrite in high pyrite composites.

Cyanidation of the secondary flotation product further enhanced recovery. The circuit for leaching of the concentrate is small due to low mass pull, allowing for aggressive procedures in the first stage. The second stage leach is performed by recombing with float tailing, providing the overall leach response. For Composite M2 (MG), the mid grade blend cyanidation recovered an additional 9% of gold and 12% of silver. For Composite M1 (HG), the higher-grade blend recovered 8% of gold and 14% of silver, while for Composite M3 (LG), the lowest grade blend, an additional 19% of gold and 21% of silver were recovered from the overall leach circuit.

The combined metallurgical performance achieved excellent total recoveries of gold and silver. Composite M2 (MG) showed a total gold recovery of 96.3% and silver recovery of 96.4%. Composite M1 (HG) achieved 93.9% gold recovery and 94.4% silver recovery, while Composite M3 (LG) demonstrated 96.5% gold recovery and 86.3% silver recovery. These results underscore the effectiveness of the combined gravity, flotation, and cyanidation processes in maximizing precious metal recoveries. Summary of the results are available in Table 2.

Table 2: Master Composite Zone Blends and Head Assay

The preliminary findings indicate no issues with the flowsheet in terms of mass balance or recovery, affirming the project’s robustness as it progresses.

Quality Assurance and Control

Original mineral samples that were selected for metallurgical evaluation were analyzed at ALS Global Laboratories (Geochemistry Division) in Vancouver, Canada (an ISO/IEC 17025:2017 accredited facility). The geological sampling program was undertaken by Company personnel under the direction of Rob L’Heureux, P.Geol. Metallurgical testing was primarily performed by SGS Canada Inc. at their laboratory located in Burnaby BC. SGS is globally recognized in the mining industry and accredited with International Standards Organization (ISO) 9001 for quality assurance, and ISO/IEC 17025 for general requirements of laboratory competence in testing and calibration. A secure chain of custody is maintained in transporting and storing of all samples.

The technical content of this news release has been reviewed and approved by Frank Wright, P.Eng., independent metallurgical consultant and qualified person as defined by National Instrument 43-101.

On behalf of the Board of Directors Thesis Gold Inc.

“Ewan Webster”

Ewan Webster Ph.D., P.Geo. President, CEO, and Director About Thesis Gold Inc.

Thesis Gold is unlocking the combined potential of the Lawyers-Ranch Gold-Silver Project in the Toodoggone mining district of north central British Columbia, Canada. A 2022 Preliminary Economic Assessment for the Lawyers project alone projected an open-pit mining operation yielding an average of 163,000 gold equivalent ounces annually over a 12-year span 1 . By integrating the Ranch Project, the Company aims to enhance the economics and bolster the overall project’s potential. Central to this ambition was the expansive 2023 drill program, which continues to define a high-grade out-of-pit Mineral Resource at Lawyers and augment the near-surface high-grade deposits at Ranch. The project now boasts a combined Measured & Indicated Mineral Resource of 4.0 Moz and an Inferred Mineral Resource of 727 koz, at respective grades of 1.51 and 1.82 g/t AuEq. The Company roadmap includes, new metallurgical work (now delivered), a robust 2024 exploration and drill program and a combined updated Preliminary Economic Assessment slated for Q3 2024. Through these strategic moves, Thesis Gold intends to elevate the Ranch-Lawyers Project to the forefront of global precious metals ventures.

1 Preliminary Economic Assessment: Lawyers Gold & Silver Project (2022). JDS Energy & Mining.

For further information or investor relations inquiries, please contact:

Dave Burwell Vice President Corporate Development Email: [email protected] Tel: 403-410-7907 Toll Free: 1-888-221-0915

Neither the TSX Venture Exchange nor its Regulation Services Provider (as that term is defined in the policies of the TSX Venture Exchange) accepts responsibility for the adequacy or accuracy of this press release.

Cautionary Statement Regarding Forward-Looking Information

This press release contains “forward-looking information” within the meaning of applicable Canadian securities legislation. Forward-looking information includes, without limitation, statements regarding the use of proceeds from the Company’s recently completed financings and the future plans or prospects of the Company. Generally, forward-looking information can be identified by the use of forward-looking terminology such as “plans”, “expects” or “does not expect”, “is expected”, “budget”, “scheduled”, “estimates”, “forecasts”, “intends”, “anticipates” or “does not anticipate”, or “believes”, or variations of such words and phrases or state that certain actions, events or results “may”, “could”, “would”, “might” or “will be taken”, “occur” or “be achieved”. Forward-looking statements are necessarily based upon a number of assumptions that, while considered reasonable by management, are inherently subject to business, market, and economic risks, uncertainties, and contingencies that may cause actual results, performance, or achievements to be materially different from those expressed or implied by forward-looking statements. Although the Company has attempted to identify important factors that could cause actual results to differ materially from those contained in forward-looking information, there may be other factors that cause results not to be as anticipated, estimated, or intended. There can be no assurance that such information will prove to be accurate, as actual results and future events could differ materially from those anticipated in such statements. Accordingly, readers should not place undue reliance on forward-looking information. Other factors which could materially affect such forward-looking information are described in the risk factors in the Company’s most recent annual management’s discussion and analysis, which is available on the Company’s profile on SEDAR at www.sedarplus.com . The Company does not undertake to update any forward-looking information, except in accordance with applicable securities laws.

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• How to Write a Literature Review | Guide, Examples, & Templates

How to Write a Literature Review | Guide, Examples, & Templates

Published on January 2, 2023 by Shona McCombes . Revised on September 11, 2023.

What is a literature review? A literature review is a survey of scholarly sources on a specific topic. It provides an overview of current knowledge, allowing you to identify relevant theories, methods, and gaps in the existing research that you can later apply to your paper, thesis, or dissertation topic .

There are five key steps to writing a literature review:

• Search for relevant literature
• Evaluate sources
• Identify themes, debates, and gaps
• Outline the structure
• Write your literature review

A good literature review doesn’t just summarize sources—it analyzes, synthesizes , and critically evaluates to give a clear picture of the state of knowledge on the subject.

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Table of contents

What is the purpose of a literature review, examples of literature reviews, step 1 – search for relevant literature, step 2 – evaluate and select sources, step 3 – identify themes, debates, and gaps, step 4 – outline your literature review’s structure, step 5 – write your literature review, free lecture slides, other interesting articles, frequently asked questions, introduction.

• Quick Run-through
• Step 1 & 2

When you write a thesis , dissertation , or research paper , you will likely have to conduct a literature review to situate your research within existing knowledge. The literature review gives you a chance to:

• Demonstrate your familiarity with the topic and its scholarly context
• Develop a theoretical framework and methodology for your research
• Position your work in relation to other researchers and theorists
• Show how your research addresses a gap or contributes to a debate
• Evaluate the current state of research and demonstrate your knowledge of the scholarly debates around your topic.

Writing literature reviews is a particularly important skill if you want to apply for graduate school or pursue a career in research. We’ve written a step-by-step guide that you can follow below.

Prevent plagiarism. Run a free check.

Writing literature reviews can be quite challenging! A good starting point could be to look at some examples, depending on what kind of literature review you’d like to write.

• Example literature review #1: “Why Do People Migrate? A Review of the Theoretical Literature” ( Theoretical literature review about the development of economic migration theory from the 1950s to today.)
• Example literature review #2: “Literature review as a research methodology: An overview and guidelines” ( Methodological literature review about interdisciplinary knowledge acquisition and production.)
• Example literature review #3: “The Use of Technology in English Language Learning: A Literature Review” ( Thematic literature review about the effects of technology on language acquisition.)
• Example literature review #4: “Learners’ Listening Comprehension Difficulties in English Language Learning: A Literature Review” ( Chronological literature review about how the concept of listening skills has changed over time.)

You can also check out our templates with literature review examples and sample outlines at the links below.

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Before you begin searching for literature, you need a clearly defined topic .

If you are writing the literature review section of a dissertation or research paper, you will search for literature related to your research problem and questions .

Make a list of keywords

Start by creating a list of keywords related to your research question. Include each of the key concepts or variables you’re interested in, and list any synonyms and related terms. You can add to this list as you discover new keywords in the process of your literature search.

• Social media, Facebook, Instagram, Twitter, Snapchat, TikTok
• Body image, self-perception, self-esteem, mental health
• Generation Z, teenagers, adolescents, youth

Search for relevant sources

Use your keywords to begin searching for sources. Some useful databases to search for journals and articles include:

• Your university’s library catalogue
• Google Scholar
• Project Muse (humanities and social sciences)
• Medline (life sciences and biomedicine)
• EconLit (economics)
• Inspec (physics, engineering and computer science)

You can also use boolean operators to help narrow down your search.

Make sure to read the abstract to find out whether an article is relevant to your question. When you find a useful book or article, you can check the bibliography to find other relevant sources.

You likely won’t be able to read absolutely everything that has been written on your topic, so it will be necessary to evaluate which sources are most relevant to your research question.

For each publication, ask yourself:

• What question or problem is the author addressing?
• What are the key concepts and how are they defined?
• What are the key theories, models, and methods?
• Does the research use established frameworks or take an innovative approach?
• What are the results and conclusions of the study?
• How does the publication relate to other literature in the field? Does it confirm, add to, or challenge established knowledge?
• What are the strengths and weaknesses of the research?

Make sure the sources you use are credible , and make sure you read any landmark studies and major theories in your field of research.

You can use our template to summarize and evaluate sources you’re thinking about using. Click on either button below to download.

Take notes and cite your sources

As you read, you should also begin the writing process. Take notes that you can later incorporate into the text of your literature review.

It is important to keep track of your sources with citations to avoid plagiarism . It can be helpful to make an annotated bibliography , where you compile full citation information and write a paragraph of summary and analysis for each source. This helps you remember what you read and saves time later in the process.

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To begin organizing your literature review’s argument and structure, be sure you understand the connections and relationships between the sources you’ve read. Based on your reading and notes, you can look for:

• Trends and patterns (in theory, method or results): do certain approaches become more or less popular over time?
• Themes: what questions or concepts recur across the literature?
• Debates, conflicts and contradictions: where do sources disagree?
• Pivotal publications: are there any influential theories or studies that changed the direction of the field?
• Gaps: what is missing from the literature? Are there weaknesses that need to be addressed?

This step will help you work out the structure of your literature review and (if applicable) show how your own research will contribute to existing knowledge.

• Most research has focused on young women.
• There is an increasing interest in the visual aspects of social media.
• But there is still a lack of robust research on highly visual platforms like Instagram and Snapchat—this is a gap that you could address in your own research.

There are various approaches to organizing the body of a literature review. Depending on the length of your literature review, you can combine several of these strategies (for example, your overall structure might be thematic, but each theme is discussed chronologically).

Chronological

The simplest approach is to trace the development of the topic over time. However, if you choose this strategy, be careful to avoid simply listing and summarizing sources in order.

Try to analyze patterns, turning points and key debates that have shaped the direction of the field. Give your interpretation of how and why certain developments occurred.

If you have found some recurring central themes, you can organize your literature review into subsections that address different aspects of the topic.

For example, if you are reviewing literature about inequalities in migrant health outcomes, key themes might include healthcare policy, language barriers, cultural attitudes, legal status, and economic access.

Methodological

If you draw your sources from different disciplines or fields that use a variety of research methods , you might want to compare the results and conclusions that emerge from different approaches. For example:

• Look at what results have emerged in qualitative versus quantitative research
• Discuss how the topic has been approached by empirical versus theoretical scholarship
• Divide the literature into sociological, historical, and cultural sources

Theoretical

A literature review is often the foundation for a theoretical framework . You can use it to discuss various theories, models, and definitions of key concepts.

You might argue for the relevance of a specific theoretical approach, or combine various theoretical concepts to create a framework for your research.

Like any other academic text , your literature review should have an introduction , a main body, and a conclusion . What you include in each depends on the objective of your literature review.

The introduction should clearly establish the focus and purpose of the literature review.

Depending on the length of your literature review, you might want to divide the body into subsections. You can use a subheading for each theme, time period, or methodological approach.

As you write, you can follow these tips:

• Summarize and synthesize: give an overview of the main points of each source and combine them into a coherent whole
• Analyze and interpret: don’t just paraphrase other researchers — add your own interpretations where possible, discussing the significance of findings in relation to the literature as a whole
• Critically evaluate: mention the strengths and weaknesses of your sources
• Write in well-structured paragraphs: use transition words and topic sentences to draw connections, comparisons and contrasts

In the conclusion, you should summarize the key findings you have taken from the literature and emphasize their significance.

When you’ve finished writing and revising your literature review, don’t forget to proofread thoroughly before submitting. Not a language expert? Check out Scribbr’s professional proofreading services !

This article has been adapted into lecture slides that you can use to teach your students about writing a literature review.

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If you want to know more about the research process , methodology , research bias , or statistics , make sure to check out some of our other articles with explanations and examples.

• Sampling methods
• Simple random sampling
• Stratified sampling
• Cluster sampling
• Likert scales
• Reproducibility

 Statistics

• Null hypothesis
• Statistical power
• Probability distribution
• Effect size
• Poisson distribution

Research bias

• Optimism bias
• Cognitive bias
• Implicit bias
• Hawthorne effect
• Anchoring bias
• Explicit bias

A literature review is a survey of scholarly sources (such as books, journal articles, and theses) related to a specific topic or research question .

It is often written as part of a thesis, dissertation , or research paper , in order to situate your work in relation to existing knowledge.

There are several reasons to conduct a literature review at the beginning of a research project:

• To familiarize yourself with the current state of knowledge on your topic
• To ensure that you’re not just repeating what others have already done
• To identify gaps in knowledge and unresolved problems that your research can address
• To develop your theoretical framework and methodology
• To provide an overview of the key findings and debates on the topic

Writing the literature review shows your reader how your work relates to existing research and what new insights it will contribute.

The literature review usually comes near the beginning of your thesis or dissertation . After the introduction , it grounds your research in a scholarly field and leads directly to your theoretical framework or methodology .

A literature review is a survey of credible sources on a topic, often used in dissertations , theses, and research papers . Literature reviews give an overview of knowledge on a subject, helping you identify relevant theories and methods, as well as gaps in existing research. Literature reviews are set up similarly to other  academic texts , with an introduction , a main body, and a conclusion .

An  annotated bibliography is a list of  source references that has a short description (called an annotation ) for each of the sources. It is often assigned as part of the research process for a  paper .  

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McCombes, S. (2023, September 11). How to Write a Literature Review | Guide, Examples, & Templates. Scribbr. Retrieved June 7, 2024, from https://www.scribbr.com/dissertation/literature-review/

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