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Research Results Section – Writing Guide and Examples

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Research Results

Research results refer to the findings and conclusions derived from a systematic investigation or study conducted to answer a specific question or hypothesis. These results are typically presented in a written report or paper and can include various forms of data such as numerical data, qualitative data, statistics, charts, graphs, and visual aids.

Results Section in Research

The results section of the research paper presents the findings of the study. It is the part of the paper where the researcher reports the data collected during the study and analyzes it to draw conclusions.

In the results section, the researcher should describe the data that was collected, the statistical analysis performed, and the findings of the study. It is important to be objective and not interpret the data in this section. Instead, the researcher should report the data as accurately and objectively as possible.

Structure of Research Results Section

The structure of the research results section can vary depending on the type of research conducted, but in general, it should contain the following components:

• Introduction: The introduction should provide an overview of the study, its aims, and its research questions. It should also briefly explain the methodology used to conduct the study.
• Data presentation : This section presents the data collected during the study. It may include tables, graphs, or other visual aids to help readers better understand the data. The data presented should be organized in a logical and coherent way, with headings and subheadings used to help guide the reader.
• Data analysis: In this section, the data presented in the previous section are analyzed and interpreted. The statistical tests used to analyze the data should be clearly explained, and the results of the tests should be presented in a way that is easy to understand.
• Discussion of results : This section should provide an interpretation of the results of the study, including a discussion of any unexpected findings. The discussion should also address the study’s research questions and explain how the results contribute to the field of study.
• Limitations: This section should acknowledge any limitations of the study, such as sample size, data collection methods, or other factors that may have influenced the results.
• Conclusions: The conclusions should summarize the main findings of the study and provide a final interpretation of the results. The conclusions should also address the study’s research questions and explain how the results contribute to the field of study.
• Recommendations : This section may provide recommendations for future research based on the study’s findings. It may also suggest practical applications for the study’s results in real-world settings.

Outline of Research Results Section

The following is an outline of the key components typically included in the Results section:

I. Introduction

• A brief overview of the research objectives and hypotheses
• A statement of the research question

II. Descriptive statistics

• Summary statistics (e.g., mean, standard deviation) for each variable analyzed
• Frequencies and percentages for categorical variables

III. Inferential statistics

• Results of statistical analyses, including tests of hypotheses
• Tables or figures to display statistical results

IV. Effect sizes and confidence intervals

• Effect sizes (e.g., Cohen’s d, odds ratio) to quantify the strength of the relationship between variables
• Confidence intervals to estimate the range of plausible values for the effect size

V. Subgroup analyses

• Results of analyses that examined differences between subgroups (e.g., by gender, age, treatment group)

VI. Limitations and assumptions

• Discussion of any limitations of the study and potential sources of bias
• Assumptions made in the statistical analyses

VII. Conclusions

• A summary of the key findings and their implications
• A statement of whether the hypotheses were supported or not
• Suggestions for future research

Example of Research Results Section

An Example of a Research Results Section could be:

• This study sought to examine the relationship between sleep quality and academic performance in college students.
• Hypothesis : College students who report better sleep quality will have higher GPAs than those who report poor sleep quality.
• Methodology : Participants completed a survey about their sleep habits and academic performance.

II. Participants

• Participants were college students (N=200) from a mid-sized public university in the United States.
• The sample was evenly split by gender (50% female, 50% male) and predominantly white (85%).
• Participants were recruited through flyers and online advertisements.

III. Results

• Participants who reported better sleep quality had significantly higher GPAs (M=3.5, SD=0.5) than those who reported poor sleep quality (M=2.9, SD=0.6).
• See Table 1 for a summary of the results.
• Participants who reported consistent sleep schedules had higher GPAs than those with irregular sleep schedules.

IV. Discussion

• The results support the hypothesis that better sleep quality is associated with higher academic performance in college students.
• These findings have implications for college students, as prioritizing sleep could lead to better academic outcomes.
• Limitations of the study include self-reported data and the lack of control for other variables that could impact academic performance.

V. Conclusion

• College students who prioritize sleep may see a positive impact on their academic performance.
• These findings highlight the importance of sleep in academic success.
• Future research could explore interventions to improve sleep quality in college students.

Example of Research Results in Research Paper :

Our study aimed to compare the performance of three different machine learning algorithms (Random Forest, Support Vector Machine, and Neural Network) in predicting customer churn in a telecommunications company. We collected a dataset of 10,000 customer records, with 20 predictor variables and a binary churn outcome variable.

Our analysis revealed that all three algorithms performed well in predicting customer churn, with an overall accuracy of 85%. However, the Random Forest algorithm showed the highest accuracy (88%), followed by the Support Vector Machine (86%) and the Neural Network (84%).

Furthermore, we found that the most important predictor variables for customer churn were monthly charges, contract type, and tenure. Random Forest identified monthly charges as the most important variable, while Support Vector Machine and Neural Network identified contract type as the most important.

Overall, our results suggest that machine learning algorithms can be effective in predicting customer churn in a telecommunications company, and that Random Forest is the most accurate algorithm for this task.

Example 3 :

Title : The Impact of Social Media on Body Image and Self-Esteem

Abstract : This study aimed to investigate the relationship between social media use, body image, and self-esteem among young adults. A total of 200 participants were recruited from a university and completed self-report measures of social media use, body image satisfaction, and self-esteem.

Results: The results showed that social media use was significantly associated with body image dissatisfaction and lower self-esteem. Specifically, participants who reported spending more time on social media platforms had lower levels of body image satisfaction and self-esteem compared to those who reported less social media use. Moreover, the study found that comparing oneself to others on social media was a significant predictor of body image dissatisfaction and lower self-esteem.

Conclusion : These results suggest that social media use can have negative effects on body image satisfaction and self-esteem among young adults. It is important for individuals to be mindful of their social media use and to recognize the potential negative impact it can have on their mental health. Furthermore, interventions aimed at promoting positive body image and self-esteem should take into account the role of social media in shaping these attitudes and behaviors.

Importance of Research Results

Research results are important for several reasons, including:

• Advancing knowledge: Research results can contribute to the advancement of knowledge in a particular field, whether it be in science, technology, medicine, social sciences, or humanities.
• Developing theories: Research results can help to develop or modify existing theories and create new ones.
• Improving practices: Research results can inform and improve practices in various fields, such as education, healthcare, business, and public policy.
• Identifying problems and solutions: Research results can identify problems and provide solutions to complex issues in society, including issues related to health, environment, social justice, and economics.
• Validating claims : Research results can validate or refute claims made by individuals or groups in society, such as politicians, corporations, or activists.
• Providing evidence: Research results can provide evidence to support decision-making, policy-making, and resource allocation in various fields.

How to Write Results in A Research Paper

Here are some general guidelines on how to write results in a research paper:

• Organize the results section: Start by organizing the results section in a logical and coherent manner. Divide the section into subsections if necessary, based on the research questions or hypotheses.
• Present the findings: Present the findings in a clear and concise manner. Use tables, graphs, and figures to illustrate the data and make the presentation more engaging.
• Describe the data: Describe the data in detail, including the sample size, response rate, and any missing data. Provide relevant descriptive statistics such as means, standard deviations, and ranges.
• Interpret the findings: Interpret the findings in light of the research questions or hypotheses. Discuss the implications of the findings and the extent to which they support or contradict existing theories or previous research.
• Discuss the limitations : Discuss the limitations of the study, including any potential sources of bias or confounding factors that may have affected the results.
• Compare the results : Compare the results with those of previous studies or theoretical predictions. Discuss any similarities, differences, or inconsistencies.
• Avoid redundancy: Avoid repeating information that has already been presented in the introduction or methods sections. Instead, focus on presenting new and relevant information.
• Be objective: Be objective in presenting the results, avoiding any personal biases or interpretations.

When to Write Research Results

Here are situations When to Write Research Results”

• After conducting research on the chosen topic and obtaining relevant data, organize the findings in a structured format that accurately represents the information gathered.
• Once the data has been analyzed and interpreted, and conclusions have been drawn, begin the writing process.
• Before starting to write, ensure that the research results adhere to the guidelines and requirements of the intended audience, such as a scientific journal or academic conference.
• Begin by writing an abstract that briefly summarizes the research question, methodology, findings, and conclusions.
• Follow the abstract with an introduction that provides context for the research, explains its significance, and outlines the research question and objectives.
• The next section should be a literature review that provides an overview of existing research on the topic and highlights the gaps in knowledge that the current research seeks to address.
• The methodology section should provide a detailed explanation of the research design, including the sample size, data collection methods, and analytical techniques used.
• Present the research results in a clear and concise manner, using graphs, tables, and figures to illustrate the findings.
• Discuss the implications of the research results, including how they contribute to the existing body of knowledge on the topic and what further research is needed.
• Conclude the paper by summarizing the main findings, reiterating the significance of the research, and offering suggestions for future research.

Purpose of Research Results

The purposes of Research Results are as follows:

• Informing policy and practice: Research results can provide evidence-based information to inform policy decisions, such as in the fields of healthcare, education, and environmental regulation. They can also inform best practices in fields such as business, engineering, and social work.
• Addressing societal problems : Research results can be used to help address societal problems, such as reducing poverty, improving public health, and promoting social justice.
• Generating economic benefits : Research results can lead to the development of new products, services, and technologies that can create economic value and improve quality of life.
• Supporting academic and professional development : Research results can be used to support academic and professional development by providing opportunities for students, researchers, and practitioners to learn about new findings and methodologies in their field.
• Enhancing public understanding: Research results can help to educate the public about important issues and promote scientific literacy, leading to more informed decision-making and better public policy.
• Evaluating interventions: Research results can be used to evaluate the effectiveness of interventions, such as treatments, educational programs, and social policies. This can help to identify areas where improvements are needed and guide future interventions.
• Contributing to scientific progress: Research results can contribute to the advancement of science by providing new insights and discoveries that can lead to new theories, methods, and techniques.
• Informing decision-making : Research results can provide decision-makers with the information they need to make informed decisions. This can include decision-making at the individual, organizational, or governmental levels.
• Fostering collaboration : Research results can facilitate collaboration between researchers and practitioners, leading to new partnerships, interdisciplinary approaches, and innovative solutions to complex problems.

Advantages of Research Results

Some Advantages of Research Results are as follows:

• Improved decision-making: Research results can help inform decision-making in various fields, including medicine, business, and government. For example, research on the effectiveness of different treatments for a particular disease can help doctors make informed decisions about the best course of treatment for their patients.
• Innovation : Research results can lead to the development of new technologies, products, and services. For example, research on renewable energy sources can lead to the development of new and more efficient ways to harness renewable energy.
• Economic benefits: Research results can stimulate economic growth by providing new opportunities for businesses and entrepreneurs. For example, research on new materials or manufacturing techniques can lead to the development of new products and processes that can create new jobs and boost economic activity.
• Improved quality of life: Research results can contribute to improving the quality of life for individuals and society as a whole. For example, research on the causes of a particular disease can lead to the development of new treatments and cures, improving the health and well-being of millions of people.

About the author

Muhammad Hassan

Researcher, Academic Writer, Web developer

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Qualitative Data Analysis

23 Presenting the Results of Qualitative Analysis

Mikaila Mariel Lemonik Arthur

Qualitative research is not finished just because you have determined the main findings or conclusions of your study. Indeed, disseminating the results is an essential part of the research process. By sharing your results with others, whether in written form as scholarly paper or an applied report or in some alternative format like an oral presentation, an infographic, or a video, you ensure that your findings become part of the ongoing conversation of scholarship in your field, forming part of the foundation for future researchers. This chapter provides an introduction to writing about qualitative research findings. It will outline how writing continues to contribute to the analysis process, what concerns researchers should keep in mind as they draft their presentations of findings, and how best to organize qualitative research writing

As you move through the research process, it is essential to keep yourself organized. Organizing your data, memos, and notes aids both the analytical and the writing processes. Whether you use electronic or physical, real-world filing and organizational systems, these systems help make sense of the mountains of data you have and assure you focus your attention on the themes and ideas you have determined are important (Warren and Karner 2015). Be sure that you have kept detailed notes on all of the decisions you have made and procedures you have followed in carrying out research design, data collection, and analysis, as these will guide your ultimate write-up.

First and foremost, researchers should keep in mind that writing is in fact a form of thinking. Writing is an excellent way to discover ideas and arguments and to further develop an analysis. As you write, more ideas will occur to you, things that were previously confusing will start to make sense, and arguments will take a clear shape rather than being amorphous and poorly-organized. However, writing-as-thinking cannot be the final version that you share with others. Good-quality writing does not display the workings of your thought process. It is reorganized and revised (more on that later) to present the data and arguments important in a particular piece. And revision is totally normal! No one expects the first draft of a piece of writing to be ready for prime time. So write rough drafts and memos and notes to yourself and use them to think, and then revise them until the piece is the way you want it to be for sharing.

Bergin (2018) lays out a set of key concerns for appropriate writing about research. First, present your results accurately, without exaggerating or misrepresenting. It is very easy to overstate your findings by accident if you are enthusiastic about what you have found, so it is important to take care and use appropriate cautions about the limitations of the research. You also need to work to ensure that you communicate your findings in a way people can understand, using clear and appropriate language that is adjusted to the level of those you are communicating with. And you must be clear and transparent about the methodological strategies employed in the research. Remember, the goal is, as much as possible, to describe your research in a way that would permit others to replicate the study. There are a variety of other concerns and decision points that qualitative researchers must keep in mind, including the extent to which to include quantification in their presentation of results, ethics, considerations of audience and voice, and how to bring the richness of qualitative data to life.

Quantification, as you have learned, refers to the process of turning data into numbers. It can indeed be very useful to count and tabulate quantitative data drawn from qualitative research. For instance, if you were doing a study of dual-earner households and wanted to know how many had an equal division of household labor and how many did not, you might want to count those numbers up and include them as part of the final write-up. However, researchers need to take care when they are writing about quantified qualitative data. Qualitative data is not as generalizable as quantitative data, so quantification can be very misleading. Thus, qualitative researchers should strive to use raw numbers instead of the percentages that are more appropriate for quantitative research. Writing, for instance, “15 of the 20 people I interviewed prefer pancakes to waffles” is a simple description of the data; writing “75% of people prefer pancakes” suggests a generalizable claim that is not likely supported by the data. Note that mixing numbers with qualitative data is really a type of mixed-methods approach. Mixed-methods approaches are good, but sometimes they seduce researchers into focusing on the persuasive power of numbers and tables rather than capitalizing on the inherent richness of their qualitative data.

A variety of issues of scholarly ethics and research integrity are raised by the writing process. Some of these are unique to qualitative research, while others are more universal concerns for all academic and professional writing. For example, it is essential to avoid plagiarism and misuse of sources. All quotations that appear in a text must be properly cited, whether with in-text and bibliographic citations to the source or with an attribution to the research participant (or the participant’s pseudonym or description in order to protect confidentiality) who said those words. Where writers will paraphrase a text or a participant’s words, they need to make sure that the paraphrase they develop accurately reflects the meaning of the original words. Thus, some scholars suggest that participants should have the opportunity to read (or to have read to them, if they cannot read the text themselves) all sections of the text in which they, their words, or their ideas are presented to ensure accuracy and enable participants to maintain control over their lives.

Audience and Voice

When writing, researchers must consider their audience(s) and the effects they want their writing to have on these audiences. The designated audience will dictate the voice used in the writing, or the individual style and personality of a piece of text. Keep in mind that the potential audience for qualitative research is often much more diverse than that for quantitative research because of the accessibility of the data and the extent to which the writing can be accessible and interesting. Yet individual pieces of writing are typically pitched to a more specific subset of the audience.

Let us consider one potential research study, an ethnography involving participant-observation of the same children both when they are at daycare facility and when they are at home with their families to try to understand how daycare might impact behavior and social development. The findings of this study might be of interest to a wide variety of potential audiences: academic peers, whether at your own academic institution, in your broader discipline, or multidisciplinary; people responsible for creating laws and policies; practitioners who run or teach at day care centers; and the general public, including both people who are interested in child development more generally and those who are themselves parents making decisions about child care for their own children. And the way you write for each of these audiences will be somewhat different. Take a moment and think through what some of these differences might look like.

If you are writing to academic audiences, using specialized academic language and working within the typical constraints of scholarly genres, as will be discussed below, can be an important part of convincing others that your work is legitimate and should be taken seriously. Your writing will be formal. Even if you are writing for students and faculty you already know—your classmates, for instance—you are often asked to imitate the style of academic writing that is used in publications, as this is part of learning to become part of the scholarly conversation. When speaking to academic audiences outside your discipline, you may need to be more careful about jargon and specialized language, as disciplines do not always share the same key terms. For instance, in sociology, scholars use the term diffusion to refer to the way new ideas or practices spread from organization to organization. In the field of international relations, scholars often used the term cascade to refer to the way ideas or practices spread from nation to nation. These terms are describing what is fundamentally the same concept, but they are different terms—and a scholar from one field might have no idea what a scholar from a different field is talking about! Therefore, while the formality and academic structure of the text would stay the same, a writer with a multidisciplinary audience might need to pay more attention to defining their terms in the body of the text.

It is not only other academic scholars who expect to see formal writing. Policymakers tend to expect formality when ideas are presented to them, as well. However, the content and style of the writing will be different. Much less academic jargon should be used, and the most important findings and policy implications should be emphasized right from the start rather than initially focusing on prior literature and theoretical models as you might for an academic audience. Long discussions of research methods should also be minimized. Similarly, when you write for practitioners, the findings and implications for practice should be highlighted. The reading level of the text will vary depending on the typical background of the practitioners to whom you are writing—you can make very different assumptions about the general knowledge and reading abilities of a group of hospital medical directors with MDs than you can about a group of case workers who have a post-high-school certificate. Consider the primary language of your audience as well. The fact that someone can get by in spoken English does not mean they have the vocabulary or English reading skills to digest a complex report. But the fact that someone’s vocabulary is limited says little about their intellectual abilities, so try your best to convey the important complexity of the ideas and findings from your research without dumbing them down—even if you must limit your vocabulary usage.

When writing for the general public, you will want to move even further towards emphasizing key findings and policy implications, but you also want to draw on the most interesting aspects of your data. General readers will read sociological texts that are rich with ethnographic or other kinds of detail—it is almost like reality television on a page! And this is a contrast to busy policymakers and practitioners, who probably want to learn the main findings as quickly as possible so they can go about their busy lives. But also keep in mind that there is a wide variation in reading levels. Journalists at publications pegged to the general public are often advised to write at about a tenth-grade reading level, which would leave most of the specialized terminology we develop in our research fields out of reach. If you want to be accessible to even more people, your vocabulary must be even more limited. The excellent exercise of trying to write using the 1,000 most common English words, available at the Up-Goer Five website ( https://www.splasho.com/upgoer5/ ) does a good job of illustrating this challenge (Sanderson n.d.).

Another element of voice is whether to write in the first person. While many students are instructed to avoid the use of the first person in academic writing, this advice needs to be taken with a grain of salt. There are indeed many contexts in which the first person is best avoided, at least as long as writers can find ways to build strong, comprehensible sentences without its use, including most quantitative research writing. However, if the alternative to using the first person is crafting a sentence like “it is proposed that the researcher will conduct interviews,” it is preferable to write “I propose to conduct interviews.” In qualitative research, in fact, the use of the first person is far more common. This is because the researcher is central to the research project. Qualitative researchers can themselves be understood as research instruments, and thus eliminating the use of the first person in writing is in a sense eliminating information about the conduct of the researchers themselves.

But the question really extends beyond the issue of first-person or third-person. Qualitative researchers have choices about how and whether to foreground themselves in their writing, not just in terms of using the first person, but also in terms of whether to emphasize their own subjectivity and reflexivity, their impressions and ideas, and their role in the setting. In contrast, conventional quantitative research in the positivist tradition really tries to eliminate the author from the study—which indeed is exactly why typical quantitative research avoids the use of the first person. Keep in mind that emphasizing researchers’ roles and reflexivity and using the first person does not mean crafting articles that provide overwhelming detail about the author’s thoughts and practices. Readers do not need to hear, and should not be told, which database you used to search for journal articles, how many hours you spent transcribing, or whether the research process was stressful—save these things for the memos you write to yourself. Rather, readers need to hear how you interacted with research participants, how your standpoint may have shaped the findings, and what analytical procedures you carried out.

Making Data Come Alive

One of the most important parts of writing about qualitative research is presenting the data in a way that makes its richness and value accessible to readers. As the discussion of analysis in the prior chapter suggests, there are a variety of ways to do this. Researchers may select key quotes or images to illustrate points, write up specific case studies that exemplify their argument, or develop vignettes (little stories) that illustrate ideas and themes, all drawing directly on the research data. Researchers can also write more lengthy summaries, narratives, and thick descriptions.

Nearly all qualitative work includes quotes from research participants or documents to some extent, though ethnographic work may focus more on thick description than on relaying participants’ own words. When quotes are presented, they must be explained and interpreted—they cannot stand on their own. This is one of the ways in which qualitative research can be distinguished from journalism. Journalism presents what happened, but social science needs to present the “why,” and the why is best explained by the researcher.

So how do authors go about integrating quotes into their written work? Julie Posselt (2017), a sociologist who studies graduate education, provides a set of instructions. First of all, authors need to remain focused on the core questions of their research, and avoid getting distracted by quotes that are interesting or attention-grabbing but not so relevant to the research question. Selecting the right quotes, those that illustrate the ideas and arguments of the paper, is an important part of the writing process. Second, not all quotes should be the same length (just like not all sentences or paragraphs in a paper should be the same length). Include some quotes that are just phrases, others that are a sentence or so, and others that are longer. We call longer quotes, generally those more than about three lines long, block quotes , and they are typically indented on both sides to set them off from the surrounding text. For all quotes, be sure to summarize what the quote should be telling or showing the reader, connect this quote to other quotes that are similar or different, and provide transitions in the discussion to move from quote to quote and from topic to topic. Especially for longer quotes, it is helpful to do some of this writing before the quote to preview what is coming and other writing after the quote to make clear what readers should have come to understand. Remember, it is always the author’s job to interpret the data. Presenting excerpts of the data, like quotes, in a form the reader can access does not minimize the importance of this job. Be sure that you are explaining the meaning of the data you present.

A few more notes about writing with quotes: avoid patchwriting, whether in your literature review or the section of your paper in which quotes from respondents are presented. Patchwriting is a writing practice wherein the author lightly paraphrases original texts but stays so close to those texts that there is little the author has added. Sometimes, this even takes the form of presenting a series of quotes, properly documented, with nothing much in the way of text generated by the author. A patchwriting approach does not build the scholarly conversation forward, as it does not represent any kind of new contribution on the part of the author. It is of course fine to paraphrase quotes, as long as the meaning is not changed. But if you use direct quotes, do not edit the text of the quotes unless how you edit them does not change the meaning and you have made clear through the use of ellipses (…) and brackets ([])what kinds of edits have been made. For example, consider this exchange from Matthew Desmond’s (2012:1317) research on evictions:

The thing was, I wasn’t never gonna let Crystal come and stay with me from the get go. I just told her that to throw her off. And she wasn’t fittin’ to come stay with me with no money…No. Nope. You might as well stay in that shelter.

A paraphrase of this exchange might read “She said that she was going to let Crystal stay with her if Crystal did not have any money.” Paraphrases like that are fine. What is not fine is rewording the statement but treating it like a quote, for instance writing:

The thing was, I was not going to let Crystal come and stay with me from beginning. I just told her that to throw her off. And it was not proper for her to come stay with me without any money…No. Nope. You might as well stay in that shelter.

But as you can see, the change in language and style removes some of the distinct meaning of the original quote. Instead, writers should leave as much of the original language as possible. If some text in the middle of the quote needs to be removed, as in this example, ellipses are used to show that this has occurred. And if a word needs to be added to clarify, it is placed in square brackets to show that it was not part of the original quote.

Data can also be presented through the use of data displays like tables, charts, graphs, diagrams, and infographics created for publication or presentation, as well as through the use of visual material collected during the research process. Note that if visuals are used, the author must have the legal right to use them. Photographs or diagrams created by the author themselves—or by research participants who have signed consent forms for their work to be used, are fine. But photographs, and sometimes even excerpts from archival documents, may be owned by others from whom researchers must get permission in order to use them.

A large percentage of qualitative research does not include any data displays or visualizations. Therefore, researchers should carefully consider whether the use of data displays will help the reader understand the data. One of the most common types of data displays used by qualitative researchers are simple tables. These might include tables summarizing key data about cases included in the study; tables laying out the characteristics of different taxonomic elements or types developed as part of the analysis; tables counting the incidence of various elements; and 2×2 tables (two columns and two rows) illuminating a theory. Basic network or process diagrams are also commonly included. If data displays are used, it is essential that researchers include context and analysis alongside data displays rather than letting them stand by themselves, and it is preferable to continue to present excerpts and examples from the data rather than just relying on summaries in the tables.

If you will be using graphs, infographics, or other data visualizations, it is important that you attend to making them useful and accurate (Bergin 2018). Think about the viewer or user as your audience and ensure the data visualizations will be comprehensible. You may need to include more detail or labels than you might think. Ensure that data visualizations are laid out and labeled clearly and that you make visual choices that enhance viewers’ ability to understand the points you intend to communicate using the visual in question. Finally, given the ease with which it is possible to design visuals that are deceptive or misleading, it is essential to make ethical and responsible choices in the construction of visualization so that viewers will interpret them in accurate ways.

The Genre of Research Writing

As discussed above, the style and format in which results are presented depends on the audience they are intended for. These differences in styles and format are part of the genre of writing. Genre is a term referring to the rules of a specific form of creative or productive work. Thus, the academic journal article—and student papers based on this form—is one genre. A report or policy paper is another. The discussion below will focus on the academic journal article, but note that reports and policy papers follow somewhat different formats. They might begin with an executive summary of one or a few pages, include minimal background, focus on key findings, and conclude with policy implications, shifting methods and details about the data to an appendix. But both academic journal articles and policy papers share some things in common, for instance the necessity for clear writing, a well-organized structure, and the use of headings.

So what factors make up the genre of the academic journal article in sociology? While there is some flexibility, particularly for ethnographic work, academic journal articles tend to follow a fairly standard format. They begin with a “title page” that includes the article title (often witty and involving scholarly inside jokes, but more importantly clearly describing the content of the article); the authors’ names and institutional affiliations, an abstract , and sometimes keywords designed to help others find the article in databases. An abstract is a short summary of the article that appears both at the very beginning of the article and in search databases. Abstracts are designed to aid readers by giving them the opportunity to learn enough about an article that they can determine whether it is worth their time to read the complete text. They are written about the article, and thus not in the first person, and clearly summarize the research question, methodological approach, main findings, and often the implications of the research.

After the abstract comes an “introduction” of a page or two that details the research question, why it matters, and what approach the paper will take. This is followed by a literature review of about a quarter to a third the length of the entire paper. The literature review is often divided, with headings, into topical subsections, and is designed to provide a clear, thorough overview of the prior research literature on which a paper has built—including prior literature the new paper contradicts. At the end of the literature review it should be made clear what researchers know about the research topic and question, what they do not know, and what this new paper aims to do to address what is not known.

The next major section of the paper is the section that describes research design, data collection, and data analysis, often referred to as “research methods” or “methodology.” This section is an essential part of any written or oral presentation of your research. Here, you tell your readers or listeners “how you collected and interpreted your data” (Taylor, Bogdan, and DeVault 2016:215). Taylor, Bogdan, and DeVault suggest that the discussion of your research methods include the following:

• The particular approach to data collection used in the study;
• Any theoretical perspective(s) that shaped your data collection and analytical approach;
• When the study occurred, over how long, and where (concealing identifiable details as needed);
• A description of the setting and participants, including sampling and selection criteria (if an interview-based study, the number of participants should be clearly stated);
• The researcher’s perspective in carrying out the study, including relevant elements of their identity and standpoint, as well as their role (if any) in research settings; and
• The approach to analyzing the data.

After the methods section comes a section, variously titled but often called “data,” that takes readers through the analysis. This section is where the thick description narrative; the quotes, broken up by theme or topic, with their interpretation; the discussions of case studies; most data displays (other than perhaps those outlining a theoretical model or summarizing descriptive data about cases); and other similar material appears. The idea of the data section is to give readers the ability to see the data for themselves and to understand how this data supports the ultimate conclusions. Note that all tables and figures included in formal publications should be titled and numbered.

At the end of the paper come one or two summary sections, often called “discussion” and/or “conclusion.” If there is a separate discussion section, it will focus on exploring the overall themes and findings of the paper. The conclusion clearly and succinctly summarizes the findings and conclusions of the paper, the limitations of the research and analysis, any suggestions for future research building on the paper or addressing these limitations, and implications, be they for scholarship and theory or policy and practice.

After the end of the textual material in the paper comes the bibliography, typically called “works cited” or “references.” The references should appear in a consistent citation style—in sociology, we often use the American Sociological Association format (American Sociological Association 2019), but other formats may be used depending on where the piece will eventually be published. Care should be taken to ensure that in-text citations also reflect the chosen citation style. In some papers, there may be an appendix containing supplemental information such as a list of interview questions or an additional data visualization.

Note that when researchers give presentations to scholarly audiences, the presentations typically follow a format similar to that of scholarly papers, though given time limitations they are compressed. Abstracts and works cited are often not part of the presentation, though in-text citations are still used. The literature review presented will be shortened to only focus on the most important aspects of the prior literature, and only key examples from the discussion of data will be included. For long or complex papers, sometimes only one of several findings is the focus of the presentation. Of course, presentations for other audiences may be constructed differently, with greater attention to interesting elements of the data and findings as well as implications and less to the literature review and methods.

Concluding Your Work

After you have written a complete draft of the paper, be sure you take the time to revise and edit your work. There are several important strategies for revision. First, put your work away for a little while. Even waiting a day to revise is better than nothing, but it is best, if possible, to take much more time away from the text. This helps you forget what your writing looks like and makes it easier to find errors, mistakes, and omissions. Second, show your work to others. Ask them to read your work and critique it, pointing out places where the argument is weak, where you may have overlooked alternative explanations, where the writing could be improved, and what else you need to work on. Finally, read your work out loud to yourself (or, if you really need an audience, try reading to some stuffed animals). Reading out loud helps you catch wrong words, tricky sentences, and many other issues. But as important as revision is, try to avoid perfectionism in writing (Warren and Karner 2015). Writing can always be improved, no matter how much time you spend on it. Those improvements, however, have diminishing returns, and at some point the writing process needs to conclude so the writing can be shared with the world.

Of course, the main goal of writing up the results of a research project is to share with others. Thus, researchers should be considering how they intend to disseminate their results. What conferences might be appropriate? Where can the paper be submitted? Note that if you are an undergraduate student, there are a wide variety of journals that accept and publish research conducted by undergraduates. Some publish across disciplines, while others are specific to disciplines. Other work, such as reports, may be best disseminated by publication online on relevant organizational websites.

After a project is completed, be sure to take some time to organize your research materials and archive them for longer-term storage. Some Institutional Review Board (IRB) protocols require that original data, such as interview recordings, transcripts, and field notes, be preserved for a specific number of years in a protected (locked for paper or password-protected for digital) form and then destroyed, so be sure that your plans adhere to the IRB requirements. Be sure you keep any materials that might be relevant for future related research or for answering questions people may ask later about your project.

And then what? Well, then it is time to move on to your next research project. Research is a long-term endeavor, not a one-time-only activity. We build our skills and our expertise as we continue to pursue research. So keep at it.

• Find a short article that uses qualitative methods. The sociological magazine Contexts is a good place to find such pieces. Write an abstract of the article.
• Choose a sociological journal article on a topic you are interested in that uses some form of qualitative methods and is at least 20 pages long. Rewrite the article as a five-page research summary accessible to non-scholarly audiences.
• Choose a concept or idea you have learned in this course and write an explanation of it using the Up-Goer Five Text Editor ( https://www.splasho.com/upgoer5/ ), a website that restricts your writing to the 1,000 most common English words. What was this experience like? What did it teach you about communicating with people who have a more limited English-language vocabulary—and what did it teach you about the utility of having access to complex academic language?
• Select five or more sociological journal articles that all use the same basic type of qualitative methods (interviewing, ethnography, documents, or visual sociology). Using what you have learned about coding, code the methods sections of each article, and use your coding to figure out what is common in how such articles discuss their research design, data collection, and analysis methods.
• Return to an exercise you completed earlier in this course and revise your work. What did you change? How did revising impact the final product?
• Find a quote from the transcript of an interview, a social media post, or elsewhere that has not yet been interpreted or explained. Write a paragraph that includes the quote along with an explanation of its sociological meaning or significance.

The style or personality of a piece of writing, including such elements as tone, word choice, syntax, and rhythm.

A quotation, usually one of some length, which is set off from the main text by being indented on both sides rather than being placed in quotation marks.

A classification of written or artistic work based on form, content, and style.

A short summary of a text written from the perspective of a reader rather than from the perspective of an author.

Social Data Analysis Copyright © 2021 by Mikaila Mariel Lemonik Arthur is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License , except where otherwise noted.

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.

Psst... there’s more!

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 ...

38 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?

This is very instructive and educative

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.

This was very helpful, thank you!

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How to write the analysis and discussion chapters in qualitative (SSAH) research

By charlesworth author services.

• Charlesworth Author Services
• 11 November, 2021

While it is more common for Science, Technology, Engineering and Mathematics (STEM) researchers to write separate, distinct chapters for their data/ results and analysis/ discussion , the same sections can feel less clearly defined for a researcher in Social Sciences, Arts and Humanities (SSAH). This article will look specifically at some useful approaches to writing the analysis and discussion chapters in qualitative/SSAH research.

Note : Most of the differences in approaches to research, writing, analysis and discussion come down, ultimately, to differences in epistemology – how we approach, create and work with knowledge in our respective fields. However, this is a vast topic that deserves a separate discussion.

Look for emerging themes and patterns

The ‘results’ of qualitative research can sometimes be harder to pinpoint than in quantitative research. You’re not dealing with definitive numbers and results in the same way as, say, a scientist conducting experiments that produce measurable data. Instead, most qualitative researchers explore prominent, interesting themes and patterns emerging from their data – that could comprise interviews, textual material or participant observation, for example. 

You may find that your data presents a huge number of themes, issues and topics, all of which you might find equally significant and interesting. In fact, you might find yourself overwhelmed by the many directions that your research could take, depending on which themes you choose to study in further depth. You may even discover issues and patterns that you had not expected , that may necessitate having to change or expand the research focus you initially started off with.

It is crucial at this point not to panic. Instead, try to enjoy the many possibilities that your data is offering you. It can be useful to remind yourself at each stage of exactly what you are trying to find out through this research.

What exactly do you want to know? What knowledge do you want to generate and share within your field?

Then, spend some time reflecting upon each of the themes that seem most interesting and significant, and consider whether they are immediately relevant to your main, overarching research objectives and goals.

Suggestion: Don’t worry too much about structure and flow at the early stages of writing your discussion . It would be a more valuable use of your time to fully explore the themes and issues arising from your data first, while also reading widely alongside your writing (more on this below). As you work more intimately with the data and develop your ideas, the overarching narrative and connections between those ideas will begin to emerge. Trust that you’ll be able to draw those links and craft the structure organically as you write.

Let your data guide you

A key characteristic of qualitative research is that the researchers allow their data to ‘speak’ and guide their research and their writing. Instead of insisting too strongly upon the prominence of specific themes and issues and imposing their opinions and beliefs upon the data, a good qualitative researcher ‘listens’ to what the data has to tell them.

Again, you might find yourself having to address unexpected issues or your data may reveal things that seem completely contradictory to the ideas and theories you have worked with so far. Although this might seem worrying, discovering these unexpected new elements can actually make your research much richer and more interesting. 

Suggestion: Allow yourself to follow those leads and ask new questions as you work through your data. These new directions could help you to answer your research questions in more depth and with greater complexity; or they could even open up other avenues for further study, either in this or future research.

Work closely with the literature

As you analyse and discuss the prominent themes, arguments and findings arising from your data, it is very helpful to maintain a regular and consistent reading practice alongside your writing. Return to the literature that you’ve already been reading so far or begin to check out new texts, studies and theories that might be more appropriate for working with any new ideas and themes arising from your data.

Reading and incorporating relevant literature into your writing as you work through your analysis and discussion will help you to consistently contextualise your research within the larger body of knowledge. It will be easier to stay focused on what you are trying to say through your research if you can simultaneously show what has already been said on the subject and how your research and data supports, challenges or extends those debates. By drawing from existing literature , you are setting up a dialogue between your research and prior work, and highlighting what this research has to add to the conversation.

Suggestion : Although it might sometimes feel tedious to have to blend others’ writing in with yours, this is ultimately the best way to showcase the specialness of your own data, findings and research . Remember that it is more difficult to highlight the significance and relevance of your original work without first showing how that work fits into or responds to existing studies. 

In conclusion

The discussion chapters form the heart of your thesis and this is where your unique contribution comes to the forefront. This is where your data takes centre-stage and where you get to showcase your original arguments, perspectives and knowledge. To do this effectively needs you to explore the original themes and issues arising from and within the data, while simultaneously contextualising these findings within the larger, existing body of knowledge of your specialising field. By striking this balance, you prove the two most important qualities of excellent qualitative research : keen awareness of your field and a firm understanding of your place in it.

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• USC Libraries
• Research Guides

Organizing Your Social Sciences Research Paper

• 8. The Discussion
• Purpose of Guide
• Design Flaws to Avoid
• Independent and Dependent Variables
• Glossary of Research Terms
• Reading Research Effectively
• Narrowing a Topic Idea
• Broadening a Topic Idea
• Extending the Timeliness of a Topic Idea
• Academic Writing Style
• Applying Critical Thinking
• Choosing a Title
• Making an Outline
• Paragraph Development
• Research Process Video Series
• Executive Summary
• The C.A.R.S. Model
• Background Information
• The Research Problem/Question
• Theoretical Framework
• Citation Tracking
• Content Alert Services
• Evaluating Sources
• Primary Sources
• Secondary Sources
• Tiertiary Sources
• Scholarly vs. Popular Publications
• Qualitative Methods
• Quantitative Methods
• Insiderness
• Using Non-Textual Elements
• Limitations of the Study
• Common Grammar Mistakes
• Writing Concisely
• Avoiding Plagiarism
• Footnotes or Endnotes?
• Further Readings
• Generative AI and Writing
• USC Libraries Tutorials and Other Guides
• Bibliography

The purpose of the discussion section is to interpret and describe the significance of your findings in relation to what was already known about the research problem being investigated and to explain any new understanding or insights that emerged as a result of your research. The discussion will always connect to the introduction by way of the research questions or hypotheses you posed and the literature you reviewed, but the discussion does not simply repeat or rearrange the first parts of your paper; the discussion clearly explains how your study advanced the reader's understanding of the research problem from where you left them at the end of your review of prior research.

Annesley, Thomas M. “The Discussion Section: Your Closing Argument.” Clinical Chemistry 56 (November 2010): 1671-1674; Peacock, Matthew. “Communicative Moves in the Discussion Section of Research Articles.” System 30 (December 2002): 479-497.

Importance of a Good Discussion

The discussion section is often considered the most important part of your research paper because it:

• Most effectively demonstrates your ability as a researcher to think critically about an issue, to develop creative solutions to problems based upon a logical synthesis of the findings, and to formulate a deeper, more profound understanding of the research problem under investigation;
• Presents the underlying meaning of your research, notes possible implications in other areas of study, and explores possible improvements that can be made in order to further develop the concerns of your research;
• Highlights the importance of your study and how it can contribute to understanding the research problem within the field of study;
• Presents how the findings from your study revealed and helped fill gaps in the literature that had not been previously exposed or adequately described; and,
• Engages the reader in thinking critically about issues based on an evidence-based interpretation of findings; it is not governed strictly by objective reporting of information.

Annesley Thomas M. “The Discussion Section: Your Closing Argument.” Clinical Chemistry 56 (November 2010): 1671-1674; Bitchener, John and Helen Basturkmen. “Perceptions of the Difficulties of Postgraduate L2 Thesis Students Writing the Discussion Section.” Journal of English for Academic Purposes 5 (January 2006): 4-18; Kretchmer, Paul. Fourteen Steps to Writing an Effective Discussion Section. San Francisco Edit, 2003-2008.

Structure and Writing Style

I.  General Rules

These are the general rules you should adopt when composing your discussion of the results :

• Do not be verbose or repetitive; be concise and make your points clearly
• Avoid the use of jargon or undefined technical language
• Follow a logical stream of thought; in general, interpret and discuss the significance of your findings in the same sequence you described them in your results section [a notable exception is to begin by highlighting an unexpected result or a finding that can grab the reader's attention]
• Use the present verb tense, especially for established facts; however, refer to specific works or prior studies in the past tense
• If needed, use subheadings to help organize your discussion or to categorize your interpretations into themes

II.  The Content

The content of the discussion section of your paper most often includes :

• Explanation of results : Comment on whether or not the results were expected for each set of findings; go into greater depth to explain findings that were unexpected or especially profound. If appropriate, note any unusual or unanticipated patterns or trends that emerged from your results and explain their meaning in relation to the research problem.
• References to previous research : Either compare your results with the findings from other studies or use the studies to support a claim. This can include re-visiting key sources already cited in your literature review section, or, save them to cite later in the discussion section if they are more important to compare with your results instead of being a part of the general literature review of prior research used to provide context and background information. Note that you can make this decision to highlight specific studies after you have begun writing the discussion section.
• Deduction : A claim for how the results can be applied more generally. For example, describing lessons learned, proposing recommendations that can help improve a situation, or highlighting best practices.
• Hypothesis : A more general claim or possible conclusion arising from the results [which may be proved or disproved in subsequent research]. This can be framed as new research questions that emerged as a consequence of your analysis.

III.  Organization and Structure

Keep the following sequential points in mind as you organize and write the discussion section of your paper:

• Think of your discussion as an inverted pyramid. Organize the discussion from the general to the specific, linking your findings to the literature, then to theory, then to practice [if appropriate].
• Use the same key terms, narrative style, and verb tense [present] that you used when describing the research problem in your introduction.
• Begin by briefly re-stating the research problem you were investigating and answer all of the research questions underpinning the problem that you posed in the introduction.
• Describe the patterns, principles, and relationships shown by each major findings and place them in proper perspective. The sequence of this information is important; first state the answer, then the relevant results, then cite the work of others. If appropriate, refer the reader to a figure or table to help enhance the interpretation of the data [either within the text or as an appendix].
• Regardless of where it's mentioned, a good discussion section includes analysis of any unexpected findings. This part of the discussion should begin with a description of the unanticipated finding, followed by a brief interpretation as to why you believe it appeared and, if necessary, its possible significance in relation to the overall study. If more than one unexpected finding emerged during the study, describe each of them in the order they appeared as you gathered or analyzed the data. As noted, the exception to discussing findings in the same order you described them in the results section would be to begin by highlighting the implications of a particularly unexpected or significant finding that emerged from the study, followed by a discussion of the remaining findings.
• Before concluding the discussion, identify potential limitations and weaknesses if you do not plan to do so in the conclusion of the paper. Comment on their relative importance in relation to your overall interpretation of the results and, if necessary, note how they may affect the validity of your findings. Avoid using an apologetic tone; however, be honest and self-critical [e.g., in retrospect, had you included a particular question in a survey instrument, additional data could have been revealed].
• The discussion section should end with a concise summary of the principal implications of the findings regardless of their significance. Give a brief explanation about why you believe the findings and conclusions of your study are important and how they support broader knowledge or understanding of the research problem. This can be followed by any recommendations for further research. However, do not offer recommendations which could have been easily addressed within the study. This would demonstrate to the reader that you have inadequately examined and interpreted the data.

IV.  Overall Objectives

The objectives of your discussion section should include the following: I.  Reiterate the Research Problem/State the Major Findings

Briefly reiterate the research problem or problems you are investigating and the methods you used to investigate them, then move quickly to describe the major findings of the study. You should write a direct, declarative, and succinct proclamation of the study results, usually in one paragraph.

II.  Explain the Meaning of the Findings and Why They are Important

No one has thought as long and hard about your study as you have. Systematically explain the underlying meaning of your findings and state why you believe they are significant. After reading the discussion section, you want the reader to think critically about the results and why they are important. You don’t want to force the reader to go through the paper multiple times to figure out what it all means. If applicable, begin this part of the section by repeating what you consider to be your most significant or unanticipated finding first, then systematically review each finding. Otherwise, follow the general order you reported the findings presented in the results section.

III.  Relate the Findings to Similar Studies

No study in the social sciences is so novel or possesses such a restricted focus that it has absolutely no relation to previously published research. The discussion section should relate your results to those found in other studies, particularly if questions raised from prior studies served as the motivation for your research. This is important because comparing and contrasting the findings of other studies helps to support the overall importance of your results and it highlights how and in what ways your study differs from other research about the topic. Note that any significant or unanticipated finding is often because there was no prior research to indicate the finding could occur. If there is prior research to indicate this, you need to explain why it was significant or unanticipated. IV.  Consider Alternative Explanations of the Findings

It is important to remember that the purpose of research in the social sciences is to discover and not to prove . When writing the discussion section, you should carefully consider all possible explanations for the study results, rather than just those that fit your hypothesis or prior assumptions and biases. This is especially important when describing the discovery of significant or unanticipated findings.

V.  Acknowledge the Study’s Limitations

It is far better for you to identify and acknowledge your study’s limitations than to have them pointed out by your professor! Note any unanswered questions or issues your study could not address and describe the generalizability of your results to other situations. If a limitation is applicable to the method chosen to gather information, then describe in detail the problems you encountered and why. VI.  Make Suggestions for Further Research

You may choose to conclude the discussion section by making suggestions for further research [as opposed to offering suggestions in the conclusion of your paper]. Although your study can offer important insights about the research problem, this is where you can address other questions related to the problem that remain unanswered or highlight hidden issues that were revealed as a result of conducting your research. You should frame your suggestions by linking the need for further research to the limitations of your study [e.g., in future studies, the survey instrument should include more questions that ask..."] or linking to critical issues revealed from the data that were not considered initially in your research.

NOTE: Besides the literature review section, the preponderance of references to sources is usually found in the discussion section . A few historical references may be helpful for perspective, but most of the references should be relatively recent and included to aid in the interpretation of your results, to support the significance of a finding, and/or to place a finding within a particular context. If a study that you cited does not support your findings, don't ignore it--clearly explain why your research findings differ from theirs.

V.  Problems to Avoid

• Do not waste time restating your results . Should you need to remind the reader of a finding to be discussed, use "bridge sentences" that relate the result to the interpretation. An example would be: “In the case of determining available housing to single women with children in rural areas of Texas, the findings suggest that access to good schools is important...," then move on to further explaining this finding and its implications.
• As noted, recommendations for further research can be included in either the discussion or conclusion of your paper, but do not repeat your recommendations in the both sections. Think about the overall narrative flow of your paper to determine where best to locate this information. However, if your findings raise a lot of new questions or issues, consider including suggestions for further research in the discussion section.
• Do not introduce new results in the discussion section. Be wary of mistaking the reiteration of a specific finding for an interpretation because it may confuse the reader. The description of findings [results section] and the interpretation of their significance [discussion section] should be distinct parts of your paper. If you choose to combine the results section and the discussion section into a single narrative, you must be clear in how you report the information discovered and your own interpretation of each finding. This approach is not recommended if you lack experience writing college-level research papers.
• Use of the first person pronoun is generally acceptable. Using first person singular pronouns can help emphasize a point or illustrate a contrasting finding. However, keep in mind that too much use of the first person can actually distract the reader from the main points [i.e., I know you're telling me this--just tell me!].

Analyzing vs. Summarizing. Department of English Writing Guide. George Mason University; Discussion. The Structure, Format, Content, and Style of a Journal-Style Scientific Paper. Department of Biology. Bates College; Hess, Dean R. "How to Write an Effective Discussion." Respiratory Care 49 (October 2004); Kretchmer, Paul. Fourteen Steps to Writing to Writing an Effective Discussion Section. San Francisco Edit, 2003-2008; The Lab Report. University College Writing Centre. University of Toronto; Sauaia, A. et al. "The Anatomy of an Article: The Discussion Section: "How Does the Article I Read Today Change What I Will Recommend to my Patients Tomorrow?” The Journal of Trauma and Acute Care Surgery 74 (June 2013): 1599-1602; Research Limitations & Future Research . Lund Research Ltd., 2012; Summary: Using it Wisely. The Writing Center. University of North Carolina; Schafer, Mickey S. Writing the Discussion. Writing in Psychology course syllabus. University of Florida; Yellin, Linda L. A Sociology Writer's Guide . Boston, MA: Allyn and Bacon, 2009.

Writing Tip

Don’t Over-Interpret the Results!

Interpretation is a subjective exercise. As such, you should always approach the selection and interpretation of your findings introspectively and to think critically about the possibility of judgmental biases unintentionally entering into discussions about the significance of your work. With this in mind, be careful that you do not read more into the findings than can be supported by the evidence you have gathered. Remember that the data are the data: nothing more, nothing less.

MacCoun, Robert J. "Biases in the Interpretation and Use of Research Results." Annual Review of Psychology 49 (February 1998): 259-287; Ward, Paulet al, editors. The Oxford Handbook of Expertise . Oxford, UK: Oxford University Press, 2018.

Another Writing Tip

Don't Write Two Results Sections!

One of the most common mistakes that you can make when discussing the results of your study is to present a superficial interpretation of the findings that more or less re-states the results section of your paper. Obviously, you must refer to your results when discussing them, but focus on the interpretation of those results and their significance in relation to the research problem, not the data itself.

Azar, Beth. "Discussing Your Findings."  American Psychological Association gradPSYCH Magazine (January 2006).

Yet Another Writing Tip

Avoid Unwarranted Speculation!

The discussion section should remain focused on the findings of your study. For example, if the purpose of your research was to measure the impact of foreign aid on increasing access to education among disadvantaged children in Bangladesh, it would not be appropriate to speculate about how your findings might apply to populations in other countries without drawing from existing studies to support your claim or if analysis of other countries was not a part of your original research design. If you feel compelled to speculate, do so in the form of describing possible implications or explaining possible impacts. Be certain that you clearly identify your comments as speculation or as a suggestion for where further research is needed. Sometimes your professor will encourage you to expand your discussion of the results in this way, while others don’t care what your opinion is beyond your effort to interpret the data in relation to the research problem.

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• v.74(8); 2010 Oct 11

Presenting and Evaluating Qualitative Research

The purpose of this paper is to help authors to think about ways to present qualitative research papers in the American Journal of Pharmaceutical Education . It also discusses methods for reviewers to assess the rigour, quality, and usefulness of qualitative research. Examples of different ways to present data from interviews, observations, and focus groups are included. The paper concludes with guidance for publishing qualitative research and a checklist for authors and reviewers.

INTRODUCTION

Policy and practice decisions, including those in education, increasingly are informed by findings from qualitative as well as quantitative research. Qualitative research is useful to policymakers because it often describes the settings in which policies will be implemented. Qualitative research is also useful to both pharmacy practitioners and pharmacy academics who are involved in researching educational issues in both universities and practice and in developing teaching and learning.

Qualitative research involves the collection, analysis, and interpretation of data that are not easily reduced to numbers. These data relate to the social world and the concepts and behaviors of people within it. Qualitative research can be found in all social sciences and in the applied fields that derive from them, for example, research in health services, nursing, and pharmacy. 1 It looks at X in terms of how X varies in different circumstances rather than how big is X or how many Xs are there? 2 Textbooks often subdivide research into qualitative and quantitative approaches, furthering the common assumption that there are fundamental differences between the 2 approaches. With pharmacy educators who have been trained in the natural and clinical sciences, there is often a tendency to embrace quantitative research, perhaps due to familiarity. A growing consensus is emerging that sees both qualitative and quantitative approaches as useful to answering research questions and understanding the world. Increasingly mixed methods research is being carried out where the researcher explicitly combines the quantitative and qualitative aspects of the study. 3 , 4

Like healthcare, education involves complex human interactions that can rarely be studied or explained in simple terms. Complex educational situations demand complex understanding; thus, the scope of educational research can be extended by the use of qualitative methods. Qualitative research can sometimes provide a better understanding of the nature of educational problems and thus add to insights into teaching and learning in a number of contexts. For example, at the University of Nottingham, we conducted in-depth interviews with pharmacists to determine their perceptions of continuing professional development and who had influenced their learning. We also have used a case study approach using observation of practice and in-depth interviews to explore physiotherapists' views of influences on their leaning in practice. We have conducted in-depth interviews with a variety of stakeholders in Malawi, Africa, to explore the issues surrounding pharmacy academic capacity building. A colleague has interviewed and conducted focus groups with students to explore cultural issues as part of a joint Nottingham-Malaysia pharmacy degree program. Another colleague has interviewed pharmacists and patients regarding their expectations before and after clinic appointments and then observed pharmacist-patient communication in clinics and assessed it using the Calgary Cambridge model in order to develop recommendations for communication skills training. 5 We have also performed documentary analysis on curriculum data to compare pharmacist and nurse supplementary prescribing courses in the United Kingdom.

It is important to choose the most appropriate methods for what is being investigated. Qualitative research is not appropriate to answer every research question and researchers need to think carefully about their objectives. Do they wish to study a particular phenomenon in depth (eg, students' perceptions of studying in a different culture)? Or are they more interested in making standardized comparisons and accounting for variance (eg, examining differences in examination grades after changing the way the content of a module is taught). Clearly a quantitative approach would be more appropriate in the last example. As with any research project, a clear research objective has to be identified to know which methods should be applied.

Types of qualitative data include:

• Audio recordings and transcripts from in-depth or semi-structured interviews
• Structured interview questionnaires containing substantial open comments including a substantial number of responses to open comment items.
• Audio recordings and transcripts from focus group sessions.
• Field notes (notes taken by the researcher while in the field [setting] being studied)
• Video recordings (eg, lecture delivery, class assignments, laboratory performance)
• Case study notes
• Documents (reports, meeting minutes, e-mails)
• Diaries, video diaries
• Observation notes
• Press clippings
• Photographs

RIGOUR IN QUALITATIVE RESEARCH

Qualitative research is often criticized as biased, small scale, anecdotal, and/or lacking rigor; however, when it is carried out properly it is unbiased, in depth, valid, reliable, credible and rigorous. In qualitative research, there needs to be a way of assessing the “extent to which claims are supported by convincing evidence.” 1 Although the terms reliability and validity traditionally have been associated with quantitative research, increasingly they are being seen as important concepts in qualitative research as well. Examining the data for reliability and validity assesses both the objectivity and credibility of the research. Validity relates to the honesty and genuineness of the research data, while reliability relates to the reproducibility and stability of the data.

The validity of research findings refers to the extent to which the findings are an accurate representation of the phenomena they are intended to represent. The reliability of a study refers to the reproducibility of the findings. Validity can be substantiated by a number of techniques including triangulation use of contradictory evidence, respondent validation, and constant comparison. Triangulation is using 2 or more methods to study the same phenomenon. Contradictory evidence, often known as deviant cases, must be sought out, examined, and accounted for in the analysis to ensure that researcher bias does not interfere with or alter their perception of the data and any insights offered. Respondent validation, which is allowing participants to read through the data and analyses and provide feedback on the researchers' interpretations of their responses, provides researchers with a method of checking for inconsistencies, challenges the researchers' assumptions, and provides them with an opportunity to re-analyze their data. The use of constant comparison means that one piece of data (for example, an interview) is compared with previous data and not considered on its own, enabling researchers to treat the data as a whole rather than fragmenting it. Constant comparison also enables the researcher to identify emerging/unanticipated themes within the research project.

STRENGTHS AND LIMITATIONS OF QUALITATIVE RESEARCH

Qualitative researchers have been criticized for overusing interviews and focus groups at the expense of other methods such as ethnography, observation, documentary analysis, case studies, and conversational analysis. Qualitative research has numerous strengths when properly conducted.

Strengths of Qualitative Research

• Issues can be examined in detail and in depth.
• Interviews are not restricted to specific questions and can be guided/redirected by the researcher in real time.
• The research framework and direction can be quickly revised as new information emerges.
• The data based on human experience that is obtained is powerful and sometimes more compelling than quantitative data.
• Subtleties and complexities about the research subjects and/or topic are discovered that are often missed by more positivistic enquiries.
• Data usually are collected from a few cases or individuals so findings cannot be generalized to a larger population. Findings can however be transferable to another setting.

Limitations of Qualitative Research

• Research quality is heavily dependent on the individual skills of the researcher and more easily influenced by the researcher's personal biases and idiosyncrasies.
• Rigor is more difficult to maintain, assess, and demonstrate.
• The volume of data makes analysis and interpretation time consuming.
• It is sometimes not as well understood and accepted as quantitative research within the scientific community
• The researcher's presence during data gathering, which is often unavoidable in qualitative research, can affect the subjects' responses.
• Issues of anonymity and confidentiality can present problems when presenting findings
• Findings can be more difficult and time consuming to characterize in a visual way.

PRESENTATION OF QUALITATIVE RESEARCH FINDINGS

The following extracts are examples of how qualitative data might be presented:

Data From an Interview.

The following is an example of how to present and discuss a quote from an interview.

The researcher should select quotes that are poignant and/or most representative of the research findings. Including large portions of an interview in a research paper is not necessary and often tedious for the reader. The setting and speakers should be established in the text at the end of the quote.

The student describes how he had used deep learning in a dispensing module. He was able to draw on learning from a previous module, “I found that while using the e learning programme I was able to apply the knowledge and skills that I had gained in last year's diseases and goals of treatment module.” (interviewee 22, male)

This is an excerpt from an article on curriculum reform that used interviews 5 :

The first question was, “Without the accreditation mandate, how much of this curriculum reform would have been attempted?” According to respondents, accreditation played a significant role in prompting the broad-based curricular change, and their comments revealed a nuanced view. Most indicated that the change would likely have occurred even without the mandate from the accreditation process: “It reflects where the profession wants to be … training a professional who wants to take on more responsibility.” However, they also commented that “if it were not mandated, it could have been a very difficult road.” Or it “would have happened, but much later.” The change would more likely have been incremental, “evolutionary,” or far more limited in its scope. “Accreditation tipped the balance” was the way one person phrased it. “Nobody got serious until the accrediting body said it would no longer accredit programs that did not change.”

Data From Observations

The following example is some data taken from observation of pharmacist patient consultations using the Calgary Cambridge guide. 6 , 7 The data are first presented and a discussion follows:

Pharmacist: We will soon be starting a stop smoking clinic. Patient: Is the interview over now? Pharmacist: No this is part of it. (Laughs) You can't tell me to bog off (sic) yet. (pause) We will be starting a stop smoking service here, Patient: Yes. Pharmacist: with one-to-one and we will be able to help you or try to help you. If you want it. In this example, the pharmacist has picked up from the patient's reaction to the stop smoking clinic that she is not receptive to advice about giving up smoking at this time; in fact she would rather end the consultation. The pharmacist draws on his prior relationship with the patient and makes use of a joke to lighten the tone. He feels his message is important enough to persevere but he presents the information in a succinct and non-pressurised way. His final comment of “If you want it” is important as this makes it clear that he is not putting any pressure on the patient to take up this offer. This extract shows that some patient cues were picked up, and appropriately dealt with, but this was not the case in all examples.

Data From Focus Groups

This excerpt from a study involving 11 focus groups illustrates how findings are presented using representative quotes from focus group participants. 8

Those pharmacists who were initially familiar with CPD endorsed the model for their peers, and suggested it had made a meaningful difference in the way they viewed their own practice. In virtually all focus groups sessions, pharmacists familiar with and supportive of the CPD paradigm had worked in collaborative practice environments such as hospital pharmacy practice. For these pharmacists, the major advantage of CPD was the linking of workplace learning with continuous education. One pharmacist stated, “It's amazing how much I have to learn every day, when I work as a pharmacist. With [the learning portfolio] it helps to show how much learning we all do, every day. It's kind of satisfying to look it over and see how much you accomplish.” Within many of the learning portfolio-sharing sessions, debates emerged regarding the true value of traditional continuing education and its outcome in changing an individual's practice. While participants appreciated the opportunity for social and professional networking inherent in some forms of traditional CE, most eventually conceded that the academic value of most CE programming was limited by the lack of a systematic process for following-up and implementing new learning in the workplace. “Well it's nice to go to these [continuing education] events, but really, I don't know how useful they are. You go, you sit, you listen, but then, well I at least forget.”

The following is an extract from a focus group (conducted by the author) with first-year pharmacy students about community placements. It illustrates how focus groups provide a chance for participants to discuss issues on which they might disagree.

Interviewer: So you are saying that you would prefer health related placements? Student 1: Not exactly so long as I could be developing my communication skill. Student 2: Yes but I still think the more health related the placement is the more I'll gain from it. Student 3: I disagree because other people related skills are useful and you may learn those from taking part in a community project like building a garden. Interviewer: So would you prefer a mixture of health and non health related community placements?

GUIDANCE FOR PUBLISHING QUALITATIVE RESEARCH

Qualitative research is becoming increasingly accepted and published in pharmacy and medical journals. Some journals and publishers have guidelines for presenting qualitative research, for example, the British Medical Journal 9 and Biomedcentral . 10 Medical Education published a useful series of articles on qualitative research. 11 Some of the important issues that should be considered by authors, reviewers and editors when publishing qualitative research are discussed below.

Introduction.

A good introduction provides a brief overview of the manuscript, including the research question and a statement justifying the research question and the reasons for using qualitative research methods. This section also should provide background information, including relevant literature from pharmacy, medicine, and other health professions, as well as literature from the field of education that addresses similar issues. Any specific educational or research terminology used in the manuscript should be defined in the introduction.

The methods section should clearly state and justify why the particular method, for example, face to face semistructured interviews, was chosen. The method should be outlined and illustrated with examples such as the interview questions, focusing exercises, observation criteria, etc. The criteria for selecting the study participants should then be explained and justified. The way in which the participants were recruited and by whom also must be stated. A brief explanation/description should be included of those who were invited to participate but chose not to. It is important to consider “fair dealing,” ie, whether the research design explicitly incorporates a wide range of different perspectives so that the viewpoint of 1 group is never presented as if it represents the sole truth about any situation. The process by which ethical and or research/institutional governance approval was obtained should be described and cited.

The study sample and the research setting should be described. Sampling differs between qualitative and quantitative studies. In quantitative survey studies, it is important to select probability samples so that statistics can be used to provide generalizations to the population from which the sample was drawn. Qualitative research necessitates having a small sample because of the detailed and intensive work required for the study. So sample sizes are not calculated using mathematical rules and probability statistics are not applied. Instead qualitative researchers should describe their sample in terms of characteristics and relevance to the wider population. Purposive sampling is common in qualitative research. Particular individuals are chosen with characteristics relevant to the study who are thought will be most informative. Purposive sampling also may be used to produce maximum variation within a sample. Participants being chosen based for example, on year of study, gender, place of work, etc. Representative samples also may be used, for example, 20 students from each of 6 schools of pharmacy. Convenience samples involve the researcher choosing those who are either most accessible or most willing to take part. This may be fine for exploratory studies; however, this form of sampling may be biased and unrepresentative of the population in question. Theoretical sampling uses insights gained from previous research to inform sample selection for a new study. The method for gaining informed consent from the participants should be described, as well as how anonymity and confidentiality of subjects were guaranteed. The method of recording, eg, audio or video recording, should be noted, along with procedures used for transcribing the data.

Data Analysis.

A description of how the data were analyzed also should be included. Was computer-aided qualitative data analysis software such as NVivo (QSR International, Cambridge, MA) used? Arrival at “data saturation” or the end of data collection should then be described and justified. A good rule when considering how much information to include is that readers should have been given enough information to be able to carry out similar research themselves.

One of the strengths of qualitative research is the recognition that data must always be understood in relation to the context of their production. 1 The analytical approach taken should be described in detail and theoretically justified in light of the research question. If the analysis was repeated by more than 1 researcher to ensure reliability or trustworthiness, this should be stated and methods of resolving any disagreements clearly described. Some researchers ask participants to check the data. If this was done, it should be fully discussed in the paper.

An adequate account of how the findings were produced should be included A description of how the themes and concepts were derived from the data also should be included. Was an inductive or deductive process used? The analysis should not be limited to just those issues that the researcher thinks are important, anticipated themes, but also consider issues that participants raised, ie, emergent themes. Qualitative researchers must be open regarding the data analysis and provide evidence of their thinking, for example, were alternative explanations for the data considered and dismissed, and if so, why were they dismissed? It also is important to present outlying or negative/deviant cases that did not fit with the central interpretation.

The interpretation should usually be grounded in interviewees or respondents' contributions and may be semi-quantified, if this is possible or appropriate, for example, “Half of the respondents said …” “The majority said …” “Three said…” Readers should be presented with data that enable them to “see what the researcher is talking about.” 1 Sufficient data should be presented to allow the reader to clearly see the relationship between the data and the interpretation of the data. Qualitative data conventionally are presented by using illustrative quotes. Quotes are “raw data” and should be compiled and analyzed, not just listed. There should be an explanation of how the quotes were chosen and how they are labeled. For example, have pseudonyms been given to each respondent or are the respondents identified using codes, and if so, how? It is important for the reader to be able to see that a range of participants have contributed to the data and that not all the quotes are drawn from 1 or 2 individuals. There is a tendency for authors to overuse quotes and for papers to be dominated by a series of long quotes with little analysis or discussion. This should be avoided.

Participants do not always state the truth and may say what they think the interviewer wishes to hear. A good qualitative researcher should not only examine what people say but also consider how they structured their responses and how they talked about the subject being discussed, for example, the person's emotions, tone, nonverbal communication, etc. If the research was triangulated with other qualitative or quantitative data, this should be discussed.

Discussion.

The findings should be presented in the context of any similar previous research and or theories. A discussion of the existing literature and how this present research contributes to the area should be included. A consideration must also be made about how transferrable the research would be to other settings. Any particular strengths and limitations of the research also should be discussed. It is common practice to include some discussion within the results section of qualitative research and follow with a concluding discussion.

The author also should reflect on their own influence on the data, including a consideration of how the researcher(s) may have introduced bias to the results. The researcher should critically examine their own influence on the design and development of the research, as well as on data collection and interpretation of the data, eg, were they an experienced teacher who researched teaching methods? If so, they should discuss how this might have influenced their interpretation of the results.

Conclusion.

The conclusion should summarize the main findings from the study and emphasize what the study adds to knowledge in the area being studied. Mays and Pope suggest the researcher ask the following 3 questions to determine whether the conclusions of a qualitative study are valid 12 : How well does this analysis explain why people behave in the way they do? How comprehensible would this explanation be to a thoughtful participant in the setting? How well does the explanation cohere with what we already know?

CHECKLIST FOR QUALITATIVE PAPERS

This paper establishes criteria for judging the quality of qualitative research. It provides guidance for authors and reviewers to prepare and review qualitative research papers for the American Journal of Pharmaceutical Education . A checklist is provided in Appendix 1 to assist both authors and reviewers of qualitative data.

ACKNOWLEDGEMENTS

Thank you to the 3 reviewers whose ideas helped me to shape this paper.

Appendix 1. Checklist for authors and reviewers of qualitative research.

Introduction

• □ Research question is clearly stated.
• □ Research question is justified and related to the existing knowledge base (empirical research, theory, policy).
• □ Any specific research or educational terminology used later in manuscript is defined.
• □ The process by which ethical and or research/institutional governance approval was obtained is described and cited.
• □ Reason for choosing particular research method is stated.
• □ Criteria for selecting study participants are explained and justified.
• □ Recruitment methods are explicitly stated.
• □ Details of who chose not to participate and why are given.
• □ Study sample and research setting used are described.
• □ Method for gaining informed consent from the participants is described.
• □ Maintenance/Preservation of subject anonymity and confidentiality is described.
• □ Method of recording data (eg, audio or video recording) and procedures for transcribing data are described.
• □ Methods are outlined and examples given (eg, interview guide).
• □ Decision to stop data collection is described and justified.
• □ Data analysis and verification are described, including by whom they were performed.
• □ Methods for identifying/extrapolating themes and concepts from the data are discussed.
• □ Sufficient data are presented to allow a reader to assess whether or not the interpretation is supported by the data.
• □ Outlying or negative/deviant cases that do not fit with the central interpretation are presented.
• □ Transferability of research findings to other settings is discussed.
• □ Findings are presented in the context of any similar previous research and social theories.
• □ Discussion often is incorporated into the results in qualitative papers.
• □ A discussion of the existing literature and how this present research contributes to the area is included.
• □ Any particular strengths and limitations of the research are discussed.
• □ Reflection of the influence of the researcher(s) on the data, including a consideration of how the researcher(s) may have introduced bias to the results is included.

Conclusions

• □ The conclusion states the main finings of the study and emphasizes what the study adds to knowledge in the subject area.

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Reporting Research Results in APA Style | Tips & Examples

Published on December 21, 2020 by Pritha Bhandari . Revised on January 17, 2024.

The results section of a quantitative research paper is where you summarize your data and report the findings of any relevant statistical analyses.

The APA manual provides rigorous guidelines for what to report in quantitative research papers in the fields of psychology, education, and other social sciences.

Use these standards to answer your research questions and report your data analyses in a complete and transparent way.

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Table of contents

What goes in your results section, introduce your data, summarize your data, report statistical results, presenting numbers effectively, what doesn’t belong in your results section, frequently asked questions about results in apa.

In APA style, the results section includes preliminary information about the participants and data, descriptive and inferential statistics, and the results of any exploratory analyses.

Include these in your results section:

• Participant flow and recruitment period. Report the number of participants at every stage of the study, as well as the dates when recruitment took place.
• Missing data . Identify the proportion of data that wasn’t included in your final analysis and state the reasons.
• Any adverse events. Make sure to report any unexpected events or side effects (for clinical studies).
• Descriptive statistics . Summarize the primary and secondary outcomes of the study.
• Inferential statistics , including confidence intervals and effect sizes. Address the primary and secondary research questions by reporting the detailed results of your main analyses.
• Results of subgroup or exploratory analyses, if applicable. Place detailed results in supplementary materials.

Write up the results in the past tense because you’re describing the outcomes of a completed research study.

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Before diving into your research findings, first describe the flow of participants at every stage of your study and whether any data were excluded from the final analysis.

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It’s necessary to report any attrition, which is the decline in participants at every sequential stage of a study. That’s because an uneven number of participants across groups sometimes threatens internal validity and makes it difficult to compare groups. Be sure to also state all reasons for attrition.

If your study has multiple stages (e.g., pre-test, intervention, and post-test) and groups (e.g., experimental and control groups), a flow chart is the best way to report the number of participants in each group per stage and reasons for attrition.

Also report the dates for when you recruited participants or performed follow-up sessions.

Missing data

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Data can become unusable due to equipment malfunctions, improper storage, unexpected events, participant ineligibility, and so on. For each case, state the reason why the data were unusable.

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If you applied any techniques for overcoming or compensating for lost data, report those as well.

Adverse events

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Descriptive statistics summarize your data for the reader. Present descriptive statistics for each primary, secondary, and subgroup analysis.

Don’t provide formulas or citations for commonly used statistics (e.g., standard deviation) – but do provide them for new or rare equations.

Descriptive statistics

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Include sample sizes (overall and for each group) as well as appropriate measures of central tendency and variability for the outcomes in your results section. For every point estimate , add a clearly labelled measure of variability as well.

Be sure to note how you combined data to come up with variables of interest. For every variable of interest, explain how you operationalized it.

According to APA journal standards, it’s necessary to report all relevant hypothesis tests performed, estimates of effect sizes, and confidence intervals.

When reporting statistical results, you should first address primary research questions before moving onto secondary research questions and any exploratory or subgroup analyses.

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Report the following for each hypothesis test:

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When reporting complex data analyses, such as factor analysis or multivariate analysis, present the models estimated in detail, and state the statistical software used. Make sure to report any violations of statistical assumptions or problems with estimation.

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Confidence intervals are useful for showing the variability around point estimates. They should be included whenever you report population parameter estimates.

Effect sizes indicate how impactful the outcomes of a study are. But since they are estimates, it’s recommended that you also provide confidence intervals of effect sizes.

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Briefly report the results of any other planned or exploratory analyses you performed. These may include subgroup analyses as well.

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While these analyses can be reported in less detail in the main text, you can provide the full analyses in supplementary materials.

To effectively present numbers, use a mix of text, tables , and figures where appropriate:

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Since these are general guidelines, use your own judgment and feedback from others for effective presentation of numbers.

Tables and figures should be numbered and have titles, along with relevant notes. Make sure to present data only once throughout the paper and refer to any tables and figures in the text.

Formatting statistics and numbers

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It’s important to provide a complete picture of your data analyses and outcomes in a concise way. For that reason, raw data and any interpretations of your results are not included in the results section.

It’s rarely appropriate to include raw data in your results section. Instead, you should always save the raw data securely and make them available and accessible to any other researchers who request them.

Making scientific research available to others is a key part of academic integrity and open science.

Interpretation or discussion of results

This belongs in your discussion section. Your results section is where you objectively report all relevant findings and leave them open for interpretation by readers.

While you should state whether the findings of statistical tests lend support to your hypotheses, refrain from forming conclusions to your research questions in the results section.

Explanation of how statistics tests work

For the sake of concise writing, you can safely assume that readers of your paper have professional knowledge of how statistical inferences work.

In an APA results section , you should generally report the following:

• Participant flow and recruitment period.
• Missing data and any adverse events.
• Descriptive statistics about your samples.
• Inferential statistics , including confidence intervals and effect sizes.
• Results of any subgroup or exploratory analyses, if applicable.

According to the APA guidelines, you should report enough detail on inferential statistics so that your readers understand your analyses.

• the test statistic value
• the degrees of freedom
• the exact p value (unless it is less than 0.001)
• the magnitude and direction of the effect

You should also present confidence intervals and estimates of effect sizes where relevant.

In APA style, statistics can be presented in the main text or as tables or figures . To decide how to present numbers, you can follow APA guidelines:

• To present three or fewer numbers, try a sentence,
• To present between 4 and 20 numbers, try a table,
• To present more than 20 numbers, try a figure.

Results are usually written in the past tense , because they are describing the outcome of completed actions.

The results chapter or section simply and objectively reports what you found, without speculating on why you found these results. The discussion interprets the meaning of the results, puts them in context, and explains why they matter.

In qualitative research , results and discussion are sometimes combined. But in quantitative research , it’s considered important to separate the objective results from your interpretation of them.

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Qualitative Results and Discussion

• First Online: 20 August 2020

Cite this chapter

• Peijian Paul Sun 2  

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This chapter presents the results and discussion in line with the five research questions of the present study based on the qualitative data collected from the focus groups and semi-structured interviews. A total of 7 focus groups and 10 semi-structured interviews were conducted to explore the research questions from a more in-depth qualitative perspective. Two types of interviews were utilized in order to bring different lines of insights together to ensure that more profound and appropriate understandings of the research questions could be facilitated. This chapter starts with an introduction to the background information of the participants and the coding system. The qualitative findings in relation to each research question are presented sequentially followed by a summary and discussion.

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Alrabai, Fakieh. 2015. The Influence of Teachers’ Anxiety-Reducing Strategies on Learners’ Foreign Language Anxiety. Innovation in Language Learning and Teaching 9 (2): 128–163. https://doi.org/10.1080/17501229.2014.890203 .

Article   Google Scholar  

Amiryousefi, Mohammad. 2018. Willingness to Communicate, Interest, Motives to Communicate with the Instructor, and L2 Speaking: A Focus on the Role of Age and Gender. Innovation in Language Learning and Teaching 12 (3): 221–234. https://doi.org/10.1080/17501229.2016.1170838 .

Armon-Lotem, Sharon, Susan Joffe, Hadar Abutbul-Oz, Carmit Altman, and Joel Walters. 2014. Language Exposure, Ethnolinguistic Identity and Attitudes in the Acquisition of Hebrew as a Second Language among Bilingual Preschool Children from Russian- and English-Speaking Backgrounds. In Input and Experience in Bilingual Development , edited by Theres Grüter and Johanne Paradis, 77–98. Amsterdam, Netherlands: John Benjamins.

Google Scholar  

Bright, Peter, Julia Ouzia, and Roberto Filippi. 2019. Multilingualism and Metacognitive Processing. In The Handbook of the Neuroscience of Multilingualism , ed. John W. Schwieter, 355–371. Chichester, UK: Wiley. https://doi.org/10.1002/9781119387725.ch17 .

Caprara, Gian Vittorio, Michele Vecchione, Guido Alessandri, Maria Gerbino, and Claudio Barbaranelli. 2011. The Contribution of Personality Traits and Self-Efficacy Beliefs to Academic Achievement: A Longitudinal Study. British Journal of Educational Psychology 81 (1): 78–96. https://doi.org/10.1348/2044-8279.002004 .

Cenoz, Jasone, and Durk Gorter. 2019. Multilingualism, Translanguaging, and Minority Languages in SLA. The Modern Language Journal 103: 130–135. https://doi.org/10.1111/modl.12529 .

Clément, Richard, Susuan C. Baker, and Peter D. MacIntyre. 2003. Willingness to Communicate in a Second Language: The Effect of Context, Norms, and Vitality. Journal of Language and Social Psychology 22: 190–209.

Dörnyei, Zoltán. 2005. The Psychology of the Language Learner: Individual Differences in Second Language Acquisition . Mahwah, NJ: Lawrence Erlbaum.

Dörnyei, Zoltán. 2009. The L2 Motivational Self System. In Motivation, Language Identity and the L2 Self , edited by Zoltán Dörnyei and Ema Ushioda, 9–42. Bristol, UK: Multilingual Matters.

Effiong, Okon. 2016. Getting Them Speaking: Classroom Social Factors and Foreign Language Anxiety. TESOL Journal 7 (1): 132–161. https://doi.org/10.1002/tesj.194 .

Florack, Arnd, Anette Rohmann, Johanna Palcu, and Agostino Mazziotta. 2014. How Initial Cross-Group Friendships Prepare for Intercultural Communication: The Importance of Anxiety Reduction and Self-Confidence in Communication. International Journal of Intercultural Relations 43, Part B (0): 278–288. https://doi.org///dx.doi.org/10.1016/j.ijintrel.2014.09.004 .

Ghorbani, Mohammad Reza, and Seyyed Ehsan Golparvar. 2019. Modeling the Relationship between Socioeconomic Status, Self-Initiated, Technology-Enhanced Language Learning, and Language Outcome. Computer Assisted Language Learning 1–21. https://doi.org/10.1080/09588221.2019.1585374 .

Hernández, Todd A. 2006. Integrative Motivation as a Predictor of Success in the Intermediate Foreign Language Classroom. Foreign Language Annals 22: 30–37.

Hu, Hsueh-chao Marcella, and Hossein Nassaji. 2014. Lexical Inferencing Strategies: The Case of Successful versus Less Successful Inferencers. System 45 (1): 27–38. https://doi.org/10.1016/j.system.2014.04.004 .

Huang, Becky, Yung-Hsiang Shawn Chang, Luping Niu, and Mingxia Zhi. 2018. Examining the Effects of Socio-Economic Status and Language Input on Adolescent English Learners’ Speech Production Outcomes. System 73: 27–36. https://doi.org/10.1016/j.system.2017.07.004 .

Hyland, Ken. 1993. Culture and Learning: A Study of the Learning Style Preferences of Japanese Students. RELC Journal 24 (2): 69–87. https://doi.org/10.1177/003368829302400204 .

Kang, Su-Ja. 2005. Dynamic Emergence of Situational Willingness to Communicate in a Second Language. System 33 (2): 277–292. https://doi.org/10.1016/j.system.2004.10.004 .

Khajavy, Gholam Hassan, Peter D. MacIntyre, and Elyas Barabadi. 2018. Role of the Emotions and Classroom Environment in Willingness to Communicate: Applying Doubly Latent Multilevel Analysis in Second Language Acquisition Research. Studies in Second Language Acquisition 40 (3): 605–624. https://doi.org/10.1017/S0272263117000304 .

Kim, Tae-Young, and Yoon-Kyoung Kim. 2014. A Structural Model for Perceptual Learning Styles, the Ideal L2 Self, Motivated Behavior, and English Proficiency. System 46 (0): 14–27. https://doi.org///dx.doi.org/10.1016/j.system.2014.07.007 .

Kırkgöz, Yasemin. 2018. Fostering Young Learners’ Listening and Speaking Skills. In The Routledge Handbook of Teaching English to Young Learners , ed. Sue Carton and Fiona Copland, 171–187. Routledge.

Krashen, Stephen D. 1982. Principles and Practice in Second Language Acquisition . Oxford, UK: Pergamon.

Liu, Meihua, and Wenhong Huang. 2011. An Exploration of Foreign Language Anxiety and English Learning Motivation. Education Research International 12: 1–8.

MacIntyre, Peter D. 2007. Willingness to Communicate in the Second Language: Understanding the Decision to Speak as a Volitional Process. The Modern Language Journal 91 (4): 564–576. https://doi.org/10.1111/j.1540-4781.2007.00623.x .

MacIntyre, Peter D., Zoltán Dörnyei, Richard Clément, and Kimberly A. Noels. 1998. Conceptualizing Willingness to Communicate in a L2: A Situational Model of L2 Confidence and Affiliation. The Modern Language Journal 82 (4): 545–62. https://doi.org/10.1111/j.1540-4781.1998.tb05543.x .

Magogwe, Joel Mokuedi, and Rhonda Oliver. 2007. The Relationship Between Language Learning Strategies, Proficiency, Age and Self-Efficacy Beliefs: A Study of Language Learners in Botswana. System 35 (3): 338–352. https://doi.org/10.1016/j.system.2007.01.003 .

Mahmoodzadeh, Masoud. 2012. Investigating Foreign Language Speaking Anxiety within the EFL Learner’s Interlanguage System: The Case of Iranian Learners. Journal of Language Teaching and Research 3 (3): 466–476. https://doi.org/10.4304/jltr.3.3.466-476 .

Minagawa, Harumi, Dallas Nesbitt, Masayoshi Ogino, Junji Kawai, and Ryoko de Burgh-Hirabe. 2019. Why I Am Studying Japanese: A National Survey Revealing the Voices of New Zealand Tertiary Students. Japanese Studies. https://doi.org/10.1080/10371397.2019.1678365 .

Nakatani, Yasuo. 2006. Developing an Oral Communication Strategy Inventory. The Modern Language Journal 90 (2): 151–168. https://doi.org/10.1111/j.1540-4781.2006.00390.x .

Nakatani, Yasuo, and Christine Goh. 2007. A Review of Oral Communication Strategies: Focus on Interactionist and Psycholinguistic Perspectives. In Language Learner Strategies: Thirty Years of Research and Practice , ed. Andrew D. Cohen and Ernesto Macaro, 207–227. Oxford, UK: Oxford University Press.

Naserieh, Farid, and Mohammad Reza Anani Sarab. 2013. Perceptual Learning Style Preferences among Iranian Graduate Students. System 41 (1): 122–133. https://doi.org/10.1016/j.system.2013.01.018 .

Nicolson, Margaret, and Helga Adams. 2008. Travelling in Space and Encounters of the Third Kind: Distance Language Learner Negotiation of Speaking Activities. Innovation in Language Learning and Teaching 2 (2): 105–116. https://doi.org/10.1080/17501220802158859 .

Nomura, Kazuyuki, and Rui Yuan. 2019. Long-Term Motivations for L2 Learning: A Biographical Study from a Situated Learning Perspective. Journal of Multilingual and Multicultural Development 40 (2): 164–178. https://doi.org/10.1080/01434632.2018.1497041 .

Oxford, Rebecca L. 1990. Language Learning Strategies: What Every Teacher Should Know . Boston, MA: Heinle and Heinle.

Peacock, Matthew. 2001. Match or Mismatch? Learning Styles and Teaching Styles in EFL. International Journal of Applied Linguistics 11 (1): 1–20. https://doi.org/10.1111/1473-4192.00001 .

Peng, Jian-E. 2019. The Roles of Multimodal Pedagogic Effects and Classroom Environment in Willingness to Communicate in English. System 82: 161–173. https://doi.org/10.1016/j.system.2019.04.006 .

Phongsa, Manivone, Shaik Abdul Malik Mohamed Ismail, and Hui Min Low. 2018. Multilingual Effects on EFL Learning: A Comparison of Foreign Language Anxiety Experienced by Monolingual and Bilingual Tertiary Students in the Lao PDR. Journal of Multilingual and Multicultural Development 39 (3): 271–282. https://doi.org/10.1080/01434632.2017.1371723 .

Psaltou-Joycey, Angeliki, and Zoe Gavriilidou. 2018. Language Learning Strategies of Greek EFL Primary and Secondary School Learners: How Individual Characteristics Affect Strategy Use. In Language Learning Strategies and Individual Learner Characteristics: Situating Strategy Use in Diverse Contexts , ed. Rebecca L. Oxford and Carmen M. Amerstorfer, 167–187. London, UK: Bloomsbury.

Ryan, Richard M., and Edward L. Deci. 2000. Self-Determination Theory and the Facilitation of Intrinsic Motivation, Social Development, and Well-Being. American Psychologist 55 (1): 68–78. https://doi.org/10.1037/0003-066X.55.1.68 .

Saito, Kazuya, Masatoshi Sato, and Roy Lyster. 2013. Oral Corrective Feedback in Second Language Classrooms. Language Teaching 46 (2): 1–40.

Sauer, Luzia, and Rod Ellis. 2019. The Social Lives of Adolescent Study Abroad Learners and Their L2 Development. The Modern Language Journal 103 (4): 739–762. https://doi.org/10.1111/modl.12589 .

Schauer, Gila A. 2006. The Development of ESL Learners’ Pragmatic Competence: A Longitudinal Investigation of Awareness and Production. In Pragmatics and Language Learning Volume 11 , edited by Kathleen Bardovi-Harlig, César Félix-Brasdefer, and Alwiya S. Omar, 135–64. Mānoa, HI: University of Hawaii Press.

Scovel, Thomas. 1978. The Effect of Affect on Foreign Language Learning: A Review of the Anxiety Research. Language Learning 28 (1): 129–142. https://doi.org/10.1111/j.1467-1770.1978.tb00309.x .

Segalowitz, Norman. 2010. Cognitive Bases of Second Language Fluency . New York, NY: Routledge.

Shaikholeslami, Razieh, and Mohammad Khayyer. 2006. Intrinsic Motivation, Extrinsic Motivation, and Learning English as a Foreign Language. Psychological Reports 99 (3): 813–818.

Stewart, David W, and Prem N Shamdasani. 2015. Focus Groups: Theory and Practice . 3rd ed. Thousand Oaks, CA: Sage.

Taguchi, Naoko, Feng Xiao, and Shuai Li. 2016. Effects of Intercultural Competence and Social Contact on Speech Act Production in a Chinese Study Abroad Context. Modern Language Journal 100 (4): 775–796. https://doi.org/10.1111/modl.12349 .

Tarone, Elaine. 1981. Some Thoughts on the Notion of Communication Strategy. TESOL Quarterly 15 (3): 285–95. https://doi.org/10.2307/3586754 .

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Sun, P.P. (2020). Qualitative Results and Discussion. In: Chinese as a Second Language Multilinguals’ Speech Competence and Speech Performance. Springer, Singapore. https://doi.org/10.1007/978-981-15-6941-8_7

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• Published: 13 September 2024

A qualitative analysis of health service problems and the strategies used to manage them in the COVID-19 pandemic: exploiting generic and context-specific approaches

• Hania Rahimi-Ardabili 1 ,
• Farah Magrabi 1 ,
• Brenton Sanderson 1 , 2 ,
• Thilo Schuler 1 , 3 &
• Enrico Coiera 1  

BMC Health Services Research volume  24 , Article number:  1067 ( 2024 ) Cite this article

Metrics details

The COVID-19 pandemic disrupted health systems around the globe. Lessons from health systems responses to these challenges may help design effective and sustainable health system responses for future challenges. This study aimed to 1/ identify the broad types of health system challenges faced during the pandemic and 2/ develop a typology of health system response to these challenges.

Semi-structured one-on-one online interviews explored the experience of 19 health professionals during COVID-19 in a large state health system in Australia. Data were analysed using constant comparative analysis utilising a sociotechnical system lens.

Participants described four overarching challenges: 1/ System overload, 2/ Barriers to decision-making, 3/ Education or training gaps, and 4/ Limitations of existing services. The limited time often available to respond meant that specific and well-designed strategies were often not possible, and more generic strategies that relied on the workforce to modify solutions and repair unexpected gaps were common. For example, generic responses to system overload included working longer hours, whilst specific strategies utilised pre-existing technical resources (e.g. converting non-emergency wards into COVID-19 wards).

During the pandemic, it was often not possible to rely on mature strategies to frame responses, and more generic, emergent approaches were commonly required when urgent responses were needed. The degree to which specific strategies were ready-to-hand appeared to dictate how much a strategy relied on such generic approaches. The workforce played a pivotal role in enabling emergent responses that required dealing with uncertainties.

Peer Review reports

The COVID-19 pandemic has posed a significant challenge to health systems worldwide, and many have struggled to cope, especially in the early stages [ 1 ]. The global consequences of COVID-19 on health systems are measured in loss or impairment of lives [ 2 ], healthcare professional burnout [ 3 ], reduced services, and delayed care [ 4 , 5 ].

Unfortunately, it is highly probable that health systems will confront many more such crises, with climate change risks amongst these [ 6 ]. Understanding what was common to successful COVID-19 strategies, and what was shared amongst failed ones could be instructive as we prepare for the future. The pandemic affected every aspect of operations from planning and procurement to care delivery [ 7 , 8 ]. Services, processes and tools were repurposed or created ad hoc, often from the ground up [ 9 , 10 ]. Hospitals for instance, responded by repurposing existing facilities and wards, and implementing strategies to cope with sudden rises in patient numbers that overwhelmed existing critical care services such as intensive care units [ 11 , 12 ]. The initial phase of the pandemic witnessed immediate actions, some of which succeeded such as the development of mRNA vaccines [ 13 ] and others that failed such as certain COVID-19 contact tracing applications [ 14 ].

The challenges healthcare professionals experienced during the COVID-19 pandemic has had some attention in the research literature. For example, a 2021 systematic review examining the COVID-19 burden on healthcare workers from nine different countries identified four main challenges of inadequate preparedness; emotional challenges; insufficient equipment and information; and work burnout [ 15 ].

This study goes beyond describing the challenges faced, and examines the responses to these problems using the lens of sociotechnical system theory (STS) [ 16 ]. STS thinking sees system processes as the emergent outcome of interactions between people and technology [ 16 ].

Using first-hand stories from healthcare professionals, this study first describes the different health service problems experienced by health professionals during the pandemic. Next, we attempt to categorise the different strategies they employed to deal with these problems, exploring how people and technologies came together to craft responses to these problems during the pandemic. We develop a typology of responses that identifies the different roles for generic (general-purpose strategies), and specific (local or health service-specific) approaches. Identifying the circumstances in which each of these strategy types was used may assist in preparedness and guide future crisis responses.

A series of semi-structured interviews explored the firsthand experiences of healthcare professionals in either developing or making COVID-19 pandemic responses. We utilised a qualitative and interpretive approach, which aims to generate new hypotheses by exploring emergent relationships between descriptions of phenomena [ 17 , 18 ]. This manuscript follows the COREQ (Consolidated Criteria for Reporting Qualitative Research) guidelines (See Additional file 1 for the checklist).

Participants and setting

Health system staff from a variety of professional groups and levels of seniority were recruited. Health professionals who had been involved in the pandemic response in New South Wales (NSW) were eligible for interviews. These included medical specialists (e.g. respiratory physicians), nurses and midwives, general practitioners (GPs), allied health workers (e.g. physiotherapists working in ICUs), health service executives and administrative staff, and paramedics. Participants were selected from a diverse range of health professions and services, including hospitals, public health organisations, and laboratories, in both public and private sectors as well as rural and urban settings. Our target sample size of 20 was informed by a systematic review of 14 qualitative studies that explored the experiences of healthcare professionals during the pandemic and concluded that on average, past studies reached data saturation with approximately 15 participants [ 19 ].

NSW is an Australian state with over eight million people. It includes about 9,600 full-time equivalent GPs [ 20 ] and 2000 registered pharmacies [ 21 ] governed by the federal government [ 22 ]. Further, NSW Health is the public health system for the state and includes NSW Ambulance, NSW Health Pathology, eHealth NSW, Health Protection NSW (public health legislation and surveillance), and Local Health Districts (LHDs) [ 23 ]. LHDs encompass hospitals, home hospitals, hospital pharmacies, aged health and disabilities, mental health, aboriginal health, drug health, and public health including immunisation [ 24 ]. During 2020-21, NSW had a total of 228 public hospitals and 210 private hospitals [ 25 ], and over 150 pathology collection centres [ 26 ]. Participants in this study were from general practices and community pharmacies, as well as NSW Health, including NSW Ambulance, Health Pathology (including COVID-19 testing centres), eHealth NSW, hospitals, hospital pharmacies, and immunisation services.

The research team (E.C., B.S., T.S., F.M.) initiated purposive recruitment with a convenience sample [ 27 , 28 ], identifying potential participants within their health system networks. Once enrolled, we used snowballing where participants were asked to forward the study invitation email to others who might be interested. Participants did not have any pre-existing relationship with the interviewer (H.R.-A.) who invited them via email. Transcripts were deidentified by H.R.-A. before sharing them with the other core analysis team (E.C., F.M).

Ethics and consent

Ethics approval was obtained from the Macquarie University Ethics Committee (ID: 11187) prior to commencing the study. Participants provided written informed consent prior to data collection.

Data collection

Data were collected between April and September 2022. At the time of the interview, the COVID-19 vaccine was freely available to the community, and health services in NSW have been providing in-person services in addition to tele-consultation. One-on-one interviews were conducted online using videoconferencing software (Zoom Video Communications, Inc. 2023) with each session lasting an average of 51 min (range: 27–73 min). One of the researchers (H.R-A.) with experience in qualitative interviews was responsible for conducting the interviews. Interviews were transcribed using an AI-based transcription tool (rev.com). A subset of four transcripts were manually checked for transcription accuracy (H.R-A.). Data collection and preliminary analysis were concurrent, with emerging themes from initial analysis reshaping subsequent interview questions and recruitment. Emerging themes about the use of different types of strategies led to new probe questions about strategy and whether such responses were new to the setting. The bulk of the analysis was conducted after data collection.

After the interviewer introduced herself and the reasons for conducting the research (identifying potential approaches for a crises ready health system) participants were asked about: (1) The challenges they faced while providing clinical services during the entire stages of the pandemic; (2) Specific health service responses that they were involved with and (3) what they did differently to pre COVID-19 practices (See Additional file 2 for the initial version of the interview guide).

Data analysis

Data were analysed using constant comparative analysis [ 29 ]. Two early transcripts were open-coded line-by-line to identify emerging concepts and themes (By H.R-A.). To ensure generalisability, these early codes were discussed and refined with a second analyst (E.C.). Codes were further refined and extended during the study by comparing similar categories across participants. An axial coding approach was taken, looking at connections between categories in terms of causation, strategies, consequences, context, and related conditions [ 29 ]. This process continued until all transcripts were coded. Both inductive and deductive approaches were utilised for coding and conceptualising the themes and frameworks.

Data coding was supported by QRS International NVivo ® 12 Software. Visualisation of code connections, codes and data was undertaken using Microsoft Excel. Some codes were grouped into more general constructs, and others were separated into several distinct codes. H.R-A. created memos of each transcript including key quotes, cross-indexed back to the transcripts and documented all process changes in an audit trail.

Reflexivity

Authors (E.C., B.S., T.S.; males) have a clinical background (medical doctors) and two are currently in clinical practice (B.S., T.S.). E.C. (PhD), F.M. (PhD, female) and H.R-A. (PhD, female) were academic researchers at the time of the study. All authors are experienced health system researchers, with prior experience in qualitative research. The interviewer and principal analyst (H.R.-A.) who had no previous contact with any of the participants, deidentified the transcripts before sharing them with other team members. Three participants were willing to provide feedback on the initial analyses.

Analytic framework

We analysed data to identify the types of (1) problems faced by participants or their health services during the COVID-19 pandemic; and (2) the type of health service responses employed to manage these problems. The analysis of health service responses was undertaken using the lens of STS theory which emphasises that system processes are the inevitable consequence of interaction between the people and technology, and that studying either in isolation leads to reductionism that fails to explain how the real world works adequately [ 16 ]. Thus, technological processes were analysed alongside human processes, each shaping the other in a continuous process of human-technology interaction [ 30 , 31 ]. For example, if a participant discussed technology, we probed for human processes related to the technology. We sought to understand the context that led to different social and technical response patterns with specific attention to human and technology interactions. Two researchers (H. R-A. and E.C.) analysed the health service responses reported by interviewees, and differences in interpretation were resolved by discussion.

Participant characteristics

Of 28 invited health professionals, 19 participated in our study. Participants who were involved in the pandemic response were GPs ( n  = 2), pharmacists ( n  = 2), specialists (e.g. emergency physician and respiratory physician), ( n  = 3), nurses and midwives ( n  = 3), allied health workers (e.g. physiotherapist and social worker working in ICU) ( n  = 3), pathologists ( n  = 2), a paramedic ( n  = 1), a clerical officer ( n  = 1) and public health implementation officer/ managers ( n  = 2).

Health service problem types

Participants identified four broad classes of challenges faced by their health services during COVID-19. A summary of challenges is provided below, and a detailed description with example quotes from participants available in Additional File 3 .

Health system overload . The ability for health services to meet the needs of the population as the pandemic unfolded was often compromised because of an imbalance between the supply and demand for resources. System overload was often the result.

Barriers to decision-making : In the rapidly unfolding pandemic, evidence was not being generated and distributed as quickly as health services required, and the communication pathways to share information were sometimes suboptimal.

Education and training gaps : The need to train the public and health service staff as services responded to the pandemic was triggered both by the arrival of new evidence and best-practice guidance needing to be shared widely, or by staff working in roles that were new to them.

Limitations of existing services : Faced with multiple and concurrent challenges, many existing services or care models were found to be inadequate.

Health service response types

Respondents provided a rich account of the different strategies employed to meet the problems faced during the early years of the pandemic, with multiple examples across all four problem types (Additional file 4 ).

High-level analysis of these responses identified that human organisational responses were apparently shaped by the degree of technology maturity and availability. We observed differences in the use of generic responses (applicable to many settings) and specific responses (designed to serve a given service, its unique characteristics and the problems it faced). In this section below, we contrast examples of general and specific responses, presented for each problem type to explore why these strategic differences might have been adopted. Example responses are cross-referenced to relevant quote IDs in brackets, indicating each code’s cell address and item number in the Excel sheet - Additional file 4 as “([Cell address]#[item number when available])”.

Health system overload

Generic overload management strategies: Respondents described increasing the hours worked by staff (quote IDs H03#1, H20, H21), redeploying staff to critical services (quote ID H03#2), hiring new staff (quote IDs H03#3, H20#2, H21#4) or retraining existing staff (quote IDs H14#3, H15#2) to address imbalances between service supply and demand. Work pattern changes included delaying non-urgent care (quote IDs H03#9, H13#7, H66), altering staff/patient ratios in hospitals (quote IDs H03#12, H35#2,6,7), and fast-tracking patient discharge in tandem with home monitoring and support packs for COVID-19 patients (quote ID H03#11). Clinical staff working under difficult circumstances or longer hours were supported with access to accommodation, peer and mental health support (quote IDs H15#7, H21#3, H27#2, H35#5).

The choice of generic responses appeared to be driven by time constraints necessitating immediate solutions (quote ID H20#2). For example, outsourcing recruitment was more expedient than developing new internal processes: “ they hired an external company to I guess source more [staff who] didn’t have the experience that we had it was yeah that’s what effectively led for those long [vaccine] lines… the expectation was the training would come in the same day… the workforce was ignored… it would be much helpful to know that like in two months we’re wrapping up to be 1500 [vaccinations] yeah we would have tried extra hard to train more people [Pharmacist – 14].”

Specific overload management strategies: Overload strategies were sometimes quite specific to the health service experiencing stress. Batch testing of pooled samples for polymerase chain reaction (PCR) tests was undertaken to improve the throughput of otherwise overloaded laboratory services (quote ID H07#1). Rapid antigen tests (RATs) were used in hospitals to reduce the number of PCR tests for likely-negative individuals and for symptomatic positive patients, and allow ill patients to receive COVID-19 treatment without delay (quote ID H07#2):

What a rapid test would do with someone who is symptomatic would be that if you turn positive on a RAT you are COVID positive , so what that would end up doing was then that would decrease the amount of PCR that we were doing… If we had access to them [RATs] in Delta [variant phase] a testing capacity for PCRs would have dropped , identification of COVID positive patients who have been much faster , and that would have changed our treatment or discharge plans for these patients a lot quicker [ICU Nurse – 13].

Other specific responses were increasing hospital capacity by converting non-emergency wards into COVID-19 wards (quote ID H08#1), creating temporary wards (e.g. tents in hospital car parks) (quote ID H18), and facilitating hospital discharge by providing bus services to take patients home (quote ID H55). Emergency co-ordination centres assisted in identifying beds for patients across a region (quote ID H03#10), and respiratory clinics were set up in the community to support keeping patients at home (quote ID H60#2).

Barriers to decision-making

Generic decision-making strategies: Health services adopted several generic strategies to improve data capture, and dissemination of new evidence and local data. A respondent explained how a generic electronic medical record system (EMR) was customised to capture COVID-19 specific information (quote ID H56). “ We had to make EMR kind of work for us [Emergency physician – 09].” The respondent and their colleagues “ had to sort of come up with a process … to mark that you’ve had COVID and then not test you .” General purpose strategies required staff to be vigilant for problems during their application: “people were good at that. It was just realising that it [problem] was coming. So sort of working out. Oh hang on this is going to be a problem as we go forward. So what do we do? [Emergency physician – 09] . ”

Non-specific technologies such as email, Zoom, and Microsoft Teams were often used to enhance team communication. Communication processes were also enhanced by scheduling regular daily staff meetings at hospitals (quote IDs H09#1, H14#11), and weekly meetings for GPs to speak directly with those involved in pandemic management from the public health system (quote ID H09#4). Microsoft SharePoint was used to gather information about staff activities, such as where and when they treated COVID-19 patients, to assist with infection control and for patient managements (quote IDs H47, H48#2, H49).

Specific decision-making strategies: To provide local best practice guidance, expert support teams were created to assist with troubleshooting (quote ID H09#3), local protocols were developed and updated potentially daily (quote IDs H09#2, H68#1,), and interdisciplinary collaborations (e.g. pharmacists working with nurses) developed local workflow models (quote ID H17#1). Such activities required significant effort (quote ID H09#2): “ a working group that met like daily seven days a week for months and months and months to put together the [local protocol and updates] response [Transplant nephrologist – 18]. ”

Education and training gaps

Generic training strategies: Virtual training packages were used to maximise the dissemination of educational materials where local training was not feasible (quote ID H57). Peer support networks were developed to support information sharing where training was not available (quote IDs H03#4, H34 #5, H15#2). Adaptations of such solutions required significant human effort e.g. peer support meant senior staff had to be “there every step of the way [Emergency nurse – 13]. ”

Specific training strategies: Many of the responses designed to educate the health system workforce and the community were highly targeted (quote ID H15#2). Specific training programs were instituted to meet urgent needs, e.g. training clinicians in the use of PPE and hand hygiene. Consumers received highly targeted educational messages, such as requests to avoid unnecessary calling of ambulances, and simple social distancing rules and masking advice (quote IDs H22, H25, H26). Pharmacies provided in-house RATs for members of the public who did not understand the testing process (quote ID H25).

Limitations of existing services

Generic service strategies: The early stages of the pandemic saw a flurry of new or extended health services, often implemented under significant time and resource limitations. Periods of public health mandated lockdowns and work-from-home arrangements relied upon general purpose technologies (quote IDs H3#13, H14#5). Virtual consultations were delivered over channels of varying sophistication from telephone to online telecare products (quote IDs H13#3, H44#2, H52#1, H62#1). When there was lack of supply or limited access to manufactured PCR kits for COVID-19, specialised experts using general PCR techniques “try and put together a rapid PCR type of [solution/reagent] which they didn’t have [Pathology manager – 26] ” (quote ID H64#2).

Specific service strategies: Context-specific responses to service limitations included massive expansion of contact tracing capabilities, new measures such as routine COVID-19 surveillance of clinical staff (quote ID H14#6), and the use of QR (quick response) codes in public venues to support rapid contact tracing (quote ID H14#15). COVID-19 focussed respiratory clinics (quote ID H60#2) and PCR testing facilities appeared in the community for the first time. Specialist vaccination hubs and expanded community pharmacy services such as home delivery of medications were other specific responses. Hospital emergency services expanded their triage functions by creating specialised COVID-19 assessment areas with staff in full PPE, either using repurposed hospital space or in carparks outside the emergency departments or clinics (quote ID H03#11, H13#1,2, H14#13). Laboratories took advantage of manufactured PCR kits when available (quote ID H064#4): “you just opened the box and you put it together and you go [Pathology manager – 26].”

General to specific strategies . Many early responses to the pandemic involved the use of general strategies that sought to optimise responses from existing services (such as reconfiguring rostering or using general-purpose software):

The use of general solutions seemed to coincide with urgency and lack of time or resources to craft a more specific local solution (e.g. quote ID H20#2).

General solutions also could thus be seen to “buy time” whilst uncertainty remained about the best way forward, and better more specific solutions were being developed (e.g. quote IDs H03#13, H14#5). Pre-existing SARS infection control protocols were widely used early on and adapted to local circumstances or evolving knowledge. Generic information and communication tools were used to patch together information processes whilst more sophisticated solutions could be developed (e.g. quote IDs H13#3, H44#2, H52#1, H62#1) [ 32 ].

It is the nature of such generic responses that they are never a perfect fit to a specific task or context. Consequently, some adaptation or localisation is required to better meet these local needs. Such “fitting work” [ 33 ] often fell to local staff, and could take the form of workarounds (e.g. to make standard computer systems work in a new setting) or the addition of local changes (e.g. to a PPE protocol [ 34 ]) (e.g. quote IDs H47, H48#2, H49, H56).

The need for fitting work imposes additional load on staff (e.g. quote IDs H03#1, H20, H21) to “ make things work here right now ” and could be a contributor to the high levels of staff burnout reported through the pandemic.

Specific to general strategies . Highly local solutions to pandemic challenges were often needed where services provided highly specialised services. For example, the details of changes to the workflow for laboratory processing of high volumes of PCR tests would not have wide applicability beyond the laboratory setting.

The use of specific solutions appeared to coincide with unique local problems, or some capacity to develop new specific solutions whilst generic solutions “ held the fort ” (quote ID H64 #2).

Nonetheless, general lessons from such specific responses can sometimes be drawn e.g. in the approach taken to agree upon the specific solution and how it is subsequently communicated. For example, public health services had to rapidly expand their workforce in support of contact tracing, and their use of external recruitment agencies could be adopted by very different parts of the health system.

This study has examined the challenges faced during the COVID-19 pandemic, and health system responses to those challenges in Australia.

Clearly the challenges faced during the pandemic were not uniform, and different health services found themselves better or less well prepared or capable of responding than others [ 35 ]. Our analysis of these responses identified what appeared to be two quite different response pathways that played distinct roles in crisis management – the adoption of general strategies which could be used across a wide variety of settings, or the use or creation of highly targeted context specific responses.

What lessons can be learned from these broad responses? Given the nature of crises, each will bring novel and likely unanticipated challenges.

When faced with requirements to dramatically alter the duties and workflows of existing health services, especially when constrained by time, resource or knowledge, health services can turn to general-purpose strategies to reconfigure their existing workforce, and adopt ready to hand general purpose technologies. Whilst not ideal, these strategies support quick responses and buy time for more targeted solutions to emerge.

Crisis preparedness could thus focus on understanding the range of general-purpose tools and processes that can quickly be brought to hand. Adaptation protocols might provide guidance on localisation processes that optimise speed, quality, impact on staff, or cost. For example, protocols might describe processes of problem identification, workaround development, and team communication approaches that facilitate these tasks. In developing such protocols, we should not forget that while some services must develop highly localised solutions, they nevertheless can be a rich source of lessons about general approaches to identifying issues, designing solutions, and enacting them effectively. During the pandemic, innovations commonly involved combining pre-existing services.

Theoretical frameworks for system resilience describe the importance of flexibility and adaptability to respond to unexpected and escalating situations [ 36 , 37 ]. Generic competencies are often team-based and include information management, communication and coordination, decision-making, and effect control [ 36 ]. Responses when managing the early phase of health emergencies should be simple and generic, such as using generic international guidance [ 38 ]. The Interactive Systems Framework (ISF) for dissemination and implementation distinguishes innovation-specific capacity and general capacity [ 39 ]. Various implementation frameworks suggest general organisational capacity building is an essential step in the early phase of implementation [ 40 ]. Such approaches emphasise that stabilising a situation and maintaining organizational function are key to managing uncertainty while developing specific responses.

Limitations

The problems and system responses reported in this study may lack representativeness because of the small sample size of interviewees, the focus on a single albeit large health system in Australia, and the potential for recruitment biases introduced by convenience and snowballing sampling. Different nations had distinct experiences during COVID-19, such as variations in public health measures adopted, access to vaccines, lockdowns, government policy, and health impacts of the virus on their population. Thus, these findings may not be generalisable to other health system settings. Respondents detailed challenges and system responses with many examples. We anticipated achieving theoretical saturation with 20 participants but during the analysis phase did not do so. This may be due to the richness of innovations during COVID-19 or the diverse selection of participants [ 41 , 42 ]. Failure to saturate suggests that interviewing additional participants could likely identify new examples and issues that might have uncovered additional issues. However, the concept of data saturation in qualitative studies is currently under debate [ 43 ].

Health services have a range of different response strategies available to them when faced with novel challenges, and selection of a strategy can be guided by the circumstances and the availability of ready-to-hand specific strategies. The workforce is pivotal in enabling emergent responses that require dealing with uncertainties. Recognising the important role that general purpose strategies play when time is short (e.g. emergencies) and specific solutions are not yet available suggests that health services can invest in formalising protocols for solution design and focus on workforce support, including team communication and supporting solution implementation. Such capabilities should enhance health system preparedness for crises such as new pandemics or climate-change triggered events. Much can also be learnt about the construction of context-specific solutions, a deeper exploration of when to employ such approaches and how to support them to best prepare for future crises.

Data availability

The complete datasets generated and analysed during the current study are not publicly available because consent was not obtained from study participants for data to be made public but are available from the corresponding author on reasonable request subject to approval from the Macquarie University Ethics Committee. Part of the deidentified data is provided as a supplementary file.

Abbreviations

Electronic medical record system

General practitioner

Intensive care unit

Polymerase Chain Reaction

Personal protective equipment, RAT: Rapid antigen tests

Sociotechnical system

Sheehan MC, Fox MA. Early warnings: the lessons of COVID-19 for Public Health Climate Preparedness. Int J Health Serv. 2020;50(3):264–70.

Article   PubMed   PubMed Central   Google Scholar  

Silva S, Goosby E, Reid MJA. Assessing the impact of one million COVID-19 deaths in America: economic and life expectancy losses. Sci Rep. 2023;13(1):3065.

Article   CAS   PubMed   PubMed Central   Google Scholar  

Lluch C, Galiana L, Doménech P, Sansó N. The impact of the COVID-19 pandemic on Burnout, Compassion fatigue, and Compassion satisfaction in Healthcare personnel: a systematic review of the literature published during the First Year of the pandemic. Healthc [Internet]. 2022; 10(2).

Schmidt AE, Rodrigues R, Simmons C, Steiber N. A crisis like no other? Unmet needs in healthcare during the first wave of the COVID-19 crisis in Austria. Eur J Pub Health. 2022;32(6):969–75.

Article   Google Scholar  

Gonzalez J-P, Souris M, Valdivia-Gr aW. Global spread of hemorrhagic fever viruses: Predicting Pandemics. Methods in molecular biology. (Clifton NJ). 2018;1604:3–31.

CAS   Google Scholar  

Coiera E, Braithwaite J. Turbulence health systems: engineering a rapidly adaptive health system for times of crisis. BMJ Health Care Inf. 2021;28(1).

Turner S, Niño N. Qualitative analysis of the coordination of major system change within the Colombian health system in response to COVID-19: study protocol. Implement Sci Commun. 2020;1:75.

Wensing M, Sales A, Armstrong R, Wilson P. Implementation science in times of Covid-19. Implement Sci. 2020;15(1):42.

Milella F, Minelli EA, Strozzi F, Croce D. Change and Innovation in Healthcare: findings from literature. Clinicoecon Outcomes Res. 2021;13:395–408.

Legido-Quigley H, Asgari N, Teo YY, Leung GM, Oshitani H, Fukuda K, et al. Are high-performing health systems resilient against the COVID-19 epidemic? Lancet. 2020;395(10227):848–50.

Organization WH. Strengthening the health systems response to COVID-19: technical guidance# 2: creating surge capacity for acute and intensive care, 6 April 2020. World Health Organization. Regional Office for Europe; 2020.

Winkelmann J, Webb E, Williams GA, Hernández-Quevedo C, Maier CB, Panteli D. European countries’ responses in ensuring sufficient physical infrastructure and workforce capacity during the first COVID-19 wave. Health Policy. 2022;126(5):362–72.

Article   PubMed   Google Scholar  

Hanisch M, Rake B. Repurposing without purpose? Early innovation responses to the COVID-19 crisis: evidence from clinical trials. R&D Manage. 2021;51(4):393–409.

Lucie W, van Philippe B. Without a trace: why did corona apps fail? J Med Ethics. 2021;47(12):e83.

Koontalay A, Suksatan W, Prabsangob K, Sadang JM. Healthcare workers’ burdens during the COVID-19 pandemic: a qualitative systematic review. J Multidiscip Healthc. 2021;14:3015–25.

Cooper R, Foster M. Sociotechnical systems. Am Psychol. 1971;26(5):467–74.

Thompson Burdine J, Thorne S, Sandhu G. Interpretive description: a flexible qualitative methodology for medical education research. Med Educ. 2021;55(3):336–43.

Hunt MR. Strengths and challenges in the use of interpretive description: reflections arising from a study of the moral experience of health professionals in humanitarian work. Qual Health Res. 2009;19(9):1284–92.

Billings J, Ching BCF, Gkofa V, Greene T, Bloomfield M. Experiences of frontline healthcare workers and their views about support during COVID-19 and previous pandemics: a systematic review and qualitative meta-synthesis. BMC Health Serv Res. 2021;21(1):923.

Australian Government Productivity Commission. Report on Government Services 2022. 2022.

Pharmacy Council of NSW. Annual Report 2018–2019. 2019.

Gordon J, Britt H, Miller GC, Henderson J, Scott A, Harrison C. General Practice Statistics in Australia: pushing a Round Peg into a Square Hole. Int J Environ Res Public Health. 2022;19(4).

NSW Ministry of Health. Our structure NSW Ministry of Health 2023 [ https://www.health.nsw.gov.au/about/nswhealth/Pages/structure.aspx

NSW Government. Hospitals & Services | Sydney Local Health Districts 2024 [ https://slhd.health.nsw.gov.au/hospitals-services

NSW Health. Snapshot, Annual Report 2020-21 2021.

NSW Government NHP. NSW Health Pathology, [ https://pathology.health.nsw.gov.au/

Andrade C. The Inconvenient Truth about Convenience and Purposive Samples. Indian J Psychol Med. 2020;43(1):86–8.

Campbell S, Greenwood M, Prior S, Shearer T, Walkem K, Young S, et al. Purposive sampling: complex or simple? Research case examples. J Res Nurs. 2020;25(8):652–61.

Chun Tie Y, Birks M, Francis K. Grounded theory research: a design framework for novice researchers. SAGE Open Med. 2019;7:2050312118822927.

Fox WM. Sociotechnical system principles and guidelines: past and present. J Appl Behav Sci. 1995;31(1):91–105.

Hoholm T, La Rocca A, Aanestad M. Controversies in healthcare innovation: service, technology and organization. Springer; 2018.

Coiera E. When conversation is better than computation. J Am Med Inf Assoc. 2000;7(3):277–86.

Article   CAS   Google Scholar  

Coiera E. The standard problem. J Am Med Inform Assoc. 2023;30(12):2086–97.

Coiera E. Communication spaces. J Am Med Inform Assoc. 2014;21(3):414–22.

Mustafa S, Zhang Y, Zibwowa Z, Seifeldin R, Ako-Egbe L, McDarby G, et al. COVID-19 preparedness and response plans from 106 countries: a review from a health systems resilience perspective. Health Policy Plan. 2022;37(2):255–68.

Bergström J, Dahlström N, Dekker S, Petersen K. Training organisational resilience in escalating situations. Resilience engineering in practice: CRC; 2017. pp. 45–57.

Google Scholar  

Bhamra R, Dani S, Burnard K, Resilience. The Concept, a literature review and future directions. Int J Prod Res. 2011;49:5375–93.

Crick M, McKenna T, Buglova E, Winkler G, Martincic R. Emergency management in the early phase. Radiat Prot Dosimetry. 2004;109(1–2):7–17.

Article   CAS   PubMed   Google Scholar  

Flaspohler P, Duffy J, Wandersman A, Stillman L, Maras MA. Unpacking prevention capacity: an intersection of research-to-practice models and community-centered models. Am J Community Psychol. 2008;41(3–4):182–96.

Meyers DC, Durlak JA, Wandersman A. The quality implementation framework: a synthesis of critical steps in the implementation process. Am J Community Psychol. 2012;50(3–4):462–80.

Sebele-Mpofu FY. Saturation controversy in qualitative research: complexities and underlying assumptions. A literature review. Cogent Social Sci. 2020;6(1):1838706.

Aldiabat KM, Le Navenec C-L. Data saturation: the mysterious step in grounded theory methodology. Qualitative Rep. 2018;23(1):245–61.

Braun V, Clarke V. To saturate or not to saturate? Questioning data saturation as a useful concept for thematic analysis and sample-size rationales. Qualitative Res Sport Exerc Health. 2021;13(2):201–16.

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Acknowledgements

The authors thank K-lynn Smith and Yvonne Zurynski for their valuable feedback on the manuscript.

The project was conducted with funding from the National Health and Medical Research Council: Partnership Centre for Health System Sustainability; and Centre of Research Excellence in Digital Health (APP1134919).

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E.C., B.S., T.S. and F.M. conceptualised the study. H.R.-A. developed the study protocol and collected data, E.C. and H.R.-A. analyzed the data. E.C. and H.R.-A. prepared the original draft, and all authors contributed to the final drafts of the manuscript.

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Rahimi-Ardabili, H., Magrabi, F., Sanderson, B. et al. A qualitative analysis of health service problems and the strategies used to manage them in the COVID-19 pandemic: exploiting generic and context-specific approaches. BMC Health Serv Res 24 , 1067 (2024). https://doi.org/10.1186/s12913-024-11499-7

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