Frequently Asked Questions

Frequently Asked Questions

How to cite SRQR

In your methods section, state which guideline resources you used to write your article, refer readers to the supplementary materials to view your completed checklist, and cite this reporting guideline. For example:

We used the SRQR writing guide when drafting this article, and the SRQR checklist (see supplementary materials A) to demonstrate adherence to the SRQR reporting guideline. [1].

You can use your reference manager to save citation information for this webpage, or copy the BibTeX below.

Who made SRQR?

Bridget O’Brien, PhD has been a faculty member in the Department of Medicine, Division of General Internal Medicine, since 2008. She is a professor of medicine and an education scientist in the Office of Medical Education’s Center for Faculty Educators. As co-director of the Teaching Scholars Program and the UCSF-University of Utrecht Health Professions Education doctoral program she teaches and mentors faculty and learners interested in education research and scholarship. At the San Francisco VA, she directs the Advanced Fellowship in Health Professions Education Evaluation and Research. In 2015 she was selected as one of five national Macy Faculty Scholars supported by the Josiah Macy Jr. Foundation and in 2021 she was selected as a KIPRIME Fellow at the Karolinska Instituet. She is a deputy editor for the journal Academic Medicine.

Dr. Ilene Harris, deceased, was professor and head, Department of Medical Education, University of Illinois at Chicago College of Medicine, Chicago, Illinois.

Dr. Thomas Beckman is professor of medicine and medical education, Department of Medicine, Mayo Clinic College of Medicine, Rochester, Minnesota.

Dr. Darcy Reed is associate professor of medicine and medical education, Department of Medicine, Mayo Clinic College of Medicine, Rochester, Minnesota.

Dr. David Cook is associate director, Mayo Clinic Online Learning, research chair, Mayo Multidisciplinary Simulation Center, and professor of medicine and medical education, Mayo Clinic College of Medicine, Rochester, Minnesota.

How was SRQR made?

The SRQR authors synthesised 40 sets of recommendations previously proposed by experts in qualitative methods. You can read about their development process here.

The UK EQUATOR Centre then worked with SRQR’s authors to make SRQR easier to use by clarifying language, adding definitions, examples, extra information and resources. Although worded differently, the guidance on this website is conceptually the same as the original publication and can be used interchangeably.

Does SRQR prescribe structure?

No. SRQR does not prescribe a rigid format or standardized content. Consider each item and prioritize elements that are most relevant to your study, findings, context, and readers.

You may prefer to report an item in a different order, section, or in a table or figure. For example, some authors may prefer to include some methods items in their Results section. Others may call their Results section Findings, or have a completely different manuscript structure.

How to prioritize items and keep writing concise

Although all items should be reported, you should prioritize items most relevant to your study, findings, context, and readership.

You should include information in the article body when possible so it’s easy for readers to find. However, if you are worried about word counts or brevity, consider placing information in tables.

If you feel confident that an item is less important to your study, you could report it in an appendix or supplement. Be aware that supplementary materials may not be peer reviewed, are not indexed by search engines, and can be difficult for readers to find. Therefore, they are best only used for details you feel are less important, and you should point readers to them from the article body. For example, “For more details, see the supplementary materials A”.

The UK EQUATOR centre runs training on how to write concisely.

What to write if you feel an item is not applicable

If you think an item is not applicable, state why. You could state this in the text or in the reporting checklist. Remember to publish your completed reporting checklist as a supplement, and to refer authors to it from your methods section.

What to do if asked to remove guideline related content

If a colleague or reviewer asks you to remove content that is related to this guideline, you can direct them to this guideline and the explanation for why that item is important. If they insist, consider moving the item to a supplement, table or figure.

Where can I get general writing training?

The EQUATOR Network provides in-person training for writing research articles.

AuthorAID have resources, an online course, and mentoring to help authors.

Reuse

Most of the reporting guidelines and reporting checklists on this website were originally published under permissive licenses that allowed their reuse. Some were published with propriety licenses, where copyright is held by the publisher and/or original authors. The original content of the reporting checklists and explanation pages on this website were drawn from these publications without permission from the publisher but with knowledge and permission from the reporting guideline authors, and subsequently revised in response to feedback and evidence from research as part of an ongoing scholarly dialogue about how best to disseminate reporting guidance. The UK EQUATOR Centre makes no copyright claims over reporting guideline content. Our use of copyrighted content on this website falls under <a href="https://www.copyright.gov/title17/92chap1.html#107">fair use guidelines</a>.

Citation

BibTeX citation:
@article{obrienStandardsReportingQualitative2014,
  author = {O’Brien, Bridget C. and Harris, Ilene B. and Beckman, Thomas
    J. and Reed, Darcy A. and Cook, David A.},
  title = {Standards for {Reporting} {Qualitative} {Research:} {A}
    {Synthesis} of {Recommendations}},
  journal = {Academic Medicine},
  volume = {89},
  number = {9},
  pages = {1245–1251},
  date = {},
  urldate = {2022-10-07},
  url = {https://journals.lww.com/academicmedicine/fulltext/2014/09000/Standards_for_Reporting_Qualitative_Research__A.21.aspx},
  doi = {10.1097/ACM.0000000000000388},
  langid = {en-US},
  abstract = {Purpose~ Standards for reporting exist for many types of
    quantitative research, but currently none exist for the broad
    spectrum of qualitative research. The purpose of the present study
    was to formulate and define standards for reporting qualitative
    research while preserving the requisite flexibility to accommodate
    various paradigms, approaches, and methods. Method~ The authors
    identified guidelines, reporting standards, and critical appraisal
    criteria for qualitative research by searching PubMed, Web of
    Science, and Google through July 2013; reviewing the reference lists
    of retrieved sources; and contacting experts. Specifically, two
    authors reviewed a sample of sources to generate an initial set of
    items that were potentially important in reporting qualitative
    research. Through an iterative process of reviewing sources,
    modifying the set of items, and coding all sources for items, the
    authors prepared a near-final list of items and descriptions and
    sent this list to five external reviewers for feedback. The final
    items and descriptions included in the reporting standards reflect
    this feedback. Results~ The Standards for Reporting Qualitative
    Research (SRQR) consists of 21 items. The authors define and explain
    key elements of each item and provide examples from recently
    published articles to illustrate ways in which the standards can be
    met. Conclusions~ The SRQR aims to improve the transparency of all
    aspects of qualitative research by providing clear standards for
    reporting qualitative research. These standards will assist authors
    during manuscript preparation, editors and reviewers in evaluating a
    manuscript for potential publication, and readers when critically
    appraising, applying, and synthesizing study findings.}
}
For attribution, please cite this work as:
O’Brien BC, Harris IB, Beckman TJ, Reed DA, Cook DA. Standards for Reporting Qualitative Research: A Synthesis of Recommendations. Academic Medicine. 89(9):1245-1251. doi:10.1097/ACM.0000000000000388

Reporting Guidelines are recommendations to help describe your work clearly

Your research will be used by people from different disciplines and backgrounds for decades to come. Reporting guidelines list the information you should describe so that everyone can understand, replicate, and synthesise your work.

Reporting guidelines do not prescribe how research should be designed or conducted. Rather, they help authors transparently describe what they did, why they did it, and what they found.

Reporting guidelines make writing research easier, and transparent research leads to better patient outcomes.

Easier writing

Following guidance makes writing easier and quicker.

Learn more »

Smoother publishing

Many journals require completed reporting checklists at submission.

Learn more »

Maximum impact

From nobel prizes to null results, articles have more impact when everyone can use them.

Learn more »

Who reads research?

You work will be read by different people, for different reasons, around the world, and for decades to come. Reporting guidelines help you consider all of your potential audiences. For example, your research may be read by researchers from different fields, by clinicians, patients, evidence synthesisers, peer reviewers, or editors. Your readers will need information to understand, to replicate, apply, appraise, synthesise, and use your work.

Cohort studies

A cohort study is an observational study in which a group of people with a particular exposure (e.g. a putative risk factor or protective factor) and a group of people without this exposure are followed over time. The outcomes of the people in the exposed group are compared to the outcomes of the people in the unexposed group to see if the exposure is associated with particular outcomes (e.g. getting cancer or length of life).

Source.

Case-control studies

A case-control study is a research method used in healthcare to investigate potential risk factors for a specific disease. It involves comparing individuals who have been diagnosed with the disease (cases) to those who have not (controls). By analysing the differences between the two groups, researchers can identify factors that may contribute to the development of the disease.

An example would be when researchers conducted a case-control study examining whether exposure to diesel exhaust particles increases the risk of respiratory disease in underground miners. Cases included miners diagnosed with respiratory disease, while controls were miners without respiratory disease. Participants' past occupational exposures to diesel exhaust particles were evaluated to compare exposure rates between cases and controls.

Source.

Cross-sectional studies

A cross-sectional study (also sometimes called a "cross-sectional survey") serves as an observational tool, where researchers capture data from a cohort of participants at a singular point. This approach provides a 'snapshot'— a brief glimpse into the characteristics or outcomes prevalent within a designated population at that precise point in time. The primary aim here is not to track changes or developments over an extended period but to assess and quantify the current situation regarding specific variables or conditions. Such a methodology is instrumental in identifying patterns or correlations among various factors within the population, providing a basis for further, more detailed investigation.

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Systematic reviews

A systematic review is a comprehensive approach designed to identify, evaluate, and synthesise all available evidence relevant to a specific research question. In essence, it collects all possible studies related to a given topic and design, and reviews and analyses their results.

The process involves a highly sensitive search strategy to ensure that as much pertinent information as possible is gathered. Once collected, this evidence is often critically appraised to assess its quality and relevance, ensuring that conclusions drawn are based on robust data. Systematic reviews often involve defining inclusion and exclusion criteria, which help to focus the analysis on the most relevant studies, ultimately synthesising the findings into a coherent narrative or statistical synthesis. Some systematic reviews will include a [meta-analysis]{.defined data-bs-toggle="offcanvas" href="#glossaryItemmeta_analyses" aria-controls="offcanvasExample" role="button"}.

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Systematic review protocols

TODO

Meta analyses of Observational Studies

TODO

Randomised Trials

A randomised controlled trial (RCT) is a trial in which participants are randomly assigned to one of two or more groups: the experimental group or groups receive the intervention or interventions being tested; the comparison group (control group) receive usual care or no treatment or a placebo. The groups are then followed up to see if there are any differences between the results. This helps in assessing the effectiveness of the intervention.

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Randomised Trial Protocols

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Qualitative research

Research that aims to gather and analyse non-numerical (descriptive) data in order to gain an understanding of individuals' social reality, including understanding their attitudes, beliefs, and motivation. This type of research typically involves in-depth interviews, focus groups, or field observations in order to collect data that is rich in detail and context. Qualitative research is often used to explore complex phenomena or to gain insight into people's experiences and perspectives on a particular topic. It is particularly useful when researchers want to understand the meaning that people attach to their experiences or when they want to uncover the underlying reasons for people's behaviour. Qualitative methods include ethnography, grounded theory, discourse analysis, and interpretative phenomenological analysis.

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Case Reports

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Diagnostic Test Accuracy Studies

Diagnostic accuracy studies focus on estimating the ability of the test(s) to correctly identify people with a predefined target condition, or the condition of interest (sensitivity) as well as to clearly identify those without the condition (specificity).

Prediction Models

Prediction model research is used to test the accurarcy of a model or test in estimating an outcome value or risk. Most models estimate the probability of the presence of a particular health condition (diagnostic) or whether a particular outcome will occur in the future (prognostic). Prediction models are used to support clinical decision making, such as whether to refer patients for further testing, monitor disease deterioration or treatment effects, or initiate treatment or lifestyle changes. Examples of well known prediction models include EuroSCORE II for cardiac surgery, the Gail model for breast cancer, the Framingham risk score for cardiovascular disease, IMPACT for traumatic brain injury, and FRAX for osteoporotic and hip fractures.

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Animal Research

TODO

Quality Improvement in Healthcare

Quality improvement research is about finding out how to improve and make changes in the most effective way. It is about systematically and rigourously exploring "what works" to improve quality in healthcare and the best ways to measure and disseminate this to ensure positive change. Most quality improvement effectiveness research is conducted in hospital settings, is focused on multiple quality improvement interventions, and uses process measures as outcomes. There is a great deal of variation in the research designs used to examine quality improvement effectiveness.

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Economic Evaluations in Healthcare

TODO

Meta Analyses

A meta-analysis is a statistical technique that amalgamates data from multiple studies to yield a single estimate of the effect size. This approach enhances precision and offers a more comprehensive understanding by integrating quantitative findings. Central to a meta-analysis is the evaluation of heterogeneity, which examines variations in study outcomes to ensure that differences in populations, interventions, or methodologies do not skew results. Techniques such as meta-regression or subgroup analysis are frequently employed to explore how various factors might influence the outcomes. This method is particularly effective when aiming to quantify the effect size, odds ratio, or risk ratio, providing a clearer numerical estimate that can significantly inform clinical or policy decisions.

How Meta-analyses and Systematic Reviews Work Together

Systematic reviews and meta-analyses function together, each complementing the other to provide a more robust understanding of research evidence. A systematic review meticulously gathers and evaluates all pertinent studies, establishing a solid foundation of qualitative and quantitative data. Within this framework, if the collected data exhibit sufficient homogeneity, a meta-analysis can be performed. This statistical synthesis allows for the integration of quantitative results from individual studies, producing a unified estimate of effect size. Techniques such as meta-regression or subgroup analysis may further refine these findings, elucidating how different variables impact the overall outcome. By combining these methodologies, researchers can achieve both a comprehensive narrative synthesis and a precise quantitative measure, enhancing the reliability and applicability of their conclusions. This integrated approach ensures that the findings are not only well-rounded but also statistically robust, providing greater confidence in the evidence base.

Why Don't All Systematic Reviews Use a Meta-Analysis?

Systematic reviews do not always have meta-analyses, due to variations in the data. For a meta-analysis to be viable, the data from different studies must be sufficiently similar, or homogeneous, in terms of design, population, and interventions. When the data shows significant heterogeneity, meaning there are considerable differences among the studies, combining them could lead to skewed or misleading conclusions. Furthermore, the quality of the included studies is critical; if the studies are of low methodological quality, merging their results could obscure true effects rather than explain them.

Protocol

A plan or set of steps that defines how something will be done. Before carrying out a research study, for example, the research protocol sets out what question is to be answered and how information will be collected and analysed.

Source

Research Paradigm

The set of beliefs and assumptions that guide the research process. These commonly include positivist, post-positivist, constructivist or interpretivist, and critical theory. Qualitative research generally draws from a post-positivist or constructivist/interpretivist paradigm."

Instruments

Data collection instruments include (but are not limited to) interview or focus group guides, observational protocols and prompts for field notes, and data extraction or coding protocols for selection and analysis of documents, photographs, videos, or other artifacts"

Bias

A term drawn from quantitative research, bias technically means a systematic error, where a particular research finding deviates from a 'true' finding. This might come about through errors in the manner of interviewing, or by errors in sampling. In qualitative research this is a problematic concept, since by definition the qualitative researcher is part of the process, and all researchers are different. This human factor has been said to be both the greatest strength and the greatest weakness of qualitative method. What can be done in commercial qualitative research, however, is to minimise obvious and avoidable sources of bias, for example by not confining all the fieldwork to one social group or geographic location, by taking steps to recognise the personal views of the researcher, (using techniques such as bracketing), and by working in teams.

Sampling strategy

Several sampling strategies are commonly used in qualitative research, although most fall under the umbrella of purposeful (or purposive) sampling.

Purposeful sampling means that participants, documents, or events are selected for their relevance to the research question, based on guiding theory or experiences and assumptions of the researchers. Over the course of the research process, researchers may determine that additional or different participants, documents, or events should be included to address the research question.

Other sampling techniques, such as theoretical sampling (seeking examples of theoretical constructs), snowball sampling (using study participants to identify additional participants who meet study criteria), and convenience sampling (including any volunteers with no or minimal criteria for inclusion) may be appropriate depending on the question and approach, so long as the authors provide explanation and justification.

Qualitative Approach

A qualitative “approach” is a general way of thinking about conducting qualitative research. It describes, either explicitly or implicitly, the purpose of the qualitative research, the role of the researcher(s), the stages of research, and the method of data analysis. Commonly used approaches include ethnography, grounded theory, case study, phenomenology, and narrative research.

Data Collection Methods

Researchers may choose to use information from multiple sources, contexts, and/or time points depending on their approach and research question(s). Data collection methods include (but are not limited to) interviews, focus groups, observations (direct or indirect via video), and review of written text, photographs, and other documents or materials. See {{< meta items.data-collection-instruments.title >}} for triangulation.

Iterative

Qualitative research often occurs as an iterative process, meaning that researchers begin data analysis before they complete data collection. The data collection and analysis process may occur in phases or stages. As part of an iterative collection-analysis process, researchers will often alter their data collection methods to explore their preliminary impressions in greater depth and/or actively pursue confirming and disconfirming perspectives.

Study period

The start and end dates for data collection and analysis.

Ethnography

The scientific description of peoples and cultures with their customs, habits, and mutual differences.

Read more

Grounded theory

A method consisting of a set of systematic, but flexible, guidelines for conducting inductive qualitative inquiry aimed toward theory construction. This method focuses squarely on the analytic phases of research, although both data collection and analysis inform and shape each other and are conducted in tandem.

Read more

Degree of participation

For example, if some participants were observed and interviewed and others only interviewed, or if some participants completed multiple interviews and others completed a single interview, these variations should be explained.

Unit of analysis

In qualitative research, the unit of analysis is not necessarily the same as the unit of sampling (e.g., individual participants or events). Instead, some approaches use specific events as the unit of analysis, such as mentions of a particular topic or experience, or observations of a particular behavior or phenomenon, while others use groups rather than individual group participants. This specification has implications for how the data are organized and analyzed as well as the inferences drawn from the data.

Reflexivity

Reflexivity refers to intentional, systematic consideration of the potential or actual effects of the researcher(s) on all aspects of the study process.

Transferability

The transferability of a research finding is the extent to which it can be applied in other contexts and studies. It is thus equivalent to or a replacement for the terms generalizability and external validity.

Generalizability

The appropriate scope for generalization of the findings beyond the study (e.g., to other settings, populations, time periods, circumstances)

Analytic findings

Analytic findings may include interpretations, inferences, narratives, themes, and models.

Frequency counts

The frequency of specific themes or codes.