17. Study characteristics

Cite each included study and present its characteristics.

Essential elements

  • Cite each included study.
  • Present the key characteristics of each study in a table or figure (considering a format that will facilitate comparison of characteristics across the studies).

Additional elements

  • If the review examines the effects of interventions, consider presenting an additional table that summarises the intervention details for each study.

Explanation

Reporting the details of the included studies allows readers to understand the characteristics of studies that have addressed the review question(s) and is therefore important for understanding the applicability of the review. Characteristics of interest might include study design features, characteristics of participants, how outcomes were ascertained (such as smoking cessation self reported or biochemically validated, or specific harms systematically assessed or reported by participants as they emerged), funding source, and competing interests of study authors. Presenting the key characteristics of each study in a table or figure can facilitate comparison of characteristics across the studies.1 Citing each study enables retrieval of relevant reports if desired.

For systematic reviews of interventions, presenting an additional table that summarises the intervention details for each study (such as using the template based on the Template for Intervention Description and Replication (TIDieR)2) has several benefits. An intervention summary table helps readers compare the characteristics of the interventions and consider those that may be feasible for implementation in their setting; highlights missing or unavailable details; shows which studies did not specify certain characteristics as part of the intervention; and highlights characteristics that have not been investigated in existing studies.23

Example

In a review examining the association between aspirin use and fracture risk, the authors included a table presenting for each included study the citation, study design, country, sample size, setting, mean age, percentage of females, number of years follow-up, exposure details, and outcomes assessed (Table 1).4

Table 1: The table displays for each included study the citation, study design, country, sample size, setting, mean age, percentage of females, number of years follow-up, exposure details and outcomes assessed. Reproduced from Barker et al.4
Study ID Population Exposure to aspirin Outcomes
Author (year) Study design Country Sample size Source of participants Age, mean Female, % Follow-up (years) Identification Dose Fracture Bone mineral density
Bauer (1996) Cohort USA 7786 Community 73.1 100 1.6 Self-report 1–4 times/week ✓ ✓
74.1 5–7 times/week
Bleicher (2011) Cross-sectional Australia 1705 Community 77.0 0 – Medication verified in clinic NR – ✓
Bonten (2017) Cross-sectional Netherlands 854 Community 59.0 34 – Medication verified in clinic 30–125 mg/day ✓ ✓
Carbone (2003) Cross-sectional USA 2853 Community 73.6 50 – Medication verified in clinic 328 mg/day ✓ ✓
Chuang (2016) Case-control Taiwan 555 Community 74.0 61 5 Prescription history 106 mg ✓ –
Dobnig (2007) Cohort Austria 1664 Nursing homes – 100 2 Not reported Not reported ✓ –
Hill (2008) Cross-sectional Trinidad and Tobago 340 Community 63.9 100 – Medication verified in clinic ≥3 times/week – ✓
Hill (2008) Cross-sectional Trinidad and Tobago 2501 Community 56.3 0 – Self-report NR – ✓
Lane (1997) Cross-sectional USA 499 Community 73.6 100 – Self-report 5–7 days/week – ✓
Vestergaard (2006, 2012) Case-control Denmark 498 617 Community 43.4 52 1 Prescription history ≤150 mg/day ✓ –
Vestergaard (2012) Cohort Denmark 2016 Community 50.8 100 10 Self-report 325 mg/day ✓ ✓

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References

1.
McKenzie JE, Brennan SE, Ryan RE, Thomson HJ, Johnston RV. Summarizing study characteristics and preparing for synthesis. Cochrane Handbook for Systematic Reviews of Interventions. Published online September 2019:229-240. doi:10.1002/9781119536604.ch9
2.
Hoffmann TC, Oxman AD, Ioannidis JP, et al. Enhancing the usability of systematic reviews by improving the consideration and description of interventions. BMJ. Published online July 2017:j2998. doi:10.1136/bmj.j2998
3.
Montgomery P, Underhill K, Gardner F, Operario D, Mayo-Wilson E. The oxford implementation index: A new tool for incorporating implementation data into systematic reviews and meta-analyses. Journal of Clinical Epidemiology. 2013;66(8):874-882. doi:10.1016/j.jclinepi.2013.03.006
4.
Barker AL, Soh SE, Sanders KM, et al. Aspirin and fracture risk: A systematic review and exploratory meta-analysis of observational studies. BMJ Open. 2020;10(2):e026876. doi:10.1136/bmjopen-2018-026876

Citation

For attribution, please cite this work as:
Page MJ, Moher D, Bossuyt PM, et al. PRISMA 2020 explanation and elaboration: updated guidance and exemplars for reporting systematic reviews. BMJ. 372:n160. doi:10.1136/bmj.n160

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.

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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.

Source

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.

Source

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.

Source

Randomised Trial Protocols

TODO

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 behavior. Qualitative methods include ethnography, grounded theory, discourse analysis, and interpretative phenomenological analysis.

Source

Case Reports

TODO

Diagnostic Test Accuracy Studies

Diagnostic accuracy studies focus on estimating the ability of the test(s) to correctly identify subjects 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.

Source

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.

Source

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

Systematic_review

A review that uses explicit, systematic methods to collate and synthesize findings of studies that address a clearly formulated question.

Source

Statistical synthesis

The combination of quantitative results of two or more studies. This encompasses meta-analysis of effect estimates (described below) and other methods, such as combining P values, calculating the range and distribution of observed effects, and vote counting based on the direction of effect (see McKenzie and Brennan for a description of each method)

Meta-analysis of effect estimates

A statistical technique used to synthesize results when study effect estimates and their variances are available, yielding a quantitative summary of results.

Source

Outcome

An event or measurement collected for participants in a study (such as quality of life, mortality).

Result

The combination of a point estimate (such as a mean difference, risk ratio or proportion) and a measure of its precision (such as a confidence/credible interval) for a particular outcome.

Reports

Documents (paper or electronic) supplying information about a particular study. A report could be a journal article, preprint, conference abstract, study register entry, clinical study report, dissertation, unpublished manuscript, government report, or any other document providing relevant information.

Record

The title or abstract (or both) of a report indexed in a database or website (such as a title or abstract for an article indexed in Medline). Records that refer to the same report (such as the same journal article) are “duplicates”; however, records that refer to reports that are merely similar (such as a similar abstract submitted to two different conferences) should be considered unique.

Study

An investigation, such as a clinical trial, that includes a defined group of participants and one or more interventions and outcomes. A “study” might have multiple reports. For example, reports could include the protocol, statistical analysis plan, baseline characteristics, results for the primary outcome, results for harms, results for secondary outcomes, and results for additional mediator and moderator analyses.