Systematic Reviews

In order to describe the included studies, midigate the risk of bias, and enable synthesis and and and meta-analysis, you will  need to collect data from each study. During the planning stage, state what data you plan to collect their systematic review, and develop a strategy for obtaining them. You may choose to utilize software to facilitate data extraction and coding (see Tools & Software) or use a standardized template. 

 The Cochrane Handbook for Systematic Reviews of Interventions provides detailed guidance in the following chapters: 

• Chapter 5: Collecting Data
• Chapter 6: Choosing effect measures and computing estimates of effect 
• Chapter 9: Summarizing study characteristics and preparing for synthesis
• Chapter 10: Analysing data and undertaking meta-analyses 

See also, Data Extraction & Management from Systematic Review: a How-To Guide from Dalhousie University, Dalhousie Libraries. 

• Brown, S. A., Upchurch, S. L., & Acton, G. J. (2003). A framework for developing a coding scheme for meta-analysis. Western Journal of Nursing Research, 25(2), 205-222. https://journals.sagepub.com/doi/pdf/10.1177/0193945902250038
• King, R., Hooper, B. and Wood, W. (2011) 'Using bibliographic software to appraise and code data in educational systematic review research', Medical Teacher, 33(9), 719-23,  https://www.tandfonline.com/doi/full/10.3109/0142159X.2011.558138

Table 5.3.a Checklist of items to consider in data collection from the Cochrane Handbook for Systematic Reviews of Interventions provides guidance on selecting what data to record.  

Information about data extraction from reports

• Name of data extractors, date of data extraction, and identification features of each report from which data are being extracted

Eligibility criteria

• Confirm eligibility of the study for the review
• Reason for exclusion

Study methods

• Study design:
• Parallel, factorial, crossover, cluster aspects of design for randomized trials, and/or study design features for non-randomized studies
• Single or multicentre study; if multicentre, number of recruiting centres
• Recruitment and sampling procedures used (including at the level of individual participants and clusters/sites if relevant)
• Enrollment start and end dates; length of participant follow-up
• Details of random sequence generation, allocation sequence concealment, and masking for randomized trials, and methods used to prevent and control for confounding, selection biases, and information biases for non-randomized studies*
• Methods used to prevent and address missing data*
• Statistical analysis:
• Unit of analysis (e.g. individual participant, clinic, village, body part)
• Statistical methods used if computed effect estimates are extracted from reports, including any covariates included in the statistical model
• Likelihood of reporting and other biases*
• Source(s) of funding or other material support for the study
• Authors’ financial relationship and other potential conflicts of interest

Participants

• Setting
• Region(s) and country/countries from which study participants were recruited
• Study eligibility criteria, including diagnostic criteria
• Characteristics of participants at the beginning (or baseline) of the study (e.g. age, sex, comorbidity, socio-economic status)

Intervention

• Description of the intervention(s) and comparison intervention(s), ideally with sufficient detail for replication:
• Components, routes of delivery, doses, timing, frequency, intervention protocols, length of intervention
• Factors relevant to implementation (e.g. staff qualifications, equipment requirements)
• Integrity of interventions (i.e. the degree to which specified procedures or components of the intervention were implemented as planned)
• Description of co-interventions
• Definition of ‘control’ groups (e.g. no intervention, placebo, minimally active comparator, or components of usual care)
• Components, dose, timing, frequency
• For observational studies: description of how intervention status was assessed; length of exposure, cumulative exposure

Outcomes

• For each pre-specified outcome domain (e.g. anxiety) in the systematic review:
• Whether there is evidence that the outcome domain was assessed (especially important if the outcome was assessed but the results not presented; see Chapter 13)
• Measurement tool or instrument (including definition of clinical outcomes or endpoints); for a scale, name of the scale (e.g. the Hamilton Anxiety Rating Scale), upper and lower limits, and whether a high or low score is favourable, definitions of any thresholds if appropriate
• Specific metric (e.g. post-intervention anxiety, or change in anxiety from baseline to a post-intervention time point, or post-intervention presence of anxiety (yes/no))
• Method of aggregation (e.g. mean and standard deviation of anxiety scores in each group, or proportion of people with anxiety)
• Timing of outcome measurements (e.g. assessments at end of eight-week intervention period, events occurring during the eight-week intervention period)
• Adverse outcomes need special attention depending on whether they are collected systematically or non-systematically (e.g. by voluntary report)

Results

• For each group, and for each outcome at each time point: number of participants randomly assigned and included in the analysis; and number of participants who withdrew, were lost to follow-up or were excluded (with reasons for each)
• Summary data for each group (e.g. 2×2 table for dichotomous data; means and standard deviations for continuous data)
• Between-group estimates that quantify the effect of the intervention on the outcome, and their precision (e.g. risk ratio, odds ratio, mean difference)
• If subgroup analysis is planned, the same information would need to be extracted for each participant subgroup

Miscellaneous

• Key conclusions of the study authors
• Reference to other relevant studies
• Correspondence required
• Miscellaneous comments from the study authors or by the review authors

The PRISMA checklist provides reporting guidelines for documenting & reporting your data extraction process and results.

 Item 10: Data collection process

• Describe method of data extraction from reports (e.g., piloted forms, independently, in duplicate) and any processes for obtaining and confirming data from investigators. Data items

Item 11: Data items

• List and define all variables for which data were sought (e.g., PICOS, funding sources) and any assumptions and simplifications made. Risk of bias in individual studies

Item 13: Summary measures 

• State the principal summary measures (e.g., risk ratio, difference in means). Synthesis of results 14 Describe the methods of handling data and combining results of studies, if done, including measures of consistency (e.g., I2) for each meta-analysis.

Item 18: Study characteristics 

• For each study, present characteristics for which data were extracted (e.g., study size, PICOS, follow-up period) and provide the citations.

Item 20: Results of individual studies

• For all outcomes considered (benefits or harms), present, for each study: (a) simple summary data for each intervention group (b) effect estimates and confidence intervals, ideally with a forest plot.​