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Step 6 Extract and manage data

Data extraction

The Cochrane Handbook for Systematic Reviews of Interventions outlines the types of data to consider for extraction/collection from selected studies.

Table 7.3.a:Checklist of items to consider in data collection or data extraction

Source

  • Study ID (created by review author).
  • Report ID (created by review author).
  • Review author ID (created by review author).
  • Citation and contact details.

Eligibility

  • Confirm eligibility for review.
  • Reason for exclusion.

Methods

  • Study design.
  • Total study duration.
  • Sequence generation*.
  • Allocation sequence concealment*.
  • Blinding*.
  • Other concerns about bias*.

Participants

  • Total number.
  • Setting.
  • Diagnostic criteria.
  • Age.
  • Sex.
  • Country.
  • [Co-morbidity].
  • [Socio-demographics].
  • [Ethnicity].
  • [Date of study].

Interventions

  • Total number of intervention groups.

For each intervention and comparison group of interest:

  • Specific intervention.
  •  Intervention details (sufficient for replication, if feasible).
  •  [Integrity of intervention].

Outcomes

  • Outcomes and time points (i) collected; (ii) reported*.

For each outcome of interest:

  • Outcome definition (with diagnostic criteria if relevant).
  • Unit of measurement (if relevant).
  • For scales: upper and lower limits, and whether high or low score is good.

Results

  • Number of participants allocated to each intervention group.

For each outcome of interest:

  • Sample size.
  • Missing participants*.
  • Summary data for each intervention group (e.g. 2×2 table for dichotomous data; means and SDs for continuous data).
  • [Estimate of effect with confidence interval; P value].
  • [Subgroup analyses].

Miscellaneous

  • Funding source.
  • Key conclusions of the study authors.
  • Miscellaneous comments from the study authors.
  • References to other relevant studies.
  • Correspondence required.
  • Miscellaneous comments by the review authors.

Data analysis tools

There are a number of data analysis tools that can assist reviewers interpret and manage data. For example:

  • NVIVO
  • SPSS
  • Leximancer

QUT High Performance Computing provide training and guidance with these tools.

Manage your data

As with any form of research, it is important to consider how you will manage all of the data pertaining to your systematic review throughout the research lifecycle.

Some basic considerations are:

  • Logical and secure file structures
  • Consistent naming convention for data files
  • Back up files regularly in multiple locations to avoid data loss

IFN001: Advanced Information Research Skills Module 8: Manage provides a comprehensive overview of the strategies and issues that need to be considered for appropriate management of data.