Table 6.

Data extraction

Step	Sub-step	Methods/approaches	Sources ▪ Examples
1.0 Plan the data elements to extract
	1.1 Determine the data to extract on the characteristics of SRsa		Becker 2008 [1]; Caird 2015 [31]; JBI 2015 [40, 41]; Li 2012 [44]; Ryan 2009 [53, 54]
	1.2 Determine the data required to assess which SRs address the overview question and allow assessment of the overlap across SRsa		Smith 2011 [57]
	1.3 Determine data to extract about the results from the SRs for each relevant primary outcome
		1.3.1 Extract M-A results	Becker 2008 [1]; Caird 2015 [31]; Hartling 2012 [35]; Smith 2011 [57]
		1.3.2 Extract numeric trial results	Thomson 2013 [59]
		1.3.3 Extract narrative results	Bolland 2014 [30]; JBI 2015 [40, 41]; Li 2012 [44]; Ryan 2009 [53, 54]
		1.3.4 Extract a combination of 1.3.1–1.3.3
		1.3.5 Extract risk of bias assessment (overall assessment, or domain/item level data, or both) and certainty of the evidence	Becker 2008 [1]; Hartling 2012 [35]; JBI 2015 [40, 41]; Li 2012 [44]; Ryan 2009 [53, 54]
	1.4 Determine the data to extract from primary studiesa
		1.4.1 Extract numerical trial results	Caird 2015 [31]
		1.4.2 Extract data required to assess risk of bias for each domain or item	Hartling 2012 [35]
	1.5 Develop a data extraction forma		Becker 2008 [1]; Cooper 2012 [32]; Hartling 2012 [35]; JBI 2015 [40, 41]; Singh 2012 [56]
2.0 Plan the data extraction process
	2.1 Determine the sources where data will be obtained from
		2.1.1 SRs	Becker 2008 [1]; Bolland 2014 [30]; Caird 2015 [31]; CMIMG 2012 [4]; Hartling 2014 [37]; JBI 2015 [40, 41]; Pieper 2012 [6, 45]
		2.1.2 Primary studies	Caird 2015 [31]; Salanti 2011 [3]; Thomson 2013 [59]; Whitlock 2008 [48–52]
		2.1.3 Registry entries (for SRs and/or trials)	Inferred method
		2.1.4 A combination of the above	Caird 2015 [31]; Salanti 2011 [3]; Thomson 2013 [59]; Whitlock 2008 [48–52]
	2.2 Determine how overlapping information across SRs will be handled
		2.2.1 Extract information from all SRs	Bolland 2014 [30]; Caird 2015 [31]; CMIMG 2012 [4]; Cooper 2012 [32]; Hartling 2014 [37]; JBI 2015 [40, 41]; Pieper 2014 [46]; White 2009 [48–52]
		2.2.2 Extract information from only one SR based on a priori eligibility criteria	Cooper 2012 [32]; CMIMG 2012 [4]; Foisy 2011 [34]; Hartling 2014 [37]; Pieper 2012 [6, 45]; Pieper 2014 [47]; Thomson 2013 [59] ▪ SR with the greatest number of trials (Cooper 2012 [32]) ▪ Most recent SR (Pieper 2014 [47]; Cooper 2012 [32])
	2.3 Determine how discrepant data across SRs will be handled in data extraction
		2.3.1 Extract all data, recording discrepancies	Becker 2008 [1]; Bolland 2014 [30]; Caird 2015 [31]; Kovacs 2014 [42]; Pieper 2012 [6, 45]; Pieper 2014 [46]; Smith 2011 [57]; Thomson 2010 [58]
		2.3.2 Extract data from only one SR based on a priori eligibility criteria	Cooper 2012 [32]; Pieper 2014 [47] ▪ Most recent SR and SR of the highest quality (Pieper 2014 [47]) ▪ Highest quality SR (Cooper 2012 [32])
		2.3.3 Extract data element (e.g. effect estimates, quality assessments) from the SR which meets decision rule criteria	Bolland 2014 [30]; Cooper 2012 [32] ▪ SR that reports the most complete information on effect estimates (Bolland 2014 [30])
		2.3.4 Reconcile discrepancies through approaches outlined in 2.4	Bolland 2014 [30]; Caird 2015 [31]; Flodgren 2011 [33]; JBI 2015 [40, 41]; Salanti 2011 [3]; Thomson 2010 [58]; Whitlock 2008 [48–52]
	2.4 Determine additional steps to deal with missing data from SRs, or when there is variation in information reported across SRs
		2.4.1 Retrieve reports of the primary studies	Bolland 2014 [30]; Caird 2015 [31]; CMIMG 2012 [4]; Flodgren 2011 [33]; Pieper 2012 [6, 45]; Pieper 2014 [47]; Salanti 2011 [3]; Thomson 2010 [58]; White 2009 [49–51]
		2.4.2 Contact SR or trial authors, or both, for missing info and/or clarification	Bolland 2014 [30]; Flodgren 2011 [33]; JBI 2015 [40, 41]; Whitlock 2008 [49–51]
		2.4.3 Search SR or trial registry entries for information	Inferred method
		2.4.4 A combination of the above approaches	Bolland 2014 [30]; Caird 2015 [31]; Salanti 2011 [3]; Thomson 2010 [58]; Whitlock 2008 [48–52]
		2.4.5 Do not take additional steps to deal with missing data or discrepancies	Becker 2008 [1]; Caird 2015 [31]; Foisy 2011 [34]; JBI 2015 [40, 41]
	2.5 Pilot the data extraction forma		Cooper 2012 [32]; JBI 2015 [40, 41]
	2.6 Determine the number of overview authors required to extract dataa
		2.6.1 Single, double, or more	Becker 2008 [1]; Bolland 2014 [30]; Hartling 2012 [35]; JBI 2015 [40, 41]; Li 2012 [44]; White 2009 [48–52]
		2.6.2 Data extraction versus data checking	Becker 2008 [1]; CMIMG 2012 [4]; Singh 2012 [56]; Whitlock 2008 [48–52] ▪ Evaluate a random sample of primary studies to ensure that data abstraction is accurate and reproducible (Whitlock 2008 [48–52])
	2.7 Determine if authors (co-)authored one or several of the reviews included in the overview, and if yes, plan safeguards to avoid bias in data extraction		Buchter 2015 [60] ▪ Overview authors do not extract data from their co-authored SRs

CMIMG Comparing Multiple Interventions Methods Group, JBI Joanna Briggs Institute, M-A meta-analysis, SRs systematic reviews

^aAdaption of the step from SRs to overviews. No methods evaluation required, but special consideration needs to be given to unique issues that arise in conducting overviews