When continuous outcomes are measured using different scales: guide for meta-analysis and interpretation.
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Where this comes from
- Record sourced from PubMed, PMID 30670455.
- Also identified by DOI 10.1136/bmj.k4817 and PMC identifier 6890471.
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Abstract
It is common to measure continuous outcomes using different scales (eg, quality of life, severity of anxiety or depression), therefore these outcomes need to be standardized before pooling in a meta-analysis. Common methods of standardization include using the standardized mean difference, the odds ratio derived from continuous data, the minimally important difference, and the ratio of means. Other ways of making data more meaningful to end users include transforming standardized effects back to original scales and transforming odds ratios to absolute effects using an assumed baseline risk. For these methods to be valid, the scales or instruments being combined across studies need to have assessed the same or a similar construct
Medical subject headings
- Anxiety
- Data Interpretation, Statistical
- Outcome Assessment, Health Care