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Using risk and odds ratios to assess effect size for meta‐analysis outcome measures


Alavi, M and Hunt, GE and Visentin, DC and Watson, R and Thapa, DK and Cleary, M, Using risk and odds ratios to assess effect size for meta‐analysis outcome measures, Journal of Advanced Nursing, 76, (12) pp. 3231-3234. ISSN 0309-2402 (2020) [Non Refereed Article]

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DOI: doi:10.1111/jan.14528



Best practice is built on the principle of aggregating all available evidence on a topic to make a clinical decision on the most appropriate intervention for the situation at hand. Systematic reviews and meta‐analyses are powerful tools that summarize the evidence for current best practice guidelines for the available interventions for a particular problem (Moher, Liberati, Tetzlaff, & Altman, 2009). Meta‐analysis combines the results of multiple studies to produce an aggregated and more precise estimates of the benefits of the interventions. Meta‐analysis of high‐quality randomized trials is considered the highest level of evidence to inform practice.

When reading the healthcare literature, several measures of the effect of an intervention on an outcome are available to judge whether the evidence presented can be applied to clinical practice. It is important to be able to understand, correctly interpret, and honestly communicate these reported measures (Thapa, Visentin, Hunt, Watson, & Cleary, 2020). However, it is not uncommon for clinicians and researchers to be confused about the differences between the various effect measures available (Tufanaru, Munn, Stephenson, & Aromataris, 2015). These will be outlined further in this editorial, with a focus on the risk and odds ratios.

Item Details

Item Type:Non Refereed Article
Keywords:risk and odds ratios, effect size, meta-analysis, outcome measures
Research Division:Health Sciences
Research Group:Nursing
Research Field:Nursing not elsewhere classified
Objective Division:Health
Objective Group:Evaluation of health and support services
Objective Field:Evaluation of health outcomes
UTAS Author:Visentin, DC (Dr Denis Visentin)
UTAS Author:Thapa, DK (Mr Deependra Thapa)
UTAS Author:Cleary, M (Professor Michelle Cleary)
ID Code:141306
Year Published:2020
Web of Science® Times Cited:1
Deposited By:Nursing
Deposited On:2020-10-14
Last Modified:2021-04-20

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