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Practical challenges and solutions in meta-analysis: An example from the pain medicine literature

Practical challenges and solutions in meta-analysis: An example from the pain medicine literature

Thompson, Trevor ORCID: 0000-0001-9880-782X (2020) Practical challenges and solutions in meta-analysis: An example from the pain medicine literature. SAGE Research Methods Cases: Medicine & Health. (doi:https://doi.org/10.4135/9781529741582)

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Abstract

Meta-analysis can provide a reliable overall estimate of the effect of an intervention by combining all of the available individual study evidence. Although there are an ever-increasing number of published meta-analyses, journal word limits mean that the numerous practical challenges involved in producing the final review are usually not documented. This case study is an attempt to identify these types of challenges using a concrete example of a real meta-analysis examining hypnotic interventions for pain. Specific strategies that can be used to help tackle these challenges are outlined, including preparation of a detailed study protocol, how to approach tricky screening and extraction decisions, computing effect sizes when data are not presented in conventional form, and the importance of assembling a suitable research team. This case does not describe the methodological principles of meta-analysis for which there are many excellent existing texts. Instead, it can be used as a complementary guide to these texts as it highlights the type of practical challenges that we faced and suggests possible ways to combat them that we hope will be useful to others.

Item Type: Article
Uncontrolled Keywords: Anesthesiology & Pain Medicine; Meta-analysis
Subjects: G Geography. Anthropology. Recreation > GE Environmental Sciences
R Medicine > R Medicine (General)
Faculty / Department / Research Group: Faculty of Education, Health & Human Sciences
Faculty of Education, Health & Human Sciences > Department of Psychology, Social Work & Counselling
Last Modified: 03 Aug 2020 10:50
Selected for GREAT 2016: None
Selected for GREAT 2017: None
Selected for GREAT 2018: None
Selected for GREAT 2019: None
Selected for REF2021: None
URI: http://gala.gre.ac.uk/id/eprint/28380

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