A 7-Step Guideline for Qualitative Synthesis and Meta-Analysis of Observational Studies in Health Sciences.
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2023
- doi: 10.3389/phrs.2023.1605454
- issn: 0301-0422
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info:eu-repo/semantics/altIdentifier/doi/10.3389/phrs.2023.1605454
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info:eu-repo/semantics/altIdentifier/pmid/37260612
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info:eu-repo/semantics/altIdentifier/pissn/0301-0422
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info:eu-repo/semantics/altIdentifier/urn/urn:nbn:ch:serval-BIB_0CD653F549804
info:eu-repo/semantics/openAccess , CC BY-ND 4.0 , https://creativecommons.org/licenses/by-nd/4.0/
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M. Glisic et al., « A 7-Step Guideline for Qualitative Synthesis and Meta-Analysis of Observational Studies in Health Sciences. », Serveur académique Lausannois, ID : 10.3389/phrs.2023.1605454
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Résumé
Objectives: To provide a step-by-step, easy-to-understand, practical guide for systematic review and meta-analysis of observational studies. Methods: A multidisciplinary team of researchers with extensive experience in observational studies and systematic review and meta-analysis was established. Previous guidelines in evidence synthesis were considered. Results: There is inherent variability in observational study design, population, and analysis, making evidence synthesis challenging. We provided a framework and discussed basic meta-analysis concepts to assist reviewers in making informed decisions. We also explained several statistical tools for dealing with heterogeneity, probing for bias, and interpreting findings. Finally, we briefly discussed issues and caveats for translating results into clinical and public health recommendations. Our guideline complements "A 24-step guide on how to design, conduct, and successfully publish a systematic review and meta-analysis in medical research" and addresses peculiarities for observational studies previously unexplored. Conclusion: We provided 7 steps to synthesize evidence from observational studies. We encourage medical and public health practitioners who answer important questions to systematically integrate evidence from observational studies and contribute evidence-based decision-making in health sciences.