CoChat
Sign Up
Cited by 464Meta-analysis and systematic reviewsClinical practice guidelines implementationDelphi Technique in Research

The DOI matches its Crossref record; 19 of the 24 references it cites were found in a registry or an index; none of the 24 sources its claims cite is checked for support yet.

Strengthening systematic reviews in public health: guidance in the Cochrane Handbook for Systematic Reviews of Interventions , 2nd edition

Open access
Cumpston, Miranda S, McKenzie, Joanne E, Welch, Vivian A, Brennan, Sue E·2022·Journal of Public Health
DOI 10.1093/pubmed/fdac036PMC PMC9715291
Open this paper in CoChat — free accountOpen PDF

Abstract

Aims: Decision makers in public health practice and policy rely on access to trustworthy, relevant, synthesized evidence. The second edition of the Cochrane Handbook for Systematic Reviews of Interventions (‘the Handbook’) reflects a major revision in guidance for authors of systematic reviews, incorporating a decade of methodological development and a number of significant changes to previous recommendations. This paper aims to highlight new guidance that addresses a number of key methodological challenges for authors of systematic reviews in public health. Results: The revised Handbook includes guidance on framing public health research questions for synthesis, considering equity, intervention complexity, risk of bias assessment and synthesis methods other than meta-analysis. Reviews of public health interventions frequently encounter the types of methodological complexity addressed in this new guidance. Conclusion: We hope that readers will find that the Cochrane Handbook includes detailed and thoughtful guidance on both conceptualizing and executing systematic reviews relevant to public health questions. Considering the available methods guidance will, we hope, provide support for authors of public health reviews to tackle the challenges they encounter, strengthen their analysis and provide useful answers to the important questions asked by stakeholders and users of public health evidence.

Overview

AI snapshot

Written from the paper’s full text.

TL;DR

This paper is a narrative overview of new and revised methodological guidance in the second edition of the Cochrane Handbook for Systematic Reviews of Interventions, aimed at authors of public health systematic reviews. It highlights Handbook guidance on framing review questions, equity, intervention complexity, risk of bias across diverse study designs, and synthesis methods other than meta-analysis.

Key findings

  • The second edition of the Handbook represents a major revision incorporating a decade of methodological development, with new standalone guidance on equity (Chapter 16) and, for the first time, alternative statistical synthesis methods (Chapter 12).
  • Reviews of public health interventions frequently encounter the methodological complexity addressed by this guidance, including interventions that vary in theoretical approach, components and implementation, and populations that differ in important ways.
  • Around a third to half of all systematic reviews do not use meta-analysis at all, and more do not use meta-analysis for all outcomes (citing refs 23–24).
  • Alternative synthesis methods presented in Chapter 12 include summary statistics describing the range of effect estimates, vote counting based on direction of effect, and combining P values, with companion visual displays such as box plots, harvest plots and albatross plots; these yield results "more limited for decision making in comparison to meta-analysis."

Methods

  • Design: a narrative guidance/commentary paper highlighting selected areas of updated Cochrane guidance of particular relevance to public health reviews; it is not itself a systematic review.
  • Data: no new data were generated or analysed (per the paper's data availability statement); illustrative examples are drawn from existing reviews (e.g. a school-based physical activity review and a rotavirus vaccine review).
  • Content covers Handbook chapters on scope and eligibility (Chapters 2–3), equity (Chapter 16), intervention complexity (Chapter 17), bias (Chapters 7, 13), risk-of-bias tools RoB 2 (Chapter 8) and ROBINS-I (Chapter 25), and alternative synthesis (Chapter 12), plus PRISMA 2020 and SWiM reporting guidelines.

Limitations

  • The paper states no formal limitations section; it is explicitly a selective highlight of "some areas" of updated guidance rather than a comprehensive account.
  • Evident from the text: as a narrative overview without new data or empirical evaluation, it does not assess the uptake, impact or effectiveness of the guidance it describes, and its recommendations rest on the Handbook's methodological development rather than on primary research conducted here.

Model-written summary. Check it against the paper before relying on it.

Integrity signals

Registry

Crossref · 10.1093/pubmed/fdac036

Cites

19 of 19 references verified0 citation errors · 0 not checkable

Statistics

Nothing to recompute.

Verification

Claims the paper makes

0 of 24 cited sources checked · 0 supported · 0 flagged

    • Probably not a substantial claim. 21
    • It may state two separate claims as one. 11
    22 of 22

    • The paper relies on this without support.

      It is common for reviews in public health to consider interventions that vary in theoretical approach, components and implementation among the included studies.

      “It is common for reviews in public health to consider interventions that vary in theoretical approach, components and implementation among the included studies.”

    • The paper relies on this without support.

      Planning for complexity can minimize bias arising from post hoc selection while improving clarity for readers.

      “Planning for complexity can minimize bias arising from post hoc selection while improving clarity for readers.”

    • The paper relies on this without support.

      Presenting a clear definition of each group and a rationale for the groups chosen enables transparency and replicability of the decisions to group studies in particular ways and enhances understanding for readers and end users of the review’s findings.

      “Presenting a clear definition of each group and a rationale for the groups chosen enables transparency and replicability of the decisions to group studies in particular ways and enhances understanding for readers and end users of the review’s findings.”

    • The paper relies on this without support.

      Considering equity explicitly in systematic reviews from question formulation to interpretation adds value to the review’s findings, enabling end users to understand whether and how the findings of the review apply to different populations and settings, and ensuring that high-level, aggregated results do not obscure important differences in effects.

      “Considering equity explicitly in systematic reviews from question formulation to interpretation adds value to the review’s findings, enabling end users to understand whether and how the findings of the review apply to different populations and settings, and ensuring that high-level, aggregated results do not obscure important differences in effects.”

    • The paper relies on this without support.

      It is well known that public health interventions are often comprised of multiple components (what may be considered ‘complicated’ interventions).

      “It is well known that public health interventions are often comprised of multiple components (what may be considered ‘complicated’ interventions).”

    • The paper relies on this without support.

      Exhaustively listing intervention components may complicate analysis without adding meaningful understanding to the review’s findings.

      “Exhaustively listing intervention components may complicate analysis without adding meaningful understanding to the review’s findings.”

    • The paper relies on this without support.

      It may be that the most useful review would not aim to estimate a universal effect, but to explore why and how an intervention may have been successful in specific cases.

      “It may be that the most useful review would not aim to estimate a universal effect, but to explore why and how an intervention may have been successful in specific cases.”

    • The paper relies on this without support.

      Although many systematic reviews of public health interventions include randomized trials, there are others that cannot, where randomized trials may be unethical, infeasible, unaffordable or simply do not exist.

      “Although many systematic reviews of public health interventions include randomized trials, there are others that cannot, where randomized trials may be unethical, infeasible, unaffordable or simply do not exist.”

    • The paper relies on this without support.

      Reasons why meta-analysis may not be possible are varied, but one reason may be when the included primary studies do not provide the necessary data required for a meta-analysis.

      “Reasons why meta-analysis may not be possible are varied, but one reason may be when the included primary studies do not provide the necessary data required for a meta-analysis.”

    • The paper relies on this without support.

      In some cases, synthesis may be inappropriate, for example where the included studies are at a high risk of bias or there are concerns about missing evidence.

      “In some cases, synthesis may be inappropriate, for example where the included studies are at a high risk of bias or there are concerns about missing evidence.”

    • The paper relies on this without support.

      Although these alternative synthesis methods yield results that are more limited for decision making in comparison to meta-analysis, they provide additional options for review authors when the required data for meta-analysis are not available.

      “Although these alternative synthesis methods yield results that are more limited for decision making in comparison to meta-analysis, they provide additional options for review authors when the required data for meta-analysis are not available.”

    • The paper relies on this without support.

      These methods may enable authors to make the most of the available data and provide a structured approach where authors may have felt limited to text-based descriptions of the findings of individual studies, which can become rapidly unwieldy where large numbers of studies or complex interventions are involved.

      “These methods may enable authors to make the most of the available data and provide a structured approach where authors may have felt limited to text-based descriptions of the findings of individual studies, which can become rapidly unwieldy where large numbers of studies or complex interventions are involved.”
    12 of 12

    Claims other papers make about this one

    Each is checked against this paper’s own text: does it say what the citing paper says it does?

    Citations

    Cites

    Flagged first, then by citations

    Show all 24 references

    5 of the 24 references couldn’t be matched to a known paper.

    Research works printed but not linked: 12

    1. World Health Organization, 2018, WHO Handbook for Guideline Development
    2. NICE, 2020, Developing NICE Guidelines: The Manual
    3. National Health and Medical Research Council, 2021, Guidelines for Guidelines Manual
    4. Cochrane, 2021, Cochrane COVID reviews
    5. McKenzie, 2019, Cochrane Handbook for Systematic Reviews of Interventions
    6. Welch, Cochrane Handbook for Systematic Reviews of Interventions
    7. Thomas, 2019, Cochrane Handbook for Systematic Reviews of Interventions
    8. Boutron, 2019, Cochrane Handbook for Systematic Reviews of Interventions
    9. Page, 2019, Cochrane Handbook for Systematic Reviews of Interventions
    10. Higgins, 2019, Cochrane Handbook for Systematic Reviews of Interventions, 10.1002/9781119536604 · DOI · Paper page
    11. Sterne, 2019, Cochrane Handbook for Systematic Reviews of Interventions
    12. McKenzie, 2019, Cochrane Handbook for Systematic Reviews of Interventions

    Cited by

    Sorted by citations

    Items 201–300 of 436

    Related

    See all

    Metadata

    Authors
    Cumpston, M. S., McKenzie, J. E., Welch, V. A., & Brennan, S. E.
    Affiliations
    • University of Newcastle Australia (AU)
    • Monash University (AU)
    • University of Ottawa (CA)
    Corresponding author
    Cumpston, Miranda S
    ORCID
    Venue
    Journal of Public Health
    Publisher
    Oxford University Press (OUP)
    Published
    2022-03-28
    Volume
    44
    Issue
    4
    Pages
    e588-e592
    ISSN
    • 0943-1853 (ISSN-L)
    • 1741-3842
    • 1741-3850
    DOI
    10.1093/pubmed/fdac036
    PMC
    PMC9715291
    OpenAlex
    W4213435918
    Semantic Scholar
    2d71db8c682696f6d419e48317010613d7d43d5c
    Cited by
    464
    References
    24
    Citations by year
    2026: 114 · 2025: 133 · 2024: 147 · 2023: 54 · 2022: 15
    FWCI
    28.58
    Type
    journal article
    Language
    en
    Open access
    Licence
    Locations
    • Journal of Public Health (publishedVersion, cc-by-nc)
    • PubMed Central (publishedVersion, cc-by-nc)
    • PubMed (publishedVersion)
    Funders
    • Australian National Health and Medical Research Council
    • Career Development Fellowship (1143429)
    Topics
    • Social Sciences › Decision Sciences › Statistics, Probability and Uncertainty › Meta-analysis and systematic reviews
    • Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Clinical practice guidelines implementation
    • Social Sciences › Sociology and Political Science › Delphi Technique in Research
    Keywords
    systematic reviews, public health interventions, research question formulation, equity, intervention complexity, risk of bias assessment, methodological recommendations, evidence synthesis
    MeSH terms
    Systematic Reviews as Topic, Humans, Public Health, Public Health Practice, Bias

    About these checks

    Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

    A language model drew the claims from the paper on 2026-10-08, under version 3 of the claim definition (model deepseek-v4.1-flash, prompt extract-v3).

    A second model labelled each claim on 2026-10-08 (model jev-1.13-20260917, definition revision gold-guideline-v0.2).

    Statistics and arithmetic are recomputed, not judged.

    Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

    What counts as a claim ›How we measure confidence ›How we check this ›

    Are you an author, or do you see a problem with this page? Request a review