Grading the quality of evidence in complex interventions: a guide for evidence-based practitioners
Open accessAbstract
Evidence-based practitioners who want to apply evidence from complex interventions to the care of their patients are often challenged by the difficulty of grading the quality of this evidence. Using the GRADE (Grading of Recommendations, Assessment, Development and Evaluation) approach and an illustrative example, we propose a framework for evaluating the quality of evidence that depends on obtaining feedback from the evidence user (eg, guideline panel) to inform: (1) proper framing of the question, (2) judgements about directness and consistency of evidence and (3) the need for additional contextual and qualitative evidence. Using this framework, different evidence users and based on their needs would consider the same evidence as high, moderate, low or very low.
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
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?
Public health interventions, such as WASH, are often complex, contain several interacting components, require multiple behaviours and target groups, and are often inherently difficult to randomise or mask, which makes them more likely to be rated as low or very low certainty evidence compared with interventions that can be better controlled, such as clinical interventions.
“Public health interventions, such as WASH, are often complex and contain several interacting components, require multiple behaviours and target groups, and are often inherently difficult to randomise or mask, which makes them more likely to be rated as low or very low certainty evidence compared with interventions that can be better controlled, such as clinical interventions.104, 105”
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Cited by
Sorted by citations
Wolf, J., Hubbard, S., Brauer, M., Ambelu, A., Arnold, B. F., Bain, R., Bauza, V., Brown, J., Caruso, B. A., Clasen, T., et al. (2022) · The Lancet · doi:10.1016/s0140-6736(22)00937-0 · Cited by 377 · see citing works
- Authors
- Murad, M. H., Almasri, J., Alsawas, M., & Farah, W.
- Affiliations
- Mayo Clinic (US)
- Corresponding author
- Murad, M Hassan
- Venue
- Evidence Based Medicine
- Publisher
- BMJ
- Published
- 2016-12-08
- Volume
- 22
- Issue
- 1
- Pages
- 20-22
- ISSN
- 1356-5524 (ISSN-L)
- 1473-6810
- OpenAlex
- W2559798449
- Cited by
- 22
- References
- 0
- Citations by year
- 2026: 3 · 2025: 1 · 2024: 3 · 2023: 3 · 2022: 3 · 2021: 1 · 2020: 1 · 2019: 2 · 2018: 2 · 2017: 3
- FWCI
- 2.32
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- BMJ Evidence-Based Medicine (publishedVersion)
- PubMed (publishedVersion)
- HighWire Press Open Archive (submittedVersion)
- Topics
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Clinical practice guidelines implementation
- Social Sciences › Decision Sciences › Statistics, Probability and Uncertainty › Meta-analysis and systematic reviews
- Health Sciences › Health Professions › General Health Professions › Health Policy Implementation Science
- Keywords
- quality of evidence grading, complex interventions, GRADE, evidence-based practice, contextual evidence, qualitative evidence
- MeSH terms
- Humans, Evidence-Based Medicine
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.
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