Characteristics of the sources, evaluation, and grading of the certainty of evidence in systematic reviews in public health: A methodological study
Bibliographic record
Abstract
Objectives To systematically explore how the sources of evidence, types of primary studies, and tools used to assess the quality of the primary studies vary across systematic reviews (SRs) in public health. Methods We conducted a methodological survey of SRs in public health by searching the of literature in selected journals from electronic bibliographic databases. We selected a 10% random sample of the SRs that met the explicit inclusion criteria. Two researchers independently extracted data for analysis. Results We selected 301 SRs for analysis: 94 (31.2%) of these were pre-registered, and 211 (70.1%) declared to have followed published reporting standard. All SRs searched for evidence in electronic bibliographic databases, and more than half ( n = 180, 60.0%) searched also the references of the included studies. The common types of primary studies included in the SRs were primarily cross-sectional studies ( n = 132, 43.8%), cohort studies ( n = 126, 41.9%), randomized controlled trials (RCTs, n = 89, 29.6%), quasi-experimental studies ( n = 83, 27.6%), case-control studies ( n = 58, 19.3%) qualitative studies ( n = 38, 12.6%) and mixed-methods studies ( n = 32, 10.6%). The most frequently used quality assessment tools were the Newcastle-Ottawa Scale (used for 50.0% of cohort studies and 55.6% of case-control studies), Cochrane Collaboration's Risk of Bias tool (50.7% of RCTs) and Critical Appraisal Skills Program (38.5% of qualitative studies). Only 20 (6.6%) of the SRs assessed the certainty of the body of evidence, of which 19 (95.0%) used the GRADE approach. More than 65% of the evidence in the SRs using GRADE was of low or very low certainty. Conclusions SRs should always assess the quality both at the individual study level and the body of evidence for outcomes, which will benefit patients, health care practitioners, and policymakers.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.657 | 0.382 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.007 | 0.001 |
| Bibliometrics | 0.001 | 0.008 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; both teacher heads agree on what is shown here.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".