Which resources should be used to identify RCT/CCTs for systematic reviews: a systematic review
Bibliographic record
Abstract
BACKGROUND: Systematic reviewers seek to comprehensively search for relevant studies and summarize these to present the most valid estimate of intervention effectiveness. The more resources searched, the higher the yield, and thus time and costs required to conduct a systematic review. While there is an abundance of evidence to suggest how extensive a search for randomized controlled trials (RCTs) should be, it is neither conclusive nor consistent. This systematic review was conducted in order to assess the value of different resources to identify trials for inclusion in systematic reviews. METHODS: Seven electronic databases, four journals and Cochrane Colloquia were searched. Key authors were contacted and references of relevant articles screened. Included studies compared two or more sources to find RCTs or controlled clinical trials (CCTs). A checklist was developed and applied to assess quality of reporting. Data were extracted by one reviewer and checked by a second. Medians and ranges for precision and recall were calculated; results were grouped by comparison. Meta-analysis was not performed due to large heterogeneity. Subgroup analyses were conducted for: search strategy (Cochrane, Simple, Complex, Index), expertise of the searcher (Cochrane, librarian, non-librarian), and study design (RCT and CCT). RESULTS: Sixty-four studies representing 13 electronic databases met inclusion criteria. The most common comparisons were MEDLINE vs. handsearching (n = 23), MEDLINE vs. MEDLINE+handsearching (n = 13), and MEDLINE vs. reference standard (n = 13). Quality was low, particularly for the reporting of study selection methodology. Overall, recall and precision varied substantially by comparison and ranged from 0 to 100% and 0 to 99%, respectively. The trial registries performed the best with median recall of 89% (range 84, 95) and median precision of 96.5% (96, 97), although these results are based on a small number of studies. Inadequate or inappropriate indexing was the reason most cited for missing studies. Complex and Cochrane search strategies (SS) performed better than Simple SS. CONCLUSION: Multiple-source comprehensive searches are necessary to identify all RCTs for a systematic review, although indexing needs to be improved. Although trial registries demonstrated the highest recall and precision, the Cochrane SS or a Complex SS in consultation with a librarian are recommended. Continued efforts to develop CENTRAL should be supported.
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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 | 0.932 | 0.988 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.109 | 0.019 |
| Bibliometrics | 0.005 | 0.015 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.023 | 0.003 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.017 | 0.026 |
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".