A Descriptive Analysis of Overviews of Reviews Published between 2000 and 2011
Bibliographic record
Abstract
BACKGROUND: Overviews of systematic reviews compile data from multiple systematic reviews (SRs) and are a new method of evidence synthesis. OBJECTIVES: To describe the methodological approaches in overviews of interventions. DESIGN: Descriptive study. METHODS: We searched 4 databases from 2000 to July 2011; we handsearched Evidence-based Child Health: A Cochrane Review Journal. We defined an overview as a study that: stated a clear objective; examined an intervention; used explicit methods to identify SRs; collected and synthesized outcome data from the SRs; and intended to include only SRs. We did not restrict inclusion by population characteristics (e.g., adult or children only). Two researchers independently screened studies and applied eligibility criteria. One researcher extracted data with verification by a second. We conducted a descriptive analysis. RESULTS: From 2,245 citations, 75 overviews were included. The number of overviews increased from 1 in 2000 to 14 in 2010. The interventions were pharmacological (n = 20, 26.7%), non-pharmacological (n = 26, 34.7%), or both (n = 29, 38.7%). Inclusion criteria were clearly stated in 65 overviews. Thirty-three (44%) overviews searched at least 2 databases. The majority reported the years and databases searched (n = 46, 61%), and provided key words (n = 58, 77%). Thirty-nine (52%) overviews included Cochrane SRs only. Two reviewers independently screened and completed full text review in 29 overviews (39%). Methods of data extraction were reported in 45 (60%). Information on quality of individual studies was extracted from the original SRs in 27 (36%) overviews. Quality assessment of the SRs was performed in 28 (37%) overviews; at least 9 different tools were used. Quality of the body of evidence was assessed in 13 (17%) overviews. Most overviews provided a narrative or descriptive analysis of the included SRs. One overview conducted indirect analyses and the other conducted mixed treatment comparisons. Publication bias was discussed in 18 (24%) overviews. CONCLUSIONS: This study shows considerable variation in the methods used for overviews. There is a need for methodological rigor and consistency in overviews, as well as empirical evidence to support the methods employed.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.062 | 0.268 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.006 | 0.009 |
| Bibliometrics | 0.142 | 0.101 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.005 | 0.008 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.012 | 0.002 |
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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".