A descriptive analysis of child-relevant systematic reviews in the Cochrane Database of Systematic Reviews
Bibliographic record
Abstract
BACKGROUND: Systematic reviews (SRs) are considered an important tool for decision-making. There has been no recent comprehensive identification or description of child-relevant SRs. A description of existing child-relevant SRs would help to identify the extent of available child-relevant evidence available in SRs and gaps in the evidence base where SRs are required. The objective of this study was to describe child-relevant SRs from the Cochrane Database of Systematic Reviews (CDSR, Issue 2, 2009). METHODS: SRs were assessed for relevance using pre-defined criteria. Data were extracted and entered into an electronic form. Univariate analyses were performed to describe the SRs overall and by topic area. RESULTS: The search yielded 1666 SRs; 793 met the inclusion criteria. 38% of SRs were last assessed as up-to-date prior to 2007. Corresponding authors were most often from the UK (41%). Most SRs (59%) examined pharmacological interventions. 53% had at least one external source of funding. SRs included a median of 7 studies (IQR 3, 15) and 679 participants (IQR 179, 2833). Of all studies, 48% included only children, and 27% only adults. 94% of studies were published in peer-reviewed journals. Primary outcomes were specified in 72% of SRs. Allocation concealment and the Jadad scale were used in 97% and 25% of SRs, respectively. Adults and children were analyzed separately in 12% of SRs and as a subgroup analysis in 14%. Publication bias was assessed in only 14% of SRs. A meta-analysis was conducted in 68% of SRs with a median of 5 trials (IQR 3, 9) each. Variations in these characteristics were observed across topic areas. CONCLUSIONS: We described the methodological characteristics and rigour of child-relevant reviews in the CDSR. Many SRs are not up-to-date according to Cochrane criteria. Our study describes variation in conduct and reporting across SRs and reveals clinicians' ability to access child-specific data.
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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 | 0.076 | 0.352 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.011 | 0.014 |
| Bibliometrics | 0.097 | 0.079 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.012 | 0.001 |
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".