Assessing the Reporting and Scientific Quality of Meta-Analyses of Randomized Controlled Trials of Treatments for Anxiety Disorders
Bibliographic record
Abstract
BACKGROUND: Meta-analyses of randomized controlled trials (RCTs) constitute the highest level of evidence, but their usefulness depends on their quality. OBJECTIVE: To assess the reporting and scientific quality of meta-analyses of RCTs on treatments for anxiety disorders. METHODS: Criteria for peer-reviewed, full-text retrieval included meta-analyses of RCTs of drugs versus active ingredient placebo, standard care, or psychotherapy. Sample populations were required to meet Diagnostic and Statistical Manual of Mental Disorders or International Classification of Diseases and Related Health Problems diagnostic criteria for anxiety disorders. Two reviewers independently searched EMBASE, EBM Reviews, Ovid MEDLINE, Ovid HealthSTAR, and International Pharmaceutical Abstracts from inception to August 2007. Search terms included meta-analysis, randomized controlled trials, anxiety, anxiolytic, anti-depressant/antidepressant, and pharmacotherapy, without language restrictions. References and reviews were searched manually. Quality was assessed independently by 2 raters, using the Quality of Reporting of Meta-analyses (QUOROM) and the Overview Quality Assessment Questionnaire (OQAQ). The QUOROM was used to assess the reporting quality of the study, using an 18-item checklist, and the scientific quality was assessed with the OQAQ's 10-item checklist. Kendall's tau measured interrater reliability with statistical significance at p less than or equal to 0.01. Means and standard deviations described the overall quality. A time series analysis was performed. RESULTS: A total of 136 titles and abstracts were reviewed; 48 were retrieved, including 6 from the manual search. Thirty-two were excluded (not pooled analyses, inappropriate condition/treatment, duplications), leaving 16 studies published between 1995 and 2007. Agreement was high: tau = 0.801 (p < 0.01) for QUOROM and 0.834 (p < 0.01) for OQAQ. QUOROM quality scored 61% +/- 19%. Overall, the results sections of the studies scored lowest, while the introduction and discussion sections scored highest. The overall scientific quality was 58% +/- 28%. Most studies appropriately linked results to primary objectives but did not report how bias was avoided or how study validity was assessed. Quality increased nonsignificantly over time. CONCLUSIONS: Reporting/scientific quality was considered less than fair-to-good. Stakeholders should strive for higher scientific quality of meta-analyses.
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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 | 0.554 | 0.808 |
| Meta-epidemiology (narrow) | 0.006 | 0.004 |
| Meta-epidemiology (broad) | 0.024 | 0.053 |
| Bibliometrics | 0.043 | 0.034 |
| Science and technology studies | 0.002 | 0.005 |
| Scholarly communication | 0.010 | 0.008 |
| Open science | 0.008 | 0.006 |
| Research integrity | 0.006 | 0.005 |
| Insufficient payload (model declined to judge) | 0.004 | 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; the direct Gemma label and the distilled Codex classifier 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".