An Evaluation of Epidemiological and Reporting Characteristics of Complementary and Alternative Medicine (CAM) Systematic Reviews (SRs)
Bibliographic record
Abstract
BACKGROUND: Systematic reviews (SRs) are abundant. The optimal reporting of SRs is critical to enable clinicians to use their findings to make informed treatment decisions. Complementary and alternative medicine (CAM) therapies are widely used therefore it is critical that conduct and reporting of systematic research in this field be of high quality. Here, methodological and reporting characteristics of a sample of CAM-related SRs and a sample of control SRs are evaluated and compared. METHODS: MEDLINE(®) was searched to identify non-Cochrane SRs indexed from January 2010 to May 2011. Control SRs were retrieved and a search filter was used to identify CAM SRs. Citations were screened and publications that met a pre-specified definition of a SR were included. Pre-designed, standardized data extraction forms were developed to capture reporting and methodological characteristics of the included reviews. Where appropriate, samples were compared descriptively. RESULTS: A total of 349 SRs were identified, of which 174 were CAM-related SRs and 175 were conventional SRs. We compared 131 CAM-related non-Cochrane SRs to the 175 conventional non-Cochrane reviews. Fifty-seven percent (75/131) of CAM SRs specified a primary outcome compared to 21% (37/175) of conventional sample reviews. Reporting of publication bias occurred in less than 5% (6/131) of the CAM sample versus 46% (80/175) of the conventional sample of SRs. Source of funding was frequently and consistently under-reported. Less than 5% (11/306) of all SRs reported public availability of a review protocol. CONCLUSION: The two samples of reviews exhibited different strengths and weaknesses. In some cases there were consistencies across items which indicate the need for continued improvements in reporting for all SR reports. We advise authors to utilise the PRISMA Statement or other SR guidance when reporting SRs.
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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 | 0.603 | 0.851 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.007 | 0.022 |
| Bibliometrics | 0.035 | 0.046 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.007 | 0.009 |
| Open science | 0.004 | 0.008 |
| Research integrity | 0.003 | 0.003 |
| 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".