The Consensus on Exercise Reporting Template (CERT) in a systematic review of exercise-based rehabilitation effectiveness: completeness of reporting, rater agreement, and utility
Bibliographic record
Abstract
BACKGROUND: Rehabilitation interventions are diverse - making decisions about pooling data in meta-analyses challenging. Intervention reporting templates such as the Consensus on Exercise Reporting Template (CERT) may help reviewers document intervention variability. AIM: To assess inter-rater agreement and utility of CERT used to assess completeness of reporting of one rehabilitation exercise intervention: pelvic floor muscle training (PFMT). DESIGN: A non-experimental agreement study. SETTING: Update of the Cochrane systematic review comparing different approaches to PFMT for urinary incontinence in women. POPULATION: Two PFMT arms from 21 newly identified trials. METHODS: Five raters independently used CERT to assess sufficiency of reporting of each arm (experimental PFMT and control PFMT) of each trial. One rater, PFMT non-expert, rated all trials. Four raters, all PFMT experts, assessed a mutually exclusive subgroup of the trials. In addition to rating sufficiency - "Yes" compared to No" or "Uncertain" - raters also reported on CERT utility. Expert ratings were used to determine the proportion of CERT items rated as sufficiently reported. Rater agreement was estimated using coefficient kappa and McNemar's test. RESULTS: The range of CERT items rated as sufficiently reported was 0 to 15 of 19 items, and the mean for both trial arms was 5.5. For agreement, 11 of 19 items had sufficient data to estimate coefficient kappa and only 3 of 11 had a kappa >0.4 (moderate agreement). From the 12 of 19 items for which McNemar's test could be performed, five had evidence that PFMT experts more often rated the reporting as sufficient than the non-expert. Raters reported the CERT template was comprehensive but not complete and needed contextualizing for PFMT. CONCLUSIONS: Completeness of reporting was poor for this example of a rehabilitation exercise intervention, and equally poor in both trial arms. Inter-rater agreement of completeness of reporting was also poor. Using a data extraction tool with poor rater-agreement may add unnecessary burden in a review. However, using a data extraction tool that enables assessment of intervention homogeneity has benefits in making decisions about which data to pool or not. CLINICAL REHABILITATION IMPACT: Researchers reporting clinical trials must pay more attention to completeness of rehabilitation exercise reporting.
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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 | 0.821 | 0.923 |
| Meta-epidemiology (narrow) | 0.004 | 0.006 |
| Meta-epidemiology (broad) | 0.019 | 0.027 |
| Bibliometrics | 0.028 | 0.031 |
| Science and technology studies | 0.006 | 0.010 |
| Scholarly communication | 0.014 | 0.015 |
| Open science | 0.013 | 0.013 |
| Research integrity | 0.011 | 0.012 |
| Insufficient payload (model declined to judge) | 0.003 | 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".