Consensus on Exercise Reporting Template (CERT): Modified Delphi Study
Bibliographic record
Abstract
BACKGROUND: Exercise interventions are often incompletely described in reports of clinical trials, hampering evaluation of results and replication and implementation into practice. OBJECTIVE: The aim of this study was to develop a standardized method for reporting exercise programs in clinical trials: the Consensus on Exercise Reporting Template (CERT). DESIGN AND METHODS: Using the EQUATOR Network's methodological framework, 137 exercise experts were invited to participate in a Delphi consensus study. A list of 41 items was identified from a meta-epidemiologic study of 73 systematic reviews of exercise. For each item, participants indicated agreement on an 11-point rating scale. Consensus for item inclusion was defined a priori as greater than 70% agreement of respondents rating an item 7 or above. Three sequential rounds of anonymous online questionnaires and a Delphi workshop were used. RESULTS: There were 57 (response rate=42%), 54 (response rate=95%), and 49 (response rate=91%) respondents to rounds 1 through 3, respectively, from 11 countries and a range of disciplines. In round 1, 2 items were excluded; 24 items reached consensus for inclusion (8 items accepted in original format), and 16 items were revised in response to participant suggestions. Of 14 items in round 2, 3 were excluded, 11 reached consensus for inclusion (4 items accepted in original format), and 7 were reworded. Sixteen items were included in round 3, and all items reached greater than 70% consensus for inclusion. LIMITATIONS: The views of included Delphi panelists may differ from those of experts who declined participation and may not fully represent the views of all exercise experts. CONCLUSIONS: The CERT, a 16-item checklist developed by an international panel of exercise experts, is designed to improve the reporting of exercise programs in all evaluative study designs and contains 7 categories: materials, provider, delivery, location, dosage, tailoring, and compliance. The CERT will encourage transparency, improve trial interpretation and replication, and facilitate implementation of effective exercise interventions into practice.
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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 | 0.428 | 0.474 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.004 |
| Bibliometrics | 0.008 | 0.006 |
| Science and technology studies | 0.003 | 0.005 |
| Scholarly communication | 0.003 | 0.005 |
| Open science | 0.005 | 0.013 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.007 | 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; 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".