From Protocol to Definitive Study—The State of Randomized Controlled Trial Evidence in Sports Medicine Research: A Systematic Review and Survey Study
Bibliographic record
Abstract
OBJECTIVE: To evaluate the progression, quality, and challenges associated with conducting and publishing randomized controlled trials (RCTs) in sports medicine. DESIGN: Systematic review and survey. SETTING: MEDLINE and Embase were searched for all publications before September 17, 2021. A targeted search of clinicaltrials.gov , BMC Musculoskeletal Disorders, PubMed, and Google Scholar were also conducted. The survey was administered to authors using REDCap. PARTICIPANTS: Where the systematic search revealed no corresponding published definitive trial, authors of the published pilots were surveyed. INTERVENTIONS: Survey assessing limitations to definitive trials. MAIN OUTCOME MEASURES: Protocol/method articles, pilot articles, and relevant clinical trial registry records with corresponding definitive trials were pooled. RESULTS: Our literature search yielded 27 006 studies; of which, we included 208 studies (60 (28.8%) pilot RCTs, 84 (40.4%) protocol/method articles, and 64 (30.8%) trial registry records). From these, 44 corresponding definitive RCTs were identified. Pilot study and definitive RCT methodological quality increased on average most significantly during the duration of this review (30.6% and 8.2%). Of the 176 authors surveyed, 59 (33.5%) responded; 24.6% (14/57) stated that they completed an unpublished definitive trial, while 52.6% (30/57) reported having one underway. CONCLUSIONS: The quality and number of RCT publications within the field of sports medicine has been increasing since 1999. The number of sports medicine-related protocol and pilot articles preceding a definitive trial publication showed a sharp increase over the past 10 years, although only 5 pilot studies have progressed to a definitive RCT.
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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 | 0.710 | 0.824 |
| Meta-epidemiology (narrow) | 0.002 | 0.005 |
| Meta-epidemiology (broad) | 0.011 | 0.013 |
| Bibliometrics | 0.029 | 0.030 |
| Science and technology studies | 0.004 | 0.009 |
| Scholarly communication | 0.018 | 0.029 |
| Open science | 0.006 | 0.012 |
| Research integrity | 0.008 | 0.006 |
| Insufficient payload (model declined to judge) | 0.009 | 0.003 |
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".