Transparency of Outcome Reporting and Trial Registration of Randomized Controlled Trials Published in the Journal of Consulting and Clinical Psychology
Bibliographic record
Abstract
BACKGROUND: Confidence that randomized controlled trial (RCT) results accurately reflect intervention effectiveness depends on proper trial conduct and the accuracy and completeness of published trial reports. The Journal of Consulting and Clinical Psychology (JCCP) is the primary trials journal amongst American Psychological Association (APA) journals. The objectives of this study were to review RCTs recently published in JCCP to evaluate (1) adequacy of primary outcome analysis definitions; (2) registration status; and, (3) among registered trials, adequacy of outcome registrations. Additionally, we compared results from JCCP to findings from a recent study of top psychosomatic and behavioral medicine journals. METHODS: Eligible RCTs were published in JCCP in 2013-2014. For each RCT, two investigators independently extracted data on (1) adequacy of outcome analysis definitions in the published report, (2) whether the RCT was registered prior to enrolling patients, and (3) adequacy of outcome registration. RESULTS: Of 70 RCTs reviewed, 12 (17.1%) adequately defined primary or secondary outcome analyses, whereas 58 (82.3%) had multiple primary outcome analyses without statistical adjustment or undefined outcome analyses. There were 39 (55.7%) registered trials. Only two trials registered prior to patient enrollment with a single primary outcome variable and time point of assessment. However, in one of the two trials, registered and published outcomes were discrepant. No studies were adequately registered as per Standard Protocol Items: Recommendation for Interventional Trials guidelines. Compared to psychosomatic and behavioral medicine journals, the proportion of published trials with adequate outcome analysis declarations was significantly lower in JCCP (17.1% versus 32.9%; p = 0.029). The proportion of registered trials in JCCP (55.7%) was comparable to behavioral medicine journals (52.6%; p = 0.709). CONCLUSIONS: The quality of published outcome analysis definitions and trial registrations in JCCP is suboptimal. Greater attention to proper trial registration and outcome analysis definition in published reports is needed.
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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 | 0.860 | 0.944 |
| Meta-epidemiology (narrow) | 0.003 | 0.007 |
| Meta-epidemiology (broad) | 0.012 | 0.009 |
| Bibliometrics | 0.026 | 0.031 |
| Science and technology studies | 0.006 | 0.025 |
| Scholarly communication | 0.022 | 0.022 |
| Open science | 0.013 | 0.012 |
| Research integrity | 0.018 | 0.017 |
| Insufficient payload (model declined to judge) | 0.012 | 0.007 |
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".