Outcome reporting in randomized controlled trials of major depressive disorder treatments in adolescents: a systematic scoping review protocol
Bibliographic record
Abstract
Introduction: Major depressive disorder (MDD) is a common mental health condition in adolescents. Randomized clinical trials (RCTs) are the gold-standard for assessing the safety and efficacy of interventions in this population. Heterogeneity in the outcomes measured and reported between RCTs limits the ability to compare, contrast, and combine trial results in a clinically meaningful way. There is currently no core outcome set (COS) available for use in RCTs evaluating interventions in adolescents with MDD. We will conduct a systematic scoping review of outcomes reported in adolescent depression RCTs to assess the variability of trial outcomes and to inform the development of a COS for adolescent MDD. Methods and analysis: We will apply methods based on the Joanna Briggs Institute scoping review methods manual. RCTs evaluating any treatment intervention for adolescent MDD published in the last ten years will be located using an electronic bibliographic database search (MEDLINE, PsycINFO, and Cochrane Central Register of Controlled Trials). Title and abstract screening, full-text screening, and data charting of eligible studies will be performed in duplicate. Outcomes identified will be mapped to an outcome domain framework. Data analysis will include summary statistics of the characteristics of the included trials and outcomes. Ethics and dissemination: The results of this review will inform the development of a COS for adolescent MDD. The development and implementation of a COS for RCTs evaluating interventions in adolescents with MDD promises to help reduce variability in trial outcome selection, definition, measurement, and reporting, ultimately facilitating evidence synthesis that will help to identify best treatment practices for adolescents with MDD. Registration details: This protocol was registered prospectively with the Open Science Framework (https://osf.io/xjz9u/).
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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 | 0.184 | 0.175 |
| Meta-epidemiology (narrow) | 0.007 | 0.007 |
| Meta-epidemiology (broad) | 0.018 | 0.018 |
| Bibliometrics | 0.021 | 0.023 |
| Science and technology studies | 0.006 | 0.007 |
| Scholarly communication | 0.011 | 0.011 |
| Open science | 0.008 | 0.009 |
| Research integrity | 0.011 | 0.013 |
| Insufficient payload (model declined to judge) | 0.085 | 0.019 |
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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".