Forks in the road: Definitions of response, remission, recovery, and other dichotomized outcomes in randomized controlled trials for adolescent depression. A scoping review
Bibliographic record
Abstract
BACKGROUND: Definitions of dichotomous outcome terms, such as "response," "remission," and "recovery" are central to the design, interpretation, and clinical application of randomized controlled trials of adolescent depression interventions. Accordingly, this scoping review was conducted to document how these terms have been defined and justified in clinical trials. METHOD: Bibliographic databases MEDLINE, Embase, APA PsycInfo, and CINAHL were searched from inception to February 2020 for randomized controlled trials evaluating treatments for adolescent depression. Ninety-eight trials were included for data extraction and analysis. RESULTS: Assessment of outcome measurement instruments, metric strategies, methods of aggregation, and measurement timing, yielded 53 unique outcome definitions of "response" across 45 trials that assessed response, 47 unique definitions of "remission" in 29 trials that assessed remission, and 19 unique definitions of "recovery" across 11 trials that assessed recovery. A minority of trials (N = 35) provided a rationale for dichotomous outcomes definitions, often by citing other studies that used a similar definition (N = 11). No rationale included input from youth or families with lived experience. CONCLUSION: Our review revealed that definitions of "response," "remission," "recovery," and related terms are highly variable, lack clear rationales, and are not informed by key stakeholder input. These limitations impair pooling of trial results and the incorporation of trial findings into pragmatic treatment decisions in clinical practice. Systematic approaches to establishing outcome definitions are needed to enhance the impact of trials examining adolescent depression treatment.
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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 | 0.546 | 0.754 |
| Meta-epidemiology (narrow) | 0.005 | 0.004 |
| Meta-epidemiology (broad) | 0.018 | 0.017 |
| Bibliometrics | 0.038 | 0.035 |
| Science and technology studies | 0.005 | 0.022 |
| Scholarly communication | 0.024 | 0.035 |
| Open science | 0.011 | 0.013 |
| Research integrity | 0.018 | 0.018 |
| 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".