Effects of Routine Feedback to Clinicians on Mental Health Outcomes of Youths: Results of a Randomized Trial
Bibliographic record
Abstract
OBJECTIVE: A randomized cluster controlled trial tested the hypothesis that weekly feedback to clinicians would improve the effectiveness of home-based mental health treatment received by youths in community settings. METHODS: Youths, caregivers, and clinicians at 28 sites in ten states completed assessments of the youths' symptoms and functioning every other week. Clinicians at 13 sites were provided with weekly feedback about the assessments, and clinicians at 15 sites received feedback every 90 days. Data were collected from June 1, 2006, through December 31, 2008. Intent-to-treat analyses were conducted with hierarchical linear modeling of data provided by youths, caregivers, and clinicians. RESULTS: Assessments by youths, caregivers, and clinicians indicated that youths (N=173) treated at sites where clinicians could receive weekly feedback improved faster than youths (N=167) treated at sites where clinicians did not receive weekly feedback. A dose-response analysis showed even stronger effects when clinicians viewed more feedback reports. CONCLUSIONS: Routine measurement and feedback can be used to improve outcomes for youths who receive typical home-based services in the community.
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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 | 0.010 | 0.024 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 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; 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".