Patient-reported outcome measures used to improve youth mental health services: a systematic review
Bibliographic record
Abstract
BACKGROUND: Patient-reported outcome measures (PROMs) are standardized and validated self-administered questionnaires that assess whether healthcare interventions and practices improve patients' health and quality of life. PROMs are commonly implemented in children and youth mental health services, as they increasingly emphasize patient-centered care. The objective of this study was to identify and describe the PROMs that are currently in use with children and youth living with mental health conditions (MHCs). METHODS: Three databases (MEDLINE, EMBASE, and PsycINFO) were systematically searched that used PROMs with children and youth < 18 years of age living with at least one diagnosed MHC. All methods were noted according to Preferred Reporting Items for Systematic reviews and Meta-Analysis. Four independent reviewers extracted data, which included study characteristics (country, year), setting, the type of MHC under investigation, how the PROMs were used, type of respondent, number of items, domain descriptors, and the psychometric properties. RESULTS: Of the 5004 articles returned by the electronic search, 34 full-texts were included in this review. This review identified both generic and disease-specific PROMs, and of the 28 measures identified, 13 were generic, two were generic preference-based, and 13 were disease-specific. CONCLUSION: This review shows there is a diverse array of PROMs used in children and youth living with MHCs. Integrating PROMs into the routine clinical care of youth living with MHCs could improve the mental health of youth. Further research on how relevant these PROMs are children and youth with mental health conditions will help establish more uniformity in the use of PROMs for this population.
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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 | 0.021 | 0.086 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.010 | 0.013 |
| Bibliometrics | 0.010 | 0.012 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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".