Review: System transformation to enhance transitional age youth mental health – a scoping review
Bibliographic record
Abstract
BACKGROUND: Youth mental health challenges are an emerging and persistent global public health issue despite efforts for improvement. As part of a broader social innovation study to transform youth mental health systems, this scoping review assesses interventions that aim for systems-level changes to improve the mental well-being of transitional age youth (TAY) (15-25 years) in high-income countries. METHODS: The scoping review method of Arksey and O'Malley (International Journal of Social Research Methodology, 8, 2005, 19) was used. Seven health and social service databases were utilized with study inclusion criteria applied. Titles and abstracts were screened by two independent reviewers, and four members of the research team were involved in the review and thematic analysis of selected studies. RESULTS: A total of 5652 peer-reviewed articles were screened at the title and abstract level, of which 65 were assessed in full for eligibility, and 29 were included for final analysis. The peer-reviewed articles and gray literature were based in seven different high-income countries and published between 2008 and 2019. Four major themes to support youth mental health were identified in the literature: (a) improving transitions from youth to adult mental healthcare services; (b) moving care from institutions to the community; (c) general empowerment of youth in society; and (d) youth voice within the system. Inconsistent or limited systems-level approaches to TAY mental health care were noted. CONCLUSIONS: There remains a need for innovative, evidence-based approaches to improve TAY mental health care.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.049 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.006 |
| Bibliometrics | 0.009 | 0.011 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.005 | 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".