An Online Platform to Provide Work and Study Support for Young People With Mental Health Challenges: Observational and Survey Study
Bibliographic record
Abstract
BACKGROUND: Young people, aged 15-25 years, are at a critical stage of life when they need to navigate vocational pathways and achieve work and study outcomes. Those with mental health problems are particularly at risk of disengagement with work and study and need effective support. The headspace Work and Study (hWS) service is an innovative online platform implemented in Australia to support young people aged 15-25 years with mental health problems to achieve work and study goals. OBJECTIVE: This study aims to determine whether the hWS service has been implemented as planned, provides appropriate support for young people, and achieves its main goals. METHODS: Data were collected via 2 methodologies: (1) the hWS Minimum Data Set, which includes data on all clients in the service (n=1139), services delivered, and service impact; and (2) a survey of hWS clients who volunteered to participate in an evaluation of the hWS service (n=137). RESULTS: The service was accessed by its defined target group, young people aged 15-25 years with mental health and work and study difficulties. Young people found the online platform to be acceptable, and the assistance provided and clinical integration useful; many young people achieved positive work and study outcomes, particularly those who engaged more times with the service. More assistance was sought for work than study goals, suggesting that the transition to work may be particularly challenging for young people. One-third (298/881, 33.8%) of the sample for the service impact analyses achieved at least 1 primary work or study outcome, and this increased to 44.5% (225/506) for those who engaged with 5 or more sessions, demonstrating that greater engagement with the service produced better outcomes. CONCLUSIONS: Critical work and study support can be effectively delivered via an online modality to young people with common mental health problems. Digital services are scaleable to reach many young people and are of particular value for those with difficulty accessing in-person services.
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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 | 0.005 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".