Barriers and facilitators to employment for young adults with mental illness: a scoping review
Bibliographic record
Abstract
OBJECTIVES: The issue of gaining employment for those with mental illness is a growing global concern. For many in the young adult population, who are at a transitional age, employment is a central goal. In response, we conducted a scoping review to answer the question, 'What are the barriers and facilitators to employment for young adults with mental illness?' DESIGN: We conducted a scoping review in accordance to the Arksey and O'Malley framework. We performed a thorough search of Medline, EMBASE, CINAHL, ABI/INFORM, PsycINFO and Cochrane. We included studies that considered young adults aged 15-29 years of age with a mental health diagnosis, who were seeking employment or were included in an employment intervention. RESULTS: Our search resulted in 24 research articles that focused on employment for young adults with mental illness. Four main themes were extracted from the literature: (1) integrated health and social services, (2) age-exposure to employment supports, (3) self-awareness and autonomy and (4) sustained support over the career trajectory. CONCLUSIONS: Our review suggests that consistent youth-centred employment interventions, in addition to usual mental health treatment, can facilitate young adults with mental illness to achieve their employment goals. Aligning the mental health and employment priorities of young adults may result in improved health and social outcomes for this population while promoting greater engagement of young adults in care.
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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 | 0.040 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.005 |
| Bibliometrics | 0.009 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 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".