Finding and sustaining employment: A qualitative meta-synthesis of mental health consumer views
Bibliographic record
Abstract
Background The viewpoints of employed people experiencing mental ill-health receive limited attention in reviews of employment-related research. Purpose To identify implications from studies investigating the employment-related views of people with persistent mental ill-health to guide the further development of employment supports available to this group. Methods Published qualitative studies between 1998 and 2008 were searched, resulting in 20 studies for qualitative metasynthesis. Findings Four themes were synthesized from the findings:(a) employment has varied meanings, benefits, and drawbacks to weigh up; (b) strategies for maintaining employment and mental health are important and both require ongoing, active self-management; (c) diverse supports within and beyond the workplace are helpful; and (d) systemic issues add to the employment barriers. Implications Strategies based on these themes highlight how occupational therapists could initiate improvements in employment support and mental health services to increase their success in enabling satisfying and sustainable employment.
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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 | 0.081 | 0.145 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.005 |
| Bibliometrics | 0.020 | 0.020 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".