Influence of employment and job security on physical and mental health in adults living with HIV: cross-sectional analysis.
Bibliographic record
Abstract
BACKGROUND: In the general population, job insecurity may be as harmful to health as unemployment. Some evidence suggests that employment is associated with better health outcomes among people with HIV, but it is not known whether job security offers additional quality-of-life benefits beyond the benefits of employment alone. METHODS: We used baseline data for 1660 men and 270 women who participated in the Ontario HIV Treatment Network Cohort Study, an ongoing observational cohort study that collects clinical and socio-behavioural data from people with HIV in the province of Ontario, Canada. We performed multivariable regression analyses to determine the contribution of employment and job security to health-related quality of life after controlling for potential confounders. RESULTS: Employed men with secure jobs reported significantly higher mental health-related quality of life than those who were non-employed (β = 5.27, 95% confidence interval [CI] 4.07 to 6.48), but insecure employment was not associated with higher mental health scores relative to non-employment (β = 0.18, 95% CI -1.53 to 1.90). Thus, job security was associated with a 5.09-point increase on a 100-point mental health quality-of-life score (95% CI 3.32 to 6.86). Among women, being employed was significantly associated with both physical and mental health quality of life, but job security was not associated with additional health benefits. INTERPRETATION: Participation in employment was associated with better quality of life for both men and women with HIV. Among men, job security was associated with better mental health, which suggests that employment may offer a mental health benefit only if the job is perceived to be secure. Employment policies that promote job security may offer not only income stability but also mental health benefits, although this additional benefit was observed only for men.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".