A serial mediation model of workplace social support on work productivity: the role of self-stigma and job tenure self-efficacy in people with severe mental disorders
Bibliographic record
Abstract
PURPOSE: Compared to groups with other disabilities, people with a severe mental illness face the greatest stigma and barriers to employment opportunities. This study contributes to the understanding of the relationship between workplace social support and work productivity in people with severe mental illness working in Social Enterprises by taking into account the mediating role of self-stigma and job tenure self-efficacy. METHOD: A total of 170 individuals with a severe mental disorder employed in a Social Enterprise filled out questionnaires assessing personal and work-related variables at Phase-1 (baseline) and Phase-2 (6-month follow-up). Process modeling was used to test for serial mediation. RESULTS: In the Social Enterprise workplace, social support yields better perceptions of work productivity through lower levels of internalized stigma and higher confidence in facing job-related problems. When testing serial multiple mediations, the specific indirect effect of high workplace social support on work productivity through both low internalized stigma and high job tenure self-efficacy was significant with a point estimate of 1.01 (95% CI = 0.42, 2.28). CONCLUSIONS: Continued work in this area can provide guidance for organizations in the open labor market addressing the challenges posed by the work integration of people with severe mental illness. Implications for Rehabilitation: Work integration of people with severe mental disorders is difficult because of limited access to supportive and nondiscriminatory workplaces. Social enterprise represents an effective model for supporting people with severe mental disorders to integrate the labor market. In the social enterprise workplace, social support yields better perceptions of work productivity through lower levels of internalized stigma and higher confidence in facing job-related problems.
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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 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 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".