Workplace trauma and chronic stressor exposure among direct service providers working with people experiencing homelessness
Bibliographic record
Abstract
BACKGROUND: Service providers working with people experiencing homelessness can be directly and indirectly exposed to trauma and other chronic stressors in their work. The types of individuals that are most at-risk of problematic outcomes from traumatic event exposure are unknown. AIM: This study examined exposure to and effects of workplace traumas and stressors among service providers working with people experiencing homelessness in Canada. METHODS: A cross-sectional survey was completed by 701 direct service providers working in the homeless service, supportive housing, and harm reduction sectors. Descriptive statistics, hierarchical multiple regression, and double moderation models were used in the analysis. RESULTS: Employment in homeless service settings, service provision to single adults, and more time in direct contact with service users were each positively associated with the frequency of exposure to critical events and chronic stressors. Younger age, lived experience of behavioural health problems, more frequent exposure to chronic stressors, and less social support from coworkers were significantly correlated with post-traumatic stress and general psychological distress. Emotional support from supervision moderated the relationship between direct exposure to workplace critical events and post-traumatic stress. CONCLUSIONS: More trauma-informed psychosocial supports tailored to the needs of direct service providers working with people experiencing homelessness are needed.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".