Relationships between work outcomes, work attitudes and work environments of health support workers in Ontario long-term care and home and community care settings
Bibliographic record
Abstract
BACKGROUND: Our overarching study objective is to further our understanding of the work psychology of Health Support Workers (HSWs) in long-term care and home and community care settings in Ontario, Canada. Specifically, we seek novel insights about the relationships among aspects of these workers' work environments, their work attitudes, and work outcomes in the interests of informing the development of human resource programs to enhance elder care. METHODS: We conducted a path analysis of data collected via a survey administered to a convenience sample of Ontario HSWs engaged in the delivery of elder care over July-August 2015. RESULTS: HSWs' work outcomes, including intent to stay, organizational citizenship behaviors, and performance, are directly and significantly related to their work attitudes, including job satisfaction, work engagement, and affective organizational commitment. These in turn are related to how HSWs perceive their work environments including their quality of work life (QWL), their perceptions of supervisor support, and their perceptions of workplace safety. CONCLUSIONS: HSWs' work environments are within the power of managers to modify. Our analysis suggests that QWL, perceptions of supervisor support, and perceptions of workplace safety present particularly promising means by which to influence HSWs' work attitudes and work outcomes. Furthermore, even modest changes to some aspects of the work environment stand to precipitate a cascade of positive effects on work outcomes through work attitudes.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".