Factors Influencing Nurse Assistants’ Job Satisfaction in Nursing Homes in Canada and Spain: A Comparison of Two Cross-Sectional Observational Studies
Bibliographic record
Abstract
OBJECTIVES: To access associations between job satisfaction and supervisory support as moderated by stress. METHODS: For this cross-sectional study, data collected from 591 nursing assistants in 42 nursing homes in Canada and Spain were analyzed with mixed-effects regression. RESULTS: In both countries, stress related to residents' behaviors was negatively associated with job satisfaction, and, in Canada, it moderated the positive association between supervisory support and job satisfaction. Stress related to family conflict issues moderated the positive association of supervisory support and job satisfaction differently in each location: in Canada, greater stress was associated with a weaker association between supervisory support and job satisfaction; in Spain, this was also observed but only when supervisory support was sufficiently weak. DISCUSSION: Stress was associated with lower job satisfaction and moderated the association of supervisory support and job satisfaction, reinforcing the importance of supervisors supporting nursing assistants, especially during the COVID-19 pandemic.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".