Hardiness, work support and psychological distress among nursing assistants and registered nurses in Quebec
Bibliographic record
Abstract
BACKGROUND: Although nursing assistants (NAs) represent a large segment of Canadian health care providers, little is known about psychosocial factors related to their physical and psychological well-being and how these compare with their registered nurse (RN) counterparts. AIM: Guided by Maddi and Kobasa's theoretical framework of Factors Affecting Health-Illness Status, the purpose of the present study was to examine relationships among hardiness, psychological distress and work support in NAs, and to compare results with those from a sample of RNs. METHOD: A random sample of 171 NAs in Quebec completed self-report questionnaires. The study instruments included validated French-Canadian versions of Kobasa's Hardiness Scale, Ilfeld's Psychiatric Symptom Index, and Moos' Work Relationship Index. RESULTS: As theoretically predicted, statistically significant correlations were found between hardiness and psychological distress (r = -0.42; P < 0.001), hardiness and work support (r = 0.27; P < 0.001), and between work support and psychological distress (r = -0.21; P < 0.001). Using a mediational model and multiple regression analyses, hardiness among NAs was found to be a significant mediator between work support and psychological distress. Comparative analyses revealed that whereas NAs and RNs reported similar levels of psychological distress (P = 0.25) and work support (P = 0.13), NAs reported significantly less hardiness (t = -5.58; P < 0.01). In addition, NAs and RNs reported significantly more psychological distress than the general population of Quebec, Canada (t = 9.07 and 22.84, P < 0.01, respectively). CONCLUSION: Results add support to Maddi and Kobasa's theoretical propositions linking personal and contextual resources to health-related outcomes and offer insights into specific factors that may affect the health and well-being of both NAs and RNs as well as their work climate.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".