Nurse and resident satisfaction in magnet long-term care organizations: do high involvement approaches matter?
Bibliographic record
Abstract
AIM: This study examines the association of high involvement nursing work practices with employer-of-choice (magnet) status in a sample of Canadian nursing homes. BACKGROUND: In response to a severe shortage of registered nursing personnel, it is imperative for health care organizations to more effectively recruit and retain nursing personnel. Some long-term care organizations are developing employee-centred cultures that allow them to effectively enhance nurse and resident satisfaction. At the same time, many nursing homes have adopted progressive nursing workplace practices (high involvement work practices) that emphasize greater employee empowerment, participation and commitment. METHOD: A mail survey was sent to the director of nursing in 300 nursing homes in western Canada. In total, 125 useable questionnaires were returned and constituted the data set for this study. Separate ordinary least squares regressions are performed with magnet strength, nurse satisfaction and resident satisfaction used as dependent variables. RESULTS: Nursing homes that demonstrate strong magnet (employer-of-choice) characteristics are more likely to have higher levels of nurse and patient satisfaction, even after controlling for a number of significant factors at the establishment level. Magnet nursing homes are more likely to have progressive participatory decision-making cultures and much more likely to spend considerable resources on job-related training for their nursing staff. The presence of high involvement work practices is not found to be a significant predictor in magnet strength, nurse or resident satisfaction. CONCLUSION: Merely adopting more high involvement nursing work practices may be insufficient for nursing homes, which desire to become 'employers-of-choice' in their marketplaces, especially if these practices are adopted without a concomitant investment in nurse training or an enhanced commitment to establishing a more democratic and participatory decision-making style involving all nursing staff.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".