Relationships among leadership practices, work environments, staff communication and outcomes in long-term care
Bibliographic record
Abstract
AIM: To examine the role that work relationships have on two long-term care outcomes: job satisfaction and turnover intention. BACKGROUND: It is easy to overlook the impact that human relations have in shaping work environments that are conducive to organizational effectiveness. Employee job satisfaction and retention are important organizational outcomes. METHODS: Six hundred and seventy-five nursing and other staff from 26 long-term care facilities were surveyed about their work environments, work group relationships, observed leadership practices, organizational support, job satisfaction and turnover intention. RESULTS: Higher job satisfaction was associated with lower emotional exhaustion burnout, higher global empowerment, higher organizational support, higher psychological empowerment, stronger work group cohesion and higher personal accomplishment. Higher turnover intention was associated with lower job satisfaction, higher emotional exhaustion burnout, more outside job opportunities, weaker work group cohesion, lower personal accomplishment and higher depersonalization. CONCLUSIONS: No relationship was found between leadership practices and job satisfaction or turnover intention. Stronger work group relationships, stronger sense of personal accomplishment and lower emotional exhaustion have direct effects on increasing job satisfaction and lowering turnover intention. IMPLICATIONS: To retain long-term care staff, attention should be paid to fostering positive work group cohesion, supporting and acknowledging staff accomplishments and minimizing staff burnout.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".