Predicting workplace loneliness in the nursing profession
Bibliographic record
Abstract
AIM: This study examined a model investigating how social interaction variables (leader-member exchange (interactions between managers and nurses), trust, and communication frequency) and work meaningfulness influence nurses' experiences of workplace loneliness. BACKGROUND: As workplace loneliness can result in lower job satisfaction and a decrease in workers' health, understanding the contributing factors to loneliness at work is important. METHOD: In this cross-sectional study, Turkish nurses (N = 864) completed self-report scales measuring social exchange between leaders and members, trust in leaders, communication frequency, work meaningfulness, and loneliness. To avoid fatigue and method variance influence, scales were completed over two testing times (separated by a month). RESULTS: Workplace loneliness was associated with less social interaction with leaders (lower leader-member exchange and frequency of communication), less trust in leaders, and lower reports of meaningful work. CONCLUSION: The results suggest that workplace loneliness can be reduced when managers exchange more information and communicate more frequently with their nurses. Workplace loneliness is also reduced when nurses trust their leaders and find their work meaningful. IMPLICATIONS FOR NURSING MANAGEMENT: Managers supervising nurses need to be aware that workplace loneliness occurs and that their interactions and relationships with the nurses will have an impact on experienced workplace loneliness.
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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 | 0.003 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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".