Leaders' individualized consideration, team commitment and patient loyalty: The role of social and task‐related contexts
Bibliographic record
Abstract
Abstract Drawing from transformational leadership (TFL) theory and research on contextual leadership, we examined a conditional process model of leadership in nursing teams to predict patient loyalty. Using TFL's individualized consideration dimension as a salient facet of the construct in care services, we first posited that nurses' team affective commitment would partially mediate the impact of nurse leadership. We further conceptualized nurse–physician collaboration, organizational formalization and task feedback as discrete contexts that may curb the influence of head nurses' individualized consideration. In a three‐wave, multisource and multilevel study, we surveyed 654 nurses and 1770 patients from 91 hospital units. We found that team‐level head nurses' individualized consideration positively and partially related to patient loyalty through nurses' team commitment and that higher levels of nurse–physician collaboration, organizational formalization and task feedback were associated with reduced influence of individualized consideration on team commitment and patient loyalty. We discuss the implications of these findings for advancing theory and research on TFL and contextual factors of leadership.
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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 | 0.000 |
| 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".