Mediation of professional commitment in the relationship between organizational culture and quality of care among community health centres: A multilevel study in China
Bibliographic record
Abstract
Organizational culture is increasingly recognized as crucial to improving the quality of care. However, there is limited evidence in primary care, especially the underlying mechanism between organizational culture and care quality. This study aims to investigate the relationship of organizational culture with quality of care and the mediated effect of professional commitment. We conducted a cross-sectional survey of 224 primary care physicians (PCPs) from 38 community health centres (CHCs) in four large cities in China. The director of CHC completed the organization survey including organizational culture and other organizational characteristics. PCPs completed a PCP survey, including information such as personal characteristics, professional commitment and self-reported quality of care. The data was analysed using a multilevel mediation testing method based on a hierarchical linear model. Over half of the CHCs have group culture as their dominant culture. CHCs with higher scores on developmental culture are more likely to perform better in care quality, while CHCs with higher scores on hierarchical culture are less likely to perform well in care quality, with professional commitment playing a partially mediated role. Building a developmental culture and enhancing professional commitment should be considered as modifiable strategies to improve PCPs’ quality of care.
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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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 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".