Is organizational justice associated with clinical performance in the care for patients with diabetes in primary care? Evidence from the improving Quality of care in Diabetes study
Bibliographic record
Abstract
BACKGROUND Type 2 diabetes is an increasingly prevalent illness, and there is considerable variation in the quality of care provided to patients with diabetes in primary care. OBJECTIVES The aim of this study was to explore whether organizational justice and organizational citizenship behaviour are associated with the behaviours of clinical staff when providing care for patients with diabetes. METHODS The data were from an ongoing prospective multicenter study, the 'improving Quality of care in Diabetes' (iQuaD) study. Participants (N = 467) were clinical staff in 99 primary care practices in the UK. The outcome measures were six self-reported clinical behaviours: prescribing for glycaemic control, prescribing for blood pressure control, foot examination, giving advice about weight management, providing general education about diabetes and giving advice about self-management. Organizational justice perceptions were collected using a self-administered questionnaire. The associations between organizational justice and behavioural outcomes were tested using linear multilevel regression modelling. RESULTS Higher scores on the procedural component of organizational justice were associated with more frequent weight management advice, self-management advice and provision of general education for patients with diabetes. The associations between justice and clinical behaviours were not explained by individual or practice characteristics, but evidence was found for the partial mediating role of organizational citizenship behaviour. CONCLUSIONS Quality improvement efforts aimed at increasing advice and education provision in diabetes management in primary care could target also perceptions of procedural justice.
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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 | 0.008 | 0.037 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 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".