Effects of Cultural Sensitivity Training on Health Care Provider Attitudes and Patient Outcomes
Bibliographic record
Abstract
PURPOSE: To determine the effectiveness of cultural sensitivity training on the knowledge and attitudes of health care providers, and to assess the satisfaction and health outcomes of patients from different minority groups with health care providers who received training. DESIGN: In this randomised controlled trial, 114 health care providers (nurses and homecare workers) and 133 patients (from two community agencies and one hospital) were randomly assigned to experimental (training) and control groups, and were followed for 18 months. METHODS: Providers completed the Cultural Awareness Questionnaire and the Dogmatism Scale. Patients completed the Off-Axis-Ratio (OAR) Multidimensional Measure of Functional Capacity, the Client Satisfaction Questionnaire, the Physical and Mental Health Assessment Questionnaire, and the Health and Social Services Utilization Questionnaire. A qualitative analysis was conducted to identify and analyse themes from personal journals kept by participating nurses. FINDINGS: Cultural sensitivity training resulted in increased open-mindedness and cultural awareness, improved understanding of multiculturalism, and ability to communicate with minority people. After 1 year patients of mostly European and British origin, who received care from trained providers, showed improvement in utilizing social resources and overall functional capacity without an increase in health care expenditures. CONCLUSIONS: The results of this study indicate that a cultural sensitivity training program not only improved knowledge and attitudes among health care providers, but it also yielded positive health outcomes for their patients.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".