Evaluation of a cultural competence educational programme
Bibliographic record
Abstract
AIM: This paper reports a study, which evaluated the effectiveness of a cultural competence educational programme to increase Public Health Nurses' cultural knowledge. BACKGROUND: Cultural competence has great significance for practising nurses and has become a priority and commitment of the Nursing profession. Public Health Nurses interact regularly with clients from a variety of culturally diverse backgrounds. Thus, there is a need for an integrated programme with theoretical and experiential knowledge related to cultural competence for PHNs to enhance their knowledge and skills to better meet the needs of the population. DESIGN: This study used a combination of quantitative and qualitative methods for data collection. A one-group Repeated Measures design was used to evaluate the effectiveness of the educational programme. METHOD: The sample consisted of 76 Public Health Nurses who attended a cultural competence educational programme, which was offered over five consecutive weeks, of 2 hours duration and reinforced by a booster session at 1 month postimplementation of the programme. Cultural knowledge was measured on the Cultural Knowledge Scale, which was a valid, reliable, 25-item Likert scale. Data were collected at four points in time and were analysed with repeated measures analysis of variance. Qualitative data were content analysed. RESULTS: Findings revealed that the intervention was effective [Wilks' Lambda was F(3,69) = 142.02, P < 0.01] in increasing the nurses' cultural knowledge. Qualitative results complemented the quantitative findings. Participants reported that the programme was effective in increasing their cultural knowledge. CONCLUSION: Although Public Health Nurses, who attended the educational programme increased their cultural knowledge, these findings are not generalizable to nurses working in other settings. However, the programme has clinical utility and could be adapted and given to nurses in other settings.
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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 | 0.012 | 0.024 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".