Patterns and predictors of cultural competence practice among Nigerian hospital-based healthcare professionals
Bibliographic record
Abstract
BACKGROUND: Being culturally competent would enhance the quality of care in multicultural healthcare settings like Nigeria, with over 200 million people, 500 languages, and 250 ethnic groups. This study investigated the levels of training and practice of cultural competence among clinical healthcare professionals in two purposively selected Nigerian tertiary hospitals. METHODS: The research was a cross-sectional study. A multi-stage sampling technique was used to recruit participants who completed the adapted version of Cultural Competence Assessment Instrument (CCAI-UIC). Data were analysed using descriptive statistics, Pearson's correlation, ANOVA, and multivariate linear regression. RESULTS: The participants were mainly women (66.4%), aged 34.98 ± 10.18 years, with ≤ 5 years of practice (64.6%). Personal competence had a positive weak correlation with age (p < 0.001), practice years (p = 0.01), training (p = 0.001), practice (p < 0.001), and organisational competence (p < 0.001). There were significant professional differences in the level of training (p = 0.005), and differences in training (p = 0.005), and personal competence (p = 0.015) across levels of educational qualifications. Increasing practise years (p = 0.05), medical/dental profession relative to nursing (p = 0.029), higher personal (p = 0.013), and organisational (p < 0.001) cultural competences were significant predictors of the level of training. Male gender (p = 0.005), higher years in practice (p = 0.05), local language ability (p = 0.037), rehabilitation professionals relative to nursing (p = 0.05), high culturally competent practice (p < 0.001), higher training opportunities (p = 0.013), and higher organisational competence (p = 0.001) were significant predictors of higher personal competence. CONCLUSION: About a third of the participants had no formal training in cultural competence. Incorporating cultural competence in the Nigerian healthcare professionals' education curricula may enhance the quality of care in the multicultural setting.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".