Self–Perceptions of Cultural Competence Among Dental Students and Recent Graduates
Bibliographic record
Abstract
This study assessed self-perceptions of cultural competence in dental students and recent graduates of the University of British Columbia. The sample consisted of 106 predoctoral students (response rate 98 percent) and thirty-three recent graduates (response rate 43 percent). The two cohorts completed similar questionnaires. Over 80 percent of responding predoctoral students reported encountering patients from culturally different groups, 50 percent of them admitted that their communication is not effective, two-thirds were not confident in caring for patients from diverse cultural groups, and over 60 percent perceived that sociocultural differences affect the provision of care. Some significant differences between the genders and study years were observed. Exploratory Factor Analyses validated multiple indicators in five domains: 1) encountering culturally diverse patients, 2) communication challenges in sociocultural situations, 3) cultural competence-related skills, 4) cultural competence related to diagnosis and patient treatment, and 5) training in cultural competence. Through qualitative assessments, important culturally relevant topics and interactive training methods preferred by students for developing cultural competence were identified. This study concluded that cultural competence was perceived as important by both dental students and recent graduates but also as partly deficient, particularly by predoctoral students. For teaching cultural competence, participants recommended various topics and interactive teaching modalities.
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 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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".