Assessing Cultural Competency and Agility Among Occupational Therapists in Canada: A Cross-Sectional Mixed-Methods Survey
Bibliographic record
Abstract
Background. National and provincial professional associations and regulatory bodies for occupational therapists (OTs) in Canada emphasize culture, equity, and justice as essential competencies. This study investigates the diversity within the occupational therapy profession and explores OTs’ perspectives on providing culturally responsive care to members of equity-deserving groups, with a particular focus on cultural competence and agility. Method. OTs were administered a cross-sectional mixed-methods survey that included demographics, the Cultural Competence Assessment Instrument (Two subscales: Awareness and Sensitivity and Competence Behaviour), and an open-ended question examining their perceived cultural competence. Quantitative data were analyzed using descriptive statistics, and qualitative themes were determined through content analysis. Findings. A total of 240 OTs participated in this survey, with an average age of 45.3 (22.5), identifying primarily as females/women (90.7%). Less than half of respondents (41%) identified their race; of those who did, they were primarily of Southeast Asian descent (21.3%). OTs had lower scores for Cultural Awareness and Sensitivity (3.17/7 [3.11, 3.23]) and for Cultural Competence Behavior (3.22/7 [3.08, 3.37]). While highlighting the healthcare system distrust and barriers to culturally responsive care, most felt confident addressing them. OTs reported that greater awareness and inclusivity at individual and systemic levels are needed. Conclusion. Our sample of OTs suggests little diversity related to gender, race, and ethnicity. OTs in Canada vary in their perceptions of health disparities, barriers for patients in accessing and receiving health care, and efficacy in addressing barriers.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.004 | 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) | 0.001 | 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".