Providing culturally responsive care in a pediatric setting: are our trainees ready?
Bibliographic record
Abstract
BACKGROUND: Extensive data consistently demonstrates inequities in access and delivery of healthcare for patients from historically marginalized populations, resulting in poorer health outcomes. To address this systemic oppression in healthcare, it is necessary to embed principles of equity, diversity, and inclusion (EDI) at an early stage within medical education. This study aimed to assess pediatric trainees' perceived interest in EDI curricula as well as their confidence in applying this knowledge to provide culturally responsive care. METHODS: An anonymous online survey was distributed to pediatric trainees at the University of Toronto. Closed-ended questions used a Likert scale to assess respondents' confidence and interest in providing culturally responsive care to patients. Open-ended questions explored trainees' perceptions of effective EDI learning modalities. A mixed methods approach was utilized, where quantitative data was summarized using descriptive statistics and descriptive content analysis was used to highlight themes within qualitative data. RESULTS: 116 pediatric trainees completed the survey, of which 72/116 (62%) were subspecialty residents/fellows and 44/116 (38%) were core residents. 97% of all responses agreed or strongly agreed that it was important to learn about providing culturally responsive care to patients from historically marginalized communities; however, many trainees lacked confidence in their knowledge of providing culturally responsive care (42%) and applying their knowledge in clinical practice (47%). Respondents identified direct clinical exposure through rotations, immersive experiences, and continuity clinics as effective EDI teaching modalities. Identified barriers included time constraints in the clinical environment, burnout, and lack of exposure to diverse patient populations. CONCLUSION: Most pediatric trainees want to provide culturally responsive care to patients from historically marginalized communities, but do not feel confident in their knowledge to do so. Trainees value learning about EDI through direct clinical exposure and immersive experiences, rather than didactic lectures or modules. These study findings will be utilized to develop and implement an enhanced EDI education curriculum for pediatric trainees at the University of Toronto and other postgraduate residency programs.
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 | 0.007 | 0.025 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".