Exploring equity, diversity, and inclusion strategies in geriatric healthcare education: A scoping review
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This scoping review explores Equity, Diversity, and Inclusion (EDI) initiatives within geriatric healthcare professional education, aiming to understand strategies, outcomes, and challenges. The aging global population necessitates healthcare systems that are culturally competent and inclusive, prompting a closer examination of educational interventions. Eight articles met inclusion criteria, predominantly utilizing qualitative and mixed-methods designs. Initiatives ranged from active learning to online simulations, targeting physicians and allied healthcare providers. Participants generally reported high satisfaction and improved attitudes toward diversity and inclusion post-training. Challenges such as resource constraints and curriculum updates were noted. Multidisciplinary training and technological advancements emerged as key strategies, alongside recommendations for enhanced resource allocation and inclusivity in content and faculty. The findings underscore the increased uptake and desire to integrate EDI principles into geriatric healthcare education to prepare professionals to provide equitable care to racial, ethnic, socioeconomic, and gender diverse older adults. This review provides valuable insights for educators and policymakers seeking to foster a culturally competent and inclusive healthcare workforce capable of meeting the evolving needs of aging populations worldwide.
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.
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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.006 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.021 |
| Research integrity | 0.001 | 0.002 |
| 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 it