First Nations Curriculum Development for Undergraduate Health Courses: A Scoping Review
Bibliographic record
Abstract
Background: Cultural safety is a foundational principle in Australian health education, defined by Aboriginal and Torres Strait Islander peoples and recognised by AHPRA (2019). Despite national frameworks encouraging its adoption, integration into undergraduate curricula remains inconsistent, characterised by fragmented definitions, limited Indigenous leadership in curriculum design, variable assessment approaches and outcomes, and reforms that often lack sustainability and genuine community co-design. Models of health including deficit, strengths‑based, and social determinants, offer critical perspectives but are variably embedded in teaching. Objective: To systematically map the literature on cultural safety integration within undergraduate foundation or entry‑level health courses in Australia, identifying teaching methods, assessment strategies, Indigenous involvement in curriculum design, and alignment with nationally recognised cultural safety frameworks. Research Question: What methods and approaches are currently implemented in the design and delivery of undergraduate foundation health courses to embed cultural safety and strengthen cultural capability? Methods: Following PRISMA‑ScR framework, we will search peer‑reviewed and grey literature published in English from 2000 onwards. Inclusion criteria: Australian First Nations health contexts; concepts of cultural safety, responsiveness, strengths‑based models, and social/cultural determinants; undergraduate foundation or entry‑level health courses. Exclusion criteria: postgraduate, vocational, or continuing education; studies without curriculum focus. Databases include PubMed, Scopus, CINAHL, Informit, and Google Scholar, supplemented by Lowitja Institute and government reports. Impact: Findings will provide an evidence base for redesigning the Griffith University course 1205MED Health Challenges for the 21st Century, and will be transferable to other foundation, entry-level health courses, ensuring reforms embed strengths‑based approaches, social determinants, and Indigenous co‑design. This review will contribute to improving cultural capability among students and instructors, preparing graduates to deliver respectful care and challenge systemic inequities.
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 | 0.033 | 0.101 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.020 | 0.024 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.004 | 0.006 |
| Open science | 0.004 | 0.005 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 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".