Lifestyle Medicine as a Curricular Thread in Occupational Therapy Education: A Scoping Review and Discussion of Feasibility
Bibliographic record
Abstract
Occupational therapists (OT) are trained in interventions related to health and well-being, facilitating individuals in achieving occupational balance. This scoping review explored the current methods of disseminating Lifestyle Medicine (LM) knowledge in post-secondary health education and assessed the potential integration of LM principles into OT education. The review covered publications related to LM implementation in post-secondary health professions curricula. Six databases were searched. The authors conducted initial blind reviews of titles and abstracts, followed by a similar screening of full-text articles. Included full-text articles were obtained from university databases with the assistance of systematic review software. Among the 304 abstracts reviewed, 60 full-text articles were assessed, with 16 included in this scoping review. However, none of the programs in the literature were OT programs. The results show that the six pillars of lifestyle medicine were not equally emphasized in the reviewed programs, with social connection being the least addressed. However, OT education places importance on social connections, and the other pillars align well with the 2018 standards set by Accreditation Council of OT Education (ACOTE) and the parameters outlined in OT Practice Framework 4th Edition (OTFP-4). This alignment can be valuable for OT programs in meeting their accreditation requirements.
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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 | 0.057 | 0.133 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.007 |
| Bibliometrics | 0.014 | 0.017 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.009 | 0.007 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.004 | 0.003 |
| 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".