Combining to innovate: A collaborative interprofessional learning approach to delivering Tobacco Use Prevention and Cessation (TUPAC) education for undergraduate oral health students
Bibliographic record
Abstract
This paper provides a description of a pilot project in Tobacco Use Prevention and Cessation (TUPAC) in response to a national and international trend to include TUPAC curriculum components in the clinical education of undergraduate oral health students. In order to deliver quality brief intervention strategies for smokers a need to adequately prepare oral health students was identified during student clinical placements. An interprofessional (IP) project team was established with membership from the University of Adelaide’s School of Dentistry, QuitSA, Cancer Council SA, the South Australian Dental Service (SADS) Somerton Park and TAFESA’s Faculty of Dental Studies to streamline the efficient use of resources and most importantly draw on a diverse range of interprofessional health care expertise. On the website for The UK Centre for the Advancement of Interprofessional Education (CAIPE) (2002) it states that “Interprofessional education occurs when two or more professions learn from and about each other to improve collaboration and the quality of care”. Through interprofessional learning (IPL) in classroom and clinical settings, second year Bachelor and Advanced Diploma oral health students were provided with the opportunity to develop an understanding of the respective roles of each health professional responsible for delivering positive health initiatives in the area of TUPAC. With limited national oral health curricula in the area of TUPAC, the project team forged links with the University of Manitoba’s Dental Hygiene Program, and the convenor of the TUPAC in Dental and Dental Hygiene Undergraduate Education European Workshops for curriculum benchmarking against evidence based criteria. Most importantly as the IP concept of health care considers the patient at the centre of the health care team, assessment was designed to encourage a patient centred approach through the review and analysis of a clinical case study. A formal evaluation of this project is currently in progress, however results were not yet available at the time of publication.
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How this classification was reachedexpand
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 | 0.009 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".