Dental students' reflections about long‐term care experiences through an existing model of oral health
Bibliographic record
Abstract
OBJECTIVE: The aim of this study was to explore students' reflective thinking about long-term care experiences from the perspective of a model of oral health. MATERIALS AND METHODS: A total of 186 reflections from 193 second-year undergraduate dental students enrolled between 2011/12 and 2014/15 at the University of British Columbia were explored qualitatively. Reflections had a word limit of 300, and students were asked to relate an existing model of oral health to their long-term care experiences. We have identified the main ideas via a thematic analysis related to the geriatric dentistry experience in long-term care. RESULTS: The thematic analysis revealed that students attempted to demystify their pre-conceived ideas about older people and long-term care facilities, to think outside the box, for example away from a typical dental office, and to consider caring for elderly people from an interprofessional lens. According to some students, not all domains from the existing model of oral health were directly relevant to their geriatric experience while other domains, including interprofessionalism and cognition, were missing. While some participants had a positive attitude towards caring for this cohort of the population, others did not take this educational activity as a constructive experience. CONCLUSIONS: The nature of most students' reflective thinking within a long-term care experience showed to be related to an existing model of oral health. This model can help to give meaning to the dental geriatric experience of an undergraduate curriculum. Such experience has been instrumental in overcoming potential misconceptions about long-term care and geriatric dentistry.
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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 | 0.009 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.005 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.002 | 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".