Dental student's perceptions and experience treating adults with developmental disabilities
Bibliographic record
Abstract
OBJECTIVES: The objective of this study was to investigate the perceptions and experiences of dental students with regards to treating adults with developmental disabilities (AWDDs). METHODS: Semi-structured interviews were conducted with three groups of participants: experts who extensively work with AWDDs (n = 3), students who had no clinical training to treat AWDDs (n = 3), and students who had completed their clinical training to treat AWDDs (n = 8). One-on-one interviews were conducted in-person or via video call with each participant. Interviews were transcribed, coded, and analyzed for themes. RESULTS: Experts described their motivations for working with AWDDs. Students in both groups identified the challenges of working with AWDDs and highlighted the impact of the informal curriculum as well as the increased importance of clinical training. Students who had received clinical training described the clinical rotation as a transformative learning experience that instilled a sense of health advocacy. There was alignment of themes between all three groups in terms of skills desired, acquired, and required to work with AWDDs; however, the students who had received clinical training and the experts differed on their opinion of the relative importance of the skills they developed. CONCLUSIONS: The alignment of perceptions between students and experts is promising and demonstrates the successes of the existing curriculum. The misalignment between students and experts highlights areas in the curriculum that can be improved through adjustments and augmentation.
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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".