<i>They stole her teeth</i>! An exploration of adults with developmental disability experiences with dental care
Bibliographic record
Abstract
PURPOSE: The aim of this paper was to explore the experiences of adults with developmental disabilities (AWDD) in accessing and utilizing dental services in Vancouver, BC. METHODS: Participants were either self-advocates or parents/caregivers who discussed their experiences in five focus group discussions with 20 participants in total (age range 17-60 years, 2 males). Each focus group lasted on average 40 minutes. Transcripts were coded for thematic analysis; the codes were organized into themes and finally into domains. RESULTS: Seven domains relating to the participants' experiences with dental care were identified, and included communication, trust, and respect as provided-based domains to the quality of the dental experience for AWDD and their parents, while financial issues, transitional services, and waiting times were system-based barriers to access to dental care for theses AWDD. Finally, what makes for a positive dental experience was shared in terms of acknowledging parent's role as advocates and making simple accommodations to see AWDD by the dental office. CONCLUSIONS: Access to a care provider did not necessarily equate to satisfaction with quality of experience. Efforts have to focus on establishing communication and trust with AWDD patients as key to a positive dental experience. We encourage a global discussion on the need to better incorporate dental care for special needs individuals within dental school curricula.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.005 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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".