Exploring barriers to oral health care experienced by individuals living with autism spectrum disorder.
Bibliographic record
Abstract
Background: Autism spectrum disorder (ASD) is a developmental disorder that affects behaviour and communication skills. ASD is estimated to affect approximately 1 in 66 Canadians, with symptoms typically arising within the first 3 years of life. Individuals with ASD present with an increased burden of disease and face heightened barriers to oral care. Objective: This narrative literature review aims to raise awareness of the additional needs that individuals with ASD have when seeking oral care and to identify how barriers to such care may be reduced. Methods: Twenty-one articles were included in this review, with a wide range of study designs and methodologies. Search terms in PubMed, Education Source, and CINAHL databases included autism spectrum disorder, barriers, dental, dental hygiene, developmental disability, oral health, and unmet needs. Results and discussion: Key themes that emerged as barriers to care were behavioural challenges, inhibited social and communication skills, parental dependence, clinic environment, and abilities of oral health professionals to treat clients with special care needs. Conclusion: Current literature reveals that individuals with ASD face numerous barriers when accessing oral care and attempting to achieve adequate oral health, thus contributing to an increased burden of disease. Oral health professionals should aim to improve their understanding of special care populations such as the ASD community and raise awareness among health care professionals to work towards diminishing the barriers to care these populations experience.
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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 | 0.004 | 0.024 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| 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".