MétaCan
Menu
Back to cohort
Record W4200628527

Exploring barriers to oral health care experienced by individuals living with autism spectrum disorder.

2021· article· en· W4200628527 on OpenAlexaff
Bianka Bernath, Zul Kanji

Bibliographic record

VenuePubMed · 2021
Typearticle
Languageen
FieldDentistry
TopicDental Health and Care Utilization
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsAutism spectrum disorderCINAHLOral hygieneMedicineAffect (linguistics)Health careAutismOral healthPsychologyPsychiatryFamily medicinePsychological interventionDentistry
DOInot available

Abstract

fetched live from OpenAlex

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.

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 imitation

Not 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.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.024
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.037
Threshold uncertainty score0.073

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.024
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0050.007
Science and technology studies0.0010.001
Scholarly communication0.0030.003
Open science0.0010.002
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.038
GPT teacher head0.284
Teacher spread0.246 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

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".

Quick stats

Citations22
Published2021
Admission routes1
Has abstractyes

Explore more

Same venuePubMedSame topicDental Health and Care UtilizationFrench-language works237,207