Access to Dental Services for Children with Special Health Care Needs: A Pilot Study at the Dental Department of BC Children's Hospital.
Bibliographic record
Abstract
OBJECTIVES: This pilot study at the dentistry department of BC Children's Hospital (DD-BCCH) in Vancouver, British Columbia, Canada, aimed to explore issues of access to dental services for children with special health care needs (CSHCN). METHODS: Caregivers of CSHCN, who were patients of record at DD-BCCH, were recruited to participate in this study. We collected sociodemographic characteristics, insurance coverage and medical diagnosis, and information on caregivers' perceptions of enabling factors and barriers to dental services using a pretested survey instrument with 33 closed and open-ended questions. We also obtained referral source, insurance coverage and medical diagnosis from the child's dental record. We analyzed quantitative data descriptively and qualitative comments from caregivers thematically. RESULTS: Common medical diagnoses among this sample of CSHCN (n = 50) were: genetic disorder/syndrome, developmental delay, sensory impairments and autism. Half of the children were referred by a medical professional; most (90%) had had a dental appointment within the last year that included preventive treatment. Although most caregivers reported some available dental benefits, affordability of dental services was a concern. Lack of dentist's training or comfort treating CSHCN, because of the complexity of the child's medical condition or behavioural challenges was also a reported barrier. CONCLUSIONS: The complexity of the child's medical status, the limited ability of dentists to provide care and financial obstacles were commonly reported barriers to care. Current efforts may best be focused on encouraging the province's health professionals, including dentists, to facilitate early referral to tertiary-level care for CSHCN whom they consider medically or behaviourally complex beyond their skill or comfort level.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| 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".