Access to dental services for children with special health care needs : a pilot study at British Columbia Children's Hospital Department of Dentistry
Bibliographic record
Abstract
Objectives: This pilot project, conducted at the Dental Department of BC Children’s Hospital (DD-BCCH), aimed to 1) identify issues that affect access to dental services for Children with Special Health Care Needs (CSHCN), 2) assess parental perceptions of the oral health status of their child and 3) determine the practicality and feasibility of survey research with this patient population Methods: Caregivers of CSHCN who were patients of the DD-BCCH were recruited by letter, posted advertisement and direct request. Information on caregiver’s perceptions of enabling factors and barriers to dental services and their understanding of their child’s oral health status were collected using a pre-tested survey instrument. In addition, demographic information, referral source, insurance coverage, medical diagnosis, and anticipated dental treatment were gathered from the child’s dental record. Quantitative data was analyzed descriptively and qualitative comments from parents by thematic analysis. Results: Common medical diagnoses for the sample of CSHCN (n=50) were genetic disorder/syndrome, developmental delay, sensory impairments and autism. Caregivers from mid-to-upper income levels formed 50% of the sample. Payment methods reported by parents included private dental insurance (52%), public benefits (36%), or out-of-pocket funds (24%). Of the sample, 50% were referred by a medical professional and most children (90%) had had a dental appointment within the last year. About 50% of caregivers reported the following barriers to obtaining dental care prior to attending at BCCH: dentist not trained or comfortable treating or managing the child’s behaviour; complexity of child’s medical condition and financial barriers. We were unable to determine a true parental perception of the oral health of the child because many parents answered the survey after the oral examination had been completed. Conclusions: 1) The complexity of the child’s medical status, limited ability of dental providers to deliver care and financial obstacles were commonly-reported barriers to dental care identified by parents 2) Parental perceptions of the oral health status of the child were not able to be reliably assessed. 3) A mail out survey was not a suitable method to obtain information about issues of access to dental services for CSHCN within the population at the DD-BCCH.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| 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".