Barriers to utilisation of dental care services among children with special needs: A systematic review
Bibliographic record
Abstract
BACKGROUND: Disabled population accounts for 2.86 Crore of total Indian population. Among these 27.4% of population consists of children within age group of age 0 to 19 years. Studies have shown oral health status of children with special needs is lower than children without special needs. Though there are various attributing factors, access to dental care delivery and difficulties faced during dental treatment delivery are of major concern. Therefore the aim of this systematic review was set to assess the barriers faced by children with special needs during utilization of dental services; through caregiver's perception. MATERIALS AND METHODS: For this review MEDLINE, EBSCO, COCHRANE, EMBASE and Google Scholar were the electronic data bases searched based on the PICO. PRISMA guidelines were followed for final inclusion of articles. RESULTS: The search generated a total of 259 articles from five different electronic bases: PUBMED, EMBASE, EBSCO, COCHRANE and GOOGLE SCHOLAR. Based on inclusion criteria, 7 articles made it to final analysis. All the 7 studies reported that dentist were unwilling to treat children with special needs as a major barrier followed by fear towards dentist by the children with special needs. CONCLUSION: The cross sectional studies of this review were assessed for quality using a modified Newcastle Ottawa Scale, proposed by Egger et al. in 2003. Even though the available literature forms a lower standard of evidence, further evaluation of barriers are recommended using better designed studies to substantiate the in equal access to healthcare facilities by these marginalized population.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".