Barriers to access dental care services among adult population: A systematic review
Bibliographic record
Abstract
Objective: This systematic review was done with the aim of assessing the barriers faced in utilizing dental care services by general population in age group between 20 and 60 years in India as these findings would provide evidence for making appropriate decisions in our National Oral Health Policy which could further improve access to dental care services for people across India. This was a systematic review. Materials and Methods: For this review, PubMed, TRIP database, Cochrane, and Google Scholar were the electronic databases searched based on the PICO. Preferred Reporting Items for Systematic Reviews and Meta- Analyses guidelines were followed for the final inclusion of articles. Results: The search generated a total of 91 articles from four different electronic bases: PubMed, TRIP database, Cochrane, and Google Scholar. Based on the inclusion criteria, 14 articles made it to the final analysis. All 14 studies reported a lack of time and nonavailability of dentists as major barriers in accessing dental care services. 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 using a standardized questionnaire is recommended using better-designed studies to substantiate the unequal access to health-care facilities to Indian Population.
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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 | 0.008 | 0.038 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.007 |
| Bibliometrics | 0.008 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".