Diagnostic accuracy of tele‐dentistry in screening children for dental caries by community health workers in a lower‐middle‐income country
Bibliographic record
Abstract
BACKGROUND: Tele-dentistry can be useful for dental caries screening of children, especially in lower-middle-income countries (LMICs). AIM: To evaluate the diagnostic accuracy of mobile phone photographs taken by a community health worker (CHW) for caries detection in Iran. DESIGN: Children aged 6-12 years were visually examined by a paediatric dentist. Following dental examinations, intraoral photographs were taken by a trained CHW. Two remote dentists assessed intraoral photographs for dental caries. Diagnostic accuracy of tele-dentistry for caries detection was evaluated. In addition, the questionnaire about oral health and parents' views towards tele-dentistry was prepared. RESULTS: One hundred thirty-one children aged 8.74 ± 1.62 years participated. The caries prevalence was 30% for the whole dentition. Tele-dentistry demonstrated high accuracy, with a sensitivity exceeding 80% and specificity exceeding 90%. The inter-rater reliability for remote dentists' assessments to the gold standard dental examination ranged from substantial to almost perfect (kappa: 75%-93%). Additionally, 80% of parents whose children participated in this study had positive views towards tele-dentistry. CONCLUSION: Tele-dentistry was shown to be an alternative approach to clinical examinations for caries detection among school children. Employing non-dental care professionals in tele-dentistry has been emerged as a reliable and cost-effective approach, especially in LMICs.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".