Development and Refinement of the Indian Caries Risk Assessment Tool for Children
Bibliographic record
Abstract
Aim and background: Early childhood caries (ECC) is a significant oral health problem in India. Personalized care based on individual or group risk has become a key aspect of dental caries prevention and management. However, an appropriate tool for caries risk assessment (CRA), taking into consideration the protective and risk factors for ECC specific to the Indian population, does not exist. This study aimed to report on the development and refinement of an evidence-based CRA tool for Indian children <6 years of age through consultation and feedback by dental professionals. Materials and methods: Stakeholder consultation sessions were conducted with 65 participants, which included dental professionals and postgraduate residents. A survey questionnaire was also used to collect feedback on the initial draft of the newly developed Indian CRA tool. Predominant preferences and recommendations for improvement were taken into consideration, and the data were descriptively analyzed. Results: The consultation sessions were conducted separately with three groups. A total of 80% of participants also completed the survey questionnaire. Survey questionnaire results reveal that 82.7% considered the current proposed questions in the Indian CRA tool to be sufficient, while 86.5% indicated that the tool would be understandable by parents. Overall, the majority of respondents (96.2%) agreed on the importance of the drafted Indian CRA tool for tailoring anticipatory guidance and treatment for individual children. Conclusion: The newly developed CRA tool for Indian preschool children will be a useful resource for dental practitioners to assess young children's individual caries risk levels and assist with providing a personalized preventive service to children. The developed tool was refined based on dental professional feedback and was found to be a user-friendly, simple, practical, and evidence-based approach. Clinical significance: This study developed the first evidence-based CRA tool for preschoolers in India. Researchers drafted and then refined the tool through consultation with stakeholders. The final CRA tool is evidence- and algorithm-based, easy to use, and considers the risk factors specific to ECC of the Indian preschool population. How to cite this article: Khan SY, Schroth RJ, Javed F. Development and Refinement of the Indian Caries Risk Assessment Tool for Children <6 Years of Age. Int J Clin Pediatr Dent 2025;18(1):58-63.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".