Promoting Oral Health in Cleft Lip and Palate Patients: A Teledentistry and Social Media Messaging Intervention
Bibliographic record
Abstract
Abstract Background Teledentistry, which uses social media platforms, has the potential to improve oral health awareness and increase access to dental services in remote areas. This study aimed to evaluate the impact of a teledentistry-based oral health promotion program on changes in toothbrushing behaviour and oral health status among children with cleft lip and palate (CLP). Methods A pre-post intervention study was conducted from October to December 2023, involved 32 children aged 6—14 years and their guardians. The teledentistry-based program included two components: an onsite oral health education session with entertainment activities and toothbrushing with plaque-disclosing tablets and a social network group for guardians to share close-up photographs of their children's teeth marked with plaque-disclosing tablets on a weekly basis. Data collection included weeks of participation, clinical parameters such as plaque and gingival indices, and self-reported brushing behaviour assessed through questionnaires. Results A total of 27 participants (84%) participated in a follow-up assessment: 11 (34%) actively engaged in the group chat for four to seven weeks, 9 (28%) participated for one to three weeks, and 7 (22%) did not engage in the activities. Self-reported improvements included increased brushing duration (p < 0.001), improved brushing technique (p = 0.003) and a more positive attitude toward oral care (p < 0.001). Significant reductions were observed in both the gingival and plaque indices (p < 0.001). There was no significant association between participation level and either clinical parameters or brushing behaviour outcomes. Conclusion A teledentistry-based program improves oral hygiene in children with CLP and has the potential to increase the accessibility of dental care.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 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".