Protective psychosocial factors and dental caries in children and adolescents: a systematic review and meta‐analysis
Bibliographic record
Abstract
BACKGROUND: Psychosocial protective factors include dispositional and family attributes that may reduce the occurrence of dental caries. AIM: This review analysed the evidence on the relationship between protective psychosocial factors and dental caries in children and adolescents. DESIGN: Primary studies involving children and adolescents were searched in the following electronic databases: Medline, SCOPUS, LILACS, SciELO, and Web of Science. The reference lists were also screened. Protective psychosocial factor descriptors were in accordance with the salutogenic theory. The outcome was clinical measure of dental caries. Quality assessments were performed using the Newcastle-Ottawa scale. RESULTS: The final search resulted in 35 studies, including 7 cohort, one case-control, and 27 cross-sectional studies. Most studies were of moderate quality. Meta-analyses revealed that low parental internal locus of control (cohort studies: OR = 1.42, 95% CI: 1.20-1.64; cross-sectional studies: OR = 1.30, 95% CI: 1.19-1.41), high parental external chance (OR = 1.20, 95% CI: 1.10-1.29), and high maternal sense of coherence (OR = 0.77, 95% CI: 0.62-0.93) were associated with dental caries in children. High social support (OR = 0.81, 95% CI: 0.68-0.93) and greater self-efficacy (OR = 1.50, 95% CI: 1.12-1.22) were also associated with dental caries in adolescents. CONCLUSIONS: The current evidence suggests that some salutogenic factors are important protective factors of dental caries during childhood and adolescence.
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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 | 0.007 | 0.019 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.014 | 0.022 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| 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".