Associations between self-efficacy, social support, racial discrimination, and adolescents oral health
Bibliographic record
Abstract
OBJECTIVE: This study aimed to develop a conceptual model exploring the relationships between perceived social support (PSS), self-efficacy, racial discrimination, and oral health (OH) in adolescents. METHODS: A cross-sectional study of adolescents aged 12-18 was conducted at a university dental clinic. Participants completed a questionnaire on demographics, OH, PSS, general self-efficacy, and task-specific self-efficacy (TSSE). Structural Equation Modeling (SEM) was used for analysis. RESULTS: A total of 252 adolescents participated in the study, with an average age of 14 years; 60% were female, 81% were born in Canada, 56% identified as White, and 20% perceived discrimination. PSS was positively associated with general self-efficacy (p = 0.002), TSSE for dental visits (p = 0.004), dietary habits (p = 0.004), and tooth-brushing (p = 0.002), while also elevating sugar consumption (p = 0.002). PSS (p = 0.048) and discrimination (p = 0.01) reduced tooth-brushing frequency. Self-efficacy for dietary habits (p = 0.005) and tooth-brushing (p = 0.002) positively correlated with increased tooth-brushing, while self-efficacy for dietary habits decreased sugar consumption (p = 0.001). Self-efficacy for tooth-brushing was linked to reduced dental visits (p = 0.02). PSS indirectly increased brushing frequency (p = 0.02) and reduced dental-care utilization (p = 0.004). Discrimination indirectly reduced self-efficacy for dental visits (p = 0.003) but increased self-efficacies for tooth-brushing (p = 0.01) and dietary habits (p = 0.03). CONCLUSION: PSS was directly related to increased self-efficacy, while discrimination indirectly affected OH. Oral health was associated with self-efficacy for dietary habits and tooth-brushing, but not dental visits alone. IMPLICATIONS FOR HEALTH EQUITY: The findings underscore the critical need to address systemic inequities in oral health care access. By exploring the interplay between social support, discrimination, and self-efficacy, this study highlights actionable pathways to reduce disparities and improve oral health outcomes among adolescents.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".