Unmasking oral health stigma: a qualitative scoping review
Bibliographic record
Abstract
INTRODUCTION: Health-related stigma can limit access to care, impair adherence to treatment, and negatively impact mental health and quality-of-life. Oral health stigma, defined as stigma arising from oral conditions that diverge from sociocultural norms, operates through labelling, stereotyping, othering, and exclusion. Oral health stigma can lead to shame, diminished self-confidence, and avoidance of dental care, creating a self-perpetuating cycle of poor oral health and reinforcing internalised and anticipated stigma. While previous research has explored the social implications of oral appearance, little is known about the broader concept of oral health stigma or strategies to mitigate it. METHODS: This scoping review adopted Levac et al.'s six-stage framework. The review utilised data from qualitative studies to explore lived experiences of oral health stigma and consider ways to mitigate it. Patient and public involvement (PPI) informed the development of the research question, search strategy, and interpretation of findings. RESULTS: Seventy-two qualitative studies were included, comprising 2,455 participants. Themes included stigma associated with physical appearance and attractiveness, judgement, labelling, and stereotyping. Consequences included low self-esteem, social exclusion, impacts to care seeking behaviours, and efforts to conceal oral appearance. Participants highlighted the transformative value of dental care and described coping strategies to build resilience. Other proposed solutions included fostering social connection and implementing trauma-informed, non-judgemental dental care. CONCLUSION: Oral health stigma has significant social and psychological consequences and impacts on care-seeking behaviours. Addressing it requires targeted interventions at multiple levels, including individual, community, professionals and wider system / policy.
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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 | 0.043 | 0.088 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.018 | 0.019 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.003 | 0.008 |
| Research integrity | 0.003 | 0.002 |
| 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".