Cannabis and Oral Health Implications for 3 Priority Populations: A Special Communication
Bibliographic record
Abstract
As the legal status and social perceptions of cannabis shift globally, the potential impact of cannabis use on health and well-being merits heightened attention among practitioners and researchers, including possible effects on oral health. Evidence suggests that cannabis use may be associated with adverse oral health outcomes, including periodontal disease and xerostomia, with less conclusive links to dental caries and oral cancer. It is also becoming increasingly clear that certain population segments are at greater risk of cannabis use and may consequently face a greater burden of oral disease, underscoring the need for focused research and targeted interventions. In response to these concerns, a group of researchers convened a symposium titled "Cannabis and Oral Health: A Focus on Priority Populations" at the 2025 AADOCR/CADR Annual Meeting and Exhibition (American Association for Dental, Oral, and Craniofacial Research and Canadian Association for Dental Research). This session aimed to highlight the unique oral health challenges faced by priority populations in the context of a changing landscape of cannabis use. The presenters examined cannabis' impact among populations with whom they closely work, including Indigenous Canadians, adolescents and young adults, and 2SLGBTQI+ youth (Two-Spirit, lesbian, gay, bisexual, transgender, queer or questioning, intersex, and people that identify with other sexual orientations, gender identities, and expressions). Understanding the specific effects of cannabis on these groups is crucial, as social determinants of health are deeply intertwined with oral health outcomes. Historical and societal inequities, compounded by emerging health risks, demand a participatory research approach and targeted public health strategies. Evidence presented at the symposium highlights the need of addressing cannabis-related oral health impacts through inclusive, population-specific research and policy. A nuanced understanding of this evolving issue can inform the development of clinical guidelines and public health initiatives aimed at mitigating harm among populations that have been vulnerable within our societies. The symposium and this communication serve as a call to action for the dental and research communities to prioritize these perspectives in future work.Knowledge Transfer Statement:Amid shifting social and legal contexts, cannabis takes on heightened importance as a potential risk factor for oral diseases. Among specific priority populations, cannabis is one of several confluent health determinants that merits greater recognition and tailored research attention to inform appropriate clinical and public health practice.
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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 | 0.006 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".