What are the self‐reported unmet dental treatment needs of people living with HIV in British Columbia? A case of minority subpopulation in Canada
Bibliographic record
Abstract
OBJECTIVES: To identify associations of Andersen and Newman's (A&N) predisposing, enabling, and need factors with self-reported oral health status and self-reported unmet dental treatment needs in a sample of people living with HIV (PLHIV) in British Columbia (BC), Canada. METHODS: Participants responded anonymously to a 41-item online questionnaire with the following inclusion criteria: a) be at least 19 years old; b) self-identify as HIV-positive; c) be able to provide consent and be willing to voluntarily participate in the study; d) be residing in British Columbia; and e) be able to proficiently respond to the questions in English. Following the descriptive statistics, associations between A&N model factors and the main outcome variables (self-reported oral health status and self-reported dental treatment needs) were evaluated using bivariate inferential analyses. RESULTS: A total of 186 participants met the inclusion criteria. Approximately 40% (n = 74) of participants rated the health of their mouth as fair/poor and more than half (n = 112; 60.2%) reported having bleeding gums, tooth decay or tooth sensitivity. The bivariate analysis for the self-reported oral status as the outcome variable showed "having fair/poor general health" (P = 0.001), "unemployment" (P = 0.019), "avoiding dental treatment due to cost" (P = 0.005), and "not visiting a dental professional within the last year" (P < 0.001) as the strongest predictors. For the second outcome variable unmet dental treatment needs, the strongest predictors were "experience of being discriminated by dental professionals" (P = 0.001), "having fair/poor general health" (P = 0.006), and "suffering from past and current medical conditions due to HIV" (P < 0.001). CONCLUSIONS: Several predisposing, enabling and need factors from the A&N model were associated with self-reported oral health status and unmet dental treatment needs of PLHIV. Results from this study highlight the needs of improving access to affordable dental care to address the unmet oral health needs of PLHIV.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.007 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".