Understanding the complexities of oral healthcare delivery in correctional settings: a qualitative exploration of barriers, facilitators, and opportunities
Bibliographic record
Abstract
Abstract Background People living in prison face exceptionally high prevalence rates of tooth decay, periodontal disease, and poor oral health-related quality of life. Despite its importance, various aspects of oral healthcare in prison settings remain understudied. The present study investigates the barriers and facilitators associated with providing and utilizing oral health services in prison settings, drawing on insights from prison health experts, managerial and custodial staff, healthcare providers, and individuals with lived experience of imprisonment. Methods From March to June 2023, a total of fifteen participants participated in semi-structured in-depth interviews. Interviews were conducted until data saturation to identify barriers and facilitators of oral health services in prisons. Potential areas for improvement were also explored. Thematic analysis was used to analyze the data. Themes and sub-themes were derived from the dataset and converted into preliminary codes which aligned with research objectives. Results The first topic, barriers, included two themes: organizational barriers related to the provision of services, and individual barriers related to the utilization of services. The second topic, facilitating factors, included six themes: funding, community partnership, substance use treatment, communicating with policy makers, transportation, and education. Conclusion Ensuring the oral health of incarcerated individuals is a fundamental aspect of their right to health and a crucial factor in their successful reintegration into society. Formerly incarcerated people are often hard to reach in the community, making the period of confinement a unique opportunity to deliver quality oral healthcare. Given that most incarcerated individuals will eventually return to their communities, providing comprehensive healthcare, including oral health interventions, represents a valuable public health investment.
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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 | 0.013 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.011 | 0.010 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.002 | 0.003 |
| 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".