Addressing oral health equity through community service-learning and person-centered care in Ontario: patient and provider perspectives
Bibliographic record
Abstract
This study aimed to investigate the influence of the Community Service-Learning (CSL) program at Schulich Dentistry on the experiences and perceptions of patients and healthcare providers (HCP) at the Oxford County Community Health Centre (OCCHC) in Ontario, Canada. The CSL program aimed to address the oral health needs of equity-deserving populations and provide dental learners with experiential, community-based training. A qualitative research methodology using a Community-Engaged Research (CEnR) framework was employed. Data was collected through one-on-one interviews with 21 patients and six HCPs at the OCCHC. Inductive thematic analysis was conducted to identify key themes. As a result, five main themes were identified, with overlap between patients and HCPs. Two major themes emerged from the interviews with patients (1) challenges and barriers to dental care and (2) enhanced access to dental care through the CSL program; highlighting stigma and discrimination due to public dental insurances and low socioeconomic status. From the HCPs' perspectives, (3) person-centred care was the main identified theme, emphasizing the importance of understanding patients' individualized circumstances and social determinants of health when providing dental care. Additionally, common themes between patients and HCPs were also identified as (4) supportive environment and (5) patient empowerment and self-confidence. In conclusion, the CSL program addressed the oral health needs of equity-deserving patients by improving patient access to dental care while increasing patients' self-esteem and confidence through a person-centred care approach. These findings highlight the importance of community-integrated models of dental care in addressing oral health inequities and training future dental professionals.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.009 | 0.003 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".