Investigating Changes in Overall Oral Health and Exploring Patient Perception and Experiences After Treatment at the One Smile Research Program: An Exploratory Mixed-Methods Case Study with a 2-Year Follow-Up
Bibliographic record
Abstract
Background: In Canada, despite universal healthcare coverage, dental care remains predominantly privately financed, creating financial barriers that prevent many from accessing essential services. This case study is part of a larger initiative, the One Smile Research program, which evaluates the impact of cost-free dental care on oral health, and overall well-being of individuals, who have been unable to access dental services in the past two years due to financial constraints. Participants in the program receive necessary dental care and attend follow-up appointments to assess the long-term effects of continuous cost-free care. Method: This mixed-methods case study focuses on a 26-year-old male participant and integrates qualitative semi-structured interviews with clinical and self-reported data, providing an in-depth understanding of his experiences. Results: Clinical outcomes demonstrated the effectiveness of the provided dental treatments, while self-reported measures indicated improved oral health, satisfaction with dental appearance, enhanced psychosocial well-being, increased self-esteem, reduced dental anxiety, and better oral hygiene habits. The qualitative interview identified three key themes reflecting positive experiences with the program: ease of admission, staff kindness, and overall well-being improvement. The integration of both quantitative and qualitative analyses revealed significant advancements in both objective and subjective measures, particularly regarding overall well-being. Conclusion: The continuity of cost-free dental care effectively addressed the participants’ oral health and overall well-being, with most benefits sustained even at the two-year follow-up. These longer-term positive outcomes emphasize the critical advantages of universal dental coverage within the Canadian healthcare system.
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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 | 0.008 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.003 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.003 | 0.003 |
| 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".