The perspective of dental students regarding the implementation of a social prescription scheme at McGill University
Bibliographic record
Abstract
Background: Social prescribing is a healthcare approach that connects individuals with community-based resources to address non-medical factors affecting their well-being. It helps patients access social support, financial assistance, recreational activities, and essential services, complementing clinical care to improve overall health and quality of life. This model is widely implemented in primary care to tackle social determinants of health. But in dentistry, this approach is still relatively new and unexplored. At McGill University, undergraduate students receive introductory training on social prescribing, yet its integration into dental practice is still in its early stages. This thesis explores how fourth-year dental students at McGill University perceive about bringing social prescribing into dental practice, looking at its potential to address social determinants that impact health and improve patient care. Objectives: To better understand how dental students perceive social prescribing as well as the barriers and facilitators to implementing this approach in dental practice.Methodology: This qualitative descriptive study is based on semi-structured interviews with fourth-year dental students at McGill University. A purposeful sampling approach, specifically maximum variation sampling, was used to ensure diversity in age, gender, and levels of openness to social prescribing among the selected students. Twelve students participated in the study and were interviewed individually. The discussions were audio-recorded, transcribed verbatim, and analyzed using both deductive and inductive coding methods. This process helped identify key themes related to students’ perceptions of social prescribing. Findings:Participants perceived social prescribing as a valuable approach to providing holistic, person-centered dental care by addressing social and psychological factors that impact oral health. They recognized its potential to strengthen patient relationships and improve well-being. However, when considering how to apply it within their academic dental setting, they reported several challenges. These included time limitations during appointments, minimal faculty guidance, and unclear professional boundaries. Many were uncertain whether addressing social determinants truly fit within the scope of dental practice.Despite these concerns, participants identified several factors that could support integration. They emphasized the importance of early and continuous training in social prescribing throughout the dental program, increased faculty involvement and mentorship, and stronger partnerships with community organizations. Some also mentioned the need for clear referral processes and better tools to connect patients with appropriate services. When thinking about their future careers, many participants showed interest in adopting social prescribing, seeing its potential to improve patient care, while also recognizing that its success would rely on having the right support and systems in place.Conclusion:These findings highlight the importance of better training, clearer role definitions, and stronger system-level support to prepare students for integrating social prescribing into both education and practice
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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 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.017 | 0.009 |
| Scholarly communication | 0.008 | 0.002 |
| Open science | 0.003 | 0.008 |
| Research integrity | 0.003 | 0.007 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".