Perspectives on integrating an oral health helpline into a dental and dental hygiene school
Bibliographic record
Abstract
Background: Oral health inequities and access disparities in Canada disproportionately affect underserved populations. Access to care was further limited during the COVID-19 pandemic when non-urgent dental services were suspended. Community organizations identified a need for an oral health helpline to provide information and support service navigation. Objectives: This dissertation aimed to (1) explore the experiences and resource needs of underserved populations during service disruptions; (2) develop and implement a dental school–based oral health helpline; (3) examine the helpline’s educational impact on dental and dental hygiene students; (4) explore student and faculty perspectives on integrating the helpline into a dental and dental hygiene school (DDHS); and (5) develop a conceptual model outlining helpline integration into a DDHS. Methods: This dissertation included qualitative studies guided by the transformative research paradigm and grounded theory methodology, and an oral health helpline pilot project. Data collection included interviews with 13 underserved community members, 18 organization staff, 12 dental and dental hygiene students, and 17 faculty members. Interview data were transcribed, coded in NVivo© (Version 12) software, and analyzed. Credibility and trustworthiness were enhanced through memoing, reflexivity, and member checking. Results: Underserved populations reported reduced access to oral health care and resorted to coping mechanisms to manage unmet needs during the beginning of the pandemic. The oral health helpline supported underserved individuals by answering oral health questions, providing information on public dental benefits, and connecting users to lower barrier services. Helpline education enhanced students’ understanding of navigating oral health services, dental insurances, and barriers to care, while strengthening communication skills. Faculty and students valued the helpline as a community resource and educational tool but identified integration barriers including limited resources, curriculum overload, and competing institutional priorities. A model was developed, highlighting three domains influencing integration: perceived usefulness, educational components, and integration factors. Conclusion: A dental school–based oral health helpline can improve access to oral health information and services while preparing students to provide oral health information and facilitate services navigation. Integration requires alignment with institutional values, sustained resources, and faculty engagement. The conceptual model provides a framework to guide helpline integration into a DDHS.
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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 | 0.014 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.018 | 0.013 |
| Scholarly communication | 0.010 | 0.007 |
| Open science | 0.002 | 0.013 |
| Research integrity | 0.003 | 0.006 |
| 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".