Access to oral health care for persons who are d/Deaf in Montreal: a focused ethnography
Bibliographic record
Abstract
Background: Over five percent (N=1,266,120) of the Canadian population is reported to have some degree of hearing loss, of which 83,160 persons are profoundly deaf. Persons who are deaf are reported to have both poorer oral health, and oral health knowledge compared to their hearing counterparts in the population. Studies have indicated that due to communication barriers, accessing oral health care services can be a challenge for the d/Deaf community. There is, however, little research regarding the barriers that d/Deaf persons may encounter on their pathways to oral health care. Therefore, the present study was designed to explore the barriers and facilitators of access to oral health care for d/Deaf persons, particularly the Anglophone d/Deaf population in Montreal. Methodology: Using a participatory research framework, I conducted a focused ethnography to explore the experiences and perceptions of the Anglophone d/Deaf population in Montreal related to access to oral health care. Data collection constituted participant observation at social and educational activities (~50 hours), and 11 semi-structured interviews with d/Deaf participants. All interviews were conducted in American Sign Language (ASL), interpreted in English, and transcribed verbatim. Data analysis included three levels of analysis: 1) within-case; 2) across-case; and 3) ethnographic analysis. Critical theory of disability, and selected components of Grembowski and colleagues' ‘public health model of dental care process' guided data collection, analysis and interpretation. Results: The findings of this study reveal important gaps between the oral health care system and the needs of persons who are d/Deaf. As a result, the Anglophone d/Deaf population face several barriers on their pathways to oral health care, including the following: poor access to ASL interpreters for dental appointments; difficulties in interacting with dental office staff, including telephone communication and in waiting areas; and communication barriers with dentists both during consultation and procedures, resulting from the lack of awareness by dental professionals. Participants proposed several recommendations for overcoming these challenges, starting with health insurance to cover the cost of interpreters for dental appointments; office staff using Video Relay Services (VRS), text (SMS) or e-mail for booking appointments, and dentists asking patients for their preferred mode of communication, removing masks when speaking, and using gestures during procedures. Conclusion: The d/Deaf population is vulnerable to poor access to oral health care. Barriers that the Anglophone d/Deaf community in Montreal face on their oral health care pathways mainly result from a non-accommodating environment as well as the lack of awareness by dental professionals towards providing care to persons who are d/Deaf. Therefore, the Quebec government, dental educators, and community organizations supporting d/Deaf persons should take collaborative actions to improve access to oral health care for d/Deaf persons.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.011 | 0.005 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.004 |
| 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".