Physician Experiences Providing Primary Care to People with Disabilities
Bibliographic record
Abstract
The 2003 Statistics Canada Health Services Access Survey found that 12% of Canadians polled did not have a family doctor, and 18% reported access problems such as long waiting times and difficulty contacting the doctor. Research has repeatedly shown that where a problem with access exists in the general population, it is considerably more severe in subsets of the population that are most disadvantaged. Statistics at both the national and local levels confirm that although people with disabilities have greater need for health services, including both institutional and community services, they also experience significant disadvantages in attempting to access service. The question explored in this study is how physicians' perceptions of disabled patients and behaviour towards them might affect access to primary care for adults with disabilities. The study used a qualitative interpretive approach to uncover physicians' perspectives on working with people with disabilities. Semi-structured interviews were conducted with a sample of 34 physicians in Eastern Ontario. Physicians were asked: How are disabled patients similar to/different from non-disabled patients? How are you as a physician different with disabled patients? Physicians' perceptions, as revealed by their responses to these questions, were interpreted in terms of four types of barriers to access to primary care for disabled adults: physical, attitudinal, expertise-related and systemic. These barriers were examined for their impact on finding a doctor, getting an appointment, getting into the office and receiving a reasonable standard of care.
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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 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.003 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".