An Exploratory Analysis of Access to Specialist Dermatological Care in Ontario
Bibliographic record
Abstract
Access has been a significant issue within the discourse in health geography for decades (Wilson and Rosenberg, 2004; Harrington et al., 2013). In the Canadian healthcare system, access to dermatological services generally involves receiving a referral from a general practitioner to a dermatologist. Literature on dermatological care has revealed inequities and comorbidities associated with skin disease that require greater attention. This thesis is thus an exploratory project on access to dermatological care to see what might be found at this specific level of specialist care in Ontario. I surveyed 49 adults who had visited a dermatologist regarding a chronic skin disease. Responses were analyzed using four stages of quantitative analysis as well as qualitative analysis of open-ended survey responses. Simple logistic regression revealed that there were significant differences between respondents who saw a specialist relatively quickly and those who had to wait a longer time. The likelihood of having to wait longer for a dermatologist visit increased between the youngest and oldest age cohorts, which was consistent with the general literature on specialist access. The likelihood of having to wait longer also increased for high-income individuals and males. A one-way analysis of variance was conducted using mean self-reported scores from the Dermatology Quality of Life Index (DQLI). The differences between the means was significant, where stigma and cutaneous body image had the highest mean scores out of all areas addressed by the DQLI. As an exploratory study, the results cannot be considered conclusive but make the case that further research is required on how access to dermatological care fits within the broader context of equity in Canadian healthcare, as well as how it relates to psychosocial issues like stigma and body image.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".