Health literacy awareness among Canadian surgeons
Bibliographic record
Abstract
Adequate health literacy is essential to navigate the healthcare system and has a major role in peri-operative care and outcomes. Minimal information exists regarding surgeons’ understanding of health literacy, clinical implications, and awareness of universal measures of support. This study assessed Canadian surgeons’ perceptions of patients’ health literacy and their knowledge of available supportive resources. We conducted a cross-sectional study using an electronic survey distributed to surgeons at academic institutions. Data collected included sociodemographics, health literacy knowledge, and practice surrounding the use of supportive measures. Across four Canadian academic institutions (University of Toronto, McMaster University, University of Alberta, and University of Calgary), 35 surgeons from various surgical specialties, including general, plastic, and orthopedic surgery, completed the survey. Approximately 74% of surgeons reported familiarity with the concept “health literacy”, but they used general impressions to estimate their patients’ health literacy levels. Surgeons’ perceptions were that patients who had proficient health literacy represented 50% or less of their practice. However, knowledge of supportive tools for measuring patient health literacy was variable. Surgeons familiar with health literacy spent significantly more time (>15 minutes) counselling patients (38%, p=0.02) and used language at a 10th grade level or less (92%, p=0.04). Common supportive measures included using simple, non-medical terms (97%, n=34), repetition (83%, n=29), and drawing pictures/diagrams (83%, n=29). This study highlights the importance of surgeon awareness of health literacy and how improved awareness may guide patient-surgeon interactions and improve the quality 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 | 0.001 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".