Cross-sectional study of resident physician knowledge and perceptions regarding MASLD in Canada
Bibliographic record
Abstract
Background: Metabolic dysfunction-associated steatotic liver disease (MASLD) affects approximately 25% of Canadians. As its prevalence grows, it is crucial for future primary care physicians to have a thorough understanding of MASLD to improve patient care. Methods: We conducted a nationwide cross-sectional survey among resident physicians in primary care specialties to assess their knowledge and perceptions of MASLD. “Reasonable knowledge” was defined as correctly answering over 50% of the questions. Associations were analyzed using χ 2 testing and multiple logistic regression analysis. Results: We received 413 responses, with 252 (61%) from Family Medicine residents and 161 (39%) from Internal Medicine residents. Among the respondents, 91% considered MASLD an important public health issue; however, only 11% felt they had adequate exposure to the condition and 94% endorsed a need for more teaching. Overall, 35% of the respondents displayed a reasonable knowledge of MASLD. In univariate analysis, factors associated with greater MASLD knowledge included Internal Medicine residency ( p = 0.001), higher post-graduate year ( p = 0.003), prior GI or hepatology rotations ( p = 0.003), previous MASLD lectures ( p = 0.021), and higher subjective familiarity with MASLD ( p <0.001). However, only moderate (odds ratio (OR) 5.7, 95% CI 1.1–26.3, p = 0.026) and high (OR 10.1, CI 1.6–65.3, p = 0.015) subjective familiarity with MASLD, and three or more prior MASLD lectures (OR 3.4, CI:1.1–10.4, p = 0.031) remained statistically significant in multivariate analysis. Conclusions: Resident physicians recognize MASLD as an important health issue but lack adequate exposure and knowledge about the condition. Further emphasis and education are required to bridge these knowledge gaps and improve patient outcomes.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".