ArticleMedical science educator2020
Regional variations in medical trainee diet and nutrition counseling competencies: Machine learning-augmented propensity score analysis of a prospective multi-site cohort study.
Article in Medical science educator, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT03443635 (Cooking for Health Optimization With Patients), which is not on this map. Cited by 2 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Cooking for Health Optimization With Patients
Who cites it
2 citing papers in PubMed.
- Exploring culinary medicine as a promising method of nutritional education in medical school: a scoping review.BMC medical education · 2022Article
- Culinary Medicine Experiences for Medical Students and Residents in the U.S. and Canada: A Scoping Review.Teaching and learning in medicineArticle
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Authors and funding
14 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundMedical professionals and students are inadequately trained to respond to rising global obesity and nutrition-related chronic disease epidemics, primarily focusing on cardiovascular disease. Yet, there are no multi-site studies testing evidence-based nutrition education for medical students in preventive cardiology, let alone establishing student dietary and competency patterns.
methodsCooking for Health Optimization with Patients (CHOP; NIH NCT03443635) was the first multi-national cohort study using hands-on cooking and nutrition education as preventive cardiology, monitoring and improving student diets and competencies in patient nutrition education. Propensity-score adjusted multivariable regression was augmented by 43 supervised machine learning algorithms to assess students outcomes from UT Health versus the remaining study sites.
results3,248 medical trainees from 20 medical centers and colleges met study criteria from 1 August 2012 to 31 December 2017 with 60 (1.49%) being from UTHealth. Compared to the other study sites, trainees from UTHealth were more likely to consume vegetables daily (OR 1.82, 95%CI 1.04-3.17, p=0.035), strongly agree that nutrition assessment should be routine clinical practice (OR 2.43, 95%CI 1.45-4.05, p=0.001), and that providers can improve patients' health with nutrition education (OR 1.73, 95%CI 1.03-2.91, p=0.038). UTHealth trainees were more likely to have mastered 12 of the 25 competency topics, with the top three being moderate alcohol intake (OR 1.74, 95%CI 0.97-3.11, p=0.062), dietary fats (OR 1.26, 95%CI 0.57-2.80, p=0.568), and calories (OR 1.26, 95%CI 0.70-2.28, p=0.446).
conclusionThis machine learning-augmented causal inference analysis provides the first results that compare medical students nationally in their diets and competencies in nutrition education, highlighting the results from UTHealth. Additional studies are required to determine which factors in the hands-on cooking and nutrition curriculum for UTHealth and other sites produce optimal student - and, eventually, preventive cardiology - outcomes when they educate patients in those classes.
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