ArticleBioMed research international2018
Machine Learning-Augmented Propensity Score-Adjusted Multilevel Mixed Effects Panel Analysis of Hands-On Cooking and Nutrition Education versus Traditional Curriculum for Medical Students as Preventive Cardiology: Multisite Cohort Study of 3,248 Trainees over 5 Years.
Article in BioMed research international, 2018. 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 39 papers, 1 of them a synthesis that pooled it.
What it found
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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
39 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Meta-analysis and machine learning-augmented mixed effects cohort analysis of improved diets among 5847 medical trainees, providers and patients.Public health nutrition · 2022Pooled it
- Effect of culinary education curriculum on Mediterranean diet adherence and food cost savings in families: a randomised controlled trial.Public health nutrition · 2021Trial
- Article
- Machine Learning and Artificial Intelligence in Nutrition Research: Analytical Methods, Applications, and Key Considerations.The Journal of nutrition · 2026Review
- Student-led teaching and learning initiatives in nutrition education for medical and health students: a scoping review.BMJ nutrition, prevention & health · 2026Review
- Article
- A Randomized Controlled Trial of a Culinary Medicine Intervention in a Virtual Teaching Kitchen for Primary Care Residents.Journal of general internal medicine · 2025Article
- Culinary medicine course: qualitative assessment of an innovative pedagogical approach.Public health nutrition · 2025Article
- Lifestyle Medicine Pillars and Pedagogies in Pre-registration Health Profession Degrees: A Scoping Review.Medical science educator · 2025Review
- Review
- Challenging Cognitive Load Theory: The Role of Educational Neuroscience and Artificial Intelligence in Redefining Learning Efficacy.Brain sciences · 2025Review
- Artificial Intelligence and Health Inequities in Dietary Interventions on Atherosclerosis: A Narrative Review.Nutrients · 2024Review
- The Effect of Web-Based Culinary Medicine to Enhance Protein Intake on Muscle Quality in Older Adults: Randomized Controlled Trial.JMIR formative research · 2024Article
- Development of a Culinary Medicine Curriculum to Support Nutrition Knowledge for Gastroenterology Fellows and Faculty.Nutrients · 2024Article
- From plate to planet: culturally responsive culinary practices for health system innovation.Frontiers in nutrition · 2024Article
- Cooking for Health: a comprehensive narrative review of Culinary Medicine as an educational tool in medical training in Brazil and Globally.Archives of endocrinology and metabolism · 2024Review
- Article
- Article
- Impact and evaluation of an online culinary nutrition course for health, education and industry professionals to promote vegetable knowledge and consumption.Journal of human nutrition and dietetics : the official journal of the British Dietetic Association · 2023Article
- A scoping review of nutrition education interventions to improve competencies, lifestyle and dietary habits of medical students and residents.Journal of nutritional science · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
38 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundCardiovascular disease (CVD) annually claims more lives and costs more dollars than any other disease globally amid widening health disparities, despite the known significant reductions in this burden by low cost dietary changes. The world's first medical school-based teaching kitchen therefore launched CHOP-Medical Students as the largest known multisite cohort study of hands-on cooking and nutrition education versus traditional curriculum for medical students.
methodsThis analysis provides a novel integration of artificial intelligence-based machine learning (ML) with causal inference statistics. 43 ML automated algorithms were tested, with the top performer compared to triply robust propensity score-adjusted multilevel mixed effects regression panel analysis of longitudinal data. Inverse-variance weighted fixed effects meta-analysis pooled the individual estimates for competencies.
results3,248 unique medical trainees met study criteria from 20 medical schools nationally from August 1, 2012, to June 26, 2017, generating 4,026 completed validated surveys. ML analysis produced similar results to the causal inference statistics based on root mean squared error and accuracy. Hands-on cooking and nutrition education compared to traditional medical school curriculum significantly improved student competencies (OR 2.14, 95% CI 2.00-2.28, DISCUSSION: This study provides the first machine learning-augmented causal inference analysis of a multisite cohort showing hands-on cooking and nutrition education for medical trainees improves their competencies counseling patients on nutrition, while improving students' own diets. This study suggests that the public health and medical sectors can unite population health management and precision medicine for a sustainable model of next-generation health systems providing effective, equitable, accessible care beginning with reversing the CVD epidemic.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.