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Record W1968772135 · doi:10.5539/gjhs.v4n1p112

Effect of an Integrated Case-based Nutrition Curriculum on Medical Education at Qazvin University of Medical Sciences, Iran

2011· article· en· W1968772135 on OpenAlexvenueno aff
Ahmad Afaghi, Ali Akbar Haj Agha Mohamadi, Amir Ziaee, Ramin Sarchami

Bibliographic record

VenueGlobal Journal of Health Science · 2011
Typearticle
Languageen
FieldHealth Professions
TopicObesity and Health Practices
Canadian institutionsnot available
Fundersnot available
KeywordsCurriculumMedical educationMedicinePsychologyPedagogy

Abstract

fetched live from OpenAlex

INTRODUCTION: Nutrition education is identified as an important part of medical education by organizations. Qazvin University of Medical Sciences, school of medicine (QUMS SOM), has a required basic nutrition course of 36 hr in second year of medical school, but education experts reports show that the course does not provide required therapeutic skills for graduate student. METHOD: We decided to organize an 8-hr diet therapy work shop in order to develop a patient experience clinical based case study teaching to enhance clinical skills at QUMS SOM. RESULTS: Students' perception score about adequacy of nutrition instruction increased from 20% (at baseline) to 70% (after intervention). The mean nutrition knowledge score of total students in clinical nutrition were different between before and one month after integration (8.3±2.5, 13.4±3.2, P < 0.001). And two groups of participants including staggers and interns had similar nutritional knowledge score at pre-test (7.9±2.6 and 8.9±2.3 respectively). CONCLUSION: Implemented nutrition curriculum at QUMS was appropriate method to enhance student's perception about nutrition integration and to increase and translate the knowledge to clinical practice.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.023
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.170
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0230.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0020.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.077
GPT teacher head0.476
Teacher spread0.399 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations21
Published2011
Admission routes1
Has abstractyes

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