Interprofessional nutrition management – implementation and evaluation of a course for medical and nursing students using research-based learning method Article Swipe
Bärbel Wesselborg
,
Matthias Hoenen
,
Renate Adam-Paffrath
,
Silke Kuske
,
Lena Schendel
,
Matthias Grünewald
,
Stefan Wilm
,
Thomas Rotthoff
·
YOU?
·
· 2019
· Open Access
·
· DOI: https://doi.org/10.3205/zma001276
YOU?
·
· 2019
· Open Access
·
· DOI: https://doi.org/10.3205/zma001276
Objective: The aim of the teaching project “Interprofessional Nutrition Management in Inpatient and Home Care” of the Medical Faculty of the Heinrich Heine University (HHU) and the Fliedner University of Applied Sciences Düsseldorf (FFH) was to test an interprofessional training session on the topic of malnutrition using the method of research-based learning to evaluate feasibility. Method: In the teaching project for medical and nursing students, research-based learning was applied in a case-based cross-sector setting. The teaching project was assessed quantitatively by the participating students through questionnaires and four newly-developed scales. The modeling and reliability of the scales (from 1 to 5) was confirmed by an exploratory factor analysis and Cronbach’s alpha. The scales were evaluated descriptively and through inferential statistics. Results: The medical (n=21) and nursing students (n=25) rated the teaching project positively. Across all professional groups, the social context between the students (M=4.6) and the relevance of the topic (M=4.47) were rated very highly. The use of research-based learning (M=3.9) and the final assessment of the training session (M=3.9) were rated as satisfactory. Conclusions: The method of research-based learning proved to be very suitable for interprofessional education, as it enabled situations which encouraged the health professionals to learn from one another, about one another and with one another. Through the interdisciplinary discussion of malnutrition, cooperation skills and initial competences in nutritional management can be cultivated in future doctors and nursing staff even during training.
Related Topics
Concepts
Cronbach's alpha
Context (archaeology)
Medical education
Session (web analytics)
Nursing
Interprofessional education
Psychology
Exploratory research
Test (biology)
Medicine
Health care
Biology
Anthropology
Clinical psychology
Sociology
Computer science
Economic growth
Economics
Psychometrics
Paleontology
World Wide Web
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://pubmed.ncbi.nlm.nih.gov/31844640
- OA Status
- green
- Cited By
- 8
- References
- 8
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W3002753605
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W3002753605Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.3205/zma001276Digital Object Identifier
- Title
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Interprofessional nutrition management – implementation and evaluation of a course for medical and nursing students using research-based learning methodWork title
- Type
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articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
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2019Year of publication
- Publication date
-
2019-11-15Full publication date if available
- Authors
-
Bärbel Wesselborg, Matthias Hoenen, Renate Adam-Paffrath, Silke Kuske, Lena Schendel, Matthias Grünewald, Stefan Wilm, Thomas RotthoffList of authors in order
- Landing page
-
https://pubmed.ncbi.nlm.nih.gov/31844640Publisher landing page
- Open access
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YesWhether a free full text is available
- OA status
-
greenOpen access status per OpenAlex
- OA URL
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https://doi.org/10.3205/zma001276Direct OA link when available
- Concepts
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Cronbach's alpha, Context (archaeology), Medical education, Session (web analytics), Nursing, Interprofessional education, Psychology, Exploratory research, Test (biology), Medicine, Health care, Biology, Anthropology, Clinical psychology, Sociology, Computer science, Economic growth, Economics, Psychometrics, Paleontology, World Wide WebTop concepts (fields/topics) attached by OpenAlex
- Cited by
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8Total citation count in OpenAlex
- Citations by year (recent)
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2024: 2, 2023: 4, 2021: 1, 2020: 1Per-year citation counts (last 5 years)
- References (count)
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8Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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