Case-based blended eLearning scenarios-adequate for competence development or more?

Sind Fall-basierte blended eLearning Szenarien für die Kompetenzentwicklung adäquat – oder vermitteln sie mehr?

Journal

Neuropsychiatrie : Klinik, Diagnostik, Therapie und Rehabilitation : Organ der Gesellschaft Osterreichischer Nervenarzte und Psychiater
ISSN: 2194-1327
Titre abrégé: Neuropsychiatr
Pays: Germany
ID NLM: 9440588

Informations de publication

Date de publication:
Dec 2019
Historique:
received: 28 03 2019
accepted: 03 10 2019
pubmed: 7 11 2019
medline: 18 12 2019
entrez: 8 11 2019
Statut: ppublish

Résumé

Learning, competence development and scientific thinking in medicine need several strategies to facilitate new diagnostic and therapeutic ways. The optimal collaboration between creative thinking and biomedical informatics provides innovation for the individual patient and for a medical school or society. Utilizing the flexibilities of an e‑learning platform, a case based blended learning (CBBL) framework consisting of A) case based textbook material, B) online e‑CBL with question driven learning scenarios and C) simulated patient (SP) contact seminars was developed and implemented in multiple medical fields. Real-life clinical cases were anonymized and transferred into an interactive and an interdisciplinary eLearning platform. As an example of the offered clinical teaching-case collection, an example of a psychiatric case for the disease "posttraumatic stress disorder (PTSD)" is presented: a 30-year-old man with a history of insomnia with difficulties in falling asleep and sleeping through, nightmares, nervousness and psychomotor restlessness. The students are challenged to identify possible differential diagnoses and further get to know the patient's personal history (loss of relatives due to war, torture and flight from home country). Further, the students are guided through the principles of fear conditioning including translational aspects like neurotransmitter signaling of PTSD pathomechanism (translational and research aspects like dopamine transporter gene polymorphism, long term potentiation and synaptic signaling). The case presentation comprises different learning aspects: First, declarative knowledge has to be acquired and collected in basic medical sciences, knowledge that is in fact available and can be accessed on the conscious and preconscious level in long-term memory. Second, associative learning leads to the formation of neuronal connections and is an important way of learning and discovering, founded in neural associations. Third, polythematic-crosslinking thinking is needed as ability to link information in a meaningful way. These steps are a typical intellectual ability of gifted learners and researchers that combine previously seemingly unrelated areas to each other and drive innovation.

Sections du résumé

BACKGROUND BACKGROUND
Learning, competence development and scientific thinking in medicine need several strategies to facilitate new diagnostic and therapeutic ways. The optimal collaboration between creative thinking and biomedical informatics provides innovation for the individual patient and for a medical school or society. Utilizing the flexibilities of an e‑learning platform, a case based blended learning (CBBL) framework consisting of A) case based textbook material, B) online e‑CBL with question driven learning scenarios and C) simulated patient (SP) contact seminars was developed and implemented in multiple medical fields. Real-life clinical cases were anonymized and transferred into an interactive and an interdisciplinary eLearning platform.
METHODS METHODS
As an example of the offered clinical teaching-case collection, an example of a psychiatric case for the disease "posttraumatic stress disorder (PTSD)" is presented: a 30-year-old man with a history of insomnia with difficulties in falling asleep and sleeping through, nightmares, nervousness and psychomotor restlessness. The students are challenged to identify possible differential diagnoses and further get to know the patient's personal history (loss of relatives due to war, torture and flight from home country). Further, the students are guided through the principles of fear conditioning including translational aspects like neurotransmitter signaling of PTSD pathomechanism (translational and research aspects like dopamine transporter gene polymorphism, long term potentiation and synaptic signaling).
RESULTS/CONCLUSION CONCLUSIONS
The case presentation comprises different learning aspects: First, declarative knowledge has to be acquired and collected in basic medical sciences, knowledge that is in fact available and can be accessed on the conscious and preconscious level in long-term memory. Second, associative learning leads to the formation of neuronal connections and is an important way of learning and discovering, founded in neural associations. Third, polythematic-crosslinking thinking is needed as ability to link information in a meaningful way. These steps are a typical intellectual ability of gifted learners and researchers that combine previously seemingly unrelated areas to each other and drive innovation.

Identifiants

pubmed: 31696411
doi: 10.1007/s40211-019-00322-z
pii: 10.1007/s40211-019-00322-z
pmc: PMC6901430
doi:

Types de publication

Case Reports Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

207-211

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Auteurs

Patricia Pia Wadowski (PP)

Department of Internal Medicine II, Division of Angiology, Medical University of Vienna, Vienna, Austria.

Brigitte Litschauer (B)

Department of Clinical Pharmacology, Medical University of Vienna, Vienna, Austria.

Tamara Seitz (T)

Department of Psychoanalysis and Psychotherapy, Medical University of Vienna, Währinger Gürtel 18-20, 1090, Vienna, Austria.

Sebastian Ertl (S)

Department of Psychoanalysis and Psychotherapy, Medical University of Vienna, Währinger Gürtel 18-20, 1090, Vienna, Austria.

Henriette Löffler-Stastka (H)

Department of Psychoanalysis and Psychotherapy, Medical University of Vienna, Währinger Gürtel 18-20, 1090, Vienna, Austria. henriette.loeffler-stastka@meduniwien.ac.at.

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Classifications MeSH