Simulation via instant messaging-Birmingham advance (SIMBA) model helped improve clinicians' confidence to manage cases in diabetes and endocrinology.


Journal

BMC medical education
ISSN: 1472-6920
Titre abrégé: BMC Med Educ
Pays: England
ID NLM: 101088679

Informations de publication

Date de publication:
18 Aug 2020
Historique:
received: 03 12 2019
accepted: 04 08 2020
entrez: 20 8 2020
pubmed: 20 8 2020
medline: 15 5 2021
Statut: epublish

Résumé

Simulation-based learning (SBL) has been increasingly used in both undergraduate and postgraduate medical training curricula. The aim of Simulation via Instant Messaging-Birmingham Advance (SIMBA) is to create a simple virtual learning environment to improve trainees' self-reported confidence in diabetes and Endocrinology. This study was done as part of the continuous professional development for Health Education England West Midlands speciality trainees in diabetes and Endocrinology. Standardized transcripts of anonymized real-life endocrinology (endocrine session) and diabetes cases (diabetes session) were used in the simulation model. Trainees interacted with moderators through WhatsApp® in this model. All cases were then discussed in detail by a consultant endocrinologist with reference to local, national and international guidelines. Trainee acceptance rate and improvement in their self-reported confidence levels post-simulation were assessed. 70.8% (n = 17/24) and 75% (n = 18/24) strongly agreed the simulation session accommodated their personal learning style and the session was engaging. 66.7% (n = 16/24) strongly felt that the simulation was worth their time. In the endocrine session, there was a significant improvement in trainees' confidence in the management of craniopharyngioma (p = 0.0179) and acromegaly (p = 0.0025). There was a trend towards improved confidence levels to manage Cushing's disease and macroprolactinoma. In diabetes session, there was a significant improvement in trainees' confidence to interpret continuous glucose monitor readings (p = 0.01). There was a trend towards improvement for managing monogenic diabetes, hypoglycaemic unawareness and interpreting Libre readings. Overall, there was a significant improvement in trainees' confidence in managing cases that were discussed post-simulation. SIMBA is an effective learning model to improve trainees' confidence to manage various diabetes and endocrine case scenarios. More sessions with a variety of other speciality case scenarios are needed to further assess SIMBA's effectiveness and application in other areas of medical training.

Sections du résumé

BACKGROUND BACKGROUND
Simulation-based learning (SBL) has been increasingly used in both undergraduate and postgraduate medical training curricula. The aim of Simulation via Instant Messaging-Birmingham Advance (SIMBA) is to create a simple virtual learning environment to improve trainees' self-reported confidence in diabetes and Endocrinology.
METHODS METHODS
This study was done as part of the continuous professional development for Health Education England West Midlands speciality trainees in diabetes and Endocrinology. Standardized transcripts of anonymized real-life endocrinology (endocrine session) and diabetes cases (diabetes session) were used in the simulation model. Trainees interacted with moderators through WhatsApp® in this model. All cases were then discussed in detail by a consultant endocrinologist with reference to local, national and international guidelines. Trainee acceptance rate and improvement in their self-reported confidence levels post-simulation were assessed.
RESULTS RESULTS
70.8% (n = 17/24) and 75% (n = 18/24) strongly agreed the simulation session accommodated their personal learning style and the session was engaging. 66.7% (n = 16/24) strongly felt that the simulation was worth their time. In the endocrine session, there was a significant improvement in trainees' confidence in the management of craniopharyngioma (p = 0.0179) and acromegaly (p = 0.0025). There was a trend towards improved confidence levels to manage Cushing's disease and macroprolactinoma. In diabetes session, there was a significant improvement in trainees' confidence to interpret continuous glucose monitor readings (p = 0.01). There was a trend towards improvement for managing monogenic diabetes, hypoglycaemic unawareness and interpreting Libre readings. Overall, there was a significant improvement in trainees' confidence in managing cases that were discussed post-simulation.
CONCLUSION CONCLUSIONS
SIMBA is an effective learning model to improve trainees' confidence to manage various diabetes and endocrine case scenarios. More sessions with a variety of other speciality case scenarios are needed to further assess SIMBA's effectiveness and application in other areas of medical training.

Identifiants

pubmed: 32811488
doi: 10.1186/s12909-020-02190-6
pii: 10.1186/s12909-020-02190-6
pmc: PMC7437058
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

274

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Auteurs

Eka Melson (E)

Institute of Metabolism and Systems Research, University of Birmingham, Birmingham, UK.
University Hospitals Birmingham NHS Foundation Trust, Birmingham, UK.

Meri Davitadze (M)

Clinic "Cardio", Tbilisi, Georgia.
Georgian-American Family Medicine Clinic "Medical House", Tbilisi, Georgia.

Manal Aftab (M)

University Hospitals Birmingham NHS Foundation Trust, Birmingham, UK.

Cai Ying Ng (CY)

RCSI & UCD Malaysia Campus, George Town, Malaysia.

Emma Ooi (E)

RCSI & UCD Malaysia Campus, George Town, Malaysia.

Parisha Blaggan (P)

University of Birmingham Medical School, Birmingham, UK.

Wentin Chen (W)

University of Birmingham Medical School, Birmingham, UK.

Thia Hanania (T)

University of Birmingham Medical School, Birmingham, UK.

Lucretia Thomas (L)

University of Birmingham Medical School, Birmingham, UK.

Dengyi Zhou (D)

University of Birmingham Medical School, Birmingham, UK.

Joht Singh Chandan (JS)

Institute of Applied Health Research, University of Birmingham, Birmingham, UK.

Latha Senthil (L)

University Hospitals Birmingham NHS Foundation Trust, Birmingham, UK.

Wiebke Arlt (W)

Institute of Metabolism and Systems Research, University of Birmingham, Birmingham, UK.
University Hospitals Birmingham NHS Foundation Trust, Birmingham, UK.

Sailesh Sankar (S)

Diabetes and Endocrinology Specialist Training Committee, Health Education West Midlands, Birmingham, UK.

John Ayuk (J)

University Hospitals Birmingham NHS Foundation Trust, Birmingham, UK.

Muhammad Ali Karamat (MA)

Diabetes and Endocrinology Specialist Training Committee, Health Education West Midlands, Birmingham, UK.

Punith Kempegowda (P)

Institute of Metabolism and Systems Research, University of Birmingham, Birmingham, UK. p.kempegowda@bham.ac.uk.
University Hospitals Birmingham NHS Foundation Trust, Birmingham, UK. p.kempegowda@bham.ac.uk.

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Classifications MeSH