Evidence map›Paper›PMID 38956587›Full record

ArticleBMC medical education2024

Assessing REflective simulation-based e-Training on motivational interviewing among multidisciplinary healthcare practitioners [RESeT-MI]: a mixed methods pilot study.

Angela Massouh, Nour Alayan, Mariam Shatila, Sarah Wehbeh

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Article in BMC medical education, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Angela MassouhAmerican University of Beirut School of Nursing, Beirut, Lebanon. angelamassouh@gmail.com.
Nour AlayanTurpanjian College of Health Sciences American University of Armenia, Yerevan, Armenia.
Mariam ShatilaAmerican University of Beirut Medical Center, Beirut, Lebanon.
Sarah WehbehAmerican University of Beirut School of Nursing, Beirut, Lebanon.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundMany health science curricula have integrated behavioral modification techniques in their plans. Motivational Interviewing is one such technique. Educational interventions to promote Motivational Interviewing have had limited success. Integrating simulation-based learning in health science curricula might offer a platform whereby students can train in well controlled environments with increased authenticity, provision of standardized experiences and the capacity for immediate feedback to participants. Using motivational interviewing as an exemplar, the purpose of this study was to assess the impact of a simulation-based reflective e-training program on knowledge, attitudes, and confidence in Motivational Interviewing among healthcare practitioners from diverse healthcare disciplines. A secondary aim was to explore whether self-reflection can promote reflective learning.

methodsThis was a mixed-method study design. Fifteen participants from different health disciplines were included in the quantitative phase of the study, the simulated interview, and the reflective assignments while five participated in the focus group. Pre and post tests were used to examine the effect of training on knowledge, attitudes, and confidence in Motivational Interviewing. Assessment of Motivational Interviewing Treatment Integrity [MITI] scores in a simulation-based scenario was used. A qualitative content analysis of a focus group provided a more in-depth understanding of the participants experiences. Excerpts from reflective assignments were analyzed using Transformative Learning Theory concepts.

resultsA Wilcoxon test showed that the training elicited a change in confidence in performing Motivational Interviewing [Z= -2.766, p = 0.006], median scores increased from 29 to 34. A quarter of technical scores and half of the relational scores indicated good competence. Participants reflected content transformation through feelings of empowerment and satisfaction when they were successful in engaging and motivating clients. Process transformation was evident in reflections on how to improve core skills specifically reflective listening. Reflections on Motivational Interviewing spirit related values showed premise transformation, which may indicate attitude changes.

conclusionA simulation-based e-training program on Motivational Interviewing represents an important educational modality for training in the health disciplines. Results of this study provide evidence supporting the integration of reflective simulation-based e-training into the education curricula of health disciplines in MI and beyond.

Indexed as

Motivational InterviewingSimulation TrainingAdultClinical CompetenceCurriculumFemaleFocus GroupsHealth Knowledge, Attitudes, PracticeHealth PersonnelHumansMalePilot ProjectsBlended EducationInterprofessional EducationReflective LearningSimulationTransformative Learning

Identifiers

PMID38956587
PMCPMC11218146

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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.