1. How we developed an effective e-learning module for medical students on using professional interpreters
- Author
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Umar Z. Ikram, Marie-Louise Essink-Bot, Jeanine Suurmond, Public and occupational health, and Amsterdam Public Health
- Subjects
Male ,Students, Medical ,E-learning (theory) ,education ,Language barrier ,Multilingualism ,computer.software_genre ,Education ,Education, Distance ,Nursing ,Health care ,Humans ,Medicine ,Cultural Competency ,Self-efficacy ,Internet ,Physician-Patient Relations ,business.industry ,Communication Barriers ,General Medicine ,Translating ,Self Efficacy ,Knowledge ,Vignette ,Female ,business ,Cultural competence ,computer ,Interpreter - Abstract
Language barriers may lead to poorer healthcare services for patients who do not speak the same language as their care provider. Despite the benefits of professional interpreters, care providers tend to underuse professional interpretation. Evidence suggests that students who received training on language barriers and interpreter use are more likely to utilize interpretation services. We developed an e-learning module for medical students on using professional interpreters during the medical interview, and evaluated its effects on students' knowledge and self-efficacy. In the e-learning module, three patient-physician-interpreter video vignettes were presented, with three different types of interpreters: a family member, an untrained bilingual staff member, and a professional interpreter. The students answered two questions about each vignette, followed by feedback which compared their responses with expert information. In total, 281 fourth-year medical students took the e-learning module during the academic year 2012-2013. We assessed their knowledge and self-efficacy in interpreter use pre- and post-test on 1 (lowest)-10 (highest) scale, and analysed the differences in mean scores using paired t-tests. Upon completing the e-learning module, students reported higher self-efficacy in using professional interpretation. The mean knowledge score on the pre-test was 5.5 (95% confidence interval 5.3-5.8), but on the post-test this increased to 8.4 (95% CI 8.2-8.6). The difference was highly significant (p
- Published
- 2014