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Motivational factors influencing student intentions to practise in underserved areas
Author(s) -
Abbiati Milena,
Savoldelli Georges L.,
Baroffio Anne,
Bajwa Nadia M.
Publication year - 2020
Publication title -
medical education
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.776
H-Index - 138
eISSN - 1365-2923
pISSN - 0308-0110
DOI - 10.1111/medu.14063
Subject(s) - specialty , psychology , enthusiasm , context (archaeology) , workforce , varimax rotation , medical education , variety (cybernetics) , logistic regression , social psychology , medicine , clinical psychology , psychometrics , biology , paleontology , cronbach's alpha , artificial intelligence , psychiatry , computer science , economics , economic growth
Context Exploring student intentions to practise in underserved areas (UAs) is necessary to inform the planning and training of the future medical workforce in order to increase effectiveness and fulfil societal needs. However, little is known about the motivational factors influencing these intentions. This paper explores medical students’ intentions to practise in UAs and the motivational factors predicting these intentions. Methods Eligible participants included graduating medical students from four of the five Swiss medical schools, who self‐reported specialty choice, intentions to practise in UAs, and motives that explained their career choices. Chi‐squared analysis was used to compare site, gender, specialty choice and UA practice intention. Motives were aggregated to obtain motivational factors using a principal component analysis with varimax rotation. Logistic regression was used to predict the effects of these motivational factors and of gender on UA practice intention. Results Of 1749 students included in the study, 240 (13.7%) expressed an intention to practise in UAs (62.1% of whom intended to practise in rural areas) and 719 (41.1%) were undecided. In those who wished to practise in UAs, general practice (21.6%) was the most preferred specialty. Motivational factors influencing specialty choice were intellectual challenge, work variety, work conditions and enthusiasm (Kaiser‐Meyer‐Olkin index 0.79, P < .001, 49.0% of variance explained). Students motivated by work variety (odds ratio [OR] 1.4, 95% confidence interval [CI] 1.2‐1.7) and by work conditions (OR 1.3, 95% CI 1.1‐1.6) were more likely to choose UAs and those motivated by intellectual challenge (OR 0.4, 95% CI 0.3‐0.5) were less likely. Undecided students’ motivations were very similar to those of students interested in working in UAs. Conclusions The actual number of Swiss students interested in working in UAs is low and is probably insufficient to meet current societal needs. Work variety and work conditions appear to be factors that might attract interested and undecided students towards working in UAs.