For two-group comparisons, tabulations and chi-square tests as well as t-tests were used. Analysis of variance (ANOVA) was used for simultaneously comparing graduated variables over all five fields of study. Personality related factors, such as SOC and CMQ, were defined as described in Buddeberg-Fischer et al. [26 (link)]. T-tests, confidence intervals, and Cohen’s effect size were used to assess the relative importance of the various factors influencing the choice of medical studies as opposed to other university majors. Chi2-test was used to examine gender differences.
We used content analysis, a qualitatively oriented category-guided text analysis, for the respondents’ electronic answers to the free-text question [27 (link), 37 ]. The two main steps of the content analysis were first, the development of a categorization frame with a code manual and determining operational definitions for each content category, and second, coding the text according to the categorization frame to the content categories.
For data analyses we used Stata Statistical Software: Release 16 (StataCorp, College Station, TX, USA) and IBM SPSS Statistics Version 25 (IBM Corp, Armonk, NY, USA). The significance level was set at 0.05, two-sided.
We used content analysis, a qualitatively oriented category-guided text analysis, for the respondents’ electronic answers to the free-text question [27 (link), 37 ]. The two main steps of the content analysis were first, the development of a categorization frame with a code manual and determining operational definitions for each content category, and second, coding the text according to the categorization frame to the content categories.
For data analyses we used Stata Statistical Software: Release 16 (StataCorp, College Station, TX, USA) and IBM SPSS Statistics Version 25 (IBM Corp, Armonk, NY, USA). The significance level was set at 0.05, two-sided.
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