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Gesundheitswesen. 2012 Jul;74(7):426-34. doi: 10.1055/s-0031-1280845. Epub 2011 Jul 27.

[Development, factor-analytical control and psychometric evaluation of a questionnaire on specialty choices among medical students].

[Article in German]

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Abteilung Allgemeinmedizin und Versorgungsforschung, Universitätsklinikum Heidelberg.



A questionnaire was developed and validated which assesses factors influencing career choices of medical students and their perception of possibilities in general practice.


The first questionnaire version, which was developed based on a systematic literature review, was checked for comprehensibility and redundancy using concurrent think aloud. The revised version was filled out by a pilot sample of medical students and the factor structure was assessed using principal component analysis (PCA). The final version was filled out in an online survey by medical students of all 5 Medical Faculties in the federal state of Baden-Wuerttemberg. The factor structure was validated with a confirmatory factor analysis (CFA). Reliability was assessed as internal consistency using Cronbach's α.


The questionnaire comprises 2 parts: ratings of (A) the individual importance and of (B) the possibilities in general practice on 5-point scales. The first version comprising 118 items was shortened to 63 items after conducting interviews using concurrent think aloud. A further 3 items giving no information were removed after piloting the questionnaire on 179 students. The 27 items of part A were structured in 7 factors (PCA): image, personal ambition, patient orientation, work-life balance, future perspectives, job-related ambition, and variety in job. This structure had a critical fit in the CFA applied to the final version filled out by 1 299 students. Internal consistency of the factors was satisfactory to very good (Cronbach's α=0.55-0.81).


The questionnaire showed good psychometric properties. Further, not assessed factors influence career choice resulting in unexplained variance in our dataset and the critical fit of the model.

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