Rural doctor quota students in Germany - who are they? Data on first year students from two cohorts in the federal state of Saxony.

The lack of physicians in rural areas is a universal problem. To increase the attractiveness of rural practice for medical students, the contribution of medical schools is undisputed. However, much of the evidence on interventions before and during undergraduate education comes from countries with large areas and low population density like Australia and Canada. In Germany, selective admission to medical studies for students who agree to become rural general practitioners is still a new concept. The aim of this study was to assess the sociodemographic characteristics, attitudes and career aspirations of the rural doctor quota students from one medical school in Germany compared to their non-quota counterparts. For this cross-sectional study, a paper-based anonymous questionnaire was distributed to all first year medical students at Leipzig University in two consecutive study years.Descriptive analyses and group differences were calculated using SPSS. The response rate was 87.3% with  = 604 completed questionnaires and 40 (6.6%) students self-classified as rural doctor quota students. Quota students grew up in rural areas significantly more often than their counterparts and had more working experience in the medical field. General practice was the preferred career option for 64.1% (25/39, versus 2.7% [15/549] of non-quota students). Working self-employed in one's own medical practice was the preferred option for 71.1% (27/38) of quota students (vs. 28.0% [153/546] of non-quota students). Quota students valued a broad spectrum of patients, a long-term doctor-patient relationship, employee management and prestige more highly than their fellow students. Students from the rural doctor quota largely exhibit characteristics and attitudes that are compatible with future rural practice, despite showing little differences in sociodemographic items such as age and marital status. Not all students agree with the program objective. To demonstrate an impact on the health services, longitudinal data is necessary to monitor career choices over time.