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Individual life courses in modern societies are shaped by a high degree of spatial mobility. Given the societal and individual importance, research has already intensively addressed the individual effects of spatial mobility and the resulting social inequalities. However, previous research has mainly focused on the study of employment-related outcomes (for example income or occupational position). This focus may be too narrow, because human behaviour is not only aimed at employment-related outcomes, but ultimately at improving one's own quality of life. Accordingly, it is necessary to focus more on aspects of subjective quality of life in migration research. This focus allows answers to the questions of how individuals cope with spatial mobility and how subjective quality of life changes in an increasingly mobile society.
Against this background, the project funded by the German Research Foundation in cooperation with the German Centre for Higher Education Research and Science Studies is developing the first comprehensive analysis of the effects of socially relevant forms of spatial mobility (intra-German and international educational and labour mobility) on the subjective quality of life of trainees, students and various groups of employees. Quality of life is understood as a multidimensional construct that encompasses health-related quality of life (subjective physical and mental health) and subjective well-being (general life satisfaction). In addition, the extent to which the relationship between spatial mobility and quality of life is moderated by various characteristics, such as one's own level of education or social background, is analysed. Partnership dynamics that have been little analysed to date, such as the extent to which spatial mobility affects the subjective quality of life of cohabiting or immobile partners, will also be examined in more detail.
The basis is formed by various representative data sets (Socio-Economic Panel (SOEP), German Emigration and Remigration Panel (GERPS), National Educational Panel Study (NEPS), DZHW Promovierendepanel (NACAPS)), which are evaluated using methods of longitudinal data analysis (e.g. fixed effects panel regression models, growth curve models, sequence pattern analysis).
10/2023–09/2026
DFG in-kind grant