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Research
Research focuses
1. Description and Explanation of individual Differences and Social Inequality
This lab concerns itself generally with the description and measurement of personality differences against the background of a complex, systemic, and dynamic understanding of personality with its (A) affective, (B) behavioral, (C) cognitive, and (D) dynamic-motivational components. Psychological diagnostics place great value on accurate measurements of personality. The agreement and the specificity of different diagnostic methods (e.g. self- or external reports) is of great importance. In the context of explanation, global personality dimensions, socio-political orientations and preferences, values and morality, interests, competencies, as well as individual self-concepts of people are researched regarding their genetic factors and biological correlates (e.g. hormones) on the one hand and their potential malleability through environmental factors (e.g. life events) and contexts (e.g. family and peer groups) on the other hand. In addition, the impact of these inter-individual differences on social inequality and well-being is one major focus.
2. Patterns and Sources of Personality Development across the Lifespan
This department is focused on the entire life span and investigates how personality characteristics develop during different stages of life. The major goal is to explain the developmental patterns with genetic, biological, and environmental factors, and their complex interactions. Here, accurate operationalization of individual particularities and environments plays an important role. On this basis, it is researched when, how, and why differences in personality unfold between people, are reduced, stabilized, or destabilized. These patterns and their sources are also being investigated regarding their influence on health in different age groups.
3. Modeling and Analysis of Complex Longitudinal and Relationship-Data
In order to realize the research aims formulated above, complex research designs have to be used (e.g. paired dyad- twin family- and longitudinal designs), and a multitude of different data sources (e.g. multi-method-data, biological markers, and accurate environmental measures). To analyze this multi-modal data, we utilize a comprehensive quantitative-methodical know-how. The spectrum of the department includes, among others, structural equation and multi-level modeling, as well as methods for analyzing (quasi-)causal inference. As such, this third focus represents the methodological foundation of the other research foci.