Department of ­Psychology: Research Unit 04

1. Description and Explanation of Inter-Individual Differences and Social Inequality

Our research unit is fundamentally concerned with the description and assessment of personality differences against the background of a complex, systemic and dynamic understanding of personality with its (A) affective, (B) behavioural, (C) cognitive and (D) dynamic-motivational components. Regarding description, accurate personality measurement is very important. The consistency and specificity of different measurement methods (e.g. self-assessment, assessments by acquaintances and tests) play a major role here. Against this background, broad personality dimensions, socio-political orientations and attitudes, values and morality, interests, competences and also individual self-concepts of people are examined with regard to their biological factors (e.g. genome and epigenome) on the one hand and their malleability by situational factors (e.g. life events) and contexts (e.g. important reference persons) on the other. In addition, the significance of these inter-individual differences for social inequality and well-being will be analysed.

2. Patterns and Sources of Personality Development across the Lifespan

Our research unit looks at the entire lifespan and analyses how personality characteristics develop in different phases of life. The focus here is on how genetic and environmental factors and their complex interaction and transaction can explain developmental patterns. Accurate measures of individual characteristics and environments also play a major role here. On this basis, we investigate when, how and why personality differences between people develop, reduce, stabilise and also destabilise. These patterns and their underlying sources are also analysed with regard to their significance for health in different age groups.

3. Modelling and Analysis of Complex Longitudinal and Family Data

In order to address the main research areas outlined above, complex research designs need to be realised (e.g. twin family and longitudinal designs) and complex data collected (e.g. multi-method data, biological markers and accurate environmental measures). To analyse these multimodal data, we use a comprehensive quantitative-methodological know-how. The spectrum of the working group includes structural equation and multi-level modelling as well as analytical methods for deriving (quasi-)causal inference. This third research area thus forms the methodological foundation for the other main research areas.