Affect is a fundamental ingredient of the human mind. It informs us about important changes in our environment and influences social interactions. Affective states can also contribute to the development and maintenance of psychological diseases. Our current research focuses on affective dynamics and their underlying processes, and the determinants of these processes. To address our research questions, we use multiple methods such as experience-sampling and experiments.

Modeling Intraindividual Variability in Affect (MIVA) Project. Studying the ebb and flow of affect in daily life provides important insights into psychological functioning and well-being. The MIVA project ("Modeling Intraindividual Variability in Affect") aims at improving our understanding of why individuals show fluctuations in affect, and in explaining individual differences in the underlying processes that determine affective variability, with a particular focus on age group differences. Research in the MIVA project is based on a newly developed mathematical model that incorporates theoretical ideas about affect generation and regulation. Using this model, we address our research aim by combining different methodological approaches that mutually complement and inform each other. Computational methods provide insights into the model’s behavior and can link theoretically derived parameters to simulated affective fluctuations. Ambulatory assessment methodologies will allow us to measure affective processes as they naturally occur in the daily lives of adults from various age groups. Simulation studies and ambulatory assessments will be complemented with experimental paradigms assessing affective micro-processes in the laboratory.

Reference publications:

Wirth, M., Voss, A., Wirth, S., & Rothermund, K. (2022). Affect dynamics and well-being: Explanatory power of the model of intraindividual variability in affect (MIVA). Cognition and Emotion, 36(2), 188-210. doi:10.1080/02699931.2021.1993148

Project members

Dr. Maria Wirth (FSU Jena)

Prof. Dr. Klaus Rothermund (FSU Jena)

Collaborators

Prof. Dr. Michaela Riediger (FSU Jena)

Prof. Dr. Andreas Voß (Uni Heidelberg)

Social cognition is a broad area that uses experimental paradigms to study social phenomena, like discrimination (stereotypes and prejudice), attitude formation (evaluative learning), or other interactive behaviors (lying, discrimination). The aim of this research is to identify the underlying cognitive and affective processes and mechanisms of these phenomena. Our research is inspired by models and theories of propositional learning, action regulation, and memory, and we apply these approaches to advance our understanding of social attitudes and behavior.

Activation and Cognitive Representation of Stereotypes. According to Social Cognition textbooks, stereotypes become activated automatically whenever social category information becomes salient. This prevailing account, however, has been challenged by accumulating null-findings of stereotype activation effects of mere category primes. This raises the question of what else is needed to activate stereotypes apart from category information? In several priming studies, we tested the context-dependent account of stereotyping and found that situation-specific stereotypes only become activated in matching contexts (Casper et al., 2011). Based on the perspective of context-dependent stereotypes, we also investigate the relationship between implicit and explicit stereotypical beliefs, the behavioral effects of stereotypes, and processes of stereotype formation and acquisition.

Reference publications:

Casper, C., Rothermund, K., & Wentura, D. (2011). The activation of specific facets of age stereotypes depends on individuating information. Social Cognition, 29(4), 393-414. doi:10.1521/soco.2011.29.4.393

Huang, T., & Rothermund, K. (2022). Implicit and explicit age stereotypes assessed in the same contexts are still independent. Experimental Aging Research. Advance online publication. doi:10.1080/0361073X.2022.2039507

Project members

Tingting Huang (FSU Jena)

Prof. Dr. Klaus Rothermund (FSU Jena)

"Implicit Self-esteem." Individuals typically behave in a way that seems to imply a positive evaluation of themselves even when they are not asked to self-evaluate: They like their initials better than other letters, they have more positive reactions to their own face than other faces, they are better in associating themselves with "good" than "bad", and they spontaneously react with agreement to positive statements about themselves. It has been controversially discussed, whether these different phenomena can be understood as unspoken self-evaluations that are rooted in a common underlying construct with meaningful interindividual variance, namely "implicit self-esteem". In this project we try to further this discussion by eliminating methodological and conceptual problems of existing paradigms and introducing new paradigms that circumvent these problems. Investigating dissociations of these paradigms and self-reported self-esteem, we try to assess the validity and utility of the idea of "implicit self-esteem".

Reference publications:

Jusepeitis, A., & Rothermund, K. (2021). Mixed Evidence for Name Priming Effects as a Measure of Implicit Self-Esteem: A Conceptual Replication of Krause Et Al. (2012). Social Cognition, 39(5), 591–607. doi:10.1521/soco.2021.39.5.591

Jusepeitis, A., & Rothermund, K. (2022). No elephant in the room: The incremental validity of implicit self-esteem measures. Journal of Personality. Advance online publication. doi:10.1111/jopy.12705

Project members

Adrian Jusepeitis (FSU Jena)

Prof. Dr. Klaus Rothermund (FSU Jena)

Evaluative Learning. Attitudes, preferences and tastes have a strong influence on human behavior. In our research, we study when and how these evaluative tendencies are acquired and changed. To address these questions, we pursue an experimental approach in which a simple pairing procedure (the evaluative conditioning paradigm) is combined with a diverse set of experimental manipulations, measurement procedures (direct and indirect) and data analysis techniques (e.g., multinomial modeling). In our choice of research questions, designs and tools, we seek to integrate ideas from propositional models of (evaluative) learning with the tenets of episodic models of memory formation and retrieval.

Reference publications:

Bading, K., Stahl, C., & Rothermund, K. (2020). Why a standard IAT effect cannot provide evidence for association formation: The role of similarity construction. Cognition and Emotion, 34(1), 128-143. doi:10.1080/02699931.2019.1604322

Hütter, M., & Rothermund, K. (2020). Automatic processes in evaluative learning. Cognition and Emotion, 34(1), 1-20. doi:10.1080/02699931.2019.1709315

Project members

Dr. Karoline Bading (University of Tübingen)

Prof. Dr. Klaus Rothermund (FSU Jena)

Collaborators

Dr. Jérémy Bena (Catholic University of Louvain)

Implicit measures have been developed to investigate sources of behavior that are either inaccessible to individuals themselves, or that they try to conceal from others. Although these measures figure prominently in the literature on the implicit assessment of attitudes and stereotypes, methodological and theoretical caveats are abundant in this type of research. Our approach is to investigate the functioning of these measures, to develop improved variants of these measures that have better psychometric properties, and to develop new measures that can be used to indirectly assess important constructs relating to evaluation, motivation, and personal beliefs.

Reference publications:

Meissner, F., Grigutsch, L. A., Koranyi, N., Müller, F., & Rothermund, K. (2019). Predicting behavior with implicit measures: Disillusioning findings, reasonable explanations, and sophisticated solutions. Frontiers in Psychology, 10(2483). doi:10.3389/fpsyg.2019.02483

Rothermund, K., Grigutsch, L. A., Jusepeitis, A., Koranyi, N., Meissner, F., Müller, F., . . . Wentura, D. (2020). Research with implicit measures: Suggestions for a new agenda of sub-personal psychology. Social Cognition, 38, S243-S263. doi:10.1521/soco.2020.38.supp.s243

The Implicit Association Test. The Implicit Association Test (IAT) is the most prominent implicit measure. No other implicit measure has been the subject to such lively scientific and public debates, especially with regard to its usefulness for practical applications. Despite, or perhaps because of, its popularity, the IAT has been criticized in several ways: a) from a cognitive-process-oriented perspective, b) from a test-theoretical perspective, and c) from a content-conceptual perspective. Our research examines the IAT from these different perspectives and aims at developing solutions to the identified criticisms: ad a) we investigate the underlying processes in the IAT and disentangle as well as estimate the contributions of these processes using, for example, the ReAL model (Meissner & Rothermund, 2013); ad b) we apply psychometric insights from classical test theory to the study of the IAT and, in particular, investigate the concept of test difficulty, e.g. with regard to its usefulness in increasing the measured true score variance and thus the predictive validity of the IAT; ad c) we investigate psychological constructs that have received comparatively little attention in the IAT literature, such as motivational constructs, by developing new IAT measures, e.g. the Wanting IAT (Koranyi et al., 2017).

Reference publications:

Koranyi, N., Grigutsch, L. A., Algermissen, J., & Rothermund, K. (2017). Dissociating implicit wanting from implicit liking: Development and validation of the Wanting Implicit Association Test (W-IAT). Journal of Behavior Therapy and Experimental Psychiatry, 54, 165–169. doi:10.1016/j.jbtep.2016.08.008

Meissner, F., & Rothermund, K. (2013). Estimating the contributions of associations and recoding in the Implicit Association Test: The ReAL model for the IAT. Journal of Personality and Social Psychology, 104(1), 45-69.

Rothermund, K., & Wentura, D. (2004). Underlying processes in the Implicit Association Test (IAT): Dissociating salience from associations. Journal of Experimental Psychology: General, 133(2), 139-165. doi:10.1037/0096-3445.133.2.139

Project members

Merlin Urban (FSU Jena)

Prof. Dr. Klaus Rothermund (FSU Jena)

Collaborators

Prof. Dr. Tobias Koch (FSU Jena)

Dr. Franziska Meissner (University Hospital Jena)