In Collabra: Psychology ist ein neuer Artikel aus der Arbeitsgruppe erschienen:
García Alanis, J. C., Strelow, A. E., Dort, M., Christiansen, H., Pinquart, M., & Panitz, C. (2023). Expectation violations, expectation change, and expectation persistence: The scientific landscape as revealed by bibliometric network analyses. Collabra: Psychology, 9(1), 73830. https://doi.org/10.1525/collabra.73830
Abstract: Expectation violations occur when there is a discrepancy between expected and perceived events or experiences. Often, however, expectations persist despite disconfirming evidence. Therefore, research on expectation violations, expectation change, and expectation persistence has been conducted in several fields of psychology with wide-ranging theoretical assumptions and empirical considerations. In the present review, we analysed how these research fields relate to each other using bibliometric network analyses. For this purpose, we conducted a systematic literature search to identify scientific publications on expectation violations, expectation change, and expectation persistence. The literature corpus was then quantitatively analysed using similarity measures that allow a data-driven classification of publications into groups, revealing their conceptual, theoretical, and empirical commonalities. Our results indicate that many influential publications have focused on finding reactivity measures (e.g., brain activation) to the discrepancy experienced between expectations and outcomes. Furthermore, these measures have been used to assess when and to which degree learning and behavioural adaptation (i.e., expectation change) take place. We discuss the potential application of these measures for understanding expectation violations, expectation change, and expectation persistence in more complex settings (e.g., social interaction). The goal of this review was to foster interdisciplinarity in psychology, enabling scientists and practitioners to identify new topics, promising empirical approaches, and previously neglected variables.