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Flexible diagnosticity in person impression formation: an integrative framework

In person impression formation, target characteristics such as suitability for a vacant position or interpersonal likeability are inferred from information samples. This process strongly depends on the diagnosticity of observed (i.e., sampled) behaviors. Applying a likelihood-based conceptualization...

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Bibliographic Details
Main Authors: Ziegler, Johannes (Author) , McCaughey, Linda (Author) , Fiedler, Klaus (Author)
Format: Article (Journal)
Language:English
Published: January 8, 2026
In: Personality and social psychology bulletin
Year: 2026, Pages: 1-20
ISSN:1552-7433
DOI:10.1177/01461672251405990
Online Access:Verlag, kostenfrei, Volltext: https://doi.org/10.1177/01461672251405990
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Author Notes:Johannes Ziegler, Linda McCaughey, and Klaus Fiedler

MARC

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520 |a In person impression formation, target characteristics such as suitability for a vacant position or interpersonal likeability are inferred from information samples. This process strongly depends on the diagnosticity of observed (i.e., sampled) behaviors. Applying a likelihood-based conceptualization of diagnosticity, we tested two major implications: First, diagnosticity depends on the hypothesis being tested, and second, it is shaped by situational base-rates. We examined both facets by manipulating the extent of positive versus negative valence within the big two (agency vs. communion). In Experiment 1, we varied the hypothesis to be tested by providing different job profiles in a personnel selection task. Consistent with the predictions, hypothesis-relevant information impacted both sampling and judgment behavior more than hypothesis-irrelevant information. In Experiments 2A and 2B, we manipulated big-two specific valence base-rate expectations on target persons characterized as psychotherapy patients: Genuinely diagnostic violations of group-based expectancies turned out to result in strongest judgments. The findings suggest that participants’ sampling patterns and judgments follow the proposed likelihood-based diagnosticity concept. 
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