The traits as situational sensitivities (TASS) model: a more accurate way to predict behavior

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The traits as situational sensitivities (TASS) model: a more accurate way to predict behavior

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Title: The traits as situational sensitivities (TASS) model: a more accurate way to predict behavior
Author: Marshall, Margaret A
Abstract: Interactionist models of human behavior assume that person and situation variables combine to produce behavior. This dissertation presents the traits as situational sensitivities (TASS) model, an interactionist model positing that traits function in a threshold-like manner, as sensitivities to situational strength or provocation. According to the TASS model, individuals high in a trait will manifest a relevant behavior at a lower level of situational strength than will those low in a trait. Weak and strong situations are hypothesized to elicit minimal trait differences, whereas situations of medium strength are hypothesized to elicit large trait differences in behavior. Four studies were conducted to test the TASS model. Study I examined the trait of social anxiety and confirmed the model's predictions. Scores on a trait measure correlated most highly with subsequent emotional responses in medium strength conditions. Study 2 generalized these findings to the trait of hostility, and used a behavioral dependent measure in addition to self-report of emotion. Once again, trait scores on hostility correlated highly with later behavior, but only under medium strength conditions. Study 3 examined the role of participants' subjective interpretations as a possible underlying mechanism for the observed trait differences in Study 2. Study 4 tested the TASS model using implicit and explicit measures of prejudicial attitudes. Participants' scores on an explicit measure of prejudice best predicted later discrimination against a racial minority when the participants were under conditions of medium strength. In sum, the TASS model elucidates when and why traits will manifest themselves in behavior.
Description: Thesis (Ph. D.)--University of Washington, 2002
URI: http://hdl.handle.net/1773/8991

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