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Stress Generation in Social Anxiety: A Longitudinal Study of the Role of Post-Event Processing.

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Title: Stress Generation in Social Anxiety: A Longitudinal Study of the Role of Post-Event Processing.
Authors: Moriishi, Chihiro (AUTHOR), Maeda, Shunta (AUTHOR)
Source: Cognitive Therapy & Research. Jun2025, Vol. 49 Issue 3, p631-639. 9p.
Subjects: Life change events, Cognitive psychology, Age groups, Mental depression, Clinical psychology, Social anxiety
Abstract: Background: Individuals with social anxiety experience a larger number of negative life events. However, studies applying the stress generation model to social anxiety are limited, and factors predicting stress generation have not been adequately examined. This study examined whether post-event processing (PEP) predicted stress generation in social anxiety. Methods: Five hundred students participated in the survey. The survey was conducted at two time points (T1 and T2), collecting data regarding PEP, negative life events (negative interpersonal dependent events, negative non-interpersonal dependent events, and negative independent events), social anxiety symptoms, and depressive symptoms. Results: PEP measured at T1 did not significantly predict the experience of negative dependent events at T2. Social anxiety symptoms did not predict the experience of negative interpersonal dependent events, while depressive symptoms predicted the experience of all negative life events. Conclusions: PEP may not be a predictor of stress generation in social anxiety. The influence of depressive symptoms should be considered in the stress generation model. [ABSTRACT FROM AUTHOR]
Copyright of Cognitive Therapy & Research is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Psychology and Behavioral Sciences Collection
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  Data: <searchLink fieldCode="AR" term="%22Moriishi%2C+Chihiro%22">Moriishi, Chihiro</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Maeda%2C+Shunta%22">Maeda, Shunta</searchLink> (AUTHOR)
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  Data: <searchLink fieldCode="JN" term="%22Cognitive+Therapy+%26+Research%22">Cognitive Therapy & Research</searchLink>. Jun2025, Vol. 49 Issue 3, p631-639. 9p.
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  Data: Background: Individuals with social anxiety experience a larger number of negative life events. However, studies applying the stress generation model to social anxiety are limited, and factors predicting stress generation have not been adequately examined. This study examined whether post-event processing (PEP) predicted stress generation in social anxiety. Methods: Five hundred students participated in the survey. The survey was conducted at two time points (T1 and T2), collecting data regarding PEP, negative life events (negative interpersonal dependent events, negative non-interpersonal dependent events, and negative independent events), social anxiety symptoms, and depressive symptoms. Results: PEP measured at T1 did not significantly predict the experience of negative dependent events at T2. Social anxiety symptoms did not predict the experience of negative interpersonal dependent events, while depressive symptoms predicted the experience of all negative life events. Conclusions: PEP may not be a predictor of stress generation in social anxiety. The influence of depressive symptoms should be considered in the stress generation model. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of Cognitive Therapy & Research is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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