AI Article Synopsis
- - Kalisch and colleagues discuss coping potential (CP) as a key resilience mechanism when dealing with events.
- - The authors examine how generative implicit CP self-models develop during "resting-state," which occurs before and after events.
- - This resting-state allows for Bayesian learning, enabling individuals to update their CP self-models, influencing how they assess situations and their perceived resilience.
Article Abstract
Kalisch and colleagues highlight coping potential (CP) as a principle resilience mechanism during event engagement. We complement this discussion by exploring generative implicit CP self-models, arguably emerging during "resting-state," subsequent and prior to events. Resting-state affords a propitious environment for Bayesian learning, wherein appraisals/reappraisals may update active inferential CP self-models, which then mediate appraisal style organization and resilience factor valuation.
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| http://dx.doi.org/10.1017/S0140525X14001642 | DOI Listing |
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