Novel computational algorithms to index lexical markers of psychological distancing and their relationship to emotion regulation efficacy over time.

ABSTRACT: The degree to which one employs an objective or spatially/temporally distant perspective via language, i.e., linguistic distancing, has previously been shown to be positively associated with well-being. We sought to further elucidate relationships among language and emotion over time as a function of the implementation of sub-tactics of psychological distancing. In Study 1, we developed novel deep machine learning algorithms to identify the degree to which linguistic patterns reflect two types of psychological distancing, namely objective (OBJ) and spatial/temporal (FAR) distancing. In Study 2, in an expressive writing-based longitudinal emotion regulation training task, participants transcribed their thoughts while viewing negative or neutral stimuli over 5 sessions in one of three ways:

SUBMITTER: Shahane AD 

PROVIDER: S-EPMC9053392 | biostudies-literature | 2021 Sep

REPOSITORIES: biostudies-literature