Longitudinal associations between psychological flexibility and inflexibility dimensions: A cross-lagged panel network analysis

IF 3.4 3区 心理学 Q1 PSYCHOLOGY, CLINICAL
Wei (Gabriel) Qi , Jie Wen , Zhiwei Zhou, Miao Miao
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引用次数: 0

Abstract

Psychological flexibility (PF) and psychological inflexibility (PI) are two contrasting concepts central in acceptance and commitment therapy. The multidimensional psychological flexibility inventory (MPFI) could comprehensively assess the 12 factors of PF and PI, thus providing a measure to examine their internal relationships. In the current study, we used the cross-lagged panel network approach to explore the longitudinal associations between the 12 PF/PI components. A sample of 447 Chinese adults (mean age = 31.19, SD = 6.41) completed an online survey at two timepoints. The cross-sectional network revealed the central roles of self-as-context, defusion, fusion and experiential avoidance. The cross-lagged panel network revealed that fusion, committed action, and self-as-context were influential nodes on other dimensions, whereas inaction and defusion had high levels of predictability. The current findings shed new light on the internal structure of the PF/PI components, and elucidated nodes that were central in the cross-sectional status and longitudinal changes. The identified nodes may help inform clinicians of potential loci for intervention, and clarify the theoretical connections within the complex network of psychological flexibility processes.
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来源期刊
CiteScore
8.50
自引率
18.00%
发文量
82
审稿时长
61 days
期刊介绍: The Journal of Contextual Behavioral Science is the official journal of the Association for Contextual Behavioral Science (ACBS). Contextual Behavioral Science is a systematic and pragmatic approach to the understanding of behavior, the solution of human problems, and the promotion of human growth and development. Contextual Behavioral Science uses functional principles and theories to analyze and modify action embedded in its historical and situational context. The goal is to predict and influence behavior, with precision, scope, and depth, across all behavioral domains and all levels of analysis, so as to help create a behavioral science that is more adequate to the challenge of the human condition.
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