Document Type


Journal/Book Title/Conference

Journal of Contextual Behavioral Science

Author ORCID Identifier

Korena S. Klimczak

Janice L. Snow




Elsevier BV

Publication Date


First Page


Last Page


Creative Commons License

Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.


An individual's trait-like thoughts, feelings, and behaviors are characteristic patterns that occur across time, whereas state-like iterations of these variables are isolated to specific moments in time. Although highly correlated, variables at the trait and state levels measure different phenomena and should be examined separately. In this longitudinal study, we examine the disaggregation of trait and state-level psychological inflexibility among college students. Specifically, we investigated which psychological inflexibility subprocess would significantly predict positive affect, negative affect, and meaningful activity, both at the trait and state-levels. In addition to pre- and post-assessments, participants (n = 168) completed ecological momentary assessment (EMA) surveys (n = 2251) assessing each of these variables via text message three times per day over the course of a week. Results suggested that while a greater number of state-like subprocesses significantly predict negative affect, positive affect, and meaningful activity, trait-like subprocesses hold more weight. Dominance analyses showed trait-level inaction to be the most important predictor for positive and negative affect, and trait-level of lack of contact with values to be the most important predictor for meaningful activity. Differentiating trait and state variables can enable contextual behavioral scientists to better understand pathological and therapeutic processes of change.

Available for download on Tuesday, July 01, 2025