Publication details
The structure and dynamics of client session reactions: A longitudinal network analysis
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| Year of publication | 2022 |
| Type | Appeared in Conference without Proceedings |
| MU Faculty or unit | |
| Citation | |
| Description | Objective: Understanding complex relationships among various aspects of clients’ session experience is essential for effective therapy. This study aimed to test the feasibility of applying longitudinal network modeling to understand the structure and dynamics of clients’ session reactions. Method: Data from three samples were combined (two general outpatient samples of emotion-focused therapy (EFT) and one study comparing EFT and cognitive-behavioral therapy for trauma). One hundred and twenty-three psychotherapy clients answered the Revised Session Reactions Scale after every session. Data collected after sessions 2 to 5 (413 observations) were used to fit a lag-1 dynamic latent variable model for panel data. The temporal, contemporaneous, and between-person networks were obtained and analyzed exploratively. Data from session 1 and sessions 6+ could not be used due to the nonstationarity of model parameters and low sample size. Results: Session reactions that played the most central role in the temporal prediction of other reactions included distancing from one’s thoughts, feelings, or memories and new discoveries related to the self. Both types of experience predicted, among others, the therapeutic relationship and a sense of relief. Feeling involved in therapy had a marginal role in the network. Conclusions: Longitudinal network modeling proved to be a promising approach to exploring clients’ session experience and, in a broader sense, to the analysis of psychotherapy process data. It yielded innovative and clinically meaningful findings of the interrelatedness of complex session-by-session processes. |
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