Abstract

Psychotherapy outcome research mainly focuses on scale-level changes and constructs that were developed using cross-sectional statistical analysis, possibly concealing important findings on the level of single items, and limiting the clinical utility of outcome scales. Our goal was to explore changes in symptoms, interpersonal problems, and level of functioning in everyday life and to establish groups of items with similar rates of change that could be used to form more coherent targets for measuring different therapeutic outcomes. Triangulated maximally filtered graphs were used to model the network structure of the Outcome Questionnaire-45 in a data set of N = 12,075 university counseling center patients. Dynamic exploratory graph analysis was used to establish communities of items with similar rates of change. Five item communities (anxiety, hopelessness, interpersonal problems, well-being, and work impairment) were found. Compared to the original Outcome Questionnaire-45 subscales, they showed better fit to the data. The "hopelessness" community, which describes the extent of a patient's demoralization before the start of therapy, had a significantly higher rate of change compared to other communities. The discerned item communities provide clinicians with theoretically grounded, precise targets for outcome tracking, thereby enhancing the responsiveness and adaptability of treatment interventions to individual client trajectories. Such granularity enriches our understanding of therapeutic change, with direct implications for tailoring intervention strategies to maximize early therapeutic gains and sustain long-term recovery. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

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