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ORCID

https://orcid.org/0000-0001-5856-7059

Access Type

Open Access Thesis

Document Type

thesis

Embargo Period

8-1-2022

Degree Program

Psychology

Degree Type

Master of Science (M.S.)

Year Degree Awarded

2022

Month Degree Awarded

February

Abstract

Aim: Research on close relationships demonstrates that dyadic convergence, or two people becoming more concordant in their experiences and/or beliefs over time, is commonplace and adaptive. As psychotherapy involves a close relationship, patient–therapist convergence processes may influence treatment-specific outcomes. Although prior research supports that patients and therapists tend to converge on their alliance perspectives over time, which associates with subsequent patient improvement, no research has similarly examined belief convergence during therapy. Accordingly, this study focused on patient–therapist convergence in their outcome expectation (OE), a belief variable associated with patient improvement when measured from individual participant perspectives. I predicted both that significant OE convergence would occur and relate to better posttreatment outcome. Method: Data derived from a trial of naturalistic psychotherapy. Patients and therapists repeatedly rated their respective OE through treatment, and patients rated their symptom/functional outcomes at posttreatment. For dyads (N = 154) with the requisite OE data, I tested my questions using multilevel structural equation modeling. Results: There was no discernable OE convergence pattern over treatment (g100 = 0.02, SE = 0.04, p = .275) and OE convergence was unrelated to outcome at the between-dyad (b02k = 1.86, SD = 10.08, p = .406) and between-therapist (g002 = -0.06, SD = 3.54, p = .473) levels. However, higher early patient OE was significantly associated with better outcome at the between-dyad level (b05k = -0.04, SD = 0.01, p < .001). Discussion: Results suggest that OE may be more of a facilitative patient versus relational process factor.

DOI

https://doi.org/10.7275/26968030

First Advisor

Michael J. Constantino

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.

Available for download on Monday, August 01, 2022

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