Within‐ and between therapist variability in movement and physiological synchrony and its effects on symptom change
Year: 2024
Type: article
Abstract: The predictive power of movement and electrodermal activity (EDA) synchrony has been demonstrated in various studies. Although most studies have examined each synchrony modality separately, a growing interest in the simultaneous investigation of multiple modalities has emerged. Previous research has demonstrated the importance of disentangling within and between-dyad effects, however within and between-therapist effects have yet to be investigated. The aim of the present study was to test whether movement and EDA synchrony (measured both within and between therapists) predict across-session symptom change in two types of interventions (emotion-focused vs. cognitive). The results are based on 990 session segments of 90 clients with test anxiety who were treated with a six-session treatment program by 22 therapists, treating 3-15 clients each. Movement synchrony (on the basis of motion energy analysis (MEA) values) and EDA synchrony were quantified using cross-correlations. Symptom severity was assessed before each session using the state test anxiety measure. Movement and EDA synchrony correlated negatively (-0.19, p < .001). Moreover, higher movement synchrony as well as an interaction between movement and EDA synchrony was significantly associated with symptom improvement within, but not between therapists. In addition, an interaction between EDA synchrony and cognitive (versus emotion-focused) interventions was significantly associated with symptom improvement. These results provide initial evidence that therapists' average levels of synchrony may matter less than how synchronous they are with a specific client.
Source: Psychophysiology
DOI: 10.1111/psyp.14742
Institutions: Universität Trier, MSB Medical School Berlin, Bar-Ilan University
Language: English
Subfield: Clinical Psychology
Field: Psychology
Domain: Social Sciences
Open Access status: hybrid
Estimated APC paid: $4,020
Funder: Deutsche Forschungsgemeinschaft
Awards: TherapAI Analyse des nonverbalen Emotionsausdrucks in der Psychotherapie mittels künstlicher Intelligenz, Eine interkulturelle EMA Studie zur Vorhersage von Therapieerfolg und abbruch mit digitalen, affektiven und interpersonellen Indikatoren bei Patienten mit einer depressiven Störung, Prospektiv randomisiert kontrollierte Studie zur Entwicklung und Evaluation personalisierter Vorhersagen von frühen Behandlungsstrategien in der ambulanten Psychotherapie depressiver Störungen
OpenAlex ID: W4405561428