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Movement-based patient-therapist attunement in psychological therapy and its association with early change

  • Objective: Attunement is a novel measure of nonverbal synchrony reflecting the duration of the present moment shared by two interaction partners. This study examined its association with early change in outpatient psychotherapy. Methods: Automated video analysis based on motion energy analysis (MEA) and cross-correlation of the movement time-series of patient and therapist was conducted to calculate movement synchrony for N = 161 outpatients. Movement-based attunement was defined as the range of connected time lags with significant synchrony. Latent change classes in the HSCL-11 were identified with growth mixture modeling (GMM) and predicted by pre-treatment covariates and attunement using multilevel multinomial regression. Results: GMM identified four latent classes: high impairment, no change (Class 1); high impairment, early response (Class 2); moderate impairment (Class 3); and low impairment (Class 4). Class 2 showed the strongest attunement, the largest early response, and the best outcome. Stronger attunement was associated with a higher likelihood of membership in Class 2 (b = 0.313, p = .007), Class 3 (b = 0.251, p = .033), and Class 4 (b = 0.275, p = .043) compared to Class 1. For highly impaired patients, the probability of no early change (Class 1) decreased and the probability of early response (Class 2) increased as a function of attunement. Conclusions: Among patients with high impairment, stronger patient-therapist attunement was associated with early response, which predicted a better treatment outcome. Video-based assessment of attunement might provide new information for therapists not available from self-report questionnaires and support therapists in their clinical decision-making.

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Metadaten
Verfasserangaben:Brian SchwartzORCiD, Julian A. Rubel, Anne-Katharina Deisenhofer, Wolfgang Lutz
URN:urn:nbn:de:hbz:385-1-20246
DOI:https://doi.org/10.1177/20552076221129098
Titel des übergeordneten Werkes (Englisch):Digital Health
Verlag:SAGE Publishing
Dokumentart:Wissenschaftlicher Artikel
Sprache:Englisch
Datum der Fertigstellung:27.09.2022
Datum der Veröffentlichung:27.09.2022
Veröffentlichende Institution:Universität Trier
Beteiligte Körperschaft:The publication was funded by the Open Access Fund of Universität Trier and the German Research Foundation (DFG)
Datum der Freischaltung:16.05.2023
Freies Schlagwort / Tag:Motor mimicry; early response; growth mixture modeling; motion energy analysis; nonverbal synchrony
Jahrgang:2022
Ausgabe / Heft:Band 8
Seitenzahl:17
Institute:Fachbereich 1 / Psychologie
DDC-Klassifikation:1 Philosophie und Psychologie / 15 Psychologie / 150 Psychologie
Lizenz (Deutsch):License LogoCC BY-NC: Creative-Commons-Lizenz 4.0 International

$Rev: 13581 $