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.
Verfasserangaben: | Brian SchwartzORCiD, Julian A. Rubel, Anne-Katharina Deisenhofer, Wolfgang Lutz |
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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): | CC BY-NC: Creative-Commons-Lizenz 4.0 International |