Assessing Nonverbal Interaction Dynamics in Therapeutic Relationships: a Proof-of-Concept Study using Motion Energy Analysis and Nonlinear Time-Series Analysis.

Authors

Janna van de Pol, Anna M T Bosman, Maarten L Wijnants, Chijs van Nieuwenhuizen

Published in

Nonlinear dynamics, psychology, and life sciences. Volume 30. Issue 4. Pages 459-483.

Abstract

This study examined nonverbal synchronization as a means of assessing relational processes within forensic youth psychiatry. The primary aim was to explore whether Movement Energy Analysis (MEA) combined with Cross-Recurrence Quantification Analysis (CRQA) can provide clinically meaningful insight into therapist-client interaction dynamics and potentially inform clinical supervision. We investigated synchronized bodily movement in two therapeutic relationships involving the same client: one with a key worker and one with a process supporter, whose roles imply distinct therapeutic behaviors. We examined whether nonverbal synchrony emerged over time, differed between the two therapeutic relationships, and showed leading-following patterns. Greater synchrony was expected in the process supporter-client relationship and more leading behavior in the key worker-client relationship. A single-case design was used. The client engaged in separate care-as-usual therapeutic sessions with each therapist. Bodily movement was extracted from video recordings using MEA, and CRQA assessed nonverbal synchrony and temporal coordination. Surrogate analyses indicated that the observed synchrony exceeded levels expected from chance temporal associations. Synchrony was also greater in the process supporter-client relationship than in the key worker-client relationship. No consistent leading or following behavior was observed. These findings illustrate the potential of nonlinear methods to capture dynamic relational processes in naturalistic therapeutic interactions and suggest that movement-based measures may provide clinically relevant information to complement clinical observation and support supervision. Future research should examine how movement patterns relate to therapeutic processes and outcomes, and whether movement-based feedback can improve clinical practice.

PMID:
42859910
Bibliographic data and abstract were imported from PubMed on 11 Oct 2026.

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