The authors quantified nonverbal synchrony--the coordination of patient's and therapist's movement--in a random sample of same-sex psychotherapy dyads. The authors contrasted nonverbal synchrony in these dyads with a control condition and assessed its association with session-level and overall psychotherapy outcome. Using an automated objective video analysis algorithm (Motion Energy Analysis; MEA), the authors calculated nonverbal synchrony in (n = 104) videotaped psychotherapy sessions from 70 Caucasian patients (37 women, 33 men, mean age = 36.5 years, SD = 10.2) treated at an outpatient psychotherapy clinic. The sample was randomly drawn from an archive (N = 301) of routinely videotaped psychotherapies. Patients and their therapists assessed session impact with self-report post-session questionnaires. A battery of pre- and postsymptomatology questionnaires measured therapy effectiveness. The authors found that nonverbal synchrony is higher in genuine interactions contrasted with pseudointeractions (a control condition generated by a specifically designed shuffling procedure). Furthermore, nonverbal synchrony is associated with session-level process as well as therapy outcome: It is increased in sessions rated by patients as manifesting high relationship quality and in patients experiencing high self-efficacy. Higher nonverbal synchrony characterized psychotherapies with higher symptom reduction. The results suggest that nonverbal synchrony embodies the patients' self-reported quality of the relationship and further variables of therapy process. This hitherto overlooked facet of therapeutic relationships might prove useful as an indicator of therapy progress and outcome.

In an experiment on dyadic social interaction, we invited participants to verbal interactions in cooperative, competitive, and 'fun task' conditions. We focused on the link between interactants' affectivity and their nonverbal synchrony, and explored which further variables contributed to affectivity: interactants' personality traits, sex, and the prescribed interaction tasks. Nonverbal synchrony was quantified by the coordination of interactants' body movement, using an automated video-analysis algorithm (Motion Energy Analysis, MEA). Traits were assessed with standard questionnaires of personality, attachment, interactional style, psychopathology and interpersonal reactivity. We included 168 previously unacquainted individuals who were randomly allocated to same-sex dyads (84 females, 84 males, mean age 27.3 years). Dyads discussed four topics of general interest drawn from an urn of eight topics, and finally engaged in a fun interaction. Each interaction lasted five minutes. In between interactions, participants repeatedly assessed their affect. Using hierarchical linear modeling, we found moderate to strong effect sizes for synchrony to occur, especially in competitive and fun task conditions. Positive affect was associated positively with synchrony, negative affect was associated negatively. As for causal direction, data supported the interpretation that synchrony entailed affect rather than vice versa. The link between nonverbal synchrony and affect was strongest in female dyads. The findings extend previous reports of synchrony and mimicry associated with emotion in relationships and suggest a possible mechanism of the synchrony-affect correlation.

Objective: The coordination of patient’s and therapist’s bodily movement – nonverbal synchrony – has been empirically shown to be associated with psychotherapy outcome. This finding was based on dynamic movement patterns of the whole body. The present paper is a new analysis of an existing dataset (Ramseyer & Tschacher, 2011), which extends previous findings by differentiating movements pertaining to head and upper-body regions. Method: In a sample of 70 patients (37 female, 33 male) treated at an outpatient psychotherapy clinic, we quantified nonverbal synchrony with an automated objective video-analysis algorithm (Motion Energy Analysis, MEA). Head- and body-synchrony was quantified during the initial 15 minutes of video-recorded therapy sessions. Micro-outcome was assessed with self-report post-session questionnaires provided by patients and their therapists. Macro-outcome was measured with questionnaires that quantified attainment of treatment goals and changes in experiencing and behavior at the end of therapy. Results: The differentiation of head- and body-synchrony showed that these two facets of motor coordination were differentially associated with outcome. Head-synchrony predicted global outcome of therapy, while body-synchrony did not, and body-synchrony predicted session outcome, while head-synchrony did not. Conclusions: The results pose an important amendment to previous findings, which showed that nonverbal synchrony embodied both outcome and interpersonal variables of psychotherapy dyads. The separation of head- and body-synchrony suggested that distinct mechanisms may operate in these two regions: Head-synchrony embodied phenomena with a long temporal extension (overall therapy success), while body-synchrony embodied phenomena of a more immediate nature (session-level success). More explorations with fine-grained analyses of synchronized phenomena in nonverbal behavior may shed additional light on the embodiment of psychotherapy process.

Nonverbal behavior is a central factor influencing the therapeutic relationship. Despite broad agreement on its importance, empirical studies assessing nonverbal behavior in counseling and psychotherapy are relatively scarce and often limited to few cases. One restraining factor may be the resources needed when assessing nonverbal behavior. Movement dynamics are an exemplary aspect of nonverbal behavior that can be captured with computer vision-a discipline concerned with the automated analysis of footage captured on video. One of the simplest methods requiring no special detectors, devices, or markers on patients or therapists is based on the assessment of differences in sequences of pictures (frames) found in video recordings. Algorithms of so-called frame-differencing methods may be implemented on commonly available computers, and they provide a good, straightforward assessment of, for example, patients' and therapists' movement dynamics in counseling and therapy sessions. Frame-differencing methods in psychology date back 36 years, but their use in counseling and psychotherapy research is only recently gaining momentum. In this introductory article, the use of one specific application suitable for the assessment of human motion from archival video material is presented. Motion energy analysis (MEA) is a procedure particularly appropriate for clinicians and researchers who have access to recordings of sessions or who wish to record their own video material. Focusing on the phenomenon of nonverbal synchrony-the coordination of movement between patient and therapist-a step-by-step demonstration of the stages involved in a successful application of MEA in psychotherapy research is provided. (PsycInfo Database Record (c) 2020 APA, all rights reserved).

Disordered interpersonal communication can be a serious problem in schizophrenia. Recent advances in computer-based measures allow reliable and objective quantification of nonverbal behavior. Research using these novel measures has shown that objective amounts of body and head movement in patients with schizophrenia during social interactions are closely related to the symptom profiles of these patients. In addition to and above mere amounts of movement, the degree of synchrony, or imitation, between patients and normal interactants may be indicative of core deficits underlying various problems in domains related to interpersonal communication, such as symptoms, social competence, and social functioning. Nonverbal synchrony was assessed objectively using Motion Energy Analysis (MEA) in 378 brief, videotaped role-play scenes involving 27 stabilized outpatients diagnosed with paranoid-type schizophrenia. Low nonverbal synchrony was indicative of symptoms, low social competence, impaired social functioning, and low self-evaluation of competence. These relationships remained largely significant when correcting for the amounts of patients‘ movement. When patients showed reduced imitation of their interactants’ movements, negative symptoms were likely to be prominent. Conversely, positive symptoms were more prominent in patients when their interaction partners’ imitation of their movements was reduced. Nonverbal synchrony can be an objective and sensitive indicator of the severity of patients’ problems. Furthermore, quantitative analysis of nonverbal synchrony may provide novel insights into specific relationships between symptoms, cognition, and core communicative problems in schizophrenia.