The relationship between body movements of clients and counselors in psychotherapeutic counseling: A study using the video-based quantification method

Komori, Masashi; Nagaoka, Chika

doi:10.5265/jcogpsy.8.1

Cited by 6 publications

(8 citation statements)

References 13 publications

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“…The frame shift of the window is set to 0.1 seconds. The time lag of ±0.5 seconds is used with a temporal interval of 0.1 seconds since it has been reported that the therapist’s body movements, in positive psychotherapeutic session between a client and therapist, occur with a 0.5 seconds delay compared with the clients49. Furthermore, it was also reported that the synchrony between an infant’s movement and adult speech occurred at a time lag of 0.05 ± 0.2 seconds50.…”

Section: Methodsmentioning

confidence: 99%

Prior Knowledge Facilitates Mutual Gaze Convergence and Head Nodding Synchrony in Face-to-face Communication

Thepsoonthorn

Yokozuka

Miura

et al. 2016

Sci Rep

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As prior knowledge is claimed to be an essential key to achieve effective education, we are interested in exploring whether prior knowledge enhances communication effectiveness. To demonstrate the effects of prior knowledge, mutual gaze convergence and head nodding synchrony are observed as indicators of communication effectiveness. We conducted an experiment on lecture task between lecturer and student under 2 conditions: prior knowledge and non-prior knowledge. The students in prior knowledge condition were provided the basic information about the lecture content and were assessed their understanding by the experimenter before starting the lecture while the students in non-prior knowledge had none. The result shows that the interaction in prior knowledge condition establishes significantly higher mutual gaze convergence (t(15.03) = 6.72, p < 0.0001; α = 0.05, n = 20) and head nodding synchrony (t(16.67) = 1.83, p = 0.04; α = 0.05, n = 19) compared to non-prior knowledge condition. This study reveals that prior knowledge facilitates mutual gaze convergence and head nodding synchrony. Furthermore, the interaction with and without prior knowledge can be evaluated by measuring or observing mutual gaze convergence and head nodding synchrony.

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Section: Methodsmentioning

confidence: 99%

Prior Knowledge Facilitates Mutual Gaze Convergence and Head Nodding Synchrony in Face-to-face Communication

Thepsoonthorn

Yokozuka

Miura

et al. 2016

Sci Rep

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“…After we detected peaks in the acceleration of head nods by student and teacher, we defined the phase difference as the minimum temporal difference ( t j - t i ) from the time ( t i ) of a peak in acceleration of the teacher’s head nods to that ( t j ) of the student. The range of the phase difference was limited to 1.0 s because it has been reported that the maximal delay time for nonverbal synchronization is 1.0 s [ 12 ]. Therefore, we imposed the following restriction, in addition to conditions ( 6 ) to ( 7 ), on the definition of phase difference: …”

Section: Methodsmentioning

confidence: 99%

“…In particular, Hove and Risen (2009) concluded that interpersonal synchrony is the critical factor contributing to likability with an increase of affiliation [ 10 ] and Marsh et al (2009) have reported that behavioral and embodied methods can be used for investigating the relationship between sociality and coordination with other individuals, which is fundamental and serves as the basis for our social connection to others [ 11 ]. In addition, the strong synchronization of body movements between clients and their psychotherapy counselors has been found for positively evaluated counseling groups [ 12 ]. Specifically, head nods often occur at the same time, even during conversations among multiple participants [ 6 ].…”

Section: Introductionmentioning

confidence: 99%

“…Previous researchers have used video-based analysis to measure body movement synchronization [ 6 – 9 , 12 – 17 ]. Bernieri (1988a) and Bernieri et al (1988b) have analyzed body movement synchrony by observer ratings through movement synchrony perceived in video clips [ 16 , 17 ].…”

Section: Introductionmentioning

confidence: 99%

“…Bernieri (1988a) and Bernieri et al (1988b) have analyzed body movement synchrony by observer ratings through movement synchrony perceived in video clips [ 16 , 17 ]. In addition, some researchers have analyzed the synchronization of body movements by focusing on changes in the amplitude of body movements with a predetermined video frame rate [ 12 – 15 ]. However, there is no research on phase difference as an indicator of body movement synchronization in human communication.…”

Section: Introductionmentioning

confidence: 99%

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Detection of Nonverbal Synchronization through Phase Difference in Human Communication

et al. 2015

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Nonverbal communication is an important factor in human communication, and body movement synchronization in particular is an important part of nonverbal communication. Some researchers have analyzed body movement synchronization by focusing on changes in the amplitude of body movements. However, the definition of “body movement synchronization” is still unclear. From a theoretical viewpoint, phase difference is the most important factor in synchronization analysis. Therefore, there is a need to measure the synchronization of body movements using phase difference. The purpose of this study was to provide a quantitative definition of the phase difference distribution for detecting body movement synchronization in human communication. The phase difference distribution was characterized using four statistical measurements: density, mean phase difference, standard deviation (SD) and kurtosis. To confirm the effectiveness of our definition, we applied it to human communication in which the roles of speaker and listener were defined. Specifically, we examined the difference in the phase difference distribution between two different communication situations: face-to-face communication with visual interaction and remote communication with unidirectional visual perception. Participant pairs performed a task supposing lecture in the face-to-face communication condition and in the remote communication condition via television. Throughout the lecture task, we extracted a set of phase differences from the time-series data of the acceleration norm of head nodding motions between two participants. Statistical analyses of the phase difference distribution revealed the characteristics of head nodding synchronization. Although the mean phase differences in synchronized head nods did not differ significantly between the conditions, there were significant differences in the densities, the SDs and the kurtoses of the phase difference distributions of synchronized head nods. These results show the difference in nonverbal synchronization between different communication types. Our study indicates that the phase difference distribution is useful in detecting nonverbal synchronization in various human communication situations.

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The Relationship between Robot’s Nonverbal Behaviour and Human’s Likability Based on Human’s Personality

Thepsoonthorn

Ogawa

Miyake

2018

Sci Rep

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At current state, although robotics technology has been immensely developed, the uncertainty to completely engage in human-robot interaction is still growing among people. Many current studies then started to concern about human factors that might influence human’s likability like human’s personality, and found that compatibility between human’s and robot’s personality (expressions of personality characteristics) can enhance human’s likability. However, it is still unclear whether specific means and strategy of robot’s nonverbal behaviours enhances likability from human with different personality traits and whether there is a relationship between robot’s nonverbal behaviours and human’s likability based on human’s personality. In this study, we investigated and focused on the interaction via gaze and head nodding behaviours (mutual gaze convergence and head nodding synchrony) between introvert/extravert participants and robot in two communication strategies (Backchanneling and Turn-taking). Our findings reveal that the introvert participants are positively affected by backchanneling in robot’s head nodding behaviour, which results in substantial head nodding synchrony whereas the extravert participants are positively influenced by turn-taking in gaze behaviour, which leads to significant mutual gaze convergence. This study demonstrates that there is a relationship between robot’s nonverbal behaviour and human’s likability based on human’s personality.

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The relationship between body movements of clients and counselors in psychotherapeutic counseling: A study using the video-based quantification method

Cited by 6 publications

References 13 publications

Prior Knowledge Facilitates Mutual Gaze Convergence and Head Nodding Synchrony in Face-to-face Communication

Prior Knowledge Facilitates Mutual Gaze Convergence and Head Nodding Synchrony in Face-to-face Communication

Detection of Nonverbal Synchronization through Phase Difference in Human Communication

The Relationship between Robot’s Nonverbal Behaviour and Human’s Likability Based on Human’s Personality

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