Physiological activation and co-activation in an imagery-based treatment for test anxiety

Prinz, Jessica; Rafaeli, Eshkol; Reuter, Julia K.; Bar‐Kalifa, Eran; Lutz, Wolfgang

doi:10.1080/10503307.2021.1918353

Cited by 11 publications

(12 citation statements)

References 45 publications

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“…Therapist-led synchrony was defined as the cross-correlation within a lag of 0–10 s with the therapist preceding the client, while client-led synchrony was defined as the cross-correlation within a lag of 0–10 s with the client preceding the therapist. We expected our data to provide a conceptual replication of the positive associations between physiological synchrony and adaptive therapy processes found previously [ 23 , 24 ]. Moreover, our central (though exploratory) goal was to distinguish between therapist-led and client-led physiological synchrony and determine whether either or both are associated with adaptive emotional experiences (i.e., lower negative emotions and higher positive ones) in IR sessions.…”

Section: Introductionsupporting

confidence: 74%

“…Third, the auto.arima function (forecast package for R [ 36 ]) was applied to remove the autocorrelated component for each EDA time series. (For a similar approach, see [ 23 , 24 ])…”

Section: Methodsmentioning

confidence: 99%

“…Third, the auto.arima function (forecast package for R [36]) was applied to remove the autocorrelated component for each EDA time series. (For a similar approach, see [23,24]) Two CCFs were computed per session, one in which the client led (with a maximum lag of +10 s) and one in which the therapist led (with a maximum lag of −10 s). The maximal positive (in-phase) correlations (one for each CCF) were used as the two synchrony indices.…”

Section: Client-therapist Eda Synchronymentioning

confidence: 99%

“…Both studies involved multiple sessions and used electrodermal activity (EDA) as an index of arousal (based on extensive work demonstrating the sensitivity of EDA to emotional and cognitive processing, such as in [ 21 , 22 ]). Additionally, both studies compared client–therapist EDA synchrony during imagery vs. cognitive behavioral (CB) segments of sessions and found the former (but not the latter) to be tied to therapeutic bond ratings [ 23 ] and to the next session’s (as well as overall treatment’s) outcome [ 24 ].…”

Section: Introductionmentioning

confidence: 99%

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Clients’ Emotional Experiences Tied to Therapist-Led (but Not Client-Led) Physiological Synchrony during Imagery Rescripting

Prinz

Rafaeli

Wasserheß

et al. 2021

Entropy

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Imagery rescripting (IR), an effective intervention technique, may achieve its benefits through various change mechanisms. Previous work has indicated that client–therapist physiological synchrony during IR may serve as one such mechanism. The present work explores the possibility that therapist-led vs. client-led synchrony may be differentially tied to clients’ emotional experiences in therapy. The analyses were conducted with data taken from an open trial of a brief protocol for treating test anxiety (86 IR sessions from 50 client–therapist dyads). Physiological synchrony in electrodermal activity was indexed using two cross-correlation functions per session: once for client leading and again for therapist leading (in both cases, with lags up to 10 s). The clients’ and therapists’ in-session emotions were assessed with the Profile of Mood States. Actor–partner interdependence models showed that certain client (but not therapist) in-session emotions, namely higher contentment and lower anxiety and depression, were tied to therapist-led (but not client-led) physiological synchrony. The results suggest that therapist-led synchrony (i.e., clients’ arousal tracking therapists’ earlier arousal) is tied to more positive and less negative emotional experiences for clients.

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Section: Introductionsupporting

confidence: 74%

“…Third, the auto.arima function (forecast package for R [ 36 ]) was applied to remove the autocorrelated component for each EDA time series. (For a similar approach, see [ 23 , 24 ])…”

Section: Methodsmentioning

confidence: 99%

Section: Client-therapist Eda Synchronymentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Clients’ Emotional Experiences Tied to Therapist-Led (but Not Client-Led) Physiological Synchrony during Imagery Rescripting

Prinz

Rafaeli

Wasserheß

et al. 2021

Entropy

Self Cite

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“…patient and therapist. Synchrony between patient and therapist, and its relation to therapeutic outcome and process variables has already been shown for movements (67,72,73), speech content and prosodic features (62,74) as well as physiological measures (70,75). Regarding emotions, it can also be assumed that it might be beneficial if patient and therapist are attuned to each other.…”

Section: Data Availability Statementmentioning

confidence: 93%

Validation and application of the Non-Verbal Behavior Analyzer: An automated tool to assess non-verbal emotional expressions in psychotherapy

Terhürne

Schwartz²,

Baur³

et al. 2022

Front. Psychiatry

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BackgroundEmotions play a key role in psychotherapy. However, a problem with examining emotional states via self-report questionnaires is that the assessment usually takes place after the actual emotion has been experienced which might lead to biases and continuous human ratings are time and cost intensive. Using the AI-based software package Non-Verbal Behavior Analyzer (NOVA), video-based emotion recognition of arousal and valence can be applied in naturalistic psychotherapeutic settings. In this study, four emotion recognition models (ERM) each based on specific feature sets (facial: OpenFace, OpenFace-Aureg; body: OpenPose-Activation, OpenPose-Energy) were developed and compared in their ability to predict arousal and valence scores correlated to PANAS emotion scores and processes of change (interpersonal experience, coping experience, affective experience) as well as symptoms (depression and anxiety in HSCL-11).Materials and methodsA total of 183 patient therapy videos were divided into a training sample (55 patients), a test sample (50 patients), and a holdout sample (78 patients). The best ERM was selected for further analyses. Then, ERM based arousal and valence scores were correlated with patient and therapist estimates of emotions and processes of change. Furthermore, using regression models arousal and valence were examined as predictors of symptom severity in depression and anxiety.ResultsThe ERM based on OpenFace produced the best agreement to the human coder rating. Arousal and valence correlated significantly with therapists’ ratings of sadness, shame, anxiety, and relaxation, but not with the patient ratings of their own emotions. Furthermore, a significant negative correlation indicates that negative valence was associated with higher affective experience. Negative valence was found to significantly predict higher anxiety but not depression scores.ConclusionThis study shows that emotion recognition with NOVA can be used to generate ERMs associated with patient emotions, affective experiences and symptoms. Nevertheless, limitations were obvious. It seems necessary to improve the ERMs using larger databases of sessions and the validity of ERMs needs to be further investigated in different samples and different applications. Furthermore, future research should take ERMs to identify emotional synchrony between patient and therapists into account.

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Interpersonelle Prozesse während des Imagery Rescripting

Uhl

Reuter²,

Rafaeli³

et al. 2022

Psychotherapie

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Physiological activation and co-activation in an imagery-based treatment for test anxiety

Cited by 11 publications

References 45 publications

Clients’ Emotional Experiences Tied to Therapist-Led (but Not Client-Led) Physiological Synchrony during Imagery Rescripting

Clients’ Emotional Experiences Tied to Therapist-Led (but Not Client-Led) Physiological Synchrony during Imagery Rescripting

Validation and application of the Non-Verbal Behavior Analyzer: An automated tool to assess non-verbal emotional expressions in psychotherapy

Interpersonelle Prozesse während des Imagery Rescripting

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