[Convergence of Scales to Measure Social Anxiety: An IRT Linking Approach]. / Konvergenz von Skalen zur Erfassung sozialer Ängste: Ein IRT-Linking Ansatz.

OBJECTIVE: The Liebowitz Social Anxiety Scale (LSAS) and the Social Phobia Inventory (SPIN) are established measures in the investigation of social anxiety. Furthermore, the subscale Interpersonal Sensitivity of the Brief Symptom Inventory (BSI-53) is frequently used to screen social anxiety. All three scales claim to capture the same construct, which raises the question of the convergence of these scales. To make research findings comparable by a cross-questionnaire factor (common factor), an item response theory (IRT) linking approach is used in the present study. METHODS: 64 German-speaking psychiatric patients and 295 healthy subjects completed the three questionnaires. Different IRT models, including Graded Response Models (GRM), were constructed, and their model fit compared. Regression analyses were performed based on the best-fit model. The common factor was predicted from the questionnaire total values. RESULTS: The relationship between the different scales was best explained by a bifactor GRM with one common factor and three domain-specific factors (RMSEA=0.036, CFI=0.977, WRMR=1.061). Based on the results of the regression analyses, three equations were derived for the transformation of questionnaire's total values. CONCLUSION: The IRT linking approach allows the derivation of a general factor of social anxiety, taking into account commonalities and differences between the instruments used. This has advantages for both research and practice. A replication of this study as well as the implementation of further instruments are recommended to verify the validity of this approach and to generalize the results.

The influence of vocal synchrony on outcome and attachment anxiety/avoidance in treatments of social anxiety disorder.

Research indicates an effect of nonverbal synchrony on the therapeutic relationship and patients' symptom severity within psychotherapy. However, vocal synchrony research is still rare and inconsistent. This study investigates the relationship between vocal synchrony and outcome/attachment dimensions, controlling for therapeutic alliance and movement synchrony. Our sample consisted of 64 patients with social anxiety disorder. Symptom severity was assessed with the Liebowitz Social Anxiety Scale and the Inventory of Interpersonal Problems, whereas attachment was assessed with the Experiences in Close Relationships Questionnaire at the beginning and end of therapy. Therapeutic alliance was measured with the Helping Alliance Questionnaire II. We determined vocal synchrony of the median and range of the fundamental frequency (f 0) by correlating f 0 values of manually segmented speaker turns. Movement synchrony was assessed via motion energy and time-series analyses. Patient- and therapist-led synchrony was differentiated. Statistical analyses were performed using mixed effects linear models. Vocal synchrony had a negative impact on outcome. Higher vocal synchrony led to higher symptom severity (if the patient led synchrony, at the end of therapy) as well as attachment anxiety, avoidance, and interpersonal problems at the end of therapy. Predicting attachment anxiety, the effect of therapist-led vocal synchrony went beyond the effect of therapeutic alliance and movement synchrony. High vocal synchrony may arise due to a lack of autonomy in social anxiety disorder patients or might reflect attempts to repair alliance ruptures. The results indicate that vocal synchrony and movement synchrony have different effects on treatment outcome. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Depression Severity Is Related to Less Gross Body Movement: A Motion Energy Analysis.

Psychomotor retardation is a well-known clinical phenomenon in depressed patients that can be measured in various ways. This study aimed to investigate objectively measured gross body movement (GBM) during a semi-structured clinical interview in patients with a depressive disorder and its relation with depression severity. A total of 41 patients with a diagnosis of depressive disorder were assessed both with a clinician-rated interview (Hamilton Depression Rating Scale) and a self-rating questionnaire (Beck Depression Inventory-II) for depression severity. Motion energy analysis (MEA) was applied on videos of additional semi-structured clinical interviews. We considered (partial) correlations between patients' GBM and depression scales. There was a significant, moderate negative correlation between both measures for depression severity (total scores) and GBM during the diagnostic interview. However, there was no significant correlation between the respective items assessing motor symptoms in the clinician-rated and the patient-rated depression severity scale and GBM. Findings imply that neither clinician ratings nor self-ratings of psychomotor symptoms in depressed patients are correlated with objectively measured GBM. MEA thus offers a unique insight into the embodied symptoms of depression that are not available via patients' self-ratings or clinician ratings.

Movement and Emotional Facial Expressions during the Adult Attachment Interview: Interaction Effects of Attachment and Anxiety Disorder.

INTRODUCTION: Adult attachment is commonly associated with emotion regulation. Less is known about the nonverbal embodiment of adult attachment. OBJECTIVE: We hypothesized that dismissing attachment is related to less movement and fewer facial expressions of emotions, whereas preoccupied attachment is associated with more negative emotional facial expressions. Moreover, the interaction of attachment and the presence of an anxiety disorder (AD) was explored. METHODS: The sample included 95 individuals, 21 with AD without comorbidity, 21 with AD and comorbid major depression (AD-CD), and 53 healthy controls. We analyzed nonverbal behavior during a part of the Adult Attachment Interview (AAI) asking about the family and parental figures. The movements of the interviewees were captured via Motion Energy Analysis. Facial expressions were coded according to the Facial Action Coding System using the OpenFace software. We compared individuals with secure, dismissing, and preoccupied states of mind (assessed with the AAI) with regard to the frequency and complexity of movements and the frequency of the facial expressions such as happy, sad, and contemptuous. RESULTS: As expected, dismissingly attached individuals moved less often and with lower complexity than securely attached. For emotional facial expressions, a main effect of the disorder group and interaction effects of attachment by disorder were found. In the AD-CD group, dismissingly attached patients showed comparatively fewer happy facial expressions than securely attached individuals. CONCLUSIONS: Reduced movement specifically seems to be related to dismissing attachment when interviewees talk about significant parental figures. Facial expressions of emotions related to attachment occurred when maladaptive emotion regulation strategies were intensified by a psychological disorder.

Patterns of early change in interpersonal problems and their relationship to nonverbal synchrony and multidimensional outcome.

Early change is an increasing area of investigation in psychotherapy research. In this study, we analyzed patterns of early change in interpersonal problems and their relationship to nonverbal synchrony and multiple outcome measures for the first time. We used growth mixture modeling to identify different latent classes of early change in interpersonal problems with 212 patients who underwent cognitive-behavioral treatment including interpersonal and emotion-focused elements. Furthermore, videotaped sessions were analyzed using motion energy analysis, providing values for the calculation of nonverbal synchrony to predict early change in interpersonal problems. The relationship between early change patterns and symptoms as well as overall change in interpersonal problems was also investigated. Three latent subgroups were identified: 1 class with slow improvement (n = 145), 1 class with fast improvement (n = 12), and 1 early deterioration class (n = 55). Lower levels of early nonverbal synchrony were significantly related to fast improvement in interpersonal change patterns. Furthermore, such patterns predicted treatment outcome in symptoms and interpersonal problems. The results suggest that nonverbal synchrony is associated with early change patterns in interpersonal problems, which are also predictive of treatment outcome. Limitations of the applied methods as well as possible applications in routine care are discussed. (PsycInfo Database Record (c) 2020 APA, all rights reserved).

Associations between movement synchrony and outcome in patients with social anxiety disorder: Evidence for treatment specific effects.

Background: Studies with heterogeneous samples in naturalistic treatment settings suggest that movement synchrony (MS) between therapists and patients correlates with therapeutic success. In this study, we examined a homogeneous sample of patients with social anxiety disorder and investigated whether MS in sessions 3 and 8 would be associated with therapy outcome and therapeutic alliance, and whether these associations depend on the therapeutic approach. Methods: The patients (N = 267) were treated with either manual-guided cognitive behavior therapy (CBT), manual-guided psychodynamic therapy (PDT), or naturalistic CBT. The Helping Alliance Questionnaire (HAQ), the Inventory of Interpersonal Problems (IIP) and the Beck-Depression-Inventory (BDI) were used as measures. Body motions were coded with motion energy analysis. MS was quantified using time series analysis methods. Results: MS was observed more frequently in both CBT conditions than in PDT. In both CBT groups, more synchrony was predictive of lower IIP scores at the end of therapy. If the patient lead synchrony more often than the therapist, higher IIP and BDI scores were observed at the end of treatment. PDT showed the largest effect size for the synchrony-alliance-association. Conclusion: Movement synchrony and therapeutic success are associated. The effect of therapeutic approach and leading/following are relevant for this association.

Self-Esteem as a Potential Mediator of the Association Between Social Integration, Mental Well-Being, and Physical Well-Being.

Previous research points to a significant impact of social integration and self-esteem on well-being. The present study examined whether self-esteem constitutes one pathway from social integration in the classroom to mental and physical well-being of students and accordingly serves as a mediator. Therefore, 163 students (mean age: 12.98 years, age range: 9-17 years, 57.9% male) of three German secondary schools were examined regarding their experience of social integration, self-esteem, and mental as well as physical well-being. Results revealed that self-esteem mediated the effect of social integration on mental and physical well-being. This finding elucidates one pathway from social integration to well-being and points to the importance of improving both self-esteem and social integration for the promotion of well-being among adolescents.

Nonverbal synchrony predicts premature termination of psychotherapy for social anxiety disorder.

Premature termination is a problem in psychotherapy. In addition to the examination of demographic and clinical variables as predictors of dropout, research indicates the importance of dyadic variables. Nonverbal synchrony (e.g., movement synchrony) operationalizes the coordination of patient and therapist and is a promising candidate for predicting premature termination. This secondary data analysis included data on patients with social anxiety disorder (N = 267) that were treated with > 20 sessions of cognitive-behavioral therapy or psychodynamic therapy. Therapy outcome was measured by the Inventory of Interpersonal Problems and the Beck Depression Inventory. Individual movements in the third session were assessed by motion energy analysis. Movement synchrony was identified with a windowed cross-lagged correlation and peak-picking algorithm. We performed logistic regressions and mixed effects Cox regressions to investigate synchrony as a predictor of premature termination. Therapist-patient dyads that included a patient who terminated psychotherapy prematurely had significantly lower movement synchrony at the beginning of therapy than patients who completed therapy. Gender-matching and therapeutic approach had a (marginally) significant effect in moderating the relationship. Therefore, low movement synchrony in early therapy sessions may contain clues to premature termination and reflect a mismatch between the patient and therapist or problems in the therapeutic alliance. (PsycINFO Database Record (c) 2019 APA, all rights reserved).

Identification of movement synchrony: Validation of windowed cross-lagged correlation and -regression with peak-picking algorithm.

In psychotherapy, movement synchrony seems to be associated with higher patient satisfaction and treatment outcome. However, it remains unclear whether movement synchrony rated by humans and movement synchrony identified by automated methods reflect the same construct. To address this issue, video sequences showing movement synchrony of patients and therapists (N = 10) or not (N = 10), were analyzed using motion energy analysis. Three different synchrony conditions with varying levels of complexity (naturally embedded, naturally isolated, and artificial) were generated for time series analysis with windowed cross-lagged correlation/ -regression (WCLC, WCLR). The concordance of ratings (human rating vs. automatic assessment) was computed for 600 different parameter configurations of the WCLC/WCLR to identify the parameter settings that measure movement synchrony best. A parameter configuration was rated as having a good identification rate if it yields high concordance with human-rated intervals (Cohen's kappa) and a low amount of over-identified data points. Results indicate that 76 configurations had a good identification rate (IR) in the least complex condition (artificial). Two had an acceptable IR with regard to the naturally isolated condition. Concordance was low with regard to the most complex (naturally embedded) condition. A valid identification of movement synchrony strongly depends on parameter configuration and goes beyond the identification of synchrony by human raters. Differences between human-rated synchrony and nonverbal synchrony measured by algorithms are discussed.

Quantification of nonverbal synchrony using linear time series analysis methods: Lack of convergent validity and evidence for facets of synchrony.

Nonverbal synchrony describes coordination of the nonverbal behavior of two interacting partners. Additionally, it seems to be important in human interactions, such as during psychotherapy. Currently, there are several options for the automated determination of synchrony based on linear time series analysis methods (TSAMs). However, investigations into whether the different methods measure the same construct have been missing. In this study, N = 84 patient-therapist dyads were videotaped during psychotherapy sessions. Motion energy analysis was used to assess body movements. We applied seven different TSAMs and recorded multiple output scores (average synchrony, maximum synchrony, and frequency of synchrony; in total, N = 16 scores). Convergent validity was examined using correlations of the output scores and exploratory factor analysis. Additionally, two criterion-based validations were conducted: investigations of concordant validity with a more generalized nonlinear method, and of the predictive validity of the synchrony scores for improvement in interpersonal problems at the end of therapy. We found that the synchrony measures only partially correlated with each other. The factor analysis did not support a common-factor model. A three-factor model with a second-order synchrony variable showed the best fit for eight of the selected synchrony scores. Only some synchrony scores were able to predict improvement at the end of therapy. We concluded that the considered TSAMs do not measure the same synchrony construct, but different facets of synchrony: the strength of synchrony of the total interaction, the strength of synchrony during synchronization intervals, and the frequency of synchrony.