Reactivity and stability in facial expressions as an indicator of therapeutic alliance strength.

Objective: Aspects of our emotional state are constantly being broadcast via our facial expressions. Psychotherapeutic theories highlight the importance of emotional dynamics between patients and therapists for an effective therapeutic relationship. Two emotional dynamics suggested by the literature are emotional reactivity (i.e., when one person is reacting to the other) and emotional stability (i.e., when a person has a tendency to remain in a given emotional state). Yet, little is known empirically about the association between these dynamics and the therapeutic alliance. This study investigates the association between the therapeutic alliance and the emotional dynamics of reactivity and stability, as manifested in the facial expressions of patients and therapists within the session. Methods: Ninety-four patients with major depressive disorder underwent short-term treatment for depression (N = 1256 sessions). Results: Both therapist reactivity and stability were associated with the alliance, across all time spans. Patient reactivity was associated with the alliance only in a short time span (1 s). Conclusions: These findings may potentially guide therapists in the field to attenuate not only their emotional reaction to their patients, but also their own unique presence in the therapy room.

Biological marker of withdrawal ruptures: Dyadic pattern of incongruence in oxytocin release.

Despite widespread clinical, theoretical, and empirical support for the importance of alliance ruptures, little is known about the underlying biological level at times of rupture. The overarching goal of the present study was to investigate dyadic patterns of in-session oxytocin (OT) change between patients and therapists (e.g., patient's OT increases more than therapist's OT) as markers of withdrawal ruptures. Hypothesis 1 construed that OT incongruence (e.g., larger patient increase in OT in comparison to their therapist OT increase) will mark the occurrence of withdrawal ruptures. Hypothesis 2 construed that this effect of OT incongruence will be more pronounced when anxious attachment orientation is low. Surface analysis was conducted on 628 saliva samples that were gathered before and after therapeutic sessions of 53 patient-therapist dyads enrolled in a randomized control trial treating major depression. Only Hypothesis 2 received empirical support, meaning it was only when anxious attachment orientation was low that there were significantly more withdrawal ruptures when the patient's OT increase was higher than their therapist's OT increase. This is consistent with the literature, suggesting that in times of withdrawal ruptures, the patient and therapist are in an incongruent state. Findings suggest that this incongruence is mirrored at the biological level only when anxious attachment orientation is low. Results shed light on what may be happening between patients and therapists on a biological level during a withdrawal rupture. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

A multimodal case study utilizing physiological synchrony as indicator of context in which motion synchrony is associated with the working alliance.

Interest in the association between patient and therapist's motion synchrony and the working alliance has been growing in recent years. This interest is part of a larger effort in psychotherapy research to study how the working alliance, being central to the therapeutic process, develops over the course of therapy. However, while previous studies suggest that such an association between motion synchrony and the working alliance exists, there are mixed results regarding the direction of it. The present single-case study seeks to shed light on these mixed results with a multimodal perspective of nonverbal synchrony. That is, through an exploration of a single case, the present study explores physiological synchrony as an indicator of context in which motion synchrony is associated with the working alliance. For this aim, a single case was chosen from a randomized control trial investigating short-term psychodynamic treatment for major depressive disorder. Statistical analysis identified an interaction between physiological synchrony and motion synchrony in predicting working alliance levels. Findings show that in the context of an antiphase pattern of physiological synchrony (negative association between physiological measures of the two participants), there was a positive association between motion synchrony and the working alliance. This study emphasizes the potential of a multimodal approach, while suggesting a possible explanation for mixed results in current literature that focuses on the association between motion synchrony and the working alliance. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Personalized cognitive training: Protocol for individual-level meta-analysis implementing machine learning methods.

Accumulating evidence suggests that cognitive training may enhance well-being. Yet, mixed findings imply that individual differences and training characteristics may interact to moderate training efficacy. To investigate this possibility, the current paper describes a protocol for a data-driven individual-level meta-analysis study aimed at developing personalized cognitive training. To facilitate comprehensive analysis, this protocol proposes criteria for data search, selection and pre-processing along with the rationale for each decision. Twenty-two cognitive training datasets comprising 1544 participants were collected. The datasets incorporated diverse training methods, all aimed at improving well-being. These training regimes differed in training characteristics such as targeted domain (e.g., working memory, attentional bias, interpretation bias, inhibitory control) and training duration, while participants differed in diagnostic status, age and sex. The planned analyses incorporate machine learning algorithms designed to identify which individuals will be most responsive to cognitive training in general and to discern which methods may be a better fit for certain individuals.

Diagnostic and Predictive Neuroimaging Biomarkers for Posttraumatic Stress Disorder.

BACKGROUND: Comorbidity between posttraumatic stress disorder (PTSD) and major depressive disorder (MDD) has been commonly overlooked by studies examining resting-state functional connectivity patterns in PTSD. The current study used a data-driven approach to identify resting-state functional connectivity biomarkers to 1) differentiate individuals with PTSD (with or without MDD) from trauma-exposed healthy control subjects (TEHCs), 2) compare individuals with PTSD alone with those with comorbid PTSD+MDD, and 3) explore the clinical utility of the identified biomarkers by testing their associations with clinical symptoms and treatment response. METHODS: Resting-state magnetic resonance images were obtained from 51 individuals with PTSD alone, 52 individuals with PTSD+MDD, and 76 TEHCs. Of the 103 individuals with PTSD, 55 were enrolled in prolonged exposure treatment. A support vector machine model was used to identify resting-state functional connectivity biomarkers differentiating individuals with PTSD (with or without MDD) from TEHCs and differentiating individuals with PTSD alone from those with PTSD+MDD. The associations between the identified features and symptomatology were tested with Pearson correlations. RESULTS: The support vector machine model achieved 70.6% accuracy in discriminating between individuals with PTSD and TEHCs and achieved 76.7% accuracy in discriminating between individuals with PTSD alone and those with PTSD+MDD for out-of-sample prediction. Within-network connectivity in the executive control network, prefrontal network, and salience network discriminated individuals with PTSD from TEHCs. The basal ganglia network played an important role in differentiating individuals with PTSD alone from those with PTSD+MDD. PTSD scores were inversely correlated with within-executive control network connectivity (p < .001), and executive control network connectivity was positively correlated with treatment response (p < .001). CONCLUSIONS: Results suggest that unique brain-based abnormalities differentiate individuals with PTSD from TEHCs, differentiate individuals with PTSD from those with PTSD+MDD, and demonstrate clinical utility in predicting levels of symptomatology and treatment response.