1,720,970 research outputs found
rMEA: An R package to assess nonverbal synchronization in motion energy analysis time-series
No full textIntroduction. Motion Energy Analysis (MEA) is a procedure that allows to automatically assess the amount of persons’ movement from video recordings. Recent studies used MEA to investigate nonverbal synchrony, i.e., the occurrence of simultaneous movement, suggesting the existence of an association with relationship quality. In patient-therapist dyads, synchrony predicted therapeutic alliance, empathy, as well as treatment outcome. Package description. The article presents rMEA, an open-source R package that allows to import, filter, and visualize dyadic time-series of nonverbal behaviour generated by other MEA software. The package includes a fast, state-of-the-art, moving window cross-correlation algorithm with lag analysis, which provides a user-friendly interface for the assessment of nonverbal synchrony. Through the analysis of a motivating example (40 psychotherapy intake interviews split between dropouts and good cases) the article provides an in-depth description of the package main functions and a tutorial for a typical analysis in this field, requiring only the most basic knowledge of the R language and environment. The rich visualization capabilities of the software provide powerful tools for the various steps involved in the diagnostics, analysis, interpretation and publication of these data. Conclusions. Overall, the paper aims to empower psychotherapy researchers and other interaction scientists to investigate nonverbal synchrony in their own dyads
Interpersonal biofeedback in psychodynamic psychotherapy
Full text linkThe idea that the patient-therapist relationship is at the core of change in psychotherapy has found broad consensus and ample empirical evidence in recent years (Norcross and Wampold, 2011). Engaging in an efficacious relationship is part of being an expert therapist (Kramer and Stiles, 2015), and while specific techniques are easily learnable, managing to “read the room” and to flexibly modulate the therapeutic response is still more an art than a science (McWilliams, 2004). With this article, we present the theoretical foundations supporting the development of “interpersonal biofeedback” as a tool to enhance therapists' awareness of unconscious interpersonal regulation dynamics
Examining psychological flexibility in unaccompanied refugee minors: A network analysis
No full textBackground: Refugees, particularly unaccompanied refugee minors (URM), often report poor mental health. Psychological Flexibility (PF), derived from Acceptance and Commitment Therapy (ACT), appears to positively impact mental health in various populations, including adolescents and refugees. Objectives: This study aimed to examine the structure of the PF model and the connections among its core processes, as well as the structure and connections between mental health constructs (i.e., post-traumatic stress, depression, anxiety, stress, quality of life) and PF in URM. Methods: 100 URM aged 13–18 years living in shelters in the Republic of Cyprus completed four self-reports, assessing depression, anxiety, and stress (DASS-21), PF (Psy-Flex), PTSD (CRIES-13), and HRQL (KIDSCREEN-10). Network Analysis was used to examine the structure and connections of the constructs. Results: Most core PF processes showed positive connections amongst each other, with the strongest edge between committed action and values. Together with self as context, these core processes exhibited the highest expected influence. The strongest positive connections in the mental health network were found among stress, anxiety, and depression. Stress had the highest expected influence, whereas PF had the lowest. A post hoc Johnson-Neyman analysis suggested a buffering effect of PF on the impact of PTSD on anxiety and stress. Conclusions: Proposed areas of focus for clinicians working with URM include incorporating strategies that address stress symptoms and facilitate individuals in pursuing value-based behavior. It is equally important to encourage critical reflection on values and the conceptualized self in the context of culture
The phase space of meaning model of psychopathology: A computer simulation modelling study
Full text linkIntroduction The hypothesis of a general psychopathology factor that underpins all common forms of mental disorders has been gaining momentum in contemporary clinical research and is known as the p factor hypothesis. Recently, a semiotic, embodied, and psychoanalytic conceptualisation of the p factor has been proposed called the Harmonium Model, which provides a computational account of such a construct. This research tested the core tenet of the Harmonium model, which is the idea that psychopathology can be conceptualised as due to poorly-modulable cognitive processes, and modelled the concept of Phase Space of Meaning (PSM) at the computational level. Method Two studies were performed, both based on a simulation design implementing a deep learning model, simulating a cognitive process: a classification task. The level of performance of the task was considered the simulated equivalent to the normality-psychopathology continuum, the dimensionality of the neural network’s internal computational dynamics being the simulated equivalent of the PSM’s dimensionality. Results The neural networks’ level of performance was shown to be associated with the characteristics of the internal computational dynamics, assumed to be the simulated equivalent of poorly-modulable cognitive processes. Discussion Findings supported the hypothesis. They showed that the neural network’s low performance was a matter of the combination of predicted characteristics of the neural networks’ internal computational dynamics. Implications, limitations, and further research directions are discussed
Physiological Regulation Processes Differentiate the Experience of Ruptures Between Patient and Therapist
No full textThe empirical and clinical literature emphasizes the importance of alliance ruptures, signaling therapeutic processes occurring within and between the partners of the therapeutic dyad. However, knowledge about the underlying regulatory processes that occur amid ruptures is scarce. Identifying the underlying physiological markers may shed light on these regulatory processes. The overarching goal of the present study was to explore physiological markers of withdrawal and confrontation ruptures, within the patient and the therapist. Given the little known on the subject, we used a single-case design (94 episodic segments) to explore biologically based regulatory processes in the face of a rupture, contrasting confrontation ruptures versus withdrawal ruptures versus control episodes (emotional and neutral episodes). Findings showed that the patient and the therapist had contrasting physiological responses to the ruptures, depending on the type. During withdrawal ruptures, the patient exhibited high regulation, while the therapist did not show a clear physiological reaction. During confrontation ruptures, the patient exhibited low regulation, while the therapist exhibited high regulation. The different physiological regulation processes at times of ruptures suggest that, in withdrawal, the patient relied on intrapersonal regulation, contrasting with the interpersonal regulation observed in confrontation ruptures. Findings remained robust after controlling for speech turns and 10,000 Monte Carlo permutations to assess chance-level results. These findings provide initial evidence for the link between arousal and behavior in ruptures, offering valuable psychoeducational material for therapists to improve their handling of these challenging moments
The harmonium model and its unified system view of psychopathology: a validation study by means of a convolutional neural network
Full text linkThe harmonium model (HM) is a recent conceptualization of the unifying view of psychopathology, namely the idea of a general mechanism underpinning all mental disorders (the p factor). According to HM, psychopathology consists of a low dimensional Phase Space of Meaning (PSM), where each dimension of meaning maps a component of the environmental variability. Accordingly, the lower thenumber of independent dimensions in the PSM, and hence its intrinsic complexity, the more limited the way of interpreting the environment. The current simulation study, based on a Convolutional Neural Network (CNN) framework, aims at validating the HM low-dimensionality hypothesis. CNN-based classifiers were employed to simulate normotypical and pathological cognitive processes. Results revealed that normotypical and pathological CNNs were different in terms of both classification performance and layer activation patterns. Using Principal Component Analysis to characterize the PSM associated with the two algorithms, we found that the performance of the normotypical CNN relies on a larger and more evenly distributed number of components, compared with the pathological one. This finding might be indicative of the fact that psychopathology can be modelled as a low-dimensional, poorly modulable PSM, which means the environment is detected through few components of meaning, preventing complex information patterns from being taken into account
Un metodo di integrazione tra psicologia dinamica e neuroscienze: lo studio delle esperienze ai confini con la morte
No full textPhysiological synchronization and innovative moments in psychotherapy: A single-case study of micro-process
No full textObjective: Interpersonal synchronization is increasingly studied as a biomarker of empathy, therapeutic alliance, and treatment outcome. However, most studies average data over sessions, leaving associations between synchrony and actual interactions largely unexplored. We aim to showcase a novel approach examining synchronization during specific micro-processes: Innovative Moments (IM) as markers of exceptions to clients’ problematic patterns of meaning. Methods: Electrodermal activity was recorded over 15 sessions of a psychodynamic psychotherapy single case. Moment-to-moment patient-therapist synchrony was calculated using the Adaptive Matching Interpolated Correlations (AMICo) algorithm. The Innovative Moments Coding System was utilized to identify IMs within session transcripts with precise timing. Monte-Carlo permutation tests were conducted to examine the association between physiological synchrony and IM Levels of increasing complexity (Levels 1–3). Results: Higher-than-random synchronization emerged during Level 3 IMs (p = 0.046; d = 0.21) but not in lower Levels. Post-hoc qualitative analyses linked high synchrony to sub-processes of Level 3 IMs, such as positive contrasts and attributions for change. Conclusion: Our findings show it is possible to link moment-by-moment physiological co-regulation to theoretically identified meaning-making processes. While generalization of these observations is undue, this work demonstrates a robust and promising application of a multimodal approach to investigating psychotherapy, providing insights into both the clinical case and the theoretical model adopted
Movement Synchrony in the Psychotherapy of Adolescents With Borderline Personality Pathology – A Dyadic Trait Marker for Resilience?
Full text linkMovement synchrony describes the coordination of body movements. In psychotherapy, higher movement synchrony between therapist and patient has been associated with higher levels of empathy, therapeutic alliance, better therapy outcome, and fewer drop-outs. The current study investigated movement synchrony during the psychotherapeutic treatment of female adolescents with borderline personality disorder. It was hypothesized that there are higher levels of movement synchrony in the analyzed therapy sessions compared to pseudo-interactions. Further, we tested whether higher levels of movement synchrony correlate with stronger patients’ symptom reduction and whether higher movement synchrony predicts higher post-session ratings. A total of 356 sessions from 16 completed psychotherapies of adolescent patients with BPD were analyzed. Movement synchrony was assessed with motion energy analysis and an index of synchrony was calculated by lagged cross-correlation analysis. As hypothesized, the findings support higher levels of movement synchrony in therapy sessions compared to pseudo-interactions (Cohen’s d = 0.85). Additionally, a correlation of movement synchrony with better therapy outcome was found (standardized beta = −0.43 indicating stronger personality functioning impairment reduction). The post-session ratings were negatively associated with higher levels of movement synchrony (standardized beta = −0.1). The relevance of movement synchrony and potential implications for clinical practice are discussed
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