Opening the Black Box of Family-Based Treatments: an artificial intelligence Framework to Examine therapeutic alliance and therapist Empathy

The evidence-based treatment (EBT) movement has primarily focused on core intervention content or treatment fidelity and has largely ignored practitioner skills to manage interpersonal process issues that emerge during treatment, especially with difficult-to-treat adolescents (delinquent, substance-using, medical non-adherence) and those of color. A chief complaint of real world practitioners about manualized treatments is the lack of correspondence between following a manual and managing microsocial interpersonal processes (e.g. negative affect) that arise in treating real world clients. Although family-based EBTs share core similarities (e.g. focus on family interactions, emphasis on practitioner engagement, family involvement), most of these treatments do not have an evidence base regarding common implementation and treatment process problems that practitioners experience in delivering particular models, especially in mid-treatment when demands on families to change their behavior is greatest in treatment - a lack that characterizes the field as a whole. Failure to effectively address common interpersonal processes with difficult-to-treat families likely undermines treatment fidelity and sustained use of EBTs, treatment outcome, and contributes to treatment dropout and treatment nonadherence. Recent advancements in wearables, sensing technologies, multivariate time-series analyses, and machine learning allow scientists to make significant advancements in the study of psychotherapy processes by looking under the skin of the provider-client interpersonal interactions that define therapeutic alliance, empathy, and empathic accuracy, along with the predictive validity of these therapy processes (therapeutic alliance, therapist empathy) to treatment outcome. Moreover, assessment of these processes can be extended to develop procedures for training providers to manage difficult interpersonal processes while maintaining a physiological profile that is consistent with astute skills in psychotherapeutic processes. This paper argues for opening the black box of therapy to advance the science of evidence-based psychotherapy by examining the clinical interior of evidence-based treatments to develop the next generation of audit- and feedback- (i.e., systemic review of professional performance) supervision systems

Change Process in Coaching: Interplay of Nonverbal Synchrony, Working Alliance, Self-Regulation, and Goal Attainment

Background: Psychological literature emphasizes that self-regulation is important as goal intentions, goal setting, or implementation intention does not automatically result in effective results in coaching. The question which coaching strategies to apply to strengthening clients' self-regulatory capacities as prerequisites of effective change outcomes remains a black box in coaching.Method: This quantitative study explored clients' self-regulatory mechanisms by addressing how nonverbal synchrony influences clients' cognitive and emotional self-regulation across sessions. One hundred eighty-four coach–client pairs and their evolving change process were observed over 8 months. Video-recorded sessions were assessed with motion energy analysis to automatically capture coach and client nonverbal behavior and quantify nonverbal synchrony at the level of the dyad.Results: Synchrony was differentially associated with clients' post-session questionnaires on result-oriented problem-reflection and self-reflection, affect balance, and working alliance. Network analyses suggested that the association between synchrony and other process variables did not correspond to the previously found positive association between synchrony and positive aspects of alliance or outcome. Instead, this association depended on the level of perceived outcome.Discussion: Coaching success may be predicted by process variables assessed after each session: goal reflection, alliance, and mood all predict successful coaching. The assessment of nonverbal synchrony suggests a state-dependent effect of embodied processes on a coaching outcome that warrants further inspection

NON-VERBAL COMMUNICATION WITH PHYSIOLOGICAL SENSORS. THE AESTHETIC DOMAIN OF WEARABLES AND NEURAL NETWORKS

Historically, communication implies the transfer of information between bodies, yet this phenomenon is constantly adapting to new technological and cultural standards. In a digital context, it’s commonplace to envision systems that revolve around verbal modalities. However, behavioural analysis grounded in psychology research calls attention to the emotional information disclosed by non-verbal social cues, in particular, actions that are involuntary. This notion has circulated heavily into various interdisciplinary computing research fields, from which multiple studies have arisen, correlating non-verbal activity to socio-affective inferences. These are often derived from some form of motion capture and other wearable sensors, measuring the ‘invisible’ bioelectrical changes that occur from inside the body. This thesis proposes a motivation and methodology for using physiological sensory data as an expressive resource for technology-mediated interactions. Initialised from a thorough discussion on state-of-the-art technologies and established design principles regarding this topic, then applied to a novel approach alongside a selection of practice works to compliment this. We advocate for aesthetic experience, experimenting with abstract representations. Atypically from prevailing Affective Computing systems, the intention is not to infer or classify emotion but rather to create new opportunities for rich gestural exchange, unconfined to the verbal domain. Given the preliminary proposition of non-representation, we justify a correspondence with modern Machine Learning and multimedia interaction strategies, applying an iterative, human-centred approach to improve personalisation without the compromising emotional potential of bodily gesture. Where related studies in the past have successfully provoked strong design concepts through innovative fabrications, these are typically limited to simple linear, one-to-one mappings and often neglect multi-user environments; we foresee a vast potential. In our use cases, we adopt neural network architectures to generate highly granular biofeedback from low-dimensional input data. We present the following proof-of-concepts: Breathing Correspondence, a wearable biofeedback system inspired by Somaesthetic design principles; Latent Steps, a real-time auto-encoder to represent bodily experiences from sensor data, designed for dance performance; and Anti-Social Distancing Ensemble, an installation for public space interventions, analysing physical distance to generate a collective soundscape. Key findings are extracted from the individual reports to formulate an extensive technical and theoretical framework around this topic. The projects first aim to embrace some alternative perspectives already established within Affective Computing research. From here, these concepts evolve deeper, bridging theories from contemporary creative and technical practices with the advancement of biomedical technologies.Historicamente, os processos de comunicação implicam a transferência de informação entre organismos, mas este fenómeno está constantemente a adaptar-se a novos padrões tecnológicos e culturais. Num contexto digital, é comum encontrar sistemas que giram em torno de modalidades verbais. Contudo, a análise comportamental fundamentada na investigação psicológica chama a atenção para a informação emocional revelada por sinais sociais não verbais, em particular, acções que são involuntárias. Esta noção circulou fortemente em vários campos interdisciplinares de investigação na área das ciências da computação, dos quais surgiram múltiplos estudos, correlacionando a actividade nãoverbal com inferências sócio-afectivas. Estes são frequentemente derivados de alguma forma de captura de movimento e sensores “wearable”, medindo as alterações bioeléctricas “invisíveis” que ocorrem no interior do corpo. Nesta tese, propomos uma motivação e metodologia para a utilização de dados sensoriais fisiológicos como um recurso expressivo para interacções mediadas pela tecnologia. Iniciada a partir de uma discussão aprofundada sobre tecnologias de ponta e princípios de concepção estabelecidos relativamente a este tópico, depois aplicada a uma nova abordagem, juntamente com uma selecção de trabalhos práticos, para complementar esta. Defendemos a experiência estética, experimentando com representações abstractas. Contrariamente aos sistemas de Computação Afectiva predominantes, a intenção não é inferir ou classificar a emoção, mas sim criar novas oportunidades para uma rica troca gestual, não confinada ao domínio verbal. Dada a proposta preliminar de não representação, justificamos uma correspondência com estratégias modernas de Machine Learning e interacção multimédia, aplicando uma abordagem iterativa e centrada no ser humano para melhorar a personalização sem o potencial emocional comprometedor do gesto corporal. Nos casos em que estudos anteriores demonstraram com sucesso conceitos de design fortes através de fabricações inovadoras, estes limitam-se tipicamente a simples mapeamentos lineares, um-para-um, e muitas vezes negligenciam ambientes multi-utilizadores; com este trabalho, prevemos um potencial alargado. Nos nossos casos de utilização, adoptamos arquitecturas de redes neurais para gerar biofeedback altamente granular a partir de dados de entrada de baixa dimensão. Apresentamos as seguintes provas de conceitos: Breathing Correspondence, um sistema de biofeedback wearable inspirado nos princípios de design somaestético; Latent Steps, um modelo autoencoder em tempo real para representar experiências corporais a partir de dados de sensores, concebido para desempenho de dança; e Anti-Social Distancing Ensemble, uma instalação para intervenções no espaço público, analisando a distância física para gerar uma paisagem sonora colectiva. Os principais resultados são extraídos dos relatórios individuais, para formular um quadro técnico e teórico alargado para expandir sobre este tópico. Os projectos têm como primeiro objectivo abraçar algumas perspectivas alternativas às que já estão estabelecidas no âmbito da investigação da Computação Afectiva. A partir daqui, estes conceitos evoluem mais profundamente, fazendo a ponte entre as teorias das práticas criativas e técnicas contemporâneas com o avanço das tecnologias biomédicas

A multimodal approach to persuasion in oral presentations : the case of conference presentations, research dissemination talks and product pitches

Esta tesis presenta un estudio multimodal y etnográfico del uso de estrategias persuasivas en tres géneros orales: presentaciones en conferencias, charlas de divulgación científica, y presentaciones de productos. Estos géneros comparten un importante componente persuasivo: los tres se dirigen a una audiencia tratando de convencerles del valor de un producto, servicio, o investigación. Sin embargo, se usan en dos contextos profesionales diferentes: el académico y el económico, por lo que cabe esperar que consigan su propósito comunicativo de forma diferente. Por otra parte, recientes estudios muestran como distintos discursos, tienden a adoptar cada vez más rasgos promocionales (promocionalización del discurso). En vista de ello, es factible establecer como hipótesis que los tres géneros están relacionados interdiscursivamente, y un estudio multimodal y etnográfico del uso de la persuasión en dichos géneros puede ayudar a clarificar las relaciones existentes entre ellos, así como sus diferencias.This thesis is a multimodal and ethnographic study of the use of persuasive strategies in three oral genres conference presentations, research dissemination talks and product pitches. These presentations share a strong persuasive component in their communicative purpose: the three of them address an audience to convince them of the value of a product, a service or a piece of research. However, they are used in business and academia by different discourse communities in different contexts, and therefore they can be expected to achieve their communicative goals in different ways. In addition, research suggests that there is a trend towards promotionalization of different discourses, among which academic discourse is included. In view of this, I hypothesize that these three genres are intertextually and interdiscursively related, and that a multimodal and ethnographic study of the use of persuasion in them can help to shed some light on these relationships and differences

Complexity Science in Human Change

This reprint encompasses fourteen contributions that offer avenues towards a better understanding of complex systems in human behavior. The phenomena studied here are generally pattern formation processes that originate in social interaction and psychotherapy. Several accounts are also given of the coordination in body movements and in physiological, neuronal and linguistic processes. A common denominator of such pattern formation is that complexity and entropy of the respective systems become reduced spontaneously, which is the hallmark of self-organization. The various methodological approaches of how to model such processes are presented in some detail. Results from the various methods are systematically compared and discussed. Among these approaches are algorithms for the quantification of synchrony by cross-correlational statistics, surrogate control procedures, recurrence mapping and network models.This volume offers an informative and sophisticated resource for scholars of human change, and as well for students at advanced levels, from graduate to post-doctoral. The reprint is multidisciplinary in nature, binding together the fields of medicine, psychology, physics, and neuroscience