The Quantified Relationship

The growth of self-tracking and personal surveillance has given rise to the Quantified Self movement. Members of this movement seek to enhance their personal well-being, productivity, and self-actualization through the tracking and gamification of personal data. The technologies that make this possible can also track and gamify aspects of our interpersonal, romantic relationships. Several authors have begun to challenge the ethical and normative implications of this development. In this article, we build upon this work to provide a detailed ethical analysis of the Quantified Relationship (QR). We identify eight core objections to the QR and subject them to critical scrutiny. We argue that although critics raise legitimate concerns, there are ways in which tracking technologies can be used to support and facilitate good relationships. We thus adopt a stance of cautious openness toward this technology and advocate the development of a research agenda for the positive use of QR technologies.     

The effects of clinical supervision on supervisees and patients in cognitive behavioral therapy: a systematic review

Clinical supervision is a central part of psychotherapist training but the empirical support for specific supervision theories or features is unclear. The aims of this study were to systematically review the empirical research literature regarding the effects of clinical supervision on therapists’ competences and clinical outcomes within Cognitive Behavior Therapy (CBT). A comprehensive database search resulted in 4103 identified publications. Of these, 133 were scrutinized and in the end 5 studies were included in the review for data synthesis. The five studies were heterogeneous in scope and quality and only one provided firm empirical support for the positive effects of clinical supervision on therapists’ competence. The remaining four studies suffered from methodological weaknesses, but provided some preliminary support that clinical supervision may be beneficiary for novice therapists. No study could show benefits from supervision for patients. The research literature suggests that clinical supervision may have some potential effects on novice therapists’ competence compared to no supervision but the effects on clinical outcomes are still unclear. While bug-in-the-eye live supervision may be more effective than standard delayed supervision, the effects of specific supervision models or features are also unclear. There is a continued need for high-quality empirical studies on the effects of clinical supervision in psychotherapy.     

Information Deprivation Trauma: Definition,Assessment, and Interventions

Information deprivation trauma (IDT; Schild & Dalenberg, 2012b) is a concept that has not been adequately addressed in the trauma literature. IDT is a concept requiring a negative emotional response (e.g., fear, helplessness, horror) consequent to (a) a lack of understanding of the extent, magnitude, consequences, and probability of a current or impending meaningful event; and (b) an inability to access information about this event that would reasonably allow a person to prepare, appropriately respond, or self-protect. Arguments are presented that information deprivation itself might constitute a trauma, in addition to and apart from the possibility that information deprivation might enhance vulnerability to traumatization. Clinical examples are provided, and the Information Deprivation Trauma Interview (IDTI) is introduced for use in clinical and research settings.     

Revising Probabilities and Full Beliefs

Journal of Philosophical Logic - A new formal model of belief dynamics is proposed, in which the epistemic agent has both probabilistic beliefs and full beliefs. The agent has full belief in a...     

Social competence group intervention (SOCO) for children with autism spectrum disorder: A pilot study

This study aimed to describe concept of social competence as a theoretical background for social skills group intervention for children with autism spectrum disorder (ASD). A model of social competence comprised of three components: social skills, social performance, and social adjustment. We also examined the feasibility and preliminary efficacy of the manualized Social Competence group intervention for children with autism spectrum disorder (SOCO) using a variety of outcome measures. The nine-month intervention included children groups, parental support groups and co-operation with teachers. A pilot study involved 23 children aged 7 to 12 years (n = 16 intervention, n = 7 control) and intervention outcomes were measured with questionnaires for parents and teachers, neuropsychological tests, and observations. The parents of the intervention group reported improvements in social skills and social adjustment, whereas the teachers reported increases in social performance. Findings also indicated that affect recognition skills, social overtures, and reactions to peers were improved in the intervention group. Although the evidence of the pilot study should be considered as preliminary, it gives some indication of the feasibility of the SOCO group intervention and supports the usability of the theoretical background and approach for multiple outcome measures.     

Personality Research and Assessment in the Era of Machine Learning

The increasing availability of high-dimensional, fine-grained data about human behaviour, gathered from mobile sensing studies and in the form of digital footprints, is poised to drastically alter the way personality psychologists perform research and undertake personality assessment. These new kinds and quantities of data raise important questions about how to analyse the data and interpret the results appropriately. Machine learning models are well suited to these kinds of data, allowing researchers to model highly complex relationships and to evaluate the generalizability and robustness of their results using resampling methods. The correct usage of machine learning models requires specialized methodological training that considers issues specific to this type of modelling. Here, we first provide a brief overview of past studies using machine learning in personality psychology. Second, we illustrate the main challenges that researchers face when building, interpreting, and validating machine learning models. Third, we discuss the evaluation of personality scales, derived using machine learning methods. Fourth, we highlight some key issues that arise from the use of latent variables in the modelling process. We conclude with an outlook on the future role of machine learning models in personality research and assessment.