Increased attention among the research community in exploring underlying mechanisms of emotion regulation has prompted a growth of experimental works in this field. Empirical studies have mainly focused on self‐reports, brain imaging, and electrophysiological measures, with only a few works exploring peripheral physiology. Additionally, most of such studies have not considered the specific stimuli content, even though prior literature has shown relevant differences in psychophysiological and subjective responses depending on picture categories. The current study assessed several peripheral correlates (startle amplitude, electrodermal changes, heart rate) of emotion regulation processes in a sample of 122 healthy participants. The task consisted of voluntary reappraisal of negative emotions prompted by unpleasant pictures (threat to others and victims), compared to a nonregulation control condition (looking at exemplars of the same categories and household objects). Results showed an effect of emotion regulation instructions in all psychophysiological and subjective measures. In peripheral physiology, greater responses were observed specifically when increasing negative emotions, concurring with previous research. Regarding specific content, our findings evidence a similar emotion regulation pattern, independently of the unpleasant category, suggesting a plausible effect of cognitive variables (such as cognitive effort) during voluntary reappraisal for both categories.

No abstract

Cognitive reappraisal and acceptance strategies have been shown to be effective in reducing pain experience and increasing pain tolerance. However, no systematic reviews have focused on the relationship between the use of these two strategies and peripheral physiological correlates when pain is experimentally induced. This systematic review aims to summarize the existing literature that explores the relationship between emotion regulation strategies (i.e., cognitive reappraisal and acceptance) and peripheral correlates of the autonomic nervous system and facial electromyography, such as affect-modulated responses and corrugator activity, on laboratory tasks where pain is induced. The systematic review identifies nine experimental studies that meet our inclusion criteria, none of which compare these strategies. Although cognitive reappraisal and acceptance strategies appear to be associated with decreased psychological responses, mixed results were found for the effects of the use of both strategies on all the physiological correlates. These inconsistencies between the studies might be explained by the high methodological heterogeneity in the task designs, as well as a lack of consistency between the instructions used in the different studies for cognitive reappraisal, acceptance, and the control conditions.

Emotional disorders are the most common mental disorders globally. Psychological treatments have been found to be useful for a significant number of cases, but up to 40% of patients do not respond to psychotherapy as expected. Artificial intelligence (AI) methods might enhance psychotherapy by providing therapists and patients with real- or close to real-time recommendations according to the patient’s response to treatment. The goal of this investigation is to systematically review the evidence on the use of AI-based methods to enhance outcomes in psychological interventions in real-time or close to real-time. The search included studies indexed in the electronic databases Scopus, Pubmed, Web of Science, and Cochrane Library. The terms used for the electronic search included variations of the words “psychotherapy”, “artificial intelligence”, and “emotional disorders”. From the 85 full texts assessed, only 10 studies met our eligibility criteria. In these, the most frequently used AI technique was conversational AI agents, which are chatbots based on software that can be accessed online with a computer or a smartphone. Overall, the reviewed investigations indicated significant positive consequences of using AI to enhance psychotherapy and reduce clinical symptomatology. Additionally, most studies reported high satisfaction, engagement, and retention rates when implementing AI to enhance psychotherapy in real- or close to real-time. Despite the potential of AI to make interventions more flexible and tailored to patients’ needs, more methodologically robust studies are needed.

No abstract