Emotional Biases and Recurrence in Major Depressive Disorder. Results of 2.5 Years Follow-Up of Drug-Free Cohort Vulnerable for Recurrence

An interesting factor explaining recurrence risk in Major Depressive Disorder (MDD) may be neuropsychological functioning, i.e., processing of emotional stimuli/information. Negatively biased processing of emotional stimuli/information has been found in both acute and (inconclusively) remitted states of MDD, and may be causally related to recurrence of depression. We aimed to investigate self-referent, memory and interpretation biases in recurrently depressed patients in remission and relate these biases to recurrence. We included 69 remitted recurrent MDD-patients (rrMDD-patients), 35–65 years, with ≥2 episodes, voluntarily free of antidepressant maintenance therapy for at least 4 weeks. We tested self-referent biases with an emotional categorization task, bias in emotional memory by free recall of the emotion categorization task 15 min after completing it, and interpretation bias with a facial expression recognition task. We compared these participants with 43 never-depressed controls matched for age, sex and intelligence. We followed the rrMDD-patients for 2.5 years and assessed recurrent depressive episodes by structured interview. The rrMDD-patients showed biases toward emotionally negative stimuli, faster responses to negative self-relevant characteristics in the emotional categorization, better recognition of sad faces, worse recognition of neutral faces with more misclassifications as angry or disgusting faces and less misclassifications as neutral faces (0.001 < p < 0.05). Of these, the number of misclassifications as angry and the overall performance in the emotional memory task were significantly associated with the time to recurrence (p ≤ 0.04), independent of residual symptoms and number of previous episodes. In a support vector machine data-driven model, prediction of recurrence-status could best be achieved (relative to observed recurrence-rate) with demographic and childhood adversity parameters (accuracy 78.1%; 1-sided p = 0.002); neuropsychological tests could not improve this prediction. Our data suggests a persisting (mood-incongruent) emotional bias when patients with recurrent depression are in remission. Moreover, these persisting biases might be mechanistically important for recurrence and prevention thereof

Digital phenotyping and the COVID-19 pandemic:Capturing behavioral change in patients with psychiatric disorders

Contains fulltext : 227418.pdf (publisher's version ) (Closed access)The COVID-19 pandemic has led to unprecedented societal changes limiting us in our mobility and our ability to connect with others in person. These unusual but widespread changes provide a unique opportunity for studies using digital phenotyping tools. Digital phenotyping tools, such as mobile passive monitoring platforms (MPM), provide a new perspective on human behavior and hold promise to improve human behavioral research. However, there is currently little evidence that these tools can reliably detect changes in behavior. Considering the Considering the COVID-19 pandemic as a high impact common environmental factor we studied potential impact on behavior of participants using our mobile passive monitoring platform BEHAPP that was ambulatory tracking them during the COVID-19 pandemic. We pooled data from three MPM studies involving Schizophrenia (SZ), Major Depressive Disorder (MDD) and Bipolar Disorder (BD) patients (N = 12). We compared the data collected on weekdays during three weeks prior and three weeks subsequent to the start of the quarantine. We hypothesized an increase in communication and a decrease in mobility. We observed a significant increase in the total time spent on communication applications (median 179 and 243 min per week respectively, p = 0.005), and a significant decrease in the number of unique places visited (median 6 and 3 visits per week respectively, p = 0.007), while the total time spent at home did not change significantly (median 64 and 77 h per week, respectively, p = 0.594). The data provides a proof of principle that digital phenotyping tools can identify changes in human behavior incited by a common external environmental factor.6 p

Pinard (J.). — Les précipitations et les types de temps à l'origine des crues dans le Nord-Ouest du Massif Central (1953-1962).

Loup Jean. Pinard (J.). — Les précipitations et les types de temps à l'origine des crues dans le Nord-Ouest du Massif Central (1953-1962).. In: Revue de géographie alpine, tome 54, n°2, 1966. pp. 362-363