Increased activity in the left superior frontal gyrus may be characteristic of manic episodes in PBD patients, and such a disparity between manic and euthymic phrases may attribute to more severe emotional dysregulation. Increased activity in the left superior frontal gyrus may be characteristic of manic episodes in PBD patients, and such a disparity between manic and euthymic phrases may attribute to more severe emotional dysregulation. A smartphone application (i.e., SPSRS) was developed to help people with subthreshold depression (StD) improve depressive symptoms by presenting positive word stimuli in videos. However, to date, no randomized controlled trials (RCTs) were conducted to investigate SPSRS application interventions for depressive symptoms in people with StD. Therefore, a pilot RCT was conducted to assess the preliminary efficacy of the SPSRS application intervention for people with StD. In a pilot RCT, 32 participants (female=34.4%, mean age=20.06, SD=1.24) with StD were randomized to SPSRS application intervention for approximately 10 min/a day for 5 weeks (experimental group; n=16) or no intervention (wait list control group; n=16). The primary outcome is the change from baseline in the Center for Epidemiologic Studies Depression Scale (CES-D) score after the 5-week intervention. The secondary outcomes are the change from baseline in the Kessler Screening Scale for Psychological Distress (K-6) score and the Generalized Anxiety Disorder 7-item scale (GAD-7) after the 5-week intervention. No participants dropped out of the study. The experimental group displayed medium, small, and small improvements in CES-D, K-6, and GAD-7 scores (adjusted Hedge's g=-0.64, -0.29, and -0.40), respectively, compared with control. The observed effects must be considered preliminary due to the small sample size. The results suggest the potential of intervention using the SPSRS application to reduce depressive symptoms in people with StD. Future studies should replicate these findings in a full-scale RCT. The results suggest the potential of intervention using the SPSRS application to reduce depressive symptoms in people with StD. Future studies should replicate these findings in a full-scale RCT. The status of melancholia as a categorical or dimensional condition remains unclear, and no measure of melancholia has achieved definitive status. This study aimed to use a machine learning approach to assess whether a pre-established cut-off score on the Sydney Melancholia Prototype Index (SMPI) provided clear differentiation of melancholic/non-melancholic depression, and to identify the items making the most distinct contribution. We analysed amalgamated data sets of 1513 clinically depressed patients assessed via the clinician-rated version of the SMPI (SMPI-CR). We also evaluated the self-report version of the SMPI (SMPI-SR) in a combined clinical/community sample of 2025 depressed patients and senior high school students. Rule ensembles were derived in which the outcome measure was the presence/absence of melancholia (defined as scoring at or above a SMPI cut-off score that had been established in previous studies) and the predictive variables were the individual SMPI items. The pre-established SMPelancholia is categorically or dimensionally distinct from non-melancholic depression. Recently, mindfulness-based therapies have emerged as a treatment modality for OCD, but there is sparse controlled data. We report the efficacy of mindfulness-based cognitive therapy (MBCT) in treating OCD in comparison with stress management training (SMT). 60 outpatients with DSM-IV-TR OCD attending a specialty OCD clinic were randomly assigned in 11 ratioto either MBCT (n=30) or SMT (n= 30). Both the groups received 12 weekly sessions of assigned intervention. https://www.selleckchem.com/products/zasocitinib.html An independent blind rater assessed the primary outcome measure at baseline and at the end of 12 weeks. Significantly greater proportion of patients responded to MBCT than to SMT (80% vs. 27%, P <0.001). In the linear mixed-effects modelling for intent-to-treat analysis, there was a significant reduction in the illness severity measured using the Yale-Brown Obsessive-Compulsive Scale, obsessive beliefs of 'responsibility/threat estimation' and 'perfectionism/intolerance of uncertainty' measured using the Obsessive Beliefs Questionnaire and anxiety. Small sample size with a relatively high attrition in the control group. Lack of a cognitive behaviour therapy (CBT) control group. Mindfulness-based cognitive therapy is efficacious in the treatment of OCD. Future studies should compare MBCT with CBT in larger representative samples and also examine the sustainability of change in longitudinal studies. Mindfulness-based cognitive therapy is efficacious in the treatment of OCD. Future studies should compare MBCT with CBT in larger representative samples and also examine the sustainability of change in longitudinal studies. Recent studies have demonstrated that passive smartphone and wearable sensor data collected throughout daily life can predict anxiety symptoms cross-sectionally. However, to date, no research has demonstrated the capacity for these digital biomarkers to predict long-term prognosis. We utilized deep learning models based on wearable sensor technology to predict long-term (17-18-year) deterioration in generalized anxiety disorder and panic disorder symptoms from actigraphy data on daytime movement and nighttime sleeping patterns. As part of Midlife in the United States (MIDUS), a national longitudinal study of health and well-being, subjects (N=265) (i) completed a phone-based interview that assessed generalized anxiety disorder and panic disorder symptoms at enrollment, (ii) participated in a one-week actigraphy study 9-14 years later, and (iii) completed a long-term follow-up, phone-based interview to quantify generalized anxiety disorder and panic disorder symptoms 17-18 years from initial enrollment. A deep auto-encoder paired with a multi-layered ensemble deep learning model was leveraged to predict whether participants experienced increased anxiety disorder symptoms across this 17-18 year period. Out-of-sample cross-validated results suggested that wearable movement data could significantly predict which individuals would experience symptom deterioration (AUC=0.696, CI [0.598, 0.793], 84.6% sensitivity, 52.7% specificity, balanced accuracy=68.7%). Passive wearable actigraphy data could be utilized to predict long-term deterioration of anxiety disorder symptoms. Future studies should examine whether these methods could be implemented to prevent deterioration of anxiety disorder symptoms. Passive wearable actigraphy data could be utilized to predict long-term deterioration of anxiety disorder symptoms. Future studies should examine whether these methods could be implemented to prevent deterioration of anxiety disorder symptoms.