The Experience of Psychosis in Psychiatric Inpatients During the COVID-19 Pandemic Among Unhoused Individuals.

This research investigates the impact of Coronavirus-2019 on individuals without housing and experiencing psychosis using semi-structured qualitative interviews and a case study format. We found that for our participants, life in the pandemic was generally more difficult and filled with violence. Further, the pandemic seemed to impact the content of psychosis directly, such that in some cases voices referred to politics around the virus. Being unhoused during the pandemic may increase the sense of powerlessness, social defeat, and the sense of failure in social interactions. Despite national and local measures to mitigate virus spread in unhoused communities, the pandemic seemed to be particularly hard on those who were unhoused. This research should support our efforts to see access to secure housing as a human rights issue.

Digital Mental Health Interventions for Depression: Scoping Review of User Engagement.

BACKGROUND: While many digital mental health interventions (DMHIs) have been found to be efficacious, patient engagement with DMHIs has increasingly emerged as a concern for implementation in real-world clinical settings. To address engagement, we must first understand what standard engagement levels are in the context of randomized controlled trials (RCTs) and how these compare with other treatments. OBJECTIVE: This scoping review aims to examine the state of reporting on intervention engagement in RCTs of mobile app-based interventions intended to treat symptoms of depression. We sought to identify what engagement metrics are and are not routinely reported as well as what the metrics that are reported reflect about standard engagement levels. METHODS: We conducted a systematic search of 7 databases to identify studies meeting our eligibility criteria, namely, RCTs that evaluated use of a mobile app-based intervention in adults, for which depressive symptoms were a primary outcome of interest. We then extracted 2 kinds of information from each article: intervention details and indices of DMHI engagement. A 5-element framework of minimum necessary DMHI engagement reporting was derived by our team and guided our data extraction. This framework included (1) recommended app use as communicated to participants at enrollment and, when reported, app adherence criteria; (2) rate of intervention uptake among those assigned to the intervention; (3) level of app use metrics reported, specifically number of uses and time spent using the app; (4) duration of app use metrics (ie, weekly use patterns); and (5) number of intervention completers. RESULTS: Database searching yielded 2083 unique records. Of these, 22 studies were eligible for inclusion. Only 64% (14/22) of studies included in this review specified rate of intervention uptake. Level of use metrics was only reported in 59% (13/22) of the studies reviewed. Approximately one-quarter of the studies (5/22, 23%) reported duration of use metrics. Only half (11/22, 50%) of the studies reported the number of participants who completed the app-based components of the intervention as intended or other metrics related to completion. Findings in those studies reporting metrics related to intervention completion indicated that between 14.4% and 93.0% of participants randomized to a DMHI condition completed the intervention as intended or according to a specified adherence criteria. CONCLUSIONS: Findings suggest that engagement was underreported and widely varied. It was not uncommon to see completion rates at or below 50% (11/22) of those participants randomized to a treatment condition or to simply see completion rates not reported at all. This variability in reporting suggests a failure to establish sufficient reporting standards and limits the conclusions that can be drawn about level of engagement with DMHIs. Based on these findings, the 5-element framework applied in this review may be useful as a minimum necessary standard for DMHI engagement reporting.

The effect of aging on facial emotion recognition in bipolar disorder.

OBJECTIVE: Convergent data point to an exaggerated negativity bias in bipolar disorder (BD), and little is known about whether people with BD experience the 'positivity effect' with increasing age. METHOD: This is a cross sectional study of 202 participants with BD aged 18-65, and a sample (n = 53) of healthy controls (HCs). Participants completed the CANTAB Emotion Recognition Task (ERT). Using analysis of variance, we tested for a main effect of age, diagnosis, and an interaction of age x diagnosis on both negative and positive conditions. RESULTS: We observed increased accuracy in identifying positive stimuli in the HC sample as a function of increasing age, a pattern that was not seen in participants with BD. Specifically, there was a significant diagnosis by age cohort interaction on ERT performance that was specific to the identification of happiness, where the Later Adulthood cohort of HCs was more accurate when identifying happy faces relative to the same cohort of BD patients. CONCLUSION: Later life looks different for people with BD. With an aging population globally, gaining a clearer picture of the effects of recurrent mood dysregulation on the brain will be critical in guiding efforts to effectively optimize outcomes in older adults with BD.