Perceptions of Helpful and Unhelpful Responses to Disclosures of Suicidality in a Sample of Mobile App Users.

OBJECTIVE: Assessment and management of suicide risk is dependent on the individual at risk disclosing their suicidal thoughts. This study analyzed self-reported data collected via Youper, a mental-health app, to explore user experiences with suicide-related disclosure. METHOD: 2,952 international users who endorsed suicidal ideation reported on experiences with suicide-related disclosure. Differences in experiences were examined according to age, gender, and symptoms of psychopathology. RESULTS: Just over half of users (56.17%) shared their suicidal thoughts. The primary reason for not sharing was thinking others would not understand. Of those who had disclosed their suicidal thoughts, 56.31% perceived the listener's response to be helpful, with listening and expressing care identified as most helpful. More severe depression and generalized anxiety symptoms were associated with higher disclosure likelihood, whereas higher borderline-personality and social-anxiety symptoms were associated with lower disclosure likelihood. Perceptions of what users found helpful when they disclosed suicidality varied by gender. Lack of understanding was the most frequently reported unhelpful response universally. CONCLUSION: Findings suggest that listening and expressing care should be prioritized to maximize suicidal individuals' experiences of feeling supported. That said, gender and symptoms impact likelihoods of and experiences with disclosure, which should be considered when receiving suicide-related disclosure.HIGHLIGHTSNearly half of users shared suicidal thoughts and found listener responses helpful.Users most often endorsed listening as helpful and not understanding as unhelpful.Symptom severity and gender informed suicide-related disclosure experiences.

Acceptability and Effectiveness of Artificial Intelligence Therapy for Anxiety and Depression (Youper): Longitudinal Observational Study.

BACKGROUND: Youper is a widely used, commercially available mobile app that uses artificial intelligence therapy for the treatment of anxiety and depression. OBJECTIVE: Our study examined the acceptability and effectiveness of Youper. Further, we tested the cumulative regulation hypothesis, which posits that cumulative emotion regulation successes with repeated intervention engagement will predict longer-term anxiety and depression symptom reduction. METHODS: We examined data from paying Youper users (N=4517) who allowed their data to be used for research. To characterize the acceptability of Youper, we asked users to rate the app on a 5-star scale and measured retention statistics for users' first 4 weeks of subscription. To examine effectiveness, we examined longitudinal measures of anxiety and depression symptoms. To test the cumulative regulation hypothesis, we used the proportion of successful emotion regulation attempts to predict symptom reduction. RESULTS: Youper users rated the app highly (mean 4.36 stars, SD 0.84), and 42.66% (1927/4517) of users were retained by week 4. Symptoms decreased in the first 2 weeks of app use (anxiety: d=0.57; depression: d=0.46). Anxiety improvements were maintained in the subsequent 2 weeks, but depression symptoms increased slightly with a very small effect size (d=0.05). A higher proportion of successful emotion regulation attempts significantly predicted greater anxiety and depression symptom reduction. CONCLUSIONS: Youper is a low-cost, completely self-guided treatment that is accessible to users who may not otherwise access mental health care. Our findings demonstrate the acceptability and effectiveness of Youper as a treatment for anxiety and depression symptoms and support continued study of Youper in a randomized clinical trial.

Impact of the COVID-19 Pandemic on Mental Health among 157,213 Americans.

BACKGROUND: The coronavirus (COVID-19) pandemic presents an unprecedented crisis with potential negative mental health impacts. METHODS: This study used data collected via Youper, a mental health app, from February through July 2020. Youper users (N = 157,213) in the United States self-reported positive and negative emotions and anxiety and depression symptoms during the pandemic. We examined emotions and symptoms before (pre), during (acute), and after (sustained) COVID-related stay-at-home orders. RESULTS: For changes in frequency of reported acute emotions, from the pre to acute periods, anxiety increased while tiredness, calmness, happiness, and optimism decreased. From the acute to sustained periods, sadness, depression, and gratitude increased. Anxiety, stress, and tiredness decreased. Between the pre and sustained periods, sadness and depression increased, as did happiness and calmness. Anxiety and stress decreased. Among symptom measures, anxiety increased initially, from the pre to the acute periods, but later returned to baseline. LIMITATIONS: The study sample was primarily comprised of young people and women. The app does not collect racial or ethnicity data. These factors may limit generalizability. Sample size was also not consistent for all data collected. CONCLUSIONS: The present study suggests that although there were initial negative impacts on emotions and mental health symptoms in the first few weeks, many Americans demonstrated resilience over the following months. The impact of the pandemic on mental health may not be as severe as predicted, although future work is necessary to understand longitudinal effects as the pandemic continues.

Characterization of the p10 gene region of Anticarsia gemmatalis nucleopolyhedrovirus.

The Anticarsia gemmatalis nucleopolyhedrovirus (AgMNPV) p10 gene region was cloned, sequenced and the putative p10 gene expression characterized by Northern-blot analysis. Sequence analysis of the p10 gene region indicated the presence of two complete open reading frames (ORFs) of 713 and 281 nucleotides, which codes for polypeptides of 273 and 93 amino acids, with homology to the P26 and P10 proteins of baculoviruses, respectively. Two additional partial ORFs, coding for partial polypeptides of 110 and 146 amino acids, showed homology to the p22.2 gene of Choristoneura fumiferana nucleopolyhedrovirus (CfMNPV) and p74 genes of different baculoviruses, respectively. A small ORF of 224 nucleotides coding for a protein of 74 amino acids showed homology to the 3'-end of the early p94 gene of AcMNPV. A putative baculovirus very late promoter motif TAAG was identified in the 5'-non-translated region (5'-UTR) at position-54 upstream of the start codon. The consensus polyadenylation sequence AATAAA is present 146nt downstream of the termination codon and the p10 ORF is flanked by the p26 and p74 ORFs. Homology comparisons showed that the P10 protein of AgMNPV is most closely related (82% amino acid sequence identity) to the P10 from the Orgyia pseudotsugata nucleopolyhedrovirus (OpMNPV). Transcriptional analysis of the AgMNPV p10 gene showed that p10-specific transcripts could be detected late in infection.