Longitudinal associations of daily affective dynamics with depression, generalized anxiety, and social anxiety symptoms.

BACKGROUND: Low average affect, measured using ecological momentary assessment (EMA), has been consistently linked with depression, generalized anxiety, and social anxiety, supporting trait-like negative affect as a shared underlying feature. However, while theoretical models of emotion regulation would also implicate greater variability in daily affect in these conditions, empirical evidence linking EMA of mood variability with affective disorders is mixed. We used multilevel modeling to test relationships of daily mood and mood variability with depression, generalized anxiety, and social anxiety symptoms. METHODS: Participants (N = 1004; 72.31 % female; Mage = 40.85) responded to EMA of mood 2-3×/day and completed measures of depression (PHQ-8), generalized anxiety (GAD-7), and social anxiety (SPIN) every three weeks. RESULTS: Lower mean affect predicted all symptoms at both the between-person (PHQ-8: ß = -0.486, p < 0.001; GAD-7: ß = -0.429, p < 0.001; SPIN: ß = -0.284, p < 0.001) and within-person (PHQ-8: ß = -0.219, p < 0.001; GAD-7: ß = -0.196, p < 0.001; SPIN: ß = -0.049, p < 0.001) levels. Similarly, at the between-person level, greater affective variability was linked with all three clinical symptoms (PHQ-8: ß = 0.617, p < 0.001; GAD-7: ß = 0.703, p < 0.001; SPIN: ß = 0.449, p < 0.001). However, within-person, affective variability related to depression (ß = 0.144, p < 0.001) and generalized anxiety (ß = 0.150, p < 0.001), but not social anxiety (ß = 0.006, p = 0.712). LIMITATIONS: The COVID-19 pandemic lockdown period occurred midway through the study. CONCLUSION: Findings point to common and specific emotion dynamics that characterize affective symptoms severity, with implications for affective monitoring in a clinical context.

Differences in the functional brain architecture of sustained attention and working memory in youth and adults.

Sustained attention (SA) and working memory (WM) are critical processes, but the brain networks supporting these abilities in development are unknown. We characterized the functional brain architecture of SA and WM in 9- to 11-year-old children and adults. First, we found that adult network predictors of SA generalized to predict individual differences and fluctuations in SA in youth. A WM model predicted WM performance both across and within children-and captured individual differences in later recognition memory-but underperformed in youth relative to adults. We next characterized functional connections differentially related to SA and WM in youth compared to adults. Results revealed 2 network configurations: a dominant architecture predicting performance in both age groups and a secondary architecture, more prominent for WM than SA, predicting performance in each age group differently. Thus, functional connectivity (FC) predicts SA and WM in youth, with networks predicting WM performance differing more between youths and adults than those predicting SA.

Smartphone digital phenotyping, surveys, and cognitive assessments for global mental health: Initial data and clinical correlations from an international first episode psychosis study.

Objective: To examine feasibility and acceptability of smartphone mental health app use for symptom, cognitive, and digital phenotyping monitoring among people with schizophrenia in India and the United States. Methods: Participants in Boston, USA and Bhopal and Bangalore, India used a smartphone app to monitor symptoms, play cognitive games, access relaxation and psychoeducation resources and for one month, with an initial clinical and cognitive assessment and a one-month follow-up clinical assessment. Engagement with the app was compared between study sites, by clinical symptom severity and by cognitive functioning. Digital phenotyping data collection was also compared between three sites. Results: By Kruskal-Wallis rank-sum test, we found no difference between app activities completed or digital phenotyping data collected across the three study sites. App use also did not correlate to clinical or cognitive assessment scores. When using the app for symptom monitoring, preliminary findings suggest app-based assessment correlate with standard cognitive and clinical assessments. Conclusions: Smartphone app for symptom monitoring and digital phenotyping for individuals with schizophrenia appears feasible and acceptable in a global context. Clinical utility of this app for real-time assessments is promising, but further research is necessary to determine the long-term efficacy and generalizability for serious mental illness.

Current directions in digital interventions for mood and anxiety disorders.

PURPOSE OF REVIEW: The purpose of this review is to provide an overview of the current scope of digital interventions for anxiety and mood disorders, with a focus on smartphone apps, for clinicians and mental healthcare providers. RECENT FINDINGS: Of the 11 randomized controlled trials analyzed, 7 showed evidence that guided digital interventions (those supported by humans) were effective in improving anxiety and mood symptoms, and 3 showed evidence that unguided (those not supported by humans) interventions were effective. Psychoeducation was the most popular feature of both guided and unguided interventions. Attrition was highest (50%) in the unguided app-based intervention and lowest in the guided interventions. Many studies lacked active control groups and comparison was often made to a nondigital or waitlist control condition. SUMMARY: Guided digital interventions continue to show promising results and can be used to enhance clinical care with minimal resources although more direct comparisons to existing treatments are necessary to understand their actual efficacy. Unguided self-help apps and chatbots remain promising, but more work is necessary to understand the real-world engagement and efficacy of these interventions.

A qualitative exploration of perceived needs and barriers of individuals with schizophrenia, caregivers and clinicians in using mental health applications in Madhya Pradesh, India.

Introduction: About 3.5 million people are living with schizophrenia in India, with most failing to receive minimally adequate care. Digital mental health applications could potentially decrease this treatment gap; however, these applications should be tailored to meet the needs and overcoming barriers of its end-users to ensure their adoption and sustained usage. Few studies in India have explored the perspectives of target stakeholders to understand how digital tools could be viable for supporting care. Therefore, this study explores the perceived needs and barriers of patients with schizophrenia, caregivers and clinicians in using digital mental health applications. Methods: Focus group discussions (FGDs) were conducted with patients having schizophrenia attending outpatient clinics at a government tertiary hospital, and their caregivers, and mental health clinicians in Bhopal, Madhya Pradesh, India. FGDs were audio-recorded and coded. Framework analysis was employed to guide the analysis, involving deductive and inductive generation of themes, data triangulation and comparison of perspectives between participant groups. Results: Six FGDs were conducted with individuals with schizophrenia (n â€‹= â€‹11), their caregivers (n â€‹= â€‹14), and mental health clinicians (n â€‹= â€‹19). Four a priori themes were established: a) Prior experiences with health applications; b) Content of a mental health application; c) Involvement of caregivers in mental health application usage and d) Supporting doctors' work through mental health applications. Additionally, two themes were generated inductively: a) Qualities of a mental health application and b) Data privacy and confidentiality. Conclusion: Exploration of stakeholder perspectives on the content, features, and uses of mental health applications is crucial to yield initial insights about the use of these digital programs in India. This study generated a multitude of suggestions on app functionality and components, which can guide ongoing efforts to develop and deliver digital mental health applications for patients living with schizophrenia in low-resource settings, with limited access to mental health services.

Cross cultural and global uses of a digital mental health app: results of focus groups with clinicians, patients and family members in India and the United States.

BACKGROUND: Despite significant advancements in healthcare technology, digital health solutions - especially those for serious mental illnesses - continue to fall short of their potential across both clinical practice and efficacy. The utility and impact of medicine, including digital medicine, hinges on relationships, trust, and engagement, particularly in the field of mental health. This paper details results from Phase 1 of a two-part study that seeks to engage people with schizophrenia, their family members, and clinicians in co-designing a digital mental health platform for use across different cultures and contexts in the United States and India. METHODS: Each site interviewed a mix of clinicians, patients, and their family members in focus groups (n = 20) of two to six participants. Open-ended questions and discussions inquired about their own smartphone use and, after a demonstration of the mindLAMP platform, specific feedback on the app's utility, design, and functionality. RESULTS: Our results based on thematic analysis indicate three common themes: increased use and interest in technology during coronavirus disease 2019 (COVID-19), concerns over how data are used and shared, and a desire for concurrent human interaction to support app engagement. CONCLUSION: People with schizophrenia, their family members, and clinicians are open to integrating technology into treatment to better understand their condition and help inform treatment. However, app engagement is dependent on technology that is complementary - not substitutive - of therapeutic care from a clinician.