Digital phenotyping correlates of mobile cognitive measures in schizophrenia: A multisite global mental health feasibility trial.

Traditional cognitive assessments in schizophrenia are time-consuming and necessitate specialized training, making routine evaluation challenging. To overcome these limitations, this study investigates the feasibility and advantages of utilizing smartphone-based assessments to capture both cognitive functioning and digital phenotyping data and compare these results to gold standard measures. We conducted a secondary analysis of data from 76 individuals with schizophrenia, who were recruited across three sites (one in Boston, two in India) was conducted. The open-source mindLAMP smartphone app captured digital phenotyping data and Trails A/B assessments of attention / memory for up to 12 months. The smartphone-cognitive tasks exhibited potential for normal distribution and these scores showed small but significant correlations with the results from the Brief Assessment of Cognition in Schizophrenia, especially the digital span and symbol coding tasks (r2 = 0.21). A small but significant correlation (r2 = 0.29) between smartphone-derived cognitive scores and health-related behaviors such as sleep duration patterns was observed. Smartphone-based cognitive assessments show promise as cross-cultural tools that can capture relevant data on momentary states among individuals with schizophrenia. Cognitive results related to sleep suggest functional applications to digital phenotyping data, and the potential of this multimodal data approach in research.

ESSENCE: An Implementation Research Program to Scale Up Depression Care in Rural Communities.

BACKGROUND: Task sharing may involve training nonspecialist health workers (NSHWs) to deliver brief mental health interventions. This approach is promising for reducing the global mental health treatment gap. However, capacity is limited for training large cadres of frontline workers in low- and middle-income countries, hindering uptake of these interventions at scale. METHODS: The ESSENCE (enabling translation of science to service to enhance depression care) project in Madhya Pradesh, India, aims to address these challenges through two sequential randomized controlled trials. First, a training trial will evaluate the effectiveness and cost-effectiveness of digital training, compared with conventional face-to-face training, in achieving clinical competency of NSHWs in delivering an intervention for depression. This initial trial will be followed by an implementation trial aimed at evaluating the effectiveness of a remote enhanced implementation support, compared with routine implementation support, in addressing barriers to delivery of depression care in primary care facilities. RESULTS: This project involved developing and pilot testing a scalable smartphone-based program for training NSHWs to deliver a brief psychological intervention for depression screening. This initial research guided a randomized trial of a digital training approach with NSHWs to evaluate the effectiveness of this approach. This trial will be followed by a cluster-randomized trial to evaluate the effectiveness of remote implementation support in ensuring efficient delivery of depression care in primary care facilities. NEXT STEPS: Findings from these trials may inform sustainable training and implementation support models to integrate depression care into primary care for scale-up in resource-constrained settings.

"We are everyone's ASHAs but who's there for us?" a qualitative exploration of perceptions of work stress and coping among rural frontline workers in Madhya Pradesh, India.

OBJECTIVE: More than a million female village-level lay providers called 'Accredited Social Health Activists (ASHAs)', who deliver primary care, face high levels of stress due to work demands and low compensation, within the context of poverty and gender inequality. Evidence on ASHAs has focused on workplace challenges from a system perspective, without sufficient probing into individual-level stress. This study aims to gain perspectives into the experiences of work stress, the related health symptoms, and the responses to stress among ASHAs in India. METHODS: Focus group discussions (FGDs) conducted with ASHAs in Sehore district, Madhya Pradesh, were audio-recorded and transcribed. Grounded theory was used to generate themes under the various domains of ASHAs' work and domestic life. We identified pathways between the conditions that trigger stressful events, experiences of these events, resulting perceptions, effects on health and wellbeing, and approaches used by ASHAs to respond to stress. RESULTS: Six FGDs with 59 ASHAs generated the following themes: (a) Facility: Workload, undue pressures, unstructured work; ASHAs' relationships with seniors (e.g., feelings of being disrespected, blamed, or targeted), and low access to physical and administrative resources; (b) Home: Feelings of guilt for putting less time for family/child care; disrespect by the elderly for a poorly incentivised job; (c) Community: Low acceptance by the villagers; caste- and gender-bias; difficult community-level relationships (emotional labour, fear/stigma towards her services); (d) Somatic and psychological symptoms: headache, exhaustion, depressive symptoms (to cite a few); and (e) Responses to stress: Motivation (support from peers, family, a sense of identity/pride, incentives), Individual strengths (e.g., social responsibility), and spiritual recourse mechanisms. CONCLUSIONS: This study will inform the development of a strengths-based coaching intervention to address work stress among ASHAs. The findings are relevant to building the evidence on alleviation of work stress among female frontline cadres in low-resource settings globally.

Relapse prediction in schizophrenia with smartphone digital phenotyping during COVID-19: a prospective, three-site, two-country, longitudinal study.

Smartphone technology provides us with a more convenient and less intrusive method of detecting changes in behavior and symptoms that typically precede schizophrenia relapse. To take advantage of the aforementioned, this study examines the feasibility of predicting schizophrenia relapse by identifying statistically significant anomalies in patient data gathered through mindLAMP, an open-source smartphone app. Participants, recruited in Boston, MA in the United States, and Bangalore and Bhopal in India, were invited to use mindLAMP for up to a year. The passive data (geolocation, accelerometer, and screen state), active data (surveys), and data quality metrics collected by the app were then retroactively fed into a relapse prediction model that utilizes anomaly detection. Overall, anomalies were 2.12 times more frequent in the month preceding a relapse and 2.78 times more frequent in the month preceding and following a relapse compared to intervals without relapses. The anomaly detection model incorporating passive data proved a better predictor of relapse than a naive model utilizing only survey data. These results demonstrate that relapse prediction models utilizing patient data gathered by a smartphone app can warn the clinician and patient of a potential schizophrenia relapse.

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.

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.

A qualitative assessment of barriers and facilitators to implementing recommended infant nutrition practices in Mumbai, India.

BACKGROUND: Childhood malnutrition has been a longstanding crisis in Mumbai, India. Despite national IYCF (Infant Young Child Feeding) guidelines to promote best practices for infant/toddler feeding, nearly one-third of children under age five are stunted or underweight. To improve child nutrition, interventions should address the cultural, social, and environmental influences on infant feeding practices. This study is an in-depth qualitative assessment of family barriers and facilitators to implementing recommended nutrition practices in two Mumbai slum communities, within the context of an existing nutrition education-based intervention by a local non-governmental non-profit organization. METHODS: The population was purposively sampled to represent a variety of household demographics. Data were collected through 33 in-depth semi-structured interviews with caregivers (mothers and paternal grandmothers) of children age 0-2 years. Transcripts were translated and transcribed, and analyzed using qualitative analysis procedures and software. RESULTS: A complex set of barriers and facilitators influence mothers'/caregivers' infant-toddler feeding practices. Most infants were fed complementary foods and non-nutritious processed snacks, counter to IYCF recommendations. Key barriers included: lack of nutrition knowledge and experience, receiving conflicting messages from different sources, limited social support, and poor self-efficacy for maternal decision-making. Key facilitators included: professional nutrition guidance, personal self-efficacy and empowerment, and family support. Interventions to improve child nutrition should address mothers'/caregivers' key barriers and facilitators to recommended infant-toddler feeding practices. CONCLUSIONS: Nutrition interventions should prioritize standard messaging across healthcare providers, engage all family members, target prevention of early introduction of sugary and non-nutritious processed foods, and strengthen maternal self-efficacy for following IYCF recommended guidelines.

Social Media and Mental Health: Benefits, Risks, and Opportunities for Research and Practice.

Social media platforms are popular venues for sharing personal experiences, seeking information, and offering peer-to-peer support among individuals living with mental illness. With significant shortfalls in the availability, quality, and reach of evidence-based mental health services across the United States and globally, social media platforms may afford new opportunities to bridge this gap. However, caution is warranted, as numerous studies highlight risks of social media use for mental health. In this commentary, we consider the role of social media as a potentially viable intervention platform for offering support to persons with mental disorders, promoting engagement and retention in care, and enhancing existing mental health services. Specifically, we summarize current research on the use of social media among mental health service users, and early efforts using social media for the delivery of evidence-based programs. We also review the risks, potential harms, and necessary safety precautions with using social media for mental health. To conclude, we explore opportunities using data science and machine learning, for example by leveraging social media for detecting mental disorders and developing predictive models aimed at characterizing the aetiology and progression of mental disorders. These various efforts using social media, as summarized in this commentary, hold promise for improving the lives of individuals living with mental disorders.

Improvement in Neurocognitive Manifestations with Short-term Multidisciplinary Intervention in DiGeorge Syndrome.

BACKGROUND: DiGeorge syndrome involves deletion of chromosomal region 22q11.2. CASE CHARACTERISTICS: 3-year-old girl presenting with speech delay showed defiant behaviour and sensory concerns. OUTCOME: Multidisciplinary intervention with parental counselling improved communication and social skills. MESSAGE: Cognitive and behavioral issues in DiGeorge syndrome should be addressed through timely, multidisciplinary intervention.