Digital phenotyping data and anomaly detection methods to assess changes in mood and anxiety symptoms across a transdiagnostic clinical sample.

INTRODUCTION: Clinical assessment of mood and anxiety change often relies on clinical assessment or self-reported scales. Using smartphone digital phenotyping data and resulting markers of behavior (e.g., sleep) to augment clinical symptom scores offers a scalable and potentially more valid method to understand changes in patients' state. This paper explores the potential of using a combination of active and passive sensors in the context of smartphone-based digital phenotyping to assess mood and anxiety changes in two distinct cohorts of patients to assess the preliminary reliability and validity of this digital phenotyping method. METHODS: Participants from two different cohorts, each n = 76, one with diagnoses of depression/anxiety and the other schizophrenia, utilized mindLAMP to collect active data (e.g., surveys on mood/anxiety), along with passive data consisting of smartphone digital phenotyping data (geolocation, accelerometer, and screen state) for at least 1 month. Using anomaly detection algorithms, we assessed if statistical anomalies in the combination of active and passive data could predict changes in mood/anxiety scores as measured via smartphone surveys. RESULTS: The anomaly detection model was reliably able to predict symptom change of 4 points or greater for depression as measured by the PHQ-9 and anxiety as measured for the GAD-8 for both patient populations, with an area under the ROC curve of 0.65 and 0.80 for each respectively. For both PHQ-9 and GAD-7, these AUCs were maintained when predicting significant symptom change at least 7 days in advance. Active data alone predicted around 52% and 75% of the symptom variability for the depression/anxiety and schizophrenia populations respectively. CONCLUSION: These results indicate the feasibility of anomaly detection for predicting symptom change in transdiagnostic cohorts. These results across different patient groups, different countries, and different sites (India and the US) suggest anomaly detection of smartphone digital phenotyping data may offer a reliable and valid approach to predicting symptom change. Future work should emphasize prospective application of these statistical methods.

Governing the Access to COVID-19 Tools Accelerator: towards greater participation, transparency, and accountability.

The Access to COVID-19 Tools Accelerator (ACT-A) is a multistakeholder initiative quickly constructed in the early months of the COVID-19 pandemic to respond to a catastrophic breakdown in global cooperation. ACT-A is now the largest international effort to achieve equitable access to COVID-19 health technologies, and its governance is a matter of broad public importance. We traced the evolution of ACT-A's governance through publicly available documents and analysed it against three principles embedded in the founding mission statement of ACT-A: participation, transparency, and accountability. We found three challenges to realising these principles. First, the roles of the various organisations in ACT-A decision making are unclear, obscuring who might be accountable to whom and for what. Second, the absence of a clearly defined decision making body; ACT-A instead has multiple centres of legally binding decision making and uneven arrangements for information transparency, inhibiting meaningful participation. Third, the nearly indiscernible role of governments in ACT-A, raising key questions about political legitimacy and channels for public accountability. With global public health and billions in public funding at stake, short-term improvements to governance arrangements can and should now be made. Efforts to strengthen pandemic preparedness for the future require attention to ethical, legitimate arrangements for governance.

Adaptation and translation of a scalable measure for assessing health worker competence to deliver a brief psychological intervention: A case study from central India of its comparison to a performance-based measure.

Efforts to reduce the global burden of common mental disorders have focused on scaling up evidence-based training programs for non-specialist providers to deliver brief psychological interventions. To evaluate these provider training programs, appropriate and scalable assessments of competency need to be developed alongside them. We followed a systematic approach for the cultural adaptation and translation into Hindi of a valid, English, multiple-choice applied knowledge measure to assess non-specialists' competence to deliver a brief psychological intervention for depression in rural India. We then explored the relationship between the performance of 30 non-specialist providers on the same written measure compared with a structured performance-based measure consisting of two role-plays. The results of the multiple-choice assessment had an overall mean score of 37.40 (SD = 11.31) compared to the mean scores of role-play A (the easier role-play) of 43.25 (SD = 14.50) and role-play B (the more difficult role-play) of 43.25 (SD = 13.00). Role-play performance-based measures and written applied knowledge measures represent different approaches with unique strengths and challenges to measuring competence. Scaling up training programs requires the development of scalable methods for competency assessment. Exploring the relationship between these two measures, our team found no apparent differences between the two modes of assessment. Continued comparison of these approaches is needed to determine the consistency of outcomes across the two formats and to link the scores on these measures with clinical performance as reflected by the quality of care and patient outcomes.Trial Registration: ClinicalTrials.gov Identifier: NCT04157816; 8th November 2019.

Development of a Digital Program for Training Community Health Workers in the Detection and Referral of Schizophrenia in Rural India.

This study aimed to develop and assess the acceptability of a digital program for training community health workers (CHWs) in the detection and referral of patients with schizophrenia in community settings in rural India. An iterative design process was employed. First, evidence-based content from existing community programs for schizophrenia care was incorporated into the curriculum, and reviewed by experts to ensure clinical utility and fidelity of the adapted content. Second, CHWs provided feedback on the appropriateness of language, content, and an initial prototype of the digital training program to ensure relevance for the local context. Focus group discussions were then used to understand the acceptability of the digital training prototype and to inform modifications to the design and layout. Qualitative data was analysed using a rapid thematic analysis approach based on predetermined topics pertaining to acceptability of the training content and digital platform. Development of the initial prototype involved content review by 13 subject matter experts with clinical expertise or experience accessing and receiving mental health services, and engagement of 23 CHWs, of which 11 provided feedback for contextualization of the training content and 12 participated in focus group discussions on the acceptability of the prototype. Additionally, 2 service-users with lived experience of schizophrenia contributed to initial testing of the digital training prototype and offered feedback in a focus group discussion. During contextualization of the training content, key feedback pertained to simplifying the language and presentation of the content by removing technical terms and including interactive content and images to enhance interest and engagement with the digital training. During prototype testing, CHWs shared their familiarity with similar symptoms but were unaware of schizophrenia as a treatable illness. They shared that training can help them identify symptoms of schizophrenia and connect patients with specialized care. They were also able to understand misconceptions and discrimination towards people with schizophrenia, and how to address these challenges by supporting others and spreading awareness in their communities. Participants also appreciated the digital training, as it could save them time and could be incorporated within their routine work. This study shows the acceptability of leveraging digital technology for building capacity of CHWs to support early detection and referral of schizophrenia in community settings in rural India. These findings can inform the subsequent evaluation of this digital training program to determine its impact on enhancing the knowledge and skills of CHWs.

Impact of community-based health insurance and economic status on utilization of healthcare services: A household-level cross-sectional survey from rural central India.

Background: . Community-based health insurance (CBHI) is a health-financing mechanism based on voluntary membership, risk pooling, with a non-profit objective and relies on social capital as a driving force. It aims to improve equity in healthcare utilization in the community. We did this study to understand if CBHI schemes reach the poor, improve healthcare utilization and protect them from catastrophic health events. Methods: . Mahatma Gandhi Institute of Medical Sciences (MGIMS), Sevagram, located in Wardha district of Maharashtra, India, runs a variety of CBHI schemes in surrounding villages. Many households (HHs) have opted for these schemes. We conducted a cross-sectional survey of all HHs of 35 villages and collected information about sociodemographics, inpatient healthcare utilization (in previous 5 years), outpatient healthcare utilization (in previous 1 year) and insurance status of the HHs. We derived wealth index based on 33 sociodemographic variables and classified HHs in quintiles of wealth index. We compared the distribution of healthcare utilization variables by insurance status and wealth index and used logistic regression to evaluate if health insurance independently improves healthcare utilization, after adjusting for confounders. Results: . Of a total of 7261 HHs surveyed, 2210 (30.4%) were uninsured, 4153 (57.2%) were insured under MGIMS CBHI schemes, and 898 (12.4%) had family insurance either from MGIMS or other providers. Insured HHs had a higher wealth index compared to uninsured. Mean (SD) hospitalization episodes in an HH were 0.82 (1.75) among uninsured, 1.13 (1.56) in CBHI insured and 1.21 (1.55) in those with family insurance. Within each category, healthcare utilization was lower for poor HHs (lowest quintile of wealth index) and higher for affluent HHs (higher quintiles of wealth index). Among those who were hospitalized, catastrophic health events were less in CBHI insured (7.9%) compared to uninsured (12.3%). After adjusting for socioeconomic status and other confounders, our data suggest that participating in a CBHI scheme increased odds of utilization of inpatient services (OR 1.18; 95% CI 1.04-1.33) and protected from catastrophic health events (OR 0.52; 95% CI 0.43-0.64). Conclusion: . CBHI schemes improve healthcare utilization and protect against catastrophic health expenditure among those who get hospitalized. However, there also exists a socioeconomic gradient both in membership and in utilization of healthcare services favouring those who are more affluent.

Evaluating community engagement in global health research: the need for metrics.

BACKGROUND: Community engagement in research has gained momentum as an approach to improving research, to helping ensure that community concerns are taken into account, and to informing ethical decision-making when research is conducted in contexts of vulnerability. However, guidelines and scholarship regarding community engagement are arguably unsettled, making it difficult to implement and evaluate. DISCUSSION: We describe normative guidelines on community engagement that have been offered by national and international bodies in the context of HIV-related research, which set the stage for similar work in other health related research. Next, we review the scholarly literature regarding community engagement, outlining the diverse ethical goals ascribed to it. We then discuss practical guidelines that have been issued regarding community engagement. There is a lack of consensus regarding the ethical goals and approaches for community engagement, and an associated lack of indicators and metrics for evaluating success in achieving stated goals. To address these gaps we outline a framework for developing indicators for evaluating the contribution of community engagement to ethical goals in health research. There is a critical need to enhance efforts in evaluating community engagement to ensure that the work on the ground reflects the intentions expressed in the guidelines, and to investigate the contribution of specific community engagement practices for making research responsive to community needs and concerns. Evaluation mechanisms should be built into community engagement practices to guide best practices in community engagement and their replication across diverse health research settings.

Saviour siblings in India: A reminder of our existing challenges and biases.

Saviour babies or saviour siblings are conceived specifically to be sources of biological materials - ranging from cord blood, stem cells or even organs - to save another child, usually an older sibling, who is suffering from a disease like thalassemia that can be cured with this biological material. In 2020, the media reported about the birth of India's first saviour baby, in the state of Gujarat [1]. In January 2023, there was a report of the birth of another saviour baby, in the state of Maharashtra [2]. Ethical concerns relating to saviour siblings find a place in the western bioethics discourse. However, it is little discussed in the Indian context.

Trials Methodology Research: what is it and why should India invest in it?

This Viewpoint presents an overview of trials methodology research (TMR) and the case for investing in TMR in India. Randomised controlled trials and other types of clinical research inform evidence-based medicine, but this endeavour is dependent on the quality of such research. TMR is aimed at improving the way in which clinical trials are designed, conducted, analysed, and reported. The evolution of TMR in countries like the UK has been nurtured through dedicated funding support. Similar funding opportunities for TMR in India will help optimise the ethical and methodological rigour of the growing number of trials conducted in India. Such funding could help initiate an interdisciplinary network of key stakeholders in India to lead on TMR priority-setting exercises so that methodological questions of relevance to India are addressed. The establishment of trials methodology hubs will enhance initiatives such as the disease-specific clinical trials networks being set up as part of the National Biopharma Mission in India. We posit that promoting and establishing TMR as a distinct field of study in India will ensure the improvement of our health research ecosystem and call on national and international funding bodies to initiate consultation, consensus building and ringfenced funding for TMR in India.

Experiences of transgender persons in accessing routine healthcare services in India: Findings from a participatory qualitative study.

Despite having a higher burden of health problems, transgender persons face challenges in accessing healthcare in India. Most studies on healthcare access of transgender persons in India focus only on HIV related care, mental healthcare, gender affirmative services or on the ethno-cultural communities or transgender women. This study fills this gap by focusing on diverse gender identities within the transgender community with a specific focus on experiences in accessing general or routine healthcare services. A qualitative descriptive approach was used in this study. 23 in-depth interviews and 6 focus group discussions were conducted virtually and in-person with a total of 63 transgender persons in different regions of India between May and September 2021. The study used a community-based participatory research approach and was informed by the intersectionality approach. Thematic analysis was conducted to analyze the data. Four key themes emerged: (i) intersectional challenges in accessing healthcare start outside of the health system, continue through cisgender-binary-normative health systems that exclude transgender persons; and at the interface with individuals such as health professionals, support staff and bystanders; (ii) the experiences negatively impact transgender persons at an individual level; (iii) in response, transgender persons navigate these challenges across each of the levels: individual, health system level and from outside of the health system. This is a first of its kind qualitative participatory study focusing on routine healthcare services of transgender persons in India. The findings indicate the need to move conversations on trans-inclusion in healthcare from HIV and gender affirmative services to routine comprehensive healthcare services considering the higher burden of health problems in the community and the impact of poor access on their lives and well-being.

COVID-19 Vaccine decision-making: trust among the transgender and disability communities in India.

BACKGROUND: Historical marginalisation and ongoing trust deficits in health and government systems shape present-day vaccine perceptions among marginalised communities. This paper sought to understand the role of trust in decision-making about COVID-19 vaccine uptake in the transgender and disability communities in India. METHODS: Using a participatory approach we interviewed 24 community representatives, identifying themselves as transgender individuals or as persons with disability, and 21 key informants such as vaccine programme managers, vaccine providers, and community advocates. We undertook an inductive thematic analysis of the data using a socio-ecological model. RESULTS: Fear of side effects in relation to specific needs of the two communities and mistrust of systems involved in vaccination shaped four different pathways for vaccine decision-making. Mistrust of systems was influenced by past negative experiences with the health system, creating contexts in which information and misinformation are shared and interpreted. Participants negotiated their doubts about safety and mistrust of systems by interacting with different sources of influence showing patterns of decision-making that are dynamic, context-dependent, and intersectional. CONCLUSION: These findings will help in determining the content, strategies and approaches to equitable vaccine communication for these two communities. The two communities ought to be included in vaccine trials. Vaccine information must respond to the specific needs of these two communities which could be enabled by collaboration and engagement with community members and influencers. Finally, long-term investment towards the needs of marginalised communities is vital to dismantle cycles of marginalisation and distrust and in turn improve vaccine acceptance and uptake.

Scaling up the task-sharing of psychological therapies: A formative study of the PEERS smartphone application for supervision and quality assurance in rural India.

Measurement-based peer supervision is one strategy to assure the quality of psychological treatments delivered by non-mental health specialist providers. In this formative study, we aimed to 1) describe the development and 2) examine the acceptability and feasibility of PEERS (Promoting Effective mental healthcare through peER Supervision)-a novel smartphone app that aims to facilitate registering and scheduling patients, collecting patient outcomes, rating therapy quality and assessing supervision quality-among frontline treatment providers delivering behavioral activation treatment for depression. The PEERS prototype was developed and tested in 2021, and version 1 was launched in 2022. To date, 215 treatment providers (98% female; ages 30-35) in Madhya Pradesh and Goa, India, have been trained to use PEERS and 65.58% have completed the supplemental, virtual PEERS course. Focus group discussions with 98 providers were examined according to four themes-training and education, app effectiveness, user experience and adherence and data privacy and safety. This yielded commonly endorsed facilitators (e.g., collaborative learning through group supervision, the convenience of consolidated patient data), barriers (e.g., difficulties with new technologies) and suggested changes (e.g., esthetic improvements, suicide risk assessment prompt). The PEERS app has the potential to scale measurement-based peer supervision to facilitate quality assurance of psychological treatments across contexts.

Erratum: Scaling up the task-sharing of psychological therapies: A formative study of the PEERS smartphone application for supervision and quality assurance in rural India - CORRIGENDUM.

[This corrects the article DOI: 10.1017/gmh.2024.11.].

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.

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.

Medical ethics teaching in the new undergraduate physiology competency-based curriculum in medical institutions in Delhi: A pilot, feasibility study.

BACKGROUND: Medical ethics teaching has received little attention in India's undergraduate medical curriculum, so the National Medical Commission's formal inclusion of medical ethics in the new competency-based curriculum (CBME) is creditable. However, the policymakers have left out the most crucial stakeholders - the teachers. This study was conducted to find out how physiology educators in Delhi felt about the implementation of ethics teaching in physiology in the CBME. METHODS: This was a pilot, cross-sectional, observational, feasibility study conducted using a questionnaire, involving faculty and senior residents (post-MD) in the departments of Physiology at nine medical colleges in Delhi, conducted over the period from February to October 2020. RESULTS: The response rate was 76% (60/79), of which 40% (24/60) were senior residents and 60% (36/60) were faculty. Around 55% (n=33) felt bioethics and clinical ethics are not synonymous; 53% (n=32) believed ethics education can be accomplished in a large group setting; 75% (n=45) believed it should be the responsibility of the physiology faculty, rather than the clinical faculty, and 61.7% (n=37) wanted it to be included in the formative assessment. The respondents shared ethical concerns that should be included in the physiology curriculum and the best candidates to teach them to achieve integration. Despite the challenges, the majority 65% (n=39) felt ethics in the physiology CBME should be an inseparable part of teaching in all instructional modalities. CONCLUSION: Early clinical exposure was considered preferable to the Attitude, Ethics, and Communication (AETCOM) programme. Using the five W's and one H method, we talk about how our findings can be used as a road map to help physiologists teach ethics to medical students in the new CBME.

Impact of the COVID-19 pandemic on the mental health of transgender persons in India: Findings from an exploratory qualitative study.

Introduction: Transgender persons in India, who are one of the most vulnerable groups, were particularly impacted by the COVID-19 pandemic. Increased risk of COVID-19, challenges with continuing livelihood, uncertainty, and anxiety around the pandemic over pre-existing social discrimination and exclusion pose risk of a mental health impact as well. To investigate this further, this component of a larger study on experiences in healthcare of transgender persons in India during COVID-19 and looks into the question "How did the COVID-19 pandemic impact the mental health of transgender persons in India". Methods: 22 In-depth interviews (IDI) and 6 focus group discussions (FGD) were conducted virtually and in-person with persons self-identifying as transgender or belonging to ethnocultural transgender communities from different parts of India. Community based participatory research approach was used by ensuring representation from the community in the research team and through a series of consultative workshops. Purposive sampling with snowballing was used. The IDIs and FGDs were recorded, transcribed verbatim and analyzed using an inductive thematic analysis. Results: Mental health of transgender persons were affected in the following ways. Firstly, COVID-19, its associated fear and suffering combined with pre-existing inaccessibility of healthcare and reduced access to mental health care affected their mental health. Secondly, unique social support needs of transgender persons were disrupted by pandemic linked restrictions. Thirdly, pre-existing vulnerabilities such as precarious employment and underlying stigma were exacerbated. Finally, gender dysphoria was a key mediating factor in the impact of COVID-19 on mental health with a negative and positive impact. Conclusions: The study reiterates the need to make systemic changes to make mental healthcare and general healthcare services trans-inclusive while also recognizing the essential nature of gender affirmative services and the need to continue them even during emergencies and disaster situations. While this brings out how public health emergencies can exacerbate vulnerabilities, it also shows how the lived mental health experience of transgender person is intricately linked to the way work, travel and housing is structured in our society and therefore points to the structural nature of the linkage between mental health and gender.

Stress Alleviation Methods for community-Based Health ActiVists (SAMBHAV): Development of a digital program for stress reduction for community health workers in rural India.

Background: Community health workers (CHWs) face high levels of stress (both professional and personal) and risk of burnout, highlighting the need for efforts to promote their mental health and well-being. This study seeks to develop a digital stress reduction program for CHWs in rural India. Methods: A stepwise design process was employed to adapt and digitize the evidence-based World Health Organization's Self-Help Plus (SH+) intervention for addressing psychological distress among CHWs in Madhya Pradesh, India. This involved participatory design workshops with CHWs to ensure that the digital stress reduction intervention would be relevant for their needs and the local culture and context. Small groups of CHWs reviewed the adapted program content, allowing the research team to make refinements such as simplifying language, tailoring content to the local setting, and ensuring that program materials are both interesting and relevant. Simultaneously, the research team digitized the content, leveraging a combination of video and graphical content, and uploaded it to the Sangath Learning Management System, a digital platform accessible on a smartphone app. Results: In total, 18 CHWs contributed to the adaptation of the SH+ content and digital intervention development. Participants commented on finding some terms difficult to follow and recommended simplifying the language and providing detailed explanations. Participants offered positive feedback on the adapted content, expressing that they found the examples covered in the material both relatable and relevant to their own personal experiences at home and in the workplace. By combining participants' insights and comments with feedback from content experts, it was possible to finalize a digital Hindi version of the SH+ intervention for CHWs in rural India. Conclusions: This study is timely given the continued detrimental impacts of the COVID-19 pandemic, and offers a promising and potentially scalable digital program to alleviate psychological distress among frontline health workers.

Applying Human-Centered Design in Global Mental Health to Improve Reach Among Underserved Populations in the United States and India.

INTRODUCTION: Human-centered design (HCD) refers to a diverse suite of interactive processes that engage end users in the development of a desired outcome. We showcase how 2 global mental health research teams applied HCD to develop mobile health tools, each directed at reducing treatment gaps in underserved populations. CASE STUDY 1: Refugees face higher risks for mental health problems, yet these communities face structural and cultural barriers that reduce access to and use of services. To address these challenges, the Research Program on Children and Adversity at the Boston College School of Social Work, in partnership with resettled refugee communities in the northeastern United States, used codesign methodology to digitally adapt delivery of the Family Strengthening Intervention for Refugees-a program designed to improve mental health and family functioning among resettled families. We describe how codesign methods support the development of more feasible, acceptable, and sustainable interventions. CASE STUDY 2: Sangath, an NGO in India focused on mental health services research, in partnership with Harvard Medical School, designed and evaluated a digital training program for community health workers to deliver an evidence-based, brief psychological treatment for depression as part of primary care in Madhya Pradesh, India. We describe how HCD was applied to program development and discuss our approach to scaling up training and capacity-building to deliver evidence-based treatment for depression in primary care. IMPLICATIONS: HCD involves a variety of techniques that can be flexibly adapted to engage end users in the conceptualization, implementation, scale-up, and sustainment of global mental health interventions. Community solutions generated using HCD offer important benefits for key stakeholders. We encourage widespread adoption of HCD within global mental health policy, research, and practice, especially for addressing mental health disparities with underserved populations.

"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.