Digital training for non-specialist health workers to deliver a brief psychological treatment for depression in India: Protocol for a three-arm randomized controlled trial

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.

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.

JE, Nair P, Mathews R, Malik K, Michelson D, Patel V. Developing knowledge-based psychotherapeutic competencies in non-specialist providers: A pre-post study with a nested randomised controlled trial of a coach-supported versus self-guided digital training course for a problem-solving psychological intervention in India

We evaluated a digital learning programme for non-specialists to develop knowledge-based competencies in a problem-solving intervention for adolescents to examine the overall impact of training on knowledge-based competencies among learners; and to compare the effects of two training conditions (self-guided digital training with or without coaching) in a nested parallel, two-arm, individually randomised controlled trial. Eligible participants were 18 or older; fluent in Hindi or English; able to access digital training; and had no prior experience of delivering structured psychotherapies. 277 participants were enrolled from 31 March 2022 to 19 June 2022 of which 230 (83%) completed the study. There was a significant increase in competency score from pre-training (Mean = 7.01, SD = 3.29) to post-training (Mean = 8.88, SD = 3.80), 6 weeks after the pre-training assessment. Knowledge competency scores showed larger increase among participants randomised to the coaching arm (AMD = 1.09, 95% CI 0.26-1.92, p = 0.01) with an effect size (d) of 0.33 (95% CI 0.08-0.58). More participants completed training in the coaching arm (n = 96, 69.6%) compared to the self-guided training arm (n = 56, 40.3%). In conclusion, a coach-supported remote digital training intervention is associated with enhanced participation by learners and increased psychotherapeutic knowledge competencies.

"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.

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.

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.

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.

Schizophrenia Assessment, Referral and Awareness Training for Health Auxiliaries (SARATHA): Protocol for a Mixed-Methods Pilot Study in Rural India

BACKGROUND

Workforce shortages pose major obstacles to the timely detection and treatment of schizophrenia, particularly in low-income and middle-income countries. The SARATHA (Schizophrenia Assessment, Referral, and Awareness Training for Health Auxiliaries) project involves the systematic development, iterative refinement, and pilot testing of a digital program for training community health workers in the early detection and referral of schizophrenia in primary care settings in rural India.

METHODS

SARATHA is a three-phase study. Phase 1 involves consulting with experts and clinicians, and drawing from existing evidence to inform the development of a curriculum for training community health workers. Phase 2 consists of designing and digitizing the training content for delivery on a smartphone app. Design workshops and focus group discussions will be conducted to seek input from community health workers and service users living with schizophrenia to guide revisions and refinements to the program content. Lastly, Phase 3 entails piloting the training program with a target sample of 20 community health workers to assess feasibility and acceptability. Preliminary effectiveness will be explored, as measured by community health workers' changes in knowledge about schizophrenia and the program content after completing the training.

DISCUSSION

If successful, this digital training program will offer a potentially scalable approach for building capacity of frontline community health workers towards reducing delays in early detection of schizophrenia in primary care settings in rural India. This study can inform efforts to improve treatment outcomes for persons living with schizophrenia in low-resource settings.

Psychological Analysis for Depression Detection from Social Networking Sites

Rapid technological advancements are altering people's communication styles. With the growth of the Internet, social networks (Twitter, Facebook, Telegram, and Instagram) have become popular forums for people to share their thoughts, psychological behavior, and emotions. Psychological analysis analyzes text and extracts facts, features, and important information from the opinions of users. Researchers working on psychological analysis rely on social networks for the detection of depression-related behavior and activity. Social networks provide innumerable data on mindsets of a person's onset of depression, such as low sociology and activities such as undergoing medical treatment, a primary emphasis on oneself, and a high rate of activity during the day and night. In this paper, we used five machine learning classifiers-decision trees, K-nearest neighbor, support vector machines, logistic regression, and LSTM-for depression detection in tweets. The dataset is collected in two forms-balanced and imbalanced-where the oversampling of techniques is studied technically. The results show that the LSTM classification model outperforms the other baseline models in the depression detection healthcare approach for both balanced and imbalanced data.

Assessing costs of developing a digital program for training community health workers to deliver treatment for depression: A case study in rural India

Digital technology has emerged as a promising approach for training and building capacity of community health workers in low-income and middle-income countries (LMICs). Little is known about the cost of developing digital training programs in LMICs, which hinders the adoption, implementation, and scaling up of the programs in routine primary care settings. This study assessed the costs of developing a digital program for training community health workers to deliver a psychological treatment for depression in a rural district of Madhya Pradesh, India. We developed survey instruments to document required resources in development, including involved personnel (their roles, responsibilities, time spent, and salaries or payments), information technologies (e.g., smartphones, software programs), and infrastructure-related costs (e.g., vehicle, office space, utilities). Costs were estimated from an accounting perspective. Over a 10-month developmental period, the total costs were 208,814 USD, with the largest portion on human resources (61%, with 14% on management and supervision), followed by information technologies (33%), and infrastructure-related costs (6%). These findings could inform policymakers in LMICs on costs of developing online-training programs, which will be especially useful during the COVID-19 pandemic.

Managing depression in India: Opportunities for a targeted smartphone app

BACKGROUND

More than forty million people suffer from depression in India. A lack of awareness, stigma related to mental health issues, and limited accessibility to treatment services magnify the profound personal and societal impact of depression. Given the rise of smartphones in India, mobile technology can help alleviate some of these depression-related challenges.

AIMS AND METHOD

The aim of this paper is to investigate the essential features of an India targeted depression smartphone app. We conducted an online survey to profile the needs of individuals with depression in India, which varied based on variables such as socioeconomic background, age, level of awareness toward depression, and the extent of exposure to mental health stigma. We also conducted a systematic evaluation of depression apps currently available to Indian users to investigate the user needs that these apps met and the needs that they failed to meet. Based on our findings, we made a set of recommendations related to the essential features of a future app targeted at managing depression in India.

RESULTS

Presently available depression apps fall short in providing some significant features such as local language options, content in audio and video formats, and user location matched resources. These gaps make these apps less than fully relevant to a diverse set of Indian users.

CONCLUSIONS

It is essential to provide depression-related information in a targeted manner depending upon each user's particular needs and context. Potential customizations, such as offering content in local languages and flexible formats (e.g. audio, video, and text); and providing user-relevant diagnostic tools and location matched treatment resources can help improve the suitability of the app for diverse users.

Development and implementation of COVID-19 safety protocols for conducting a randomized trial in global mental health: Field report from Central India

The COVID-19 pandemic impacted ongoing clinical trials globally resulting in the suspension, cancellation or transition to entirely remote implementation of studies. In India, the first countrywide lockdown was imposed in phases starting from March 2020 to June 2020, followed by a continued restriction on in-person activities including study procedures, which halted the ESSENCE (Enabling translation of Science to Service to ENhance Depression CarE) trial activities such as recruitment, consenting, baseline assessment, digital training orientation, face to face training and end-line assessment evaluation. This situation made it imperative to amend procedures in order to mitigate the risk and address safety requirements for participants and the research team. This paper summarizes the need, development and implementation of the protocols focused on risk reduction and safety enhancement with an objective to resume and continue the research activities while ensuring the safety of study participants and research staff. These protocols are comprised of guidelines and recommendations based on existing literature tailored according to different components in each arm of the trial such as guidelines for supervisors, travellers, training/recruitment venue safety procedures, individual safety procedures; and procedures to implement the study activities. These protocols can be adapted by researchers in other settings to conduct research trials during pandemics such as COVID-19.

Identifying challenges and recommendations for advancing global mental health implementation research: A key informant study of the National Institute of Mental Health Scale-Up Hubs

OBJECTIVE

This study explored perspectives of researchers working with the National Institute of Mental Health (NIMH) Scale-Up Hubs, consisting of research partnerships for scaling up mental health interventions in low- and middle-income countries (LMICs), to: 1) identify common barriers to conducting impactful research on the implementation of evidence-based mental health services; and 2) provide recommendations to overcome these implementation challenges.

METHODS

A sequential qualitative approach was employed. First, an open-ended survey was distributed to the 10 Scale-Up Hubs and NIMH program staff asking informants to identify challenges in conducting mental health implementation research in LMICs. Second, survey findings guided an in-person workshop to generate implementation recommendations to inform the field.

RESULTS

In total, 46 respondents completed surveys, and 101 researchers attended the workshop. The workshop produced implementation recommendations for low-resource settings: 1) identifying impact of research on policy and practice; 2) sustaining careers of early researchers in global mental health; 3) engaging policymakers and donors to value mental health research; 4) supporting the workforce for delivering evidence-based treatments for mental disorders; and 5) promoting sustainability of programs.

CONCLUSIONS

These findings can strengthen collaboration between researchers and key stakeholders, and highlight important targets for improving mental health implementation research in LMICs.