Evidence map›Paper›PMID 42415776›Full record

ArticleSSM. Mental health2026

Acceptability of a digital program for training community health workers in the early detection and referral of schizophrenia in rural India: A mixed-methods pilot study.

John A Naslund, Vidhi Tyagi, Deepak Tugnawat, Anant Bhan, Azaz Khan

Abstract read
In one paragraph

Article in SSM. Mental health, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

John A NaslundDepartment of Global Health and Social Medicine, Harvard Medical School, Boston, MA, United States.ORCID 0000-0001-6777-0104
Vidhi TyagiSangath, Bhopal, India.
Deepak TugnawatSangath, Bhopal, India.
Anant BhanSangath, Bhopal, India.
Azaz KhanSangath, Bhopal, India.

Funding

ESSENCE (Enabling translation of Science to Service to ENhance Depression CarE) Scale-UpU19MH113211 · NIMH · HARVARD MEDICAL SCHOOL · PI PATEL, VIKRAM H · 2017 to 2023
$3.7M
Digital Implementation Support to Achieve Uptake and Integration of Task-Shared Care for Schizophrenia in Primary Care in IndiaR01MH133230 · NIMH · HARVARD MEDICAL SCHOOL · PI Narayana Manjunatha, John A Naslund · 2024 to 2026
$2.1M
NIMH NIH HHS R01 MH133230NIMH NIH HHS U19 MH113211
6 · The paper itself

Abstract

Objective: Delays in detecting and treating schizophrenia result in elevated disability for patients. This mixed-methods pilot study evaluated the feasibility and acceptability of a digital program for training community health workers on early detection and referral of schizophrenia in primary care in rural India. Methods: Using convenience sampling, female community health workers, called ASHAs, enrolled in a large depression care study were invited to complete a supplemental digital training on identifying and responding to schizophrenia. Acceptability of the training was assessed through qualitative focus group discussions and satisfaction questionnaires. Framework analysis was used to code participants' feedback about the training and generate representative themes. Pre-post changes in knowledge about schizophrenia were also explored. Results: In total, N = 20 ASHAs completed the training and participated in focus group discussions. Qualitative data revealed that participants found the training helpful, while they reflected on their limited prior understanding of schizophrenia. Participants emphasized that they had previously observed symptoms of schizophrenia in their communities, yet they did not realize that schizophrenia is a mental health condition that can be treated, and that rehabilitation efforts can be successful. Participants recommended conducting the training with other ASHAs to expand access to this information. Participants' reported high satisfaction with the training, though showed no significant pre-post improvement in knowledge about schizophrenia. Conclusion: A scalable digital training may help equip community health workers to recognize schizophrenia and link people to care. Further evaluation is needed to assess effects on patient outcomes, and integration of schizophrenia care into primary care.

Indexed as

Community health workerDigital technologyGlobal mental healthIndiaRuralSchizophreniaTask-sharing

Identifiers

PMID42415776
PMCPMC13340866

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.