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The Systematic Medical Appraisal Referral and Treatment Mental Health Project: Quasi-Experimental Study to Evaluate a Technology-Enabled Mental Health Services Delivery Model Implemented in Rural India (Preprint)

Authors :
Pallab K Maulik
Siddhardha Devarapalli
Sudha Kallakuri
Amritendu Bhattacharya
David Peiris
Anushka Patel
Publication Year :
2019
Publisher :
JMIR Publications Inc., 2019.

Abstract

BACKGROUND Although around 10% of Indians experience depression, anxiety, or alcohol use disorders, very few receive adequate mental health care, especially in rural communities. Stigma and limited availability of mental health services contribute to this treatment gap. The Systematic Medical Appraisal Referral and Treatment Mental Health project aimed to address this gap. OBJECTIVE This study aimed to evaluate the effectiveness of an intervention in increasing the use of mental health services and reducing depression and anxiety scores among individuals at high risk of common mental disorders. METHODS A before-after study was conducted from 2014 to 2019 in 12 villages in Andhra Pradesh, India. The intervention comprised a community antistigma campaign, with the training of lay village health workers and primary care doctors to identify and manage individuals with stress, depression, and suicide risk using an electronic clinical decision support system. RESULTS In total, 900 of 22,046 (4.08%) adults screened by health workers had increased stress, depression, or suicide risk and were referred to a primary care doctor. At follow-up, 731 out of 900 (81.2%) reported visiting the doctor for their mental health symptoms, compared with 3.3% (30/900) at baseline (odds ratio 133.3, 95% CI 89.0 to 199.7; PPP CONCLUSIONS The intervention was associated with a marked increase in service uptake and clinically important reductions in depression and anxiety symptom scores. This will be further evaluated in a large-scale cluster randomized controlled trial.

Details

Database :
OpenAIRE
Accession number :
edsair.doi...........734a65aad38d00a1b2dbeba7edad3ce3
Full Text :
https://doi.org/10.2196/preprints.15553