Using Smartphone-Based Digital Phenotyping to Predict Relapse in Serious Mental Disorders Among Slum Residents in Dhaka, Bangladesh: Protocol for a Machine Learning Study

This study is one of the first to apply smartphone-based digital phenotyping and machine learning for relapse prediction in low- and middle-income countries' slum settings. The findings will inform scalable, low-cost digital interventions to address the mental health treatment gap in underresourced communities.

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Publication Details

Journal
JMIR Research Protocols
Published
2025-12-12
DOI
https://doi.org/10.2196/79826
Primary Topic
Digital Mental Health Interventions
Type
article
Field-Weighted Citation Impact
0.00
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article

Using Smartphone-Based Digital Phenotyping to Predict Relapse in Serious Mental Disorders Among Slum Residents in Dhaka, Bangladesh: Protocol for a Machine Learning Study

Neelabja Roy, Domenico Giacco, Sagar Jilka, Swaran P. Singh et al.
JMIR Research Protocols
Digital Mental Health Interventions
article

Using Smartphone-Based Digital Phenotyping to Predict Relapse in Serious Mental Disorders Among Slum Residents in Dhaka, Bangladesh: Protocol for a Machine Learning Study

Neelabja Roy, Domenico Giacco, Sagar Jilka, Swaran P. Singh, Chayon Kumar Das, Nadia Alam
article en

Abstract

This study is one of the first to apply smartphone-based digital phenotyping and machine learning for relapse prediction in low- and middle-income countries' slum settings. The findings will inform scalable, low-cost digital interventions to address the mental health treatment gap in underresourced communities.

JMIR Research ProtocolsVol. 15
University of Dhaka (BD), University of Warwick (GB), Coventry and Warwickshire Partnership NHS Trust (GB), National Institute of Mental Health and Neurosciences (IN)
Openalex Percentile: Top 56%
Digital Mental Health Interventions
DOIOpen Access PDFOpenAlex
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Using Smartphone-Based Digital Phenotyping to Predict Relapse in Serious Mental Disorders Among Slum Residents in Dhaka, Bangladesh: Protocol for a Machine Learning Study — Neelabja Roy, Domenico Giacco, et al. · JMIR Research Protocols (2025) | TGRS Research Map | TGRS