Evidence map›Paper›PMID 40856944›Full record

ArticleDiscover mental health2025

Engagement with digital platforms and perspectives on WhatsApp based mental health self-help solution for older adults: a qualitative study from India.

Ravikesh Tripathi, Pramita Sengupta, Abhishek Karishiddimath, Khushboo Khatri, Pratiksha Sharma, Hari Sriram, Srikanth Tk, Seema Mehrotra

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Article in Discover mental health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

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2citing papers in PubMed
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1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

8 authors.

Ravikesh TripathiNational Institute of Mental Health and Neuro Sciences (NIMHANS), Bangalore, India.
Pramita SenguptaNational Institute of Mental Health and Neuro Sciences (NIMHANS), Bangalore, India.
Abhishek KarishiddimathNational Institute of Mental Health and Neuro Sciences (NIMHANS), Bangalore, India.
Khushboo KhatriNational Institute of Mental Health and Neuro Sciences (NIMHANS), Bangalore, India.
Pratiksha SharmaNational Institute of Mental Health and Neuro Sciences (NIMHANS), Bangalore, India.
Hari SriramNational Institute of Mental Health and Neuro Sciences (NIMHANS), Bangalore, India.
Srikanth TkInternational Institute of Information Technology (IIIT), Bangalore, India.
Seema MehrotraNational Institute of Mental Health and Neuro Sciences (NIMHANS), Bangalore, India. drmehrotra_seema@yahoo.com.

Funding

Indian Council of Medical Research EMR/CAR-DEL/2023/07-Dr Seema Mehrotra dated 28/05/2024
6 · The paper itself

Abstract

backgroundThe population of older adults is increasing globally and in India. Depression, anxiety, social isolation, and loneliness commonly impact their well-being. Technology is being explored to improve access to mental health resources, with digital self-help platforms emerging as a promising approach. Given WhatsApp's wide use in India, it holds potential for delivering such support to older adults. This study explored the perspectives of urban Indian older adults on mental health and well-being needs, experiences with digital platforms, and views on a proposed WhatsApp-based self-help platform for mental health.

methodsA qualitative approach was used, involving 19 older adults (aged 55 +), with at least eight years of formal education, and fluency in English/Hindi/Kannada. Individual interviews were conducted, and participants rated potential self-help topics. The Patient Health Questionnaire (PHQ-4) documented distress levels. Data were analyzed using framework analysis.

resultsFive major themes emerged: 'Changes with Ageing', 'Protective Factors for Mental Health', 'Interactions with Digital Platforms', 'Views on WhatsApp', and 'Additional Suggestions'. Older adults reported using digital platforms for recreation, maintaining health, and socializing. They expressed openness to a WhatsApp-based mental health self-help platform with accurate content, simple interface, integration with health services, and access to support. Over three-fourths of participants rated all proposed self-help topics as important.

conclusionThe study highlights the potential acceptability and usability of a WhatsApp-based self-help platform for urban Indian older adults, with participants emphasizing the need for credible content, simplicity, support-access, and relevant self-help content. It offers valuable insights for developing WhatsApp based platforms to support mental health and well-being of older adults.

Identifiers

PMID40856944
PMCPMC12381335

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LicenceCC BY-NC-ND
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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.