Evidence map›Paper›PMID 39983112›Full record

ArticleJournal of medical Internet research2025

Depression Self-Care Apps' Characteristics and Applicability to Older Adults: Systematic Assessment.

Ruoyu Yin, Dakshayani Rajappan, Laura Martinengo, Frederick H F Chan, Helen Smith, Konstadina Griva, Mythily Subramaniam, Lorainne Tudor Car

Abstract read
In one paragraph

Article in Journal of medical Internet research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Ruoyu YinLee Kong Chian School of Medicine, Nanyang Technological University Singapore, Singapore, Singapore.ORCID 0000-0002-3008-7608
Dakshayani RajappanSchool of Social Sciences, Nanyang Technological University Singapore, Singapore, Singapore.ORCID 0000-0003-3076-9016
Laura MartinengoLee Kong Chian School of Medicine, Nanyang Technological University Singapore, Singapore, Singapore.ORCID 0000-0003-3539-7207
Frederick H F ChanLee Kong Chian School of Medicine, Nanyang Technological University Singapore, Singapore, Singapore.ORCID 0000-0002-9905-3422
Helen SmithLee Kong Chian School of Medicine, Nanyang Technological University Singapore, Singapore, Singapore.ORCID 0000-0003-1883-6124
Konstadina GrivaLee Kong Chian School of Medicine, Nanyang Technological University Singapore, Singapore, Singapore.ORCID 0000-0001-8173-5663
Mythily SubramaniamLee Kong Chian School of Medicine, Nanyang Technological University Singapore, Singapore, Singapore.ORCID 0000-0003-4530-1096
Lorainne Tudor CarLee Kong Chian School of Medicine, Nanyang Technological University Singapore, Singapore, Singapore.ORCID 0000-0001-8414-7664

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundDepression affects 32% of older adults. Loneliness and social isolation are common risk factors for depression in older adults. Mobile apps can connect users and are also effective in depression management in the general population. However, older adults have specific needs in terms of the content of depression self-care interventions and their accessibility. It remains unknown whether existing apps for depression self-care are applicable to older adults.

objectiveThe initial aim of this assessment was to systematically identify interactive depression self-care apps specifically designed for older adults. As we did not find any, we assessed the applicability of existing depression self-care apps to the needs of older adult users.

methodsUsing an established app assessment methodology, we searched for Android and iOS interactive mental health apps providing self-care for depression in English and Chinese in the 42Matters database, Chinese Android app stores, and the first 10 pages of Google and Baidu. We developed an assessment rubric based on extensive revision of the literature. The rubric consisted of the following sections: general characteristics of the apps (eg, developer, platform, and category), app content (eg, epidemiology and risk factors of depression in older adults, techniques to improve mood and well-being), and technical aspects (eg, accessibility, privacy and confidentiality, and engagement).

resultsWe identified 23 apps (n=19, 82.6%, English and n=4, 17.4%, Chinese apps), with 5 (21.7%) iOS-only apps, 3 (13%) Android-only apps, and 15 (65.2%) apps on both platforms. None specifically targeted older adults with depression. All apps were designed by commercial companies and were free to download. Most of the apps incorporated cognitive behavior therapy, mood monitoring, or journaling. All but 3 (13%) apps had a privacy and confidentiality policy. In addition, 14 (60.9%) apps covered depression risk factors in older adults, and 3 (13%) apps delivered information about depression epidemiology in older adults via a chatbot. Furthermore, 17 (73.9%) apps mentioned other topics relevant to older adults, such as pain management, grief, loneliness, and social isolation. Around 30% (n=7) of the apps were supported by an online forum. Common accessibility issues included a lack of adaptations for users with visual or hearing impairments and incompatibility with larger font sizes in the phone settings.

conclusionsThere are no depression apps developed specifically for older adults. Available mobile apps have limited applicability to older adults in terms of their clinical and technical features. Depression self-care apps should aim to incorporate content relevant to older adults, such as grief and loss; include online communities; and improve accessibility to adapt to potential health impairments in older adults.

Indexed as

DepressionMobile ApplicationsSelf CareAgedHumansadaptationsAndroid appappapplicationassessmentbehaviourdepressioneffectivenesselderelderlyimpairmentsmental disordersmental healthmental health appsmental illnessmHealthmobile applicationmobile appsmobile healthmobile interventionsmood monitoringolder adultsonline communitiesself-caresmartphonesystematic assessmenttherapy

Identifiers

PMID39983112
PMCPMC11890144

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.