Evidence map›Paper›PMID 41275170›Full record

ArticleBMC public health2025

Exploring the relationship between smartphone use diversity and depressive symptoms among older adults.

Siying Wei, Yan Yue, Jiayu Yang, Jiayue Dan, Kangle He, Xiaofeng Xie

Abstract read
In one paragraph

Article in BMC public health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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

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3 · Its place in the literature

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1 citing paper in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Siying Wei *West China School of Nursing, West China Hospital, Sichuan University, No.37, Guoxue Alley, Wuhou District, Chengdu, 610041, China.
Yan Yue *West China School of Nursing, West China Hospital, Sichuan University, No.37, Guoxue Alley, Wuhou District, Chengdu, 610041, China.
Jiayu Yang *West China School of Nursing, West China Hospital, Sichuan University, No.37, Guoxue Alley, Wuhou District, Chengdu, 610041, China.
Jiayue DanWest China School of Nursing, West China Hospital, Sichuan University, No.37, Guoxue Alley, Wuhou District, Chengdu, 610041, China.
Kangle HeWest China School of Nursing, West China Hospital, Sichuan University, No.37, Guoxue Alley, Wuhou District, Chengdu, 610041, China.
Xiaofeng XieWest China School of Nursing, West China Hospital, Sichuan University, No.37, Guoxue Alley, Wuhou District, Chengdu, 610041, China. xiaofeng_xie@scu.edu.cn.

Funding

Humanities and Social Science Fund of Ministry of Education of China 21YJC630142National Natural Science Foundation of China 72271172
6 · The paper itself

Abstract

backgroundWith the population aging and the popularization of intelligent technology, smartphones have emerged as a significant factor influencing the depressive symptoms of older adults through diversified functionalities, yet evidence remains limited. This study aims to determine the impact of the smartphone use diversity on depressive symptoms among older adults in China, and whether it varied by gender, residence, and education.

methodsThis study used data from the China Health and Retirement Longitudinal Study (CHARLS). We quantified smartphone use diversity via a composite index to measure smartphone usage capabilities among older adults. Multilevel logistic regression and propensity score matching were applied to analyze associations, with heterogeneity tests across gender, residence, and education. Additionally, latent class analysis (LCA) was conducted to identify distinct patterns of smartphone use and examine their associations with depressive symptoms.

resultsHigher smartphone use diversity was significantly associated with reduced depressive symptoms (OR = 0.493, 95% CI: 0.376-0.646; P < 0.001) among older adults, even after adjusting for confounders. The protective effect was stronger in males (OR = 0.482, 95% CI: 0.333-0.697, P < 0.001), urban residents (OR = 0.450, 95% CI: 0.308-0.656, P < 0.001), and those with higher education (OR = 0.488, 95% CI: 0.314-0.760, P < 0.01). Latent class analysis further revealed two distinct usage patterns: "Limited Users" and "Multi-functional Users". Compared with Limited Users, Multi-functional Users showed a significantly lower risk of depressive symptoms in both years (OR = 0.51 in 2018; OR = 0.66 in 2020).

conclusionSmartphone use diversity may mitigate depressive symptoms among older adults, particularly within specific subgroups. The identification of distinct usage patterns underscores the heterogeneity in digital engagement among older adults. These findings provide empirical support for technology-enabled mental health promotion interventions targeting older adults. Therefore, integrating digital literacy programs and diverse smartphone use initiatives into public health strategies aimed at enhancing mental well-being in aging populations is essential.

Indexed as

DepressionSmartphoneAgedAged, 80 and overChinaFemaleHumansLongitudinal StudiesMaleMiddle AgedSex FactorsDepressive symptomsMultilevel logistic regressionOlder adultsPropensity score matchingSmartphone use diversity

Identifiers

PMID41275170
PMCPMC12754972

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