Evidence map›Paper›PMID 41947158›Full record

Observational studyBMC medicine2026

Social and digital engagement associated with reduced depressive symptoms in adults aged 50 and older: a multi-country cohort study.

Yaping Wang, Liyuan Tao, Gram Lu, Hongguang Chen, Wenzhan Jing, Chuyao Jin, Jue Liu

Abstract readMulticenter StudyObservational Study
In one paragraph

Observational study in BMC medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

7 authors.

Yaping WangDepartment of Epidemiology and Biostatistics, School of Public Health, Peking University, 38, Xueyuan Road, Haidian District, Beijing, 100191, China.
Liyuan TaoResearch Center of Clinical Epidemiology, Peking University Third Hospital, 49, Huayuan North Road, Haidian District, Beijing, 100191, China.
Gram LuInstitute for Global Health, University College London, Gower Street, London, WC1E 6BT, UK.
Hongguang ChenPeking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), 35, Xueyuan Road, Haidian District, Beijing, 100191, China.
Wenzhan JingSchool of Medicine, Stanford University, 450 Jane Stanford Way, Stanford, CA, 94305, USA.
Chuyao JinSchool of Public Health, The University of Queensland, 266 Herston Road, Brisbane, QLD, 4072, Australia.
Jue LiuDepartment of Epidemiology and Biostatistics, School of Public Health, Peking University, 38, Xueyuan Road, Haidian District, Beijing, 100191, China. jueliu@bjmu.edu.cn.

Funding

National Natural Science Foundation of China 72122001Youth Beijing Scholar Program 087
6 · The paper itself

Abstract

backgroundSocial participation and digital use are associated with reduced depression risk among older adults, but most supporting evidence does not consider both time-invariant and time-varying confounders and is inconsistent. We aimed to evaluate the impact of social participation and digital use on the incidence of depressive symptoms among older adults by a multi-country cohort considering both time-invariant and time-varying counfounders.

methodsWe used data from four nationally representative observational studies across 18 countries (2008-2021): the Health and Retirement Study (HRS), the Survey of Health, Aging and Retirement in Europe (SHARE), the China Health and Retirement Longitudinal Study (CHARLS), and the Mexican Health and Aging Study (MHAS). Participants aged 50 years or older without depressive symptoms at baseline and without related behaviors pre-baseline were included. Interested exposure social participation and digital use were measured by specific questions. Depressive symptoms were assessed using the Center for Epidemiologic Studies Depression Scale (CES-D) and the European Depression Scale (EURO-D). Targeted maximum likelihood estimation method was applied to estimate adjusted relative risks (RRs) and 95% confidence intervals (CIs) for the long-term impact of exposure on depressive symptoms onset.

resultsA total of 69,186 eligible participants were included. At baseline, 77.0%, 44.0%, 34.2%, and 49.8% of participants were exposed to social participation in HRS, SHARE, CHARLS, and MHAS, respectively, and these proportions were 55.7%, 55.9%, 4.5%, and 69.9% for digital use exposure. During follow-up, a total of 18,245 (26.4%) individuals developed depressive symptoms. The RRs (95% CI) of depression risk under social participation versus no social participation were 0.80 (0.68-0.93) in HRS, 0.80 (0.74-0.87) in SHARE, 0.86 (0.77-0.96) in CHARLS, and 0.93 (0.85-1.02) in MHAS. Compared with no digital use, the RRs (95% CI) of depression risk under digital use were 0.88 (0.72-1.08) in HRS, 0.85 (0.77-0.93) in SHARE, 0.75 (0.60-0.92) in CHARLS, and 0.88 (0.79-0.98) in MHAS.

conclusionsEngagement in social participation and digital use are associated with a reduced incidence of depressive symptoms in older adults. In the digital world, besides social participation, promoting digital use for social connection may be an effective strategy for depression prevention in ageing populations.

Indexed as

DepressionSocial ParticipationAgedChinaCohort StudiesDigital MediaEuropeFemaleHumansLongitudinal StudiesMaleMexicoMiddle AgedDepressive symptomsDigital useOlder adultsSocial participation

Identifiers

PMID41947158
PMCPMC13188714

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
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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 Socratic graph.