Evidence map›Paper›PMID 39995949›Full record

ArticleFrontiers in psychiatry2025

The association between digital technology use and depression among older people in China: a moderated mediation model.

Qinmei Wu, Wei He, Jinfu Wang, Litao Du, Xiangli Xue, Qiang He, Yang Pan, Si Chen, Xianliang Zhang

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Frontiers in psychiatry, 2025. 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

9 authors.

Qinmei WuSchool of Physical Education, Shandong University, Jinan, China.
Wei HeChina Institute of Sport Science, Beijing, China.
Jinfu WangSchool of Physical Education, South China University of Technology, Guangzhou, China.
Litao DuSchool of Physical Education, Shandong University, Jinan, China.
Xiangli XueSchool of Physical Education, Shandong University, Jinan, China.
Qiang HeSchool of Physical Education, Shandong University, Jinan, China.
Yang PanSchool of Physical Education, Shandong University, Jinan, China.
Si ChenSchool of Nursing and Rehabilitation, Shandong University, Jinan, China.
Xianliang ZhangSchool of Physical Education, Shandong University, Jinan, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: To investigate the association among multidimensional (Digital engagement, DE; Digital devices, DD; and Digital purpose, DP) digital technology use and depression in older Chinese, considering social participation as a mediator and physical activity level (PAL) as a moderator. Methods: Data on 5,744 participants (aged≥60) were extracted from the China Health and Retirement Longitudinal Study 2020 dataset. Depression was assessed using the 10-item Center for Epidemiologic Studies Depression Scale. Logistic regression examined the association between digital technology use and depression. The PROCESS program's Model 4 evaluated the mediating role of social participation, while Model 7 assessed the moderating role of PAL. Results: Digital technology use was negatively associated with depression (DE, Conclusions: Multidimensional digital technology use showed an association with depression in older adults. Promoting social participation through digital technology use is associated with lower depressive symptom scores, and vigorous PAL further strengthens this association, leading to improved mental health.

Indexed as

depressiondigital technology useolder peoplephysical activitysocial participation

Identifiers

PMID39995949
PMCPMC11847860

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.