Evidence map›Paper›PMID 42293619›Full record

ArticleFrontiers in public health2026

Digital transformation and mental health among young adults.

Qin Zhang, Cuifang Du, Yuanchao Wang

Abstract read
In one paragraph

Article in Frontiers in public health, 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

3 authors.

Qin ZhangSchool of Philosophy and Social Development, Shandong University, Jinan, China.
Cuifang DuSchool of International Cooperation and Exchange, Weifang Engineering Vocational College, Weifang, China.
Yuanchao WangSchool of Philosophy and Social Development, Shandong University, Jinan, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Digital transformation is one of the most pervasive social changes of the 21st century. Compared with children and older adults, young adults are most profoundly affected by digital transformation. This study examines the trajectory of young adults' mental health amid digital transformation, the association between internet use and young adults' mental health, and potential heterogeneity. Methods: Drawing on data from the 2013 and 2023 waves of the Chinese General Social Survey (CGSS) and official statistics from the National Bureau of Statistics of China, this study constructed a composite indicator of mental health using principal component analysis (PCA) and factor analysis (FA), and examined the association between digital transformation and young adults' mental health. Results: Against the backdrop of digital transformation, young adults' mental health declined. Internet use had a significant and robust non-linear association with young adults' mental health, with moderate use associated with better mental health. The positive association was stronger among men and urban residents, but weaker among young adults with higher educational attainment, higher socioeconomic status, and younger birth cohorts. However, once internet use became excessive, this positive association weakened substantially and began to reverse. Conclusion: In the context of digital transformation, comprehensive societal changes are associated with an overall decline in young adults' mental health. However, moderate internet use can help alleviate negative emotions and promote young adults' mental health.

Indexed as

InternetInternet UseMental HealthAdolescentChinaDigital MediaFemaleHumansMaleYoung Adultdigital transformationinternet usemental healthsocial emotionyoung adults

Identifiers

PMID42293619
PMCPMC13259779

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.