Evidence map›Paper›PMID 40598695›Full record

ArticleBMC psychology2025

Grade-level differences in the association between cumulative family risk factors and problematic smartphone use among Chinese adolescents.

Ye Xu, Yi-Fan Lin, Liwen Yang, Herui Wu, Wenjian Lai, Ruiying Chen, Subinuer Yiming, Zhiyao Xin, Wanxin Wang, Ciyong Lu

Abstract read
In one paragraph

Article in BMC psychology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

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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.

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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

10 authors.

Ye XuDepartment of Medical Statistics and Epidemiology, School of Public Health, Sun Yat-sen University, 74 Zhongshan Rd 2, Guangzhou, Guangdong, 510080, China.
Yi-Fan LinDepartment of Spine Surgery, Shenzhen Second People's Hospital, Shenzhen, Guangdong, China.
Liwen YangDepartment of Medical Statistics and Epidemiology, School of Public Health, Sun Yat-sen University, 74 Zhongshan Rd 2, Guangzhou, Guangdong, 510080, China.
Herui WuDepartment of Medical Statistics and Epidemiology, School of Public Health, Sun Yat-sen University, 74 Zhongshan Rd 2, Guangzhou, Guangdong, 510080, China.
Wenjian LaiDepartment of Medical Statistics and Epidemiology, School of Public Health, Sun Yat-sen University, 74 Zhongshan Rd 2, Guangzhou, Guangdong, 510080, China.
Ruiying ChenDepartment of Medical Statistics and Epidemiology, School of Public Health, Sun Yat-sen University, 74 Zhongshan Rd 2, Guangzhou, Guangdong, 510080, China.
Subinuer YimingDepartment of Medical Statistics and Epidemiology, School of Public Health, Sun Yat-sen University, 74 Zhongshan Rd 2, Guangzhou, Guangdong, 510080, China.
Zhiyao XinDepartment of Medical Statistics and Epidemiology, School of Public Health, Sun Yat-sen University, 74 Zhongshan Rd 2, Guangzhou, Guangdong, 510080, China.
Wanxin WangDepartment of Medical Statistics and Epidemiology, School of Public Health, Sun Yat-sen University, 74 Zhongshan Rd 2, Guangzhou, Guangdong, 510080, China.
Ciyong LuDepartment of Medical Statistics and Epidemiology, School of Public Health, Sun Yat-sen University, 74 Zhongshan Rd 2, Guangzhou, Guangdong, 510080, China. luciyong@mail.sysu.edu.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundGlobally, more adolescents are engaged in problematic smartphone use (PSU), but there is scant research on the impact of family risk factors on PSU. This study aimed to investigate the independent and cumulative effects of various family risk factors on adolescents' PSU and to determine whether these associations differ across grade level.

methodsData were drawn from the 2023 National School-based Chinese Adolescents Health Survey, with 20,361 adolescents (mean age: 15.0 [SD: 1.7] years) included. Family risk factors, PSU, and grade level were measured. A cumulative family risk (CFR) score was constructed by summing the number of family risk factors each adolescent experienced. The prevalence of PSU was estimated, and then logistic regression models were used to examine the association between family risk factors and PSU. Additionally, stratified analyses by grade level were conducted to explore differences in the above associations.

resultsThe prevalence of PSU among adolescents was 25.8%. Significant associations were found between PSU and parental relationship, family function, parental education level, parental alcoholism, and childhood adversity, respectively. A clear dose-response relationship was observed between CFR and PSU (P for trend < 0.001), with adolescents exposed to four or more family risk factors showing the highest odds of PSU compared to those with no risk factors (OR: 2.57, 95% CI: 2.22-2.98). Furthermore, a significant interaction was found between CFR and grade level (P

conclusionsMultiple family risk factors were independently and cumulatively associated with a higher risk of PSU, particularly among middle school students. These findings underscore the importance of addressing family-related risks and fostering emotionally supportive home environments to mitigate PSU in adolescents.

Indexed as

Adolescent BehaviorFamilyInternet Addiction DisorderSmartphoneAdolescentChinaEast Asian PeopleFemaleHealth SurveysHumansMaleParent-Child RelationsPrevalenceRisk FactorsAdolescentsFamily risk factorsGrade levelProblematic smartphone use

Identifiers

PMID40598695
PMCPMC12220488

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Registered trials

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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.