Evidence map›Paper›PMID 36761134›Full record

ArticleFrontiers in public health2023

A bidirectional association between smartphone addiction and depression among college students: A cross-lagged panel model.

Kexin Zhang, Haiyun Guo, Tianli Wang, Jianghui Zhang, Guojing Yuan, Juan Ren, Xueqing Zhang, Huayu Yang, Xiaoyan Lu, Zhihui Zhu and 7 more

Open access · goldAbstract read
In one paragraph

Article in Frontiers in public health, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers.

0numbers the graph read from it
0cells of the map it votes in
25citing papers in PubMed
17.9field-weighted citation impact, top 1% of its field
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

25 citing papers in PubMed, 31 citations in OpenAlex.

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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

17 authors at 3 institutions in 1 country.

Kexin ZhangDepartment of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, Hefei, China.
Haiyun GuoDepartment of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, Hefei, China.
Tianli WangHefei Center for Disease Control and Prevention, Hefei, China.
Jianghui ZhangDepartment of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, Hefei, China.
Guojing YuanDepartment of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, Hefei, China.
Juan RenThe Second Hospital of Anhui Medical University, Hefei, China.
Xueqing ZhangDepartment of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, Hefei, China.
Huayu YangDepartment of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, Hefei, China.
Xiaoyan LuDepartment of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, Hefei, China.
Zhihui ZhuDepartment of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, Hefei, China.
Jun DuDepartment of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, Hefei, China.
Haiyan ShiDepartment of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, Hefei, China.
Guifang JinDepartment of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, Hefei, China.
Jiahu HaoDepartment of Maternal, Child, and Adolescent Health, School of Public Health, Anhui Medical University, Hefei, China.
Ying SunDepartment of Maternal, Child, and Adolescent Health, School of Public Health, Anhui Medical University, Hefei, China.
Puyu SuDepartment of Maternal, Child, and Adolescent Health, School of Public Health, Anhui Medical University, Hefei, China.
Zhihua ZhangDepartment of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, Hefei, China.
Anhui Medical University · CNAnhui Provincial Center for Disease Control and Prevention · CNSecond Hospital of Anhui Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Smartphone addiction (SA) is associated with adverse consequences, especially for freshmen. Evidence indicates that SA is associated with depression, and it is necessary to conduct a longitudinal study to explore the association further. Methods: SA (measured by the Smartphone Addiction Scale-Short Version) and depression (measured by the Zung's Self-Rating Depression Scale) among 1,186 freshmen were surveyed at baseline and a respective 12-month follow-up for each participant. The application of a cross-lagged panel model approach (CLPM) revealed an association between SA and depression after adjusting for demographic variables. Results: The CLPM results showed a significant path from baseline SA to follow-up depression (β = 0.08, Conclusions: The current study showed a significant bidirectional association between smartphone addiction and depression among freshmen, but only in the female population.

Indexed as

DepressionInternet Addiction DisorderFemaleHumansLongitudinal StudiesMaleStudentsSurveys and Questionnairescollege studentscross-lagged panel model (CLPM)depressionlongitudinal studysmartphone addiction

Identifiers

PMID36761134
PMCPMC9902510
OpenAlexW4317814930

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.