Evidence map›Paper›PMID 40256283›Full record

ArticlePsychology research and behavior management2025

Exploring the Intrinsic Association Between Perceived Social Support and Depressive Symptoms and Problematic Phone Use Among College Students Based on Network Analysis.

Enze Gao, Xinru Qi, Min Liu, Ying Zhang, Hualing Li

Abstract read
In one paragraph

Article in Psychology research and behavior management, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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

5 authors.

Enze GaoDiscipline Inspection Commission, Xuzhou Medical University, Xuzhou, Jiangsu, People's Republic of China.ORCID 0000-0001-5895-7401
Xinru QiSchool of Public Health, Xuzhou Medical University, Xuzhou, Jiangsu, People's Republic of China.ORCID 0009-0001-7533-2363
Min LiuSchool of Public Health, Xuzhou Medical University, Xuzhou, Jiangsu, People's Republic of China.
Ying ZhangSchool of Public Health, Xuzhou Medical University, Xuzhou, Jiangsu, People's Republic of China.
Hualing LiSchool of Public Health, Xuzhou Medical University, Xuzhou, Jiangsu, People's Republic of China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Purpose: A network analysis model was used to explore the complex associations between college students' perceived social support and depressive symptoms and problematic phone use from a specific symptom perspective;. Methods: A total of 3869 study participants were included in this study using convenience sampling from five different universities in five different provinces in China. Perceived Social Support Scale was been used to measure the perceived social support level of college students, the extent of problematic smartphone use was evaluated using the Smartphone Addiction Scale-Short Version, and the Patient Health Questionnaire-9 scale to assess the depressive symptoms. A network analysis model was used to explore the intrinsic associations between their specific symptoms of perceived social support, depressive symptoms and problematic phone use;. Results: The results revealed that social support from family and from friends played a potentially critical role in alleviating depressive symptoms and reducing problematic phone use among college students;. Conclusion: The support given by family and peers is of great practical importance in reducing problematic cell phone use and controlling the development of depressive symptoms in the college population.

Indexed as

depressive symptomsnetwork analysisperceived social supportproblematic phone use

Identifiers

PMID40256283
PMCPMC12009574

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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.