Evidence map›Paper›PMID 41872273›Full record

ArticleScientific reports2026

Cyberchondria among college students and associated factors: a latent profile analysis.

Ziqiang Yao, Ning Qin, Shuangjiao Shi, Xiao Li, Zhuqing Zhong

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PubMed Full text at PMC Publisher
In one paragraph

Article in Scientific reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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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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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

5 authors.

Ziqiang YaoNursing Department, The Third Xiangya Hospital, Central South University, 138 Tongzipo Road, Changsha, 410013, Hunan, China.
Ning QinNursing Department, The Third Xiangya Hospital, Central South University, 138 Tongzipo Road, Changsha, 410013, Hunan, China.
Shuangjiao ShiNursing Department, The Third Xiangya Hospital, Central South University, 138 Tongzipo Road, Changsha, 410013, Hunan, China.
Xiao LiNursing Department, The Third Xiangya Hospital, Central South University, 138 Tongzipo Road, Changsha, 410013, Hunan, China.
Zhuqing ZhongNursing Department, The Third Xiangya Hospital, Central South University, 138 Tongzipo Road, Changsha, 410013, Hunan, China. zhongzhuqing@126.com.

Funding

Hunan Province Teaching Reform Research Project, China 2024LXBZZ014
6 · The paper itself

Abstract

Online health research is highly prevalent among college students. Cyberchondria in this population often involves repeated health-related searches driven by anxiety, which can heighten distress and disrupt daily functioning. This study aims to explore the classes of cyberchondria among college students, and to identify the characteristics and associated factors. In this online cross-sectional study, a total of 5641 students were recruited from a comprehensive university. Latent profile analysis (LPA) was performed to determine subgroups of cyberchondria. Multinomial logistic regression was used to analyze the influencing factors of different cyberchondria classes. Four classes of cyberchondria were identified: “Low-Variable Group”, “Moderate Seeking Group”, “Moderate Affective Group”, “High-Severe Group”. Logistic regression analysis indicated that students with poorer health status and higher eHealth literacy were more likely to be in the High-Severe group. Female students and those reporting poorer health had increased odds of falling into the Moderate Seeking and Moderate Affective groups. Cyberchondria among college students showed clear categorical features. Female students, individuals with poorer self-reported health, and those with higher eHealth literacy are more prone to severe cyberchondria. Tailored interventions should be provided to address health anxiety and cyberchondria symptoms among college students.

Indexed as

College studentCyberchondriaHealth anxietyLatent profile analysisOnline health research

Identifiers

PMID41872273
PMCPMC13168422

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LicenceCC BY-NC-ND
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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.