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.
Data availability
The data sets generated and analyzed during this study are available from the corresponding author upon reasonable request.
References:
Petrosyan, A. Number of internet users worldwide from 2005 to 2022. https://www.statista.com/statistics/273018/number-of-internet-users-worldwide/ (2023).
Xiong, Z. et al. Frequency of online health information seeking and types of information sought among the general Chinese population: Cross-sectional study. J. Med. Internet Res. 23, e30855 (2021).
Heuberger, R. A. & Ivanitskaya, L. Preferred sources of nutrition information: contrasts between younger and older adults. J. Intergener. Relatsh. 9, 176–190 (2011).
Meng, S. & Shen, C. Current situation of eHealth literacy and health behaviors of college students in Nanjing. Chinese J. Health Edu. 34, 254–257 (2018).
White, R. W. & Horvitz, E. Experiences with web search on medical concerns and self diagnosis. AMIA Annu. Symp. Proc. 2009, 696–700 (2009).
Muse, K., McManus, F., Leung, C., Meghreblian, B. & Williams, J. M. G. Cyberchondriasis: fact or fiction? a preliminary examination of the relationship between health anxiety and searching for health information on the internet. J. Anxiety Disord. 26, 189–196 (2012).
Singh, K. & Brown, R. J. Health-related internet habits and health anxiety in university students. Anxiety Stress Coping. 27, 542–554 (2014).
Starcevic, V. Cyberchondria: Challenges of problematic online searches for health-related information. Psychother. Psychosom. 86, 129–133 (2017).
Starcevic, V., Berle, D. & Arnáez, S. Recent Insights Into Cyberchondria. Curr. Psychiatry Rep. 22, 56 (2020).
Tyrer, P., Cooper, S., Tyrer, H., Wang, D. & Bassett, P. Increase in the Prevalence of Health Anxiety in Medical Clinics: Possible Cyberchondria. Int. J. Soc. Psychiatry. 65, 566–569 (2019).
McElroy, E. & Shevlin, M. The development and initial validation of the Cyberchondria Severity Scale (CSS). J. Anxiety Disord. 28, 259–265 (2014).
McElroy, E. et al. The CSS-12: Development and validation of a short-form version of the Cyberchondria Severity Scale. Cyberpsychol. Behav. Soc. Netw. 22, 330–335 (2019).
White, R. W. & Horvitz, E. Cyberchondria: Studies of the escalation of medical concerns in web search. ACM Trans. Inf. Syst. 27, 1–37 (2009).
Hsu, W. C. EHealth literacy and cyberchondria severity among undergraduate students: Mixed methods study. JMIR Form. Res. 9, e63449 (2025).
Peng, X. Q. et al. The status and influencing factors of cyberchondria during the COVID-19 epidemic. A cross-sectional study in Nanyang City of China. Front. Psychol. 12, 712703 (2021).
Kalantari, A. et al. The relationship between E-Health literacy and cyberchondria in Iranian students of health sciences. Front. Psychiatry. 15, 1421391 (2024).
Vismara, M. et al. Is cyberchondria a new transdiagnostic digital compulsive syndrome? A systematic review of the evidence. Compr. Psychiatry. 99, 152167 (2020).
Berlin, K. S., Williams, N. A. & Parra, G. R. An introduction to latent variable mixture modeling (Part 1): Overview and cross-sectional latent class and latent profile analyses. J. Pediatr. Psychol. 39, 174–187 (2014).
McMullan, R. D., Berle, D., Arnáez, S. & Starcevic, V. The relationships between health anxiety, online health information seeking, and cyberchondria: Systematic review and meta-analysis. J. Affect. Disord. 245, 270–278 (2019).
Ciułkowicz, M. et al. The portrait of cyberchondria-a cross-sectional online study on factors related to health anxiety and cyberchondria in Polish population during SARS-CoV-2 pandemic. Int. J. Environ. Res. Public Health. https://doi.org/10.3390/ijerph19074347 (2022).
Infanti, A. et al. Predictors of cyberchondria during the COVID-19 pandemic: Cross-sectional study using supervised machine learning. JMIR Form. Res. 7, e42206 (2023).
Bodie, G. D. & Dutta, M. J. Understanding health literacy for strategic health marketing: EHealth literacy, health disparities, and the digital divide. Health Mark. Q. 25, 175–203 (2008).
Norman, C. D. & Skinner, H. A. EHEALS: The EHealth Literacy Scale. J. Med. Internet Res. 8, e27 (2006).
Jin, T., Wu, Y., Yang, X., Yang, H. & Jia, Y. Revision of the Chinese version of short-form of the Cyberchondria Severity Scale. Zhongguo Linchuang Xinli Xue Zazhi 28, 321–325 (2020).
Guo, S. et al. Adaptation and evaluation of Chinese version of eHEALS and its usage among senior high school students. Chinese J. Health Edu. 29, 106–108 (2013).
Vermunt, J. K. Latent class modeling with covariates: Two improved three-step approaches. Polit. Anal. 18, 450–469 (2010).
Liang, Y., Wu, Z. & Wu, Z. The potential categories of cyberchondria among undergraduate nursing students and the relationship with EHealth literacy and health anxiety: A survey study from Southeastern China. Psychol. Health Med. https://doi.org/10.1080/13548506.2025.2484697 (2025).
Eichenberg, C. & Schott, M. Use of web-based health services in individuals with and without symptoms of hypochondria: Survey study. J. Med. Internet Res. 21, e10980 (2019).
Fergus, T. A. & Spada, M. M. Moving toward a metacognitive conceptualization of cyberchondria: Examining the contribution of metacognitive beliefs, beliefs about rituals, and stop signals. J. Anxiety Disord. 60, 11–19 (2018).
Surawy, C., McManus, F., Muse, K. & Williams, J. M. Mindfulness-based cognitive therapy (MBCT) for health anxiety (Hypochondriasis): Rationale, implementation and case illustration. Mindfulness 6, 382–392 (2015).
Xu, D., Ding, J. & Yang, Z. Pathogenesis of cyberchondria and its impact on individuals: A qualitative study. Zhonghua Quan Ke Yi Xue 21, 2755–2759 (2018).
Wang, Y. Effects of ehealth literacy and health anxiety on cyberchondria among college students [Master] (Yanbian University, 2022).
Zhu, X., Zheng, T., Ding, L. & Zhang, X. Exploring associations between eHealth literacy, cyberchondria, online health information seeking and sleep quality among university students: A cross-section study. Heliyon 9, e17521 (2023).
Lokajova, A., Smahel, D. & Kvardova, N. Health-related social media use and COVID-19 anxiety in adolescence: Health anxiety as covariate and moderator. Front. Psychol. 14, 1079730 (2023).
Zheng, H. & Jiang, S. Linking the pathway from exposure to online vaccine information to cyberchondria during the COVID-19 pandemic: A moderated mediation model. Cyberpsychol. Behav. Soc. Netw. 25, 625–633 (2022).
Maitz, E. A. M. K. Internet-based health information-seeking behavior of students aged 12 to 14 years: Mixed methods study. J. Med. Internet Res. 22, e16281 (2020).
Yun, H. S. & Bickmore, T. Online health information-seeking in the era of large language models: Cross-sectional web-based survey study. J. Med. Internet Res. 27, e68560 (2025).
Acknowledgements
The authors would like to sincerely extend their gratitude and thanks to all participants of this study.
Funding
This work was supported by the Graduate Education Reform Project of Hunan Province, China (Grant Number is 2024LXBZZ014).
Author information
Authors and Affiliations
Contributions
Z.Y.: Conceptualization; methodology; formal analysis; writing—original draft; writing— review and editing. N.Q.: Investigation; formal analysis; writing original draft; writing—review and editing. S.S.: Conceptualization; formal analysis; writing—review and editing. X.L.: Investigation; writing—review and editing; formal analysis. Z.Z.: Conceptualization; methodology; project administration; writing—review and editing.
Corresponding author
Ethics declarations
Competing interests
The authors declare no competing interests.
Additional information
Publisher’s note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/.
About this article
Cite this article
Yao, Z., Qin, N., Shi, S. et al. Cyberchondria among college students and associated factors: a latent profile analysis. Sci Rep (2026). https://doi.org/10.1038/s41598-026-44658-3
Received:
Accepted:
Published:
DOI: https://doi.org/10.1038/s41598-026-44658-3
