Developing a cyberchondria severity scale to promote self-care among university students during COVID-19.

Wan-Chen Hsu
Author Information
  1. Wan-Chen Hsu: Center for Teaching and Learning Development, National Kaohsiung University of Science and Technology, Kaohsiung, Taiwan. wanchen@nkust.edu.tw.

Abstract

Cyberchondria is a hybrid term signifying a state in which individuals compulsively search for health-related information online because of health distress or anxiety, further aggravating their worries. This study develops a Cyberchondria Severity Scale (CSS) to assess the current situation of university students. Exploratory factor analysis (EFA) was conducted using 145 valid questionnaires. Subsequently, a nationwide survey was conducted at various universities in Taiwan, and 802 questionnaires were used for confirmatory factor analysis (CFA). The EFA led to the development of a CSS for college students with four constructs: increased anxiety (α = 0.91), obsessive-compulsive hypochondria (α = 0.87), perceived controllability (α = 0.88), and online physician-patient interaction (α = 0.86), with a Cronbach's alpha of 0.92 and variance of 66.81%. The CFA indicated that item reliability ranged from 0.50 to 0.86, factor loadings ranged from 0.71 to 0.93, and the composite reliability for latent variables ranged from 0.83 to 0.90 (p < .001). The extracted average variance ranged from 0.46 to 0.60. There were significant differences in various dimensions: perceived controllability had the highest score and obsessive-compulsive hypochondria had the lowest (F=256.26, p < .001). Therefore, CSS has emerged as a reliable and valid measure. Future studies should explore the factors that influence cyberchondria, promote online health information searches, and enhance reading comprehension skills.

Keywords

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Grants

  1. 111-2410-H-992 -037 -MY2/National Science and Technology Council

MeSH Term

Humans
COVID-19
Students
Male
Female
Universities
Surveys and Questionnaires
Young Adult
Hypochondriasis
Anxiety
Self Care
Adult
Taiwan
SARS-CoV-2
Factor Analysis, Statistical
Severity of Illness Index
Adolescent

Word Cloud

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