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Healthcare
By Wafa Hamad Almegewly, Maryam Soliman Almalki, Lama Mohammed Alanazi and 10 others.
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Cyberchondria, characterized by excessive or repeated online searching for health-related information accompanied by heightened health concerns or distress, is an increasingly recognized behavioral phenomenon. Healthcare students represent an important population for investigation due to their frequent exposure to medical information and digital health resources. However, the extent of cyberchondria-related behaviors and their relationship with demographic and academic characteristics remain insufficiently explored in this population.
This study aimed to describe the level and distribution of cyberchondria-related behaviors and to explore whether selected demographic and academic characteristics were associated with CSS-12 scores among undergraduate female healthcare students from different academic programs at a Saudi university.
A cross-sectional descriptive correlational design was employed. A proportionate stratified non-probability convenience sample of 362 female students was recruited from six health-related colleges. Data were collected using the validated Cyberchondria Severity Scale (CSS-12), which measures four dimensions: excessiveness, distress, reassurance, and compulsion. Descriptive statistics, Pearson correlation, and multiple linear regression were applied using SPSS version 29.
The overall CSS-12 mean score indicated a moderate level of cyberchondria-related behaviors (M = 32.46, SD = 5.80). At the dimensional level, Excessiveness recorded the highest mean score (M = 10.29, SD = 2.10), followed by Distress (M = 7.46, SD = 2.35), while Reassurance (M = 7.73, SD = 2.20) and Compulsion (M = 6.98, SD = 2.05) showed comparatively lower scores. Based on the sample-derived score distribution, 23.8% of participants were classified in the upper-score group, while 30.4% and 45.9% were classified in the middle- and lower-score groups, respectively. Correlation analysis revealed significant positive relationships among all CSS-12 dimensions (p < 0.001), with correlation coefficients ranging from weak to strong (r = 0.31–0.56). Multiple linear regression analysis showed that age, GPA, academic year, and academic program were not significantly associated with CSS-12 scores (p > 0.05), and the model explained a very small proportion of variance (R2 = 0.006), indicating limited explanatory power.
Cyberchondria-related behaviors were distributed across low, moderate, and high score categories among female healthcare students, with excessiveness emerging as the most prominent dimension. The findings demonstrate interrelationships among CSS-12 dimensions but no significant associations with demographic or academic variables. Overall, the results are descriptive and correlational in nature and indicate that the demographic and academic characteristics examined in this study did not meaningfully account for variation in cyberchondria-related behaviors. Psychological and behavioral factors not assessed in the present study warrant investigation in future research.
Published in Healthcare. The abstract is shown as published and remains the work of its authors; read the full article at the source.
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