Behavioural and Contextual Predictors of Cyberchondria Severity Among Preclinical Medical Students in India: A...

Background  Cyberchondria, excessive online health information seeking that amplifies health anxiety, is prevalent among medical students. Longitudinal evidence on behavioural predictors of cyberchondria is sparse, particularly from India. Objectives  The primary objective was to identify the behavioural and contextual predictors of cyberchondria severity and to assess their cross-wave stability using a repeated-measures linear mixed-effects framework among preclinical medical students. Secondary objectives were to test whether the association between online health-search frequency and cyberchondria was replicated and consistent across two waves, and to examine domain-level subscale trajectories beneath the total score. Materials and methods  This was a prospective two-wave cohort study of 100 preclinical medical students at Government Medical College Maheshwaram, Telangana, India. The 15-item Cyberchondria Severity Scale (CSS-15) was administered at Wave 1 in January 2026 and Wave 2 in April 2026, three months apart, with no intervention between waves. The questionnaire was administered through an online survey form during scheduled department contact hours; participation was voluntary. Paired t-tests, one-way ANOVA with linear trend analysis, wave-specific multiple linear regression, and linear mixed-effects models were used, with Bonferroni and Benjamini-Hochberg false discovery rate correction for domain-level comparisons. All analyses were performed in R version 4.3.2. Results  Online health-search frequency was the strongest independent predictor of cyberchondria across both waves (mixed-model β = 3.49, 95% CI: 2.26-4.71, p < 0.001), with a monotonic stepwise association replicated at both waves (ANOVA p < 0.001 for each). Symptom-searching before consulting a doctor (β = 3.63, 95% CI: 1.28-5.98, p = 0.002), hostel residence (β = 2.98, 95% CI: 0.38-5.57, p = 0.025), and chronic illness in self or family (β = 2.76, 95% CI: 0.56-4.96, p = 0.014) were also independently associated with higher cyberchondria severity. CSS-15 total scores were stable (paired t = -0.376, p = 0.708). Exploratory domain-level analysis suggested decreased physician mistrust (uncorrected p < 0.001; survived Bonferroni and Benjamini-Hochberg false discovery rate correction) and an increase in reassurance-seeking (uncorrected p = 0.032; did not survive Bonferroni or Benjamini-Hochberg false discovery rate correction). Conclusions  Online health-search frequency is a robust cross-wave predictor of cyberchondria among medical students, with severity rising in a monotonic stepwise pattern across each higher category of search frequency, replicated at both time points. This finding, together with domain-level divergence in cyberchondria components, supports the evaluation of targeted digital health literacy approaches in medical education, with online health-search behaviour as a candidate focus.