Abstract
BACKGROUND: Symptom checker applications (SCAs) may help laypeople classify their symptoms and receive recommendations on medically appropriate actions. Further research is necessary to estimate the influence of user characteristics, attitudes and (e)health-related competencies. OBJECTIVE: The objective of this study is to identify meaningful predictors for SCA use considering user characteristics. METHODS: An explorative cross-sectional survey was conducted to investigate German citizens' demographics, eHealth literacy, hypochondria, self-efficacy, and affinity for technology using German language-validated questionnaires. A total of 869 participants were eligible for inclusion in the study. As n = 67 SCA users were assessed and matched 1:1 with non-users, a sample of n = 134 participants were assessed in the main analysis. A four-step analysis was conducted involving explorative predictor selection, model comparisons, and parameter estimates for selected predictors, including sensitivity and post hoc analyses. RESULTS: Hypochondria and self-efficacy were identified as meaningful predictors of SCA use. Hypochondria showed a consistent and significant effect across all analyses OR: 1.24-1.26 (95% CI: 1.1-1.4). Self-efficacy OR: 0.64-0.93 (95% CI: 0.3-1.4) showed inconsistent and nonsignificant results, leaving its role in SCA use unclear. Over half of the SCA users in our sample met the classification for hypochondria (cut-off on the WI of 5). CONCLUSIONS: Hypochondria has emerged as a significant predictor of SCA use with a consistently stable effect, yet according to the literature, individuals with this trait may be less likely to benefit from SCA despite their greater likelihood of using it. These users could be further unsettled by risk-averse triage and unlikely but serious diagnosis suggestions. TRIAL REGISTRATION: The study was registered in the German Clinical Trials Register (DRKS) DRKS00022465, DERR1- https://doi.org/10.2196/34026 .