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Predictors of Cyberchondria During the COVID-19 Pandemic: Cross-sectional Study Using Supervised Machine Learning

Predictors of Cyberchondria During the COVID-19 Pandemic: Cross-sectional Study Using Supervised Machine Learning

Schimmenti and coworkers [12,13] proposed a model to account for fear experiences during the COVID-19 pandemic. This model posits that several domains of fear (bodily, relational/interpersonal, cognitive, and behavioral) interact and contribute to the onset and perpetuation of COVID-19–related psychological distress through maladaptive, repetitive, and functionally impairing behaviors.

Alexandre Infanti, Vladan Starcevic, Adriano Schimmenti, Yasser Khazaal, Laurent Karila, Alessandro Giardina, Maèva Flayelle, Seyedeh Boshra Hedayatzadeh Razavi, Stéphanie Baggio, Claus Vögele, Joël Billieux

JMIR Form Res 2023;7:e42206