The structural model of cyberchondria based on personality traits, health-related metacognition, cognitive bias, and emotion dysregulation

Cyberchondria is excessive seeking for online health-related information related to increasing health anxiety and distress levels. The current study investigated the mediating role of health-related metacognition, cognitive bias, and emotion dysregulation in the relationship between personality trai...

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Veröffentlicht in:Frontiers in psychiatry 2023-01, Vol.13, p.960055-960055
Hauptverfasser: Nasiri, Mohammad, Mohammadkhani, Shahram, Akbari, Mehdi, Alilou, Majid Mahmoud
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Sprache:eng
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Zusammenfassung:Cyberchondria is excessive seeking for online health-related information related to increasing health anxiety and distress levels. The current study investigated the mediating role of health-related metacognition, cognitive bias, and emotion dysregulation in the relationship between personality traits and cyberchondria. Participants were 703 individuals 18+ years old who had access to the internet (males = 43.8%, mean age = 33.82 ± 10.09 years and females = 56.2%, mean age = 34.37 ± 11.16 years). They voluntarily completed a questionnaire package that included the Cyberchondria Severity Scale (CSS), the revised NEO Personality Inventory (NEO-PI-R), the Difficulties in Emotion Regulation Scale (DERS), the Meta-Cognitions about Health Questionnaire (MCQ-HA), and the Health Cognitions Questionnaire (HCQ). The initial evaluation of the model demonstrated that the personality traits of openness to experience, agreeableness, and conscientiousness had no significant relationship with other variables in the structural model, and the effects of neuroticism and extroversion were the only significant results. Rerunning the model with the removal of non-significant variables revealed a full mediation of health-related metacognition, cognitive bias, and emotion dysregulation in the relation between personality traits (neuroticism and extraversion) and cyberchondria. Fit indices demonstrated the acceptable fit of the model with the collected data (χ = 979.24,
ISSN:1664-0640
1664-0640
DOI:10.3389/fpsyt.2022.960055