Date of Award

8-2022

Degree Type

Thesis

Degree Name

Master of Arts - Psychology

Department

Psychology

First Advisor

Dr. James D. Schaeffer

Second Advisor

Dr. Nathan Sparkman

Third Advisor

Dr. Scott Drury

Fourth Advisor

Dr. Luis Aguerrevere

Abstract

Cyberchondria is described as excessively searching online for health information that ultimately increases worry and anxiety about one’s health (Starcevic et al., 2019). Research has demonstrated an increased attentional bias in anxious individuals for threat-related stimuli. Attentional bias for health information exacerbated by the frequent exposure to health threats during the COVID-19 pandemic may contribute to additional health-seeking behavior. The current study aimed to explore the potential relationship between COVID-19 health threats and cyberchondria level on attentional bias toward illness-related stimuli (symptom words) and the intent to perform safety behaviors while controlling for Trait Anxiety and Health Anxiety. Participants (n=49) were randomly assigned to the COVID-19 prime group or the control group. An EST using illness words and neutral words was then used to assess attention allocation. Scores from surveys were used to measure safety behavior intention, cyberchondria, trait anxiety, and health anxiety. A t-test was used to measure group differences. The primed participants did not significantly differ from the control group for all measures. The regression analyses showed that Emotional Stroop performance and safety behavior intentions were not related to cyberchondria or the COVID-19 health threatening prime. Research has suggested that instead of increased attention to threatening information individuals may demonstrate increased avoidance to threat, which could explain the null findings. Further research is needed to investigate potential predictors that may influence adoption, attitudes, and intentions toward safety behaviors.

Keywords: cyberchondria, COVID-19, Emotional Stroop Task, attentional bias, safety behaviors

Creative Commons License

Creative Commons License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.

Share

COinS

Tell us how this article helped you.

 
 

To view the content in your browser, please download Adobe Reader or, alternately,
you may Download the file to your hard drive.

NOTE: The latest versions of Adobe Reader do not support viewing PDF files within Firefox on Mac OS and if you are using a modern (Intel) Mac, there is no official plugin for viewing PDF files within the browser window.