Murray State Theses and Dissertations

Abstract

Online self-diagnosis refers to an individual using the internet and applying their own knowledge to diagnose themself with a disorder without the input of a professional (Farnood, 2021). Social media platforms, such as TikTok, have created an environment full of mental health related information that may not always be correct. Individuals on this app may believe the videos they watch and which may ultimately lead to self-diagnosis. There has been a trend of popular mental health disorders on appearing TikTok, such as ADHD. The present study sought to examine potential predictors of self-diagnosis of ADHD through TikTok. This study examined how cyberchondria, mental health anxiety, gullibility, self-handicapping, and time spent on TikTok influence the number of reported ADHD symptoms. It was expected that greater scores of cyberchondria, mental health anxiety, gullibility, and self-handicapping would predict higher numbers of self-reported erroneous ADHD symptoms. Additionally, it was expected that time spent on TikTok would be the largest predictor of self-reported erroneous ADHD symptoms. Data from 87 participants who did not have an official ADHD diagnosis were examined. Results indicated that there were significant correlations between the following: mental health anxiety, cyberchondria, self-handicapping, erroneous ADHD symptoms, and clinical ADHD symptoms. Additionally, results indicated that self-handicapping was a better predictor for reporting both erroneous and clinical ADHD symptoms than any of the other predictors.

Year manuscript completed

2023

Year degree awarded

2023

Author's Keywords

self-diagnosis, TikTok, ADHD, cyberchondria, self-handicapping, mental health anxiety

Committee Chair

Jana Hackathorn

Committee Member

Laura Liljequist

Committee Member

Leigh Wright

Committee Member

Sean Rife

Document Type

Dissertation/Thesis

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