17110 The Effect of Mental Health Literacy on Self-diagnosis in Generation Z Tik-Tok Users

Many individuals tend to seek answers to mental health issues independently due to the easy access to information through the internet and social media. Among Generation Z, various factors drive the tendency to self-diagnose, with social media—particularly TikTok—playing a prominent role. One key contributing factor is the lack of mental health literacy. Mental health literacy refers to the knowledge and understanding of mental health issues and the appropriate strategies to recognize, manage, and seek help for these problems. This study aims to examine the effect of mental health literacy on self-diagnosis among Generation Z individuals who use the TikTok application. A quantitative research method was conducted with non-probability sampling techniques. The sample was determined using accidental sampling, involving 126 participants. The instruments used in this study were the Mental Health Literacy Scale and the Self-Identification of Having a Mental Illness (SELF-I). The results indicated that mental health literacy does not have a significant effect on self-diagnosis among Generation Z TikTok users. This suggests that self-diagnosis within this demographic may be more strongly influenced by other factors, such as personal experiences, social environment, or the perception of such content as mere entertainment. Furthermore, analysis of the dimensions revealed that the knowledge component of mental health literacy is most closely related to self-diagnosis. These findings suggest that individuals should explore more comprehensive and accurate information about mental health before engaging in self-diagnosis. Keywords: Mental Health Literacy, Self-Diagnosis, Generation Z, Tik-Tok.    

Publication Details

Journal
SWU eJournals System (Srinakharinwirot University)
Published
2025-08-09
Primary Topic
Electron and X-Ray Spectroscopy Techniques
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article
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article

17110 The Effect of Mental Health Literacy on Self-diagnosis in Generation Z Tik-Tok Users

SWU eJournals System (Srinakharinwirot University)
Electron and X-Ray Spectroscopy Techniques
article

17110 The Effect of Mental Health Literacy on Self-diagnosis in Generation Z Tik-Tok Users

article en

Abstract

Many individuals tend to seek answers to mental health issues independently due to the easy access to information through the internet and social media. Among Generation Z, various factors drive the tendency to self-diagnose, with social media—particularly TikTok—playing a prominent role. One key contributing factor is the lack of mental health literacy. Mental health literacy refers to the knowledge and understanding of mental health issues and the appropriate strategies to recognize, manage, and seek help for these problems. This study aims to examine the effect of mental health literacy on self-diagnosis among Generation Z individuals who use the TikTok application. A quantitative research method was conducted with non-probability sampling techniques. The sample was determined using accidental sampling, involving 126 participants. The instruments used in this study were the Mental Health Literacy Scale and the Self-Identification of Having a Mental Illness (SELF-I). The results indicated that mental health literacy does not have a significant effect on self-diagnosis among Generation Z TikTok users. This suggests that self-diagnosis within this demographic may be more strongly influenced by other factors, such as personal experiences, social environment, or the perception of such content as mere entertainment. Furthermore, analysis of the dimensions revealed that the knowledge component of mental health literacy is most closely related to self-diagnosis. These findings suggest that individuals should explore more comprehensive and accurate information about mental health before engaging in self-diagnosis. Keywords: Mental Health Literacy, Self-Diagnosis, Generation Z, Tik-Tok.    

SWU eJournals System (Srinakharinwirot University)
Quality Education
Openalex Percentile: Top 51%
Electron and X-Ray Spectroscopy Techniques
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