[PH-2-2] If the Youths Addicted Social Media have Higher Suicide-related Risk?
Background: Youth’s mental health is a significant worldwide issue. In Taiwan, the suicide rate of ages 15 to 24 is increasing rapidly over recent five years, which highlights the importance of mental health in youths. Today internet-based applications are becoming more and more popular and available for youths, youths study, make friends, and play on the internet. Unlike traditional communication methods, the social media site and platform offered instantaneous methods that allowed youths to interact and share information. However, the impact of social media use on mental health was inconsistent; some studies suggested social media use would increase youths’ depression, anxiety, and suicide, and some indicated the youths’ mental health was independent of social media use. This study aims to examine the relationship between internet use time, depression, social media use, and suicide-related behavior in Taiwan’s youths.
Methods: This study was approved by the Research Ethics Committee at National Taiwan University Hospital. We recruited 32 youths in our study, and all participants underwent an interview and completed self-report questionnaires including the Suicide/ Self-injury Questionnaire(SSQ), Bergen Social media Addiction Scale (BSMAS), and Beck Depressive Inventory second edition. The statistical analysis was conducted with SAS 9.4. We examined the association between internet-use time, depressive symptoms, suicide-related behavior, and addictive social media use by Spearman’s correlation. To clarify the relationship between addictive social media use and suicide-related behaviors, we set depressive symptoms as a covariate variable in a regression model.
Results: The mean age of participants was 21.28 (SD=1.97), and the sex ratio was 1:2.2 (male: female). The rank of most frequent use of social media is Facebook, Instagram, YouTube, and Twitter. Suicide-related behaviors have a strong statistically significant correlation with depressive symptoms (rho= 0.58, p= 0.0005), but the correlation between depressive symptoms and addictive social media use was not statistically significant. There was a moderate statistically significant negative correlation between suicide-related behavior and addictive social media use (rho= -0.38, p = 0.03). The weekday internet use time was medium statistically significant correlating with addictive social media use (rho= 0.37, p = 0.04). Controlling depressive symptoms in a regression model, the impact of addictive social media use on suicide-related behaviors were not statistically significant.
Discussion: Our result is consistent with previous evidence, although the sex ratio of our sample is unbalanced and the sample size was restricted. Adaptive social media use might offer youths appropriate social connectivity and support, then decreasing the risk of suicide-related behavior.
Conclusion: The addictive social media addictive use was independent of suicide-related behaviors in youth.
Methods: This study was approved by the Research Ethics Committee at National Taiwan University Hospital. We recruited 32 youths in our study, and all participants underwent an interview and completed self-report questionnaires including the Suicide/ Self-injury Questionnaire(SSQ), Bergen Social media Addiction Scale (BSMAS), and Beck Depressive Inventory second edition. The statistical analysis was conducted with SAS 9.4. We examined the association between internet-use time, depressive symptoms, suicide-related behavior, and addictive social media use by Spearman’s correlation. To clarify the relationship between addictive social media use and suicide-related behaviors, we set depressive symptoms as a covariate variable in a regression model.
Results: The mean age of participants was 21.28 (SD=1.97), and the sex ratio was 1:2.2 (male: female). The rank of most frequent use of social media is Facebook, Instagram, YouTube, and Twitter. Suicide-related behaviors have a strong statistically significant correlation with depressive symptoms (rho= 0.58, p= 0.0005), but the correlation between depressive symptoms and addictive social media use was not statistically significant. There was a moderate statistically significant negative correlation between suicide-related behavior and addictive social media use (rho= -0.38, p = 0.03). The weekday internet use time was medium statistically significant correlating with addictive social media use (rho= 0.37, p = 0.04). Controlling depressive symptoms in a regression model, the impact of addictive social media use on suicide-related behaviors were not statistically significant.
Discussion: Our result is consistent with previous evidence, although the sex ratio of our sample is unbalanced and the sample size was restricted. Adaptive social media use might offer youths appropriate social connectivity and support, then decreasing the risk of suicide-related behavior.
Conclusion: The addictive social media addictive use was independent of suicide-related behaviors in youth.