Today, AI is an integral part of modern society, influencing our daily lives through various applications, such as smart phones, virtual assistants, and advanced algorithms that manage social media and healthcare systems. While the rapid advancement of AI offers numerous benefits, it also raises important questions about its impact on human psychology and social relationships. This study aims to explore attitudes towards artificial intelligence (AI) and mental health, seeking to uncover patterns that contribute to a deeper understanding of individuals' reactions to AI. It was also examine how gender differences in mental health among college students. The study was involved 200 college students and is utilized a two-group design to investigate the differences in mental health between students with positive and negative attitudes towards AI. A t-test was applied to analyze the data. The results indicate a significant difference in the mean mental health scores between college students with positive and negative attitudes towards artificial intelligence and also find out a significant gender difference on mental health of college students. The review concludes with a summary of the major research findings, along with considerations for future directions and implications for practice and policy.
- Coleman, J. C. (1962). Learning method as a relevant subject variable in learning disorders. Perceptual and Motor Skills, 14(2), 263-269.
- Fink, E., Patalay, P., Sharpe, H., Holley, S., Deighton, J., & Wolpert, M. (2015). Mental health difficulties in early adolescence: a comparison of two cross-sectional studies in England from 2009 to 2014. Journal of Adolescent Health, 56(5), 502-507.
- Lacity, M. C., & Willcocks, L. P. (2016). A new approach to automating services. MIT Sloan Management Review, 58(1), 41-49.
- Long, D., & Magerko, B. (2020, April). What is AI literacy? Competencies and design considerations. In Proceedings of the 2020 CHI conference on human factors in computing systems (pp. 1-16).
- Park, J., & Woo, S. E. (2022). Who likes artificial intelligence? Personality predictors of attitudes toward artificial intelligence. The Journal of psychology, 156(1), 68-94.
- Patel, V., Flisher, A. J., Hetrick, S., & McGorry, P. (2007). Mental health of young people: a global public-health challenge. The Lancet, 369(9569), 1302-1313.
- Primack, B. A., Shensa, A., Sidani, J. E., Escobar-Viera, C. G., & Fine, M. J. (2021). Temporal associations between social media use and depression. American journal of preventive medicine, 60(2), 179-188.
- Rosenfield, S., & Mouzon, D. (2007). Gender and mental health. Handbook of the sociology of mental health, 277-296.
- Schepman, A., & Rodway, P. (2020). Initial validation of the general attitudes towards Artificial Intelligence Scale. Computers in human behavior reports, 1, 100014.
- Sindermann, C., Yang, H., Elhai, J. D., Yang, S., Quan, L., Li, M., & Montag, C. (2022). Acceptance and Fear of Artificial Intelligence: associations with personality in a German and a Chinese sample. Discover Psychology, 2(1), 8.
- Steinbauer, G., Kandlhofer, M., Chklovski, T., Heintz, F., & Koenig, S. (2021). A differentiated discussion about AI education K-12. KI-Künstliche Intelligenz, 35(2), 131-137.
- STRANGE, S. (1965). A Guide to Recent Publications in the Soci. Hypothesis, 27, 776-796.
- Talesara, S., & Bano, A. (2017). Mental health scale (MHS). National Phycological Corporation. UG-1, Nirmala Heights, Near Mental Hospital, Agra-282007
- Twenge, J. M., & Campbell, W. K. (2018). Associations between screen time and lower psychological well-being among children and adolescents: Evidence from a population-based study. Preventive medicine reports, 12, 271-283
- World Health Organization. (1948). Manual of the international statistical classification of diseases, injuries, and causes of death: sixth revision of the international lists of diseases and causes of death, adopted 1948.
