http://technology.eurekajournals.com/index.php/GJIOCAAIML <p style="text-align: justify;">Global&nbsp;Journal on Innovation, Opportunities and Challenges in Applied Artificial Intelligence and Machine Learning (GJIOCAAIML) is leading high cited refereed online journal which provides quick publication of article in the area of Applied Artificial Intelligence and Machine Learning. Papers reporting reviews, novel research, letter to the editor, short communication, and high quality notes are warmly welcome. Primary aim is to publish innovative ideas and research work which is helpful to Academician, Scholars, Consultant, Industry Experts and Scientist to enhance their Research and development work.</p> Eureka Journals en-US Global Journal on Innovation, Opportunities and Challenges in Applied Artificial Intelligence and Machine Learning [ISSN: 2581-5156 (online)] 2581-5156 http://technology.eurekajournals.com/index.php/GJIOCAAIML/article/view/822 <p><strong>Introduction</strong>: Digital technology has transformed social interactions, human development, employment, production, and productivity, empowering people and changing medicine as practised. The widespread use of social media among Jamaicans has raised significant concerns about its potential impact on mental health. While social media platforms provide opportunities for connection and self-expression, excessive or frequent usage may lead to adverse psychological outcomes such as anxiety, depression, and low self-esteem.</p> <p><strong>Objectives</strong>: This study examines the prevalence of addiction to social media usage in Jamaica and sub-components of the digital addiction scale of social media usage among the Jamaican population and evaluates the relationship between digital addiction and different mental health issues such as anxiety, depression, and self-esteem.</p> <p><strong>Methods</strong>: This study employed an explanatory cross-sectional survey research design. The population for this study consists of resident Jamaicans who are at least 18 years old, Jamaicans who live in the country at the time of the study, and children under 18. According to the 2019 population projections from the Statistical Institute of Jamaica (STATIN), Jamaica has 2,024,687 people 18 years and older, including 1,032,369women and 992,318men. The sample size in this study is calculated using this number, a 95% confidence level, a 5% margin of error, and the gender distribution of the population. Based on the population size and the data previously provided, the sample size is 385 Jamaicans aged 18 years and older. The response rate was 78.96% (<em>n</em>= 304).</p> <p><strong>Findings</strong>: Fifty-seven per cent of the sampled respondents were classified as at the normal level of internet addiction, 34.2% were mildly addicted, and 7.5% were moderately addicted to the internet. Additionally, 1.4% of respondents were severely dependent on the Internet. One in three respondents were at least moderately addicted to digital technology (internet and online activities or digital tools and digital media), and two in three were at most weakly addicted. Additionally, 4.6% of respondents were strongly to extremely addicted to digital technology, and 1.8% were extremely addicted. A cross-tabulation between the digital addiction scale (DAS) and the Patient Health Questionnaire (depression scale) of the respondents. A significant statistical association exists between the two previously mentioned variables (<em>?²</em> (df = 16) = 107.476, p-value &lt; 0.001), with the association being a moderate one (contingency coefficient = 0.532). Respondents who were severely depressed were most likely to be very highly digitally addicted (25.0%) compared to those who were moderately depressed (2.7%), mildly depressed (1.2%) and those who were minimally depressed (0.7%).</p> <p><strong>Conclusion</strong>: This study concludes that digital addiction significantly impacts mental health and productivity in Jamaica, with individuals facing low self-esteem, high anxiety, and severe depression at greater risk for severe digital dependence. Gender differences and employment status also influence addiction patterns, with part-time workers and students experiencing reduced productivity and academic performance. These findings highlight the need for targeted mental health interventions, digital literacy programs, and policy reforms to foster healthier technology use.</p> Paul Andrew Bourne, PhD. DrPH, Zandy U. Elliott, PhD, DHSc DrPH, Zandy U. Elliott, PhD Feliciano Thorpe, MSc, Dennis Brooks, BSc Vivienne L. Quarrie, PhD Ikhalfani Solan, PhD 8 2