Integrative Medicine Approaches in Oncology: Evidence-based Use of Traditional and Complementary Therapies
Year: 2025
Type: article
Abstract: In an era where digital technology is rapidly transforming social dynamics, the overuse of social media has emerged as a hidden epidemic contributing to deteriorating mental health, particularly among Ghanaian youth. This study was driven by the urgent need to examine how excessive screen time, negative self-comparison, and exposure to cyber bullying correlate with rising cases of depression, anxiety, and cognitive disturbances-especially in low-income and educationally marginalized populations. The research aimed to evaluate the extent to which these digital behaviors influence mental health outcomes and how socioeconomic status moderates the impact. Using a secondary data-based quantitative approach with a validated sample of 105 respondents, the analysis employed descriptive and inferential statistical techniques including correlation and regression analysis. Key findings revealed that excessive screen time had the strongest positive correlation with mental health challenges (r = 0.712), followed by online harassment (r = 0.683) and negative comparison (r = 0.648), with an overall correlation coefficient of 0.83 and a model R² of 0.69. Regression results confirmed that screen overuse (β = 0.491, p < 0.001) was the most significant predictor of mental health decline, while socioeconomic status had a moderating negative effect (β = -0.377). These results underscore the urgent need for national policy responses, including awareness campaigns, digital wellness programs, and integration of online safety into educational curricula. The study recommends multi-sectoral interventions, including AI-enabled digital monitoring, community-based psychological services, and stricter digital platform regulations to safeguard mental health.
Author: Jerryson Ameworgbe Gidisu*, Frank Yaw Takyi-Appiah*, Michael Marttinson Boakye**, Taurus Valmont*, Isaac Adu Kumi* & Frederick Elkanah Ayitey*
Language: English
Subfield: Sociology and Political Science
Field: Social Sciences
Domain: Social Sciences
Open Access status: green
OpenAlex ID: W7083678459
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