Media Accessibility and Use-Patterns on the Occurrence of Mental Health Conditions Among Youths in Nairobi City County, Kenya
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Date
2026-04
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InternationalJournal of Health Sciences
Abstract
im: Globally, mental health problems affect 10 to 20% of adults and youngsters, with the onset age for 50% of cases being 14 years. In Kenya, estimates suggested that 1 in 10 individuals suffered from a known mental condition, with adult Kenyans having a 9.8% likelihood of experiencing depression. A study on social media use in Kenya revealed that the most active age group was 26-35 years, with a significant proportion using platforms like Facebook, WhatsApp, Snapchat, Instagram, and Twitter. The study assessed the impact of media accessibility and use patterns on the occurrence of mental health conditions among youths in Nairobi City County, Kenya. Methods: The study design was an analytical cross-sectional study with quantitative and qualitative methods. Data collection involved SSQs, KIIs, and FGDs, with 24 KIIs and 2 FGDs being conducted. A total of 385 participants were selected using a simple random sampling method, and data analysis was conducted using Advanced Excel, including descriptive statistics and regression analysis. Transcribing, coding, and classifying were employed to establish relationships and enable data summarization performance. Results: The results indicated a statistically significant difference in self-esteem scores between the two groups, t(766) = -2.84, p = .0047. Specifically, youths engaged in informal occupations (M = 19.01, SD ≈ 17.91) reported higher self-esteem compared to those in formal occupations (M = 15.42, SD ≈ 17.14). This suggested that employment type may influence how youths perceive their self-worth, possibly due to factors like increased autonomy or flexibility in informal settings. The regression analysis showed that media use-patterns were not a statistically significant predictor of self-esteem among youths in Nairobi City County, β = -0.08, t(382) = 1.03, p = .30. Media literacy had a positive and statistically significant effect on self-esteem, β = 0.21, t(382) = 2.23, p = .03. The regression model explained approximately 1.3% of the variance in self-esteem scores, R² = .013. Conclusion: Mental health issues are widespread, often fueled by digital exposure and compounded by structural limitations like poverty, stigma, and insufficient mental health infrastructure
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Akinyi, M. S., Oyore, J. P., & Orago, A. S. S. (2026). Media accessibility and use-patterns on the occurrence of mental health conditions among youths in Nairobi City County, Kenya. International Journal of Health Sciences, 10(1), 1–22. https://doi.org/10.53730/ijhs.v10n1.15858