Mbithi G, Mabrouk A, Sarki A, Odhiambo R, Namuguzi M, Dzombo JT, Atukwatse J, Kabue M, Mwangi P, Abubakar A. Mental health and psychological well-being of Kenyan adolescents from Nairobi and the Coast regions in the context of COVID-19.
Child Adolesc Psychiatry Ment Health 2023;
17:63. [PMID:
37208781 PMCID:
PMC10198601 DOI:
10.1186/s13034-023-00613-y]
[Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/12/2023] [Accepted: 05/10/2023] [Indexed: 05/21/2023] Open
Abstract
BACKGROUND
Despite the high burden of mental health problems during adolescence and its associated negative consequences, it has remained neglected especially in sub-Saharan Africa. The 2019 novel Coronavirus disease (COVID-19) pandemic has placed additional stress on adolescent mental health. However, there are few studies documenting the burden of mental health problems and even fewer mental health services in the region. In relation to the limited body of knowledge, the present study aims to determine the psychological well-being of adolescents and to assess the risks and associated factors of mental health problems among adolescents in the context of COVID-19 pandemic in Kenya.
METHODS
We conducted a cross-sectional survey in 2022 among adolescents aged 13-19 years living in Nairobi, and the Coast region of Kenya. We utilized standardized psychological assessment tools including the Patient Health Questionnaire, Generalized Anxiety Scale, Strengths and Difficulties Questionnaire, The World Health Organization- Five Well-Being Index Scale, and the Pandemic Anxiety Scale, to evaluate the psychological wellbeing of the adolescents. A linear regression model was used to evaluate the correlates associated with quality of life, pandemic anxiety, and emotional and behavioural problems among adolescents. Subsequently, a logistic regression model was used to assess factors associated with depression and general anxiety disorders. Variables with a p-value < 0.25 in the univariate model were included in the multivariable regression model.
RESULTS
The results are based on 797 participants who met the inclusion criteria. We found the prevalence of depression to be relatively higher among out-of-school adolescents at 36.0% compared to school-going adolescents at 20.6%. Furthermore, out-of-school adolescents had significantly higher anxiety scores when compared to their school-going counterparts (27.7% vs 19.1%) respectively. In-school adolescents had a better quality of life scores, lower pandemic anxiety scores, and lower emotional and behavioral problems scores compared to their out-of-school counterparts. Key risk factors associated with depression include; being out-of-school (OR = 1.96 (95% CI 1.33- 2.88) p-value = 0.001), loneliness (OR = 10.68 (95% CI 4.49-22.86) p-value < 0.001), and living in an unsafe neighborhood (OR = 2.24 (95% CI 1.52-3.29) p-value < 0.001). An older age (OR = 1.16 (95% CI 1.03-1.30) p-value = 0.015), being out-of-school (OR = 1.81 (95% CI 1.19-2.77) p-value = 0.006), and living in an unsafe neighborhood (OR = 2.01 (95% CI 1.33-3.04) p-value = 0.001 were key factors associated with anxiety. Furthermore, key factors positively correlated with quality of life include; high socioeconomic status (ß (Std.Err) = 0.58 (0.14) p-value < 0.001, talking to friends often (ß (Std.Err) = 2.32 (0.53) p-value < 0.001, and being close to parents (ß (Std.Err) = 1.37 (0.62) = 0.026.
CONCLUSION
Our findings imply that mental health support services targeting adolescents in the country should be prioritized, especially for those who are out-of-school.
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