Speaker
Description
Background
The Kenya Finance Bill of 2024 led to country-wide protests and socio-political unrest that was characterized by police excesses, enforced disappearances, loss of life, looting of businesses, and damage to property. The protests, which started in Nairobi, quickly escalated to other parts of the country after the parliament's finance committee remained adamant on passing the controversial bill that sought to increase the price of basic commodities like bread and sanitary towels. Even after the climactic protests, political tension remains, with police excesses being at the centre of concerns, victims calling for justice, and an overload of information. We aimed to assess how the political unrest in the country has affected the mental health of the youth in Kenya, and how the youth feel they can be better supported.
Method
We conducted a cross-sectional study with 67 participants responding using a widely distributed Google form. The questionnaire was based on demographics, traumatic experiences, media exposure, coping measures, and depression and anxiety levels were measured with PHQ‑9 and GAD‑7 scales (with a score of more than 4 indicating depression or anxiety symptoms). A penalized logistic regression model was used to assess the relationship between mental health status and predictors, including age, gender, marital status, traumatic experiences, and information overload.
Results
Out of the 67 respondents, 85.1% (n = 57) showed the symptoms of depression and /or anxiety (PHQ-9 or GAD-7 > 4). The model indicated that there is no statistically significant correlation between mental health and age, gender, employment, income, education, trauma, and news overload. Although females had increased chances of reporting symptoms (OR = 2.46), the outcome was not significant (p = 0.220). The likelihood ratio test found the multivariable model not to be significantly better than a null model (p = 0.85) while the Wald’s test found some parameters may contribute significantly to the model (p=0.0013).
When asked how mental health support could be enhanced, participants reported several key areas, including affordable counselling services (n = 20) and access to finances or employment (n = 16), desire to have a confidant (n = 8) and to have access to recreational facilities and activities (n = 8).
Limitations
Our study is limited by the small sample size (n= 67), which reduces the statistical power of our model to evaluate associations between the variables. Additionally, our cross-sectional study design may restrict causal interpretation.
Conclusion
The high prevalence of mental health problems in our sample suggests a higher burden in the general population. Although the sample size limited the predictive model, and no variable was significantly associated with the participants’ mental status, the model suggests these factors may play an important role. Our findings also suggest that mental health outcomes may not be determined by a single factor but rather by numerous factors that may overlap. More research with a larger sample size needs to be conducted to clarify these relationships.
