In Rwanda and many low-resource settings, mental health diagnosis often relies on one-time clinical assessments guided by global standards like DSM- 5 and ICD. These tools, while useful, risk overlooking the complexity of lived experiences shaped by historical trauma, socioeconomic challenges, and cultural interpretations of distress.
We explored the limitations of single-time diagnosis in mental health care and assessed the relevance and applicability of longitudinal diagnostic models, such as Ecological Momentary Assessment (EMA) and Experience Sampling Method (ESM), within the Rwandan mental health context.
A narrative literature review was conducted, drawing from global research on longitudinal diagnostic approaches. In addition, contextual analysis was applied to synthesize data in Rwanda.
Findings indicate that longitudinal diagnostic models capture the fluctuating nature of psychological symptoms more effectively than one-time assessments. They reduce diagnostic errors, help differentiate between transient distress and chronic mental disorders, and enable more nuanced, culturally sensitive interventions. In Rwanda, such approaches resonate with the need for trauma-informed, community-based care.
Rwanda’s mental health system would benefit from integrating longitudinal diagnostic practices that align with local realities. This requires investment in digital tools, community-based data collection, and clinician training. Longitudinal diagnosis offers a pathway to more ethical, accurate, and effective mental health care in culturally complex and historically burdened contexts.
