Our present understanding of depression relies on a Western nosology that might not be generalizable across diverse cultures around the world. As a consequence, current clinical research and practice may not capture culturally salient features of depression. Expanded cross-cultural research that uses ethnographic methods and local instruments may yield information of clinical utility to enhance culturally sensitive research and practice. In this mixed methods study, we used ethno-semantic interview procedures based on the DSM-5’s cultural formulation process to elicit a broad range of depression features reported by the Luo people of western Kenya. We identified how the Luo conceptualize depression, including idioms of depressive distress, moods associated with persistent negative affect, and other features including context, stressors and support systems. This information informed the co-development of a Luo Depression Questionnaire (LDQ-17). We used the LDQ-17 in a cross-sectional community survey (N1⁄4116) to investigate its association with a standard Western instrument (Patient Health Questionnaire-9; PHQ-9). Factor analysis revealed a one-factor model for the PHQ-9 but not the LDQ-17 for which exploratory factor analysis suggested a three-factor model including cognitive, affective, and physical symptoms. Psychological, environmental/social, and even supernatural causes (i.e., ancestors, God and devil) of these symptoms were identified, as were support systems. Finally, visualizations through multidimensional scaling approaches showed some overlap between the LDQ-17 and the PHQ-9, but the local LDQ-17 identified salient features the Luo associated with depression that the PHQ-9 missed. Our findings illustrate how simple ethnographic procedures may guide the development of local instruments to complement current stan- dardized instruments, potentially enhancing cultural relevance.
Cross-cultural psychiatry, culture, depression, global mental health, sub-Saharan Africa
Tom L. Osborn, Arthur Kleinman, John R. Weisz