Contextualization of Harmonized Cognitive Assessment Protocol (HCAP) in an aging population in rural low-resource settings in Africa: Experiences and strategies adopted to optimize effective adaption of cognitive tests in Kenya.

Cross-cultural adaptation of cognitive assessments is crucial for detecting Alzheimer's disease (AD) and related dementias (ADRD) in aging populations. This study documents the adaptation of the Harmonized Cognitive Assessment Protocol (HCAP) for a pilot study on the Longitudinal Study of Health and Aging in Kenya (LOSHAK) in rural Kilifi County, Kenya, highlighting challenges and strategies for optimizing outcomes. As part of the LOSHAK feasibility phase, cognitive tests including: the Swahili Mental State Examination, 10-word recall, animal naming, story recall, clock drawing, and making change, were administered to 202 participants (≥45 years) from the Kaloleni/Rabai Health and Demographic Surveillance System (KRHDSS). Measures were adapted culturally and linguistically, and trained local enumerators conducted home-based assessments. Low literacy (60.1% had no schooling), linguistic diversity, cultural norms, and infrastructure limitations influenced assessments. Key adaptations included translation, culturally relevant modifications, flexible administration, and community engagement. Contextualized cognitive assessments improve validity in rural resource-limited settings, offering insights for future research. HIGHLIGHTS: This is a narrative qualitative study documenting the experiences and Strategies Adopted to Optimize Effective Adaption of Cognitive Tests in Longitudinal Study of Health and Aging in Kenya (LOSHAK). This article documents the adaptation and contextualization of the Harmonized Cognitive Assessment Protocol (HCAP) for a pilot study on health and aging (LOSHAK) in rural Kilifi County, Kenya, focusing on the challenges and strategies employed to optimize outcome. HCAP tests were administered as part of the feasibility and pilot phase of the LOSHAK, the aim of which was to validate measures and optimize data collection procedures. The median age of the 202 study participants was 64, with 57.4% being female. A majority (62.5%) were not currently working, and nearly 70% fell within the two poorest wealth quintiles. The rural setting presented unique challenges including: low literacy rates (60.1% of participants had no schooling), diverse language use (primarily Giriama and Swahili), limited infrastructure (e.g., 44.8% of households had electricity), restrictive cultural norms that influenced data collection (e.g., in-home interviews were often conducted outdoors with destructions). Key adaptations included: translating and culturally adapting test items (e.g., using local Swahili dialects and culturally relevant examples), recruiting and training local enumerators who were familiar with the community, culture and language, iterative pre-testing and using roleplay helped to ensure that enumerator scoring was consistent, accurate, and reliable. contextualization of tool and data collection strategies included: adjusting data collection methods to accommodate cultural practices and environmental limitations, for example, allowing respondents to use their preferred language for "animal naming," using paper and pen for some test items for which participants experienced difficulty using tablets, paying close special attention to time and season of administration, and adopting strategies to minimize background noise and other environmental distractions (e.g., due to rain, lunch hour, planting and harvesting, and school holidays). Prior to data collection, it was essential to engage local community health volunteers (CHVs), build rapport with participants, explain the study, and describe the idiosyncrasies of cognitive testing. The study emphasizes the importance of cultural sensitivity, linguistic appropriateness, and community engagement in cognitive assessment in diverse, resource-constrained settings. The findings offer practical recommendations for researchers aiming to conduct cognitive assessments in similar populations, contributing to the development of culturally sensitive and effective tools for understanding and addressing cognitive health in aging populations.