Abstract
Dementia is a growing global public health concern, particularly in LMICs like Bangladesh. With population aging, there is an increasing prevalence of dementia; care facilities are limited. This scarcity of services places a significant responsibility on untrained family caregivers, impacting the health of persons with dementia and their caregivers. Addressing these challenges is crucial for improving dementia care, especially in resource-constrained settings. Recognizing the urgency, the WHO developed an online self-training manual, iSupport, emphasizing education, skill development, and support for caregivers. This study aims to test feasibility of iSupport i) in improving knowledge about dementia and dementia care among family and formal caregivers, and ii) reducing family caregivers' stress and improving their caregiving skills, mental health, quality of life and relationship with the person with dementia cared for. The study protocol was approved by the Institutional Review Board of SAJIDA Foundation (2024-005-SFIRB). This non-randomized feasibility study aims to recruit 44 family caregivers and 132 formal caregivers from Dhaka, Bangladesh, using a purposive sampling technique. Participants will be provided access to iSupport for two months. Pre- and post-intervention surveys will be conducted to assess changes in knowledge about dementia care among both family and formal caregivers, as well as changes in psychological well-being among family caregivers. To assess knowledge retention, a follow-up survey will be conducted. Any differences in the outcomes from the pre-intervention period will be tested against the null hypothesis of zero mean difference using a two-sample paired t-test. Additionally, multivariable regression techniques will also be used to control for possible confounders. To understand the facilitators and barriers of implementing iSupport, a qualitative approach will be used to interview 15 family caregivers and conduct four FGDs with formal caregivers. Qualitative data will be analysed using an inductive content analysis approach.