Exploring factors influencing the adoption of in-home respite services: A data science approach

This study examines the factors that influence the adoption of in-home respite services by family caregivers in Hong Kong, with the aim of addressing the societal challenge of an aging population. The research employs data science techniques on a large-scale community project to identify patterns that impact caregivers’ decisions. The findings can inform future policies on caregiver support, enabling the Hong Kong government to design more precise services for family caregivers. The research combines data science with social science, demonstrating the value of an interdisciplinary approach to address complex societal challenges and to make the results more transparent and explainable.