A1134
Title: The development of an automatic speech analytics program to detect the level of stress burden
Authors: Amanda Chu - The Education University of Hong Kong (China)
Jacky Ngai Lam Chan - The Hong Kong University of Science and Technology (Hong Kong) [presenting]
Mike So - The Hong Kong University of Science and Technology (Hong Kong)
Abstract: The stress burden generated from family caregiving makes caregivers particularly prone to developing psychosocial health issues; however, with early diagnosis and intervention, disease progression and long-term disability can be prevented. An automatic speech analytics program (ASAP) was developed for the detection of psychosocial health issues based on clients' speech. One hundred Cantonese-speaking family caregivers were recruited. The results suggest that the ASAP can identify family caregivers with low or high-stress burden levels with an accuracy rate of 72\%. The findings indicate that digital health technology can be used to assist in psychosocial health assessment. While the conventional method requires rigorous assessments by specialists with multiple rounds of questioning, the ASAP can provide a cost-effective and immediate initial assessment to identify high levels of stress among family caregivers so they can be referred to social workers and healthcare professionals for further assessments and treatments.
