Advancing age is associated with an increased risk of developing dementia which can lead to a rapid acceleration in both the healthcare costs and caregiver burden. There is a need to develop non-pharmacological and easily accessible modalities of support for the well-being and enhancing quality of life for individuals with dementia. There is evidence that music listening is associated with stress and anxiety reduction in older adults. Here, the investigators aim to assess the effects of music listening as provided by a novel digital music-based intervention (developed by LUCID) on mood, anxiety, and quality of life in individuals at the early stages of dementia. LUCID uses reinforcement learning machine learning to curate and personalize the musical playlist while incorporating monoaural theta auditory beat stimulation (ABS) into the music. The study will be conducted remotely with study hardware (tablets and Bluetooth speakers) being delivered to caregivers/participants. The study will take place over an 8- week period, with participants completing four 30 mins music or audiobook listening sessions per week. Pre and post-intervention assessments will be done via Zoom with the presence of a research staff member. The control condition consists of a randomized list of short audiobooks. The experimental condition consists of music and monoaural ABS curated by LUCID's AI system. The investigators hypothesize that the LUCID AI music curation system, compared to audiobooks, will be correlated with a greater reduction in measures of anxiety and agitation and an enhancement of mood and quality of life.
Age range
65 Years – 85 Years
Sex
ALL
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Agitation Trait
Timeframe: 8 weeks
Agitation State
Timeframe: pre and post 20 mins session for a total of 32 sessions
Agitation State
Timeframe: pre and post 20 mins session for a total of 32 sessions