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.
Study Type
INTERVENTIONAL
Allocation
RANDOMIZED
Purpose
TREATMENT
Masking
DOUBLE
Enrollment
64
The LUCID AI-based system for song selection responds to the collected measurement data (video and HRV) and music preference information (like/dislike button, music taste profile) to recommend the playlist for the listener. The songs are selected using 76 different musical features and raw audio information. The system uses these features to recommend and optimize recommendations for the listener
A selection of 40 audiobooks spanning 4 genres (10 each from Literary Classics, Fantasy, Mystery, Non-fiction) will be available. For each session, the participant and their caregiver will be given a prompt to make a genre selection. After making the genre selection, one of the ten stories associated with that genre will be selected at random. All stories were sampled from the Audible audiobook database. Stories had to be 30 minutes in length to align with the length of the music interventions and the selected stories had to have had a 4- or 5-star rating to ensure quality.
University of Southern California
Los Angeles, California, United States
Agitation Trait
Change in agitation as measured by the Cohen-Mansfield Agitation Index
Time frame: 8 weeks
Agitation State
Change in agitation as measured by Overt Agitation Scale (OAS)
Time frame: pre and post 20 mins session for a total of 32 sessions
Agitation State
Change in agitation as measured by Positive and Negative Syndrome Scale, Excited Component (PANSS-EC)
Time frame: pre and post 20 mins session for a total of 32 sessions
Anxiety
Change in Anxiety in Dementia Scale (RAID)-Minimum value: 0, Maximum value: 54. Higher score
Time frame: 8 weeks
Anxiety
Change in State-trait cognitive and somatic anxiety (STICSA)
Time frame: 8 weeks
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