The Effects of Music Listening on Anxiety and Agitation in People With Mild and Moderate Cognitive Impairment

NCT05858541 | Completed

• 1 other identifier: APP-23-02029
• Study Type: interventional
• Target: 64
• Locations: 1 country
• Sites: 1

Brief Summary

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.

Conditions

Anxiety; Agitated Depression

Outcome Measures

Primary Outcomes (3)

• Agitation Trait

  Change in agitation as measured by the Cohen-Mansfield Agitation Index

  8 weeks

• Agitation State

  Change in agitation as measured by Overt Agitation Scale (OAS)

  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)

  pre and post 20 mins session for a total of 32 sessions

Secondary Outcomes (2)

• Anxiety

  8 weeks

• Anxiety

  8 weeks

Other Outcomes (7)

• Depression

  8 weeks

• Well-being

  8 weeks

• Caregiver Burden

  8 weeks

Study Arms (2)

Music Listening

EXPERIMENTAL

Music Intervention - Music selection by LUCID The 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. The video is only temporarily streamed from the device to extract a series of facial features to assist in music selection. This data stream is sent to the LUCID cloud platform via encrypted data in transit protocol; the facial features are extracted, and the video is deleted. The facial feature data, even when reconstructed, is not identifiable. No personally identifiable biometric measures are stored in LUCID servers at any time

Behavioral: Music Listening

Audiobooks

ACTIVE COMPARATOR

Audiobook selection 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.

Behavioral: Listening to Audiobooks

Interventions

Music Listening BEHAVIORAL

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

Music Listening

Listening to Audiobooks BEHAVIORAL

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.

Audiobooks

Eligibility Criteria

• Age: 65 Years - 85 Years
• Sex: all
• Healthy Volunteers: No
• Age Groups: Older Adult (65+)

You may qualify if:

• Mild to Moderate Cognitive Impairment (mild: MOCA scores (18-25); moderate: MOCA scores (10-17))
• Aged 65-85.

You may not qualify if:

• Unmanaged hearing loss (defined as the average pure-tone average threshold of 35 dB HL or greater without the use of hearing instruments or personal sound amplification product) - self-report
• Severe Tinnitus
• Hyperacusis
• Current (but not prior) severe psychiatric disorder, an unstable or serious medical condition that may limit participation in the assessments.

Sponsors & Collaborators

• University of Southern California: lead

Study Sites (1)

University of Southern California

Los Angeles, California, 90089, United States

Location

MeSH Terms

Conditions

Anxiety Disorders

Condition Hierarchy (Ancestors)

Mental Disorders

Study Design

• Study Type: interventional
• Phase: not applicable
• Allocation: RANDOMIZED
• Masking: DOUBLE
• Who Masked: INVESTIGATOR, OUTCOMES ASSESSOR
• Masking Details: Investigators, and research staff involved in data collection and analysis will be masked to the assignment of participants
• Purpose: TREATMENT
• Intervention Model: PARALLEL
• Sponsor Type: OTHER
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: Associate Professor

Study Record Dates

• First Submitted: April 28, 2023
• First Posted: May 15, 2023
• Study Start: June 1, 2023
• Primary Completion: December 1, 2023
• Study Completion: December 30, 2023
• Last Updated: August 1, 2024

Record last verified: 2024-07

Data Sharing

• IPD Sharing: Will share
• Shared Documents: STUDY PROTOCOL, SAP, ICF, ANALYTIC CODE
• Time Frame: The data and protocol will be available upon completion of the data and analysis

Locations

US (1)