Adaptive Music Therapy for Psychosocial and Cognitive Functions of Older Adults

Emotion Regulation, Executive Functions, Functional Abilities, Loneliness, Stress, Psychological, Well Being

Older adults, Music therapy, Cognition, Psychosocial, Intervention

The proposed study is a pilot study that aims to understand if the Pi Electronics adaptive music intervention (AM) is effective to promote positive psychosocial and cognitive outcomes, over and above a traditional music intervention (TM) among healthy older adults. This study will contribute to the ongoing literature on the benefits of music interventions and provide insight on how emerging technology can enhance the therapeutic effects of music as a viable intervention for older adults. The study will adopt a three-arm randomized controlled trial (RCT). Eligible participants will be randomized into one of three groups: traditional music therapy group (TM), Pi Electronic's adaptive music program (AM), and a waitlist control group (CG). Informed consent will be collected from all participants. All three groups will complete outcome measures at three sessions: pretest, posttest, and at a three-month follow-up, but only the TM and AM group will receive music between the pretest and posttest sessions, spanning for 4 weeks, with 4 music therapy sessions per week, and each session lasting 30 minutes. Data will be analyzed for each outcome variables to understand the group differences in the performance on the psychosocial and cognitive outcome measures. The study will also validate the Pi Electronics EEG headset with the BioSemi, 64-channel EEG system.

Objectives: 1. to further assess the benefits of traditional music interventions (TM) in older adults 2. to assess the additional benefits of the Pi Electronics adaptive music intervention (AM) as compared to TM in older adults 3. to assess the long-term durability over a 3-month period of the training benefits, if any 4. to validate Pi's real-time EEG headset and corresponding speaker for future therapeutic use. Sample: healthy older adults (65 years and older) will be recruited from the Ryerson Seniors Participants Pool (RSPP) and through community advertising. The target sample size will be 75 participants (N = 25 per group), evenly randomized into the three arms of intervention: TMT, AIT, and no-treatment waitlist control group (CG). Overall Design and Procedure: informed consent will be collected. All groups will complete behavioural and neurophysiological outcome assessments at three time-points: pretest, posttest, and 3-month follow-up. EEG and mood validation will be conducted at pretest for the AIT group. During this procedure, participants will be exposed to default music database to induce the target mood while EEG is recorded and mood regulation is monitored (e.g., Sourina et al., 2012). Participants will be asked to self-rate their positive emotional valence (happy and calm) by completing the Positive and Negative Affect Schedule (Watson, et al., 1988). Participants in the intervention groups will be given instructions on their respective intervention program to ensure they are fully familiarized. Intervention: the TM and AM groups will span for 4 weeks, requiring engagement in at least four 30-minute sessions of music listening per week, delivered on-line through cloud from the Pi Speakers. The AM and TM group will be exposed to individually selected music pieces based on the data collected at pretest. However, the AM group will be exposed to music that has been enhanced by frequencies that elicit positive mood in participants. Data Analysis Plan: To understand the training benefits, a three group by two time (pretest versus posttest), mixed model analysis of variance (ANOVA) will be employed. This will be done to understand the differences in the psychosocial and cognitive outcome variables within and between subjects from before to after the music program training. To understand the maintenance effect, a three group by two time (posttest versus three-month follow-up) mixed model ANOVA will be employed. Again, this will be used to understand if there are significant differences in training benefit maintenance for the psychosocial and cognitive outcome variables, both between and within subjects in the TM, AM, and CG. The study will also validate the Pi Electronics EEG headset with the BioSemi, 64-channel EEG system by comparing the mean peak difference of average waveforms of event related potentials using t-tests. Timeline: 1-year period starting in 2022, outlined below in months: * 1st-2nd: Research Ethics Board Approval * 2nd-3rd: Design and testing preparation * 2nd-6th: Research Assistant training; participant recruitment * 3rd-9th: Data collection and validation * 8th-11th: Data analysis * 10th-12th: Knowledge dissemination * 12th: Mitacs final report and survey

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