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Clinical Trial Details — Status: Recruiting

Administrative data

NCT number NCT05447312
Other study ID # TMU2022-CAL-Pi-AMT
Secondary ID
Status Recruiting
Phase N/A
First received
Last updated
Start date December 1, 2022
Est. completion date December 31, 2024

Study information

Verified date October 2023
Source Toronto Metropolitan University
Contact Kathryn Bolton, BA. hons
Phone 4038504258
Email kathryn.bolton@torontomu.ca
Is FDA regulated No
Health authority
Study type Interventional

Clinical Trial Summary

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.


Description:

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


Recruitment information / eligibility

Status Recruiting
Enrollment 75
Est. completion date December 31, 2024
Est. primary completion date October 31, 2024
Accepts healthy volunteers Accepts Healthy Volunteers
Gender All
Age group 65 Years and older
Eligibility Inclusion Criteria: 1. without previous mental health diagnosis; 2. with access to a computer and internet; 3. with largely normal or corrected to normal hearing; 4. without dementia-related cognitive decline (score of 24 or higher on Mini-Mental State Exam) Exclusion Criteria: 1. with previous mental health diagnosis; 2. without access to a computer and internet; 3. without largely normal or corrected to normal hearing; 4. with dementia-related cognitive decline (score of 23 or lower on Mini-Mental State Exam) 5. if participant is an outlier on the cognitive tasks, scoring +/- 2.5 standard deviations on the computerized cognitive tasks. 6. if half or more of the psychosocial questionnaires are incomplete.

Study Design


Intervention

Other:
Adaptive Music Intervention
Music that has been enhanced by frequencies that are associated with positive feelings as measured by EEG data. Music will be delivered through the Pi Electronic Inc.'s Venus Speaker that aims to promote psychosocial and cognitive functioning over and above traditional music therapy.
Traditional Music Intervention
Music that has not been enhanced by frequencies. Music is delivered through the Pi Electronic Inc.'s Venus Speaker that aims to promote psychosocial and cognitive functioning.

Locations

Country Name City State
Canada Ryerson University (renamed: Toronto Metropolitan University) Toronto Ontario

Sponsors (2)

Lead Sponsor Collaborator
Toronto Metropolitan University Mitacs

Country where clinical trial is conducted

Canada, 

References & Publications (28)

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Cahn-Weiner DA, Malloy PF, Boyle PA, Marran M, Salloway S. Prediction of functional status from neuropsychological tests in community-dwelling elderly individuals. Clin Neuropsychol. 2000 May;14(2):187-95. doi: 10.1076/1385-4046(200005)14:2;1-Z;FT187. — View Citation

Chaieb L, Wilpert EC, Reber TP, Fell J. Auditory beat stimulation and its effects on cognition and mood States. Front Psychiatry. 2015 May 12;6:70. doi: 10.3389/fpsyt.2015.00070. eCollection 2015. — View Citation

Creech, A., Hallam, S., McQueen, H., & Varvarigou, M. (2013). The power of music in the lives of older adults. Research Studies in Music Education, 35(1), 87-102. https://doi.org/10.1177/1321103X13478862

Fang R, Ye S, Huangfu J, Calimag DP. Music therapy is a potential intervention for cognition of Alzheimer's Disease: a mini-review. Transl Neurodegener. 2017 Jan 25;6:2. doi: 10.1186/s40035-017-0073-9. eCollection 2017. — View Citation

Folstein MF, Folstein SE, McHugh PR. "Mini-mental state". A practical method for grading the cognitive state of patients for the clinician. J Psychiatr Res. 1975 Nov;12(3):189-98. doi: 10.1016/0022-3956(75)90026-6. No abstract available. — View Citation

Gierveld JDJ, Tilburg TV. A 6-Item Scale for Overall, Emotional, and Social Loneliness: Confirmatory Tests on Survey Data. Res Aging. 2006;28(5):582-598. doi:10.1177/0164027506289723

Gonzalez-Ojea MJ, Dominguez-Lloria S, Pino-Juste M. Can Music Therapy Improve the Quality of Life of Institutionalized Elderly People? Healthcare (Basel). 2022 Feb 6;10(2):310. doi: 10.3390/healthcare10020310. — View Citation

Grenier AS, Lafontaine L, Sharp A. Use of Music Therapy as an Audiological Rehabilitation Tool in the Elderly Population: A Mini-Review. Front Neurosci. 2021 Sep 16;15:662087. doi: 10.3389/fnins.2021.662087. eCollection 2021. — View Citation

Gross JJ, John OP. Individual differences in two emotion regulation processes: implications for affect, relationships, and well-being. J Pers Soc Psychol. 2003 Aug;85(2):348-62. doi: 10.1037/0022-3514.85.2.348. — View Citation

Jaeger J. Digit Symbol Substitution Test: The Case for Sensitivity Over Specificity in Neuropsychological Testing. J Clin Psychopharmacol. 2018 Oct;38(5):513-519. doi: 10.1097/JCP.0000000000000941. — View Citation

Laukka, P. (2006). Uses of music and psychological well-being among the elderly. Journal of Happiness Studies, 8(2), 215. https://doi.org/10.1007/s10902-006-9024-3

Lawton MP, Brody EM. Assessment of older people: self-maintaining and instrumental activities of daily living. Gerontologist. 1969 Autumn;9(3):179-86. No abstract available. — View Citation

Lovibond, S.H. & Lovibond, P.F. (1995). Manual for the Depression Anxiety Stress Scales. (2nd. Ed.) Sydney: Psychology Foundation

Mallik A, Russo FA. The effects of music & auditory beat stimulation on anxiety: A randomized clinical trial. PLoS One. 2022 Mar 9;17(3):e0259312. doi: 10.1371/journal.pone.0259312. eCollection 2022. — View Citation

Phneah SW, Nisar H. EEG-based alpha neurofeedback training for mood enhancement. Australas Phys Eng Sci Med. 2017 Jun;40(2):325-336. doi: 10.1007/s13246-017-0538-2. Epub 2017 Mar 13. — View Citation

Salthouse, T. A. (1994). The Nature of the Influence Of Speed on Adult AgeDifferencesin Cognition. Developmental Psychology, 30(2), 20.

Sarkamo T, Tervaniemi M, Laitinen S, Numminen A, Kurki M, Johnson JK, Rantanen P. Cognitive, emotional, and social benefits of regular musical activities in early dementia: randomized controlled study. Gerontologist. 2014 Aug;54(4):634-50. doi: 10.1093/geront/gnt100. Epub 2013 Sep 5. — View Citation

Schmitter-Edgecombe M, Parsey CM. Assessment of functional change and cognitive correlates in the progression from healthy cognitive aging to dementia. Neuropsychology. 2014 Nov;28(6):881-93. doi: 10.1037/neu0000109. Epub 2014 Jun 16. — View Citation

Shankar A, Hamer M, McMunn A, Steptoe A. Social isolation and loneliness: relationships with cognitive function during 4 years of follow-up in the English Longitudinal Study of Ageing. Psychosom Med. 2013 Feb;75(2):161-70. doi: 10.1097/PSY.0b013e31827f09cd. Epub 2013 Jan 29. — View Citation

Sinclair VG, Wallston KA. The development and psychometric evaluation of the Brief Resilient Coping Scale. Assessment. 2004 Mar;11(1):94-101. doi: 10.1177/1073191103258144. — View Citation

Sourina, O., Liu, Y., & Nguyen, M. K. (2012). Real-time EEG-based emotion recognition for music therapy. Journal on Multimodal User Interfaces, 5(1-2), 27-35. https://doi.org/10.1007/s12193-011-0080-6

Thompson RG, Moulin CJ, Hayre S, Jones RW. Music enhances category fluency in healthy older adults and Alzheimer's disease patients. Exp Aging Res. 2005 Jan-Mar;31(1):91-9. doi: 10.1080/03610730590882819. — View Citation

Watson D, Clark LA, Tellegen A. Development and validation of brief measures of positive and negative affect: the PANAS scales. J Pers Soc Psychol. 1988 Jun;54(6):1063-70. doi: 10.1037//0022-3514.54.6.1063. — View Citation

Williams JM, Mathews A, MacLeod C. The emotional Stroop task and psychopathology. Psychol Bull. 1996 Jul;120(1):3-24. doi: 10.1037/0033-2909.120.1.3. — View Citation

World Health Organization. (1998). Wellbeing Measures in Primary Healthcare: The Depcare Project. https://www.euro.who.int/__data/assets/pdf_file/0016/130750/E60246.pdf

Zhao K, Bai ZG, Bo A, Chi I. A systematic review and meta-analysis of music therapy for the older adults with depression. Int J Geriatr Psychiatry. 2016 Nov;31(11):1188-1198. doi: 10.1002/gps.4494. Epub 2016 Apr 19. — View Citation

* Note: There are 28 references in allClick here to view all references

Outcome

Type Measure Description Time frame Safety issue
Primary Quality of life: Psychosocial functions of healthy older adults. All computerized on Qualtrics, no cut off scores. Psychosocial functioning will be assessed using the:
-World Health Organization - 5. Higher scores indicate increased quality of life.
Baseline (pretest), 4 weeks (posttest), and 16 weeks (3-month follow-up),
Primary Resiliency: Psychosocial functions of healthy older adults. All computerized on Qualtrics, no cut off scores. Psychosocial functioning will be assessed using the:
-Brief Resilient Coping Scale. Higher scores indicates higher resiliency coping.
Baseline (pretest), 4 weeks (posttest), and 16 weeks (3-month follow-up),
Primary Emotional Regulation: Psychosocial functions of healthy older adults. All computerized on Qualtrics, no cut off scores. Psychosocial functioning will be assessed using the:
-Emotion Regulation Questionnaire. Higher scores indicate increased emotional regulation.
Baseline (pretest), 4 weeks (posttest), and 16 weeks (3-month follow-up),
Primary Activities of Daily Living: Psychosocial functions of healthy older adults. All computerized on Qualtrics, no cut off scores. Psychosocial functioning will be assessed using the:
-Lawton Instrumental Activities of Daily Living Scale. Higher scores indicate better everyday functioning.
Baseline (pretest), 4 weeks (posttest), and 16 weeks (3-month follow-up),
Primary Loneliness: Psychosocial functions of healthy older adults. All computerized on Qualtrics, no cut off scores. Psychosocial functioning will be assessed using the:
- 6-item de Jong Gierveld. Higher scores indicate increased loneliness.
Baseline (pretest), 4 weeks (posttest), and 16 weeks (3-month follow-up),
Primary Emotional processing: Cognitive functions of healthy older adults. All computerized on PsychoPy. Cognitive performance will be measured using the:
-Emotional Stroop Task. Increased reaction time to negative emotional words indicates decreased mood.
Baseline (pretest), 4 weeks (posttest), and 16 weeks (3-month follow-up),
Primary Processing Speed: Cognitive functions of healthy older adults. All computerized on PsychoPy. Cognitive performance will be measured using the:
-Digit Symbol Substitution Test. Increased accuracy indicates better processing speed efficiency.
Baseline (pretest), 4 weeks (posttest), and 16 weeks (3-month follow-up),
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