A Digital Active Aging Training Program for Older Adults
NCT ID: NCT06270862
Last Updated: 2024-05-01
Study Results
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Basic Information
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RECRUITING
NA
240 participants
INTERVENTIONAL
2024-04-08
2024-12-31
Brief Summary
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The proposed study takes a typical pretest-training-posttest design. Pretest and posttest: a battery of outcome measures on physical, psychological, and social functions will be administered to all participants. Data will also be used to identify sociodemographic risk predictors for outcome variables (i.e., biopsychosocial functions and resilience). Training: the participants will be randomly assigned to three arms to receive 4 weeks of 16 training/practice/control treatment sessions delivered via Zoom.
In the "active aging with resilience (AR)" condition, participants will complete physical, cognitive, and social engagement training modules, starting with a 30-min resilience-building module. The traditional "active aging" (AA) training involves the same multi-domain active aging training without the initial resilience-building module. The "workshop training" (WT) control condition involves workshops following the same 4-week schedule on aging-related topics.
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Detailed Description
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1. to develop a multi-domain digital active aging training program through Zoom to promote active aging; and
2. to evaluate whether adding a resilience-building module would enhance the active aging training efficacy to mitigate the lingering detrimental impacts of the pandemic
Sample:
For Study 1, the investigators will recruit 120 Mandarin-speaking healthy older Chinese immigrants (aged 60+, Chinese migrants) through WeChat(a popular instant messaging app among Chinese)/email/lab website social media channels (e.g., Facebook, Twitter) from the community partners (see a list attached). For Study 2, we will recruit 120 English-speaking healthy White Canadian older adults (aged 60+) through TMSPSS (the senior participant pool at Toronto Metropolitan University) or advertisements.
Overall Design and Procedure:
Informed consent will be collected. The proposed study will take a traditional pretest-intervention-posttest design including three phases of research activities. In Phase 1 (pretest), the investigators will administer a large battery of outcome measures including physical, psychological (emotional and cognitive), and social function measures to assess the baseline performance. The data collected at pretest also addresses the first sub-objective to identify sociodemographic risk predictors for the biopsychosocial functions and resilience among Chinese older immigrants in Canada. In Phase 2 (intervention), participants will be randomly assigned to an "active aging with resilience", an "active aging", and a "workshop" control condition. They will go through 4 weeks of 8 sessions of training/control treatment delivered virtually through Zoom/YouTube and 8 sessions of offline self-practice. In Phase 3 (posttest), all participants who completed the intervention programs will complete the same battery of the outcome measures as administered at the pretest session. Their performance on the outcome measures at posttest will be compared against pretest to evaluate the efficacy of the training programs.
Intervention:
The virtually-delivered intervention program will be developed based on previous studies and practices that proved to be effective in resilience-building and active.
During the 4-week training period delivered through Zoom/YouTube, participants in the "active aging with resilience" group will complete 8 sessions (approximately 1.5 hours per session and 2 sessions per week) of active aging training program integrated with a resilience-building module. Each session will start with a 15-min session of resilience building activities modified from positive psychology resilience-building activities that promotes various resilience characters (e.g., gratitude, forgiveness, grit etc.). This will be followed by the 1-hour multi-dimensional active aging training activities, including progressive "aging in motion" physical and nutrition training (e.g., age-appropriate "Choose to move" physical workout on-line videos), cognitive training with executive function and speed based on a customized module on CogniFit website, socialization and social engagement (e.g., discussion on the topic and session, followed by homework on volunteering, calling friends/families, community activity participation etc.), and combined bio-psycho-social multi-component training (e.g., performing a cognitive tasks such as counting backwards or memorizing names while doing physical exercise in a virtual socialization setting). Participants in the "active aging" group will receive the same training except that the initial 15-min resilience-building activities will be replaced by warmup activities such as watching some pre-selected video on active aging and completing a quiz afterwards. Both the "active aging with resilience" and traditional "active aging" group will also engage in 8 offline practice sessions where they follow instructions to practice and repeat the last completed modules. Finally, participants in the receptive "workshop" control group will attend 8 virtual workshops or watching workshop videos (following the same 4-week schedule as the two training groups) on different aging-related topics such as physical health, mental health, cognitive wellbeing, emotional regulation, social engagement, and resilience. Each workshop will take approximately 1.5 hours (including 30 min for questions). They will also review and watch the replays of last workshops and take a short survey question after each review session. All these activities will be delivered virtually via Zoom/YouTube in groups of 10-15 individuals.
Data Analysis Plan To identify active aging and resilience predictors, a set of explorative multivariate linear regression models will be conducted on the data collected at the pretest session, with all sociodemographic as predictors and outcome measure performance as dependent variables. To evaluate the relative efficacy of the active aging intervention programs, a 3 (condition) by 2 (session) mixed model analysis of variances (ANOVA) models will be conducted on each outcome variable, after controlling for potential sociodemographic covariates. For comparison and clarity purposes, if the outcome measures within each function domain demonstrates similar patterns, the investigators will calculate a composite outcome variable based on the z-scores of all involved measures to index the performance level of that specific functional domain. This composite score will be used as the outcome variable in the ANOVA. In light of the literature, the investigators hypothesized that the "active aging with resilience" training will produce larger and wider benefits relative to the "active aging" training, both compared against the receptive "workshop" control condition.
Conditions
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Study Design
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RANDOMIZED
FACTORIAL
HEALTH_SERVICES_RESEARCH
SINGLE
Study Groups
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Active aging with resilience (AR)
In the "active aging with resilience (AR)" condition, participants will complete physical, cognitive, and social engagement training modules, starting with a 15-min resilience-building module.
Resilience training
Receive mini course on what is resilience and how to use different exercises to be more resilient in life.
cognitive training
Play games that trains attention, memory and planning using the services provided by CogniFit.
physical exercise
Engage in age-appropriate physical exercises.
social interaction
Engage in social discussion with peers in the group.
Active aging without resilience (AA)
The traditional "active aging" (AA) training involves the same multi-domain active aging training without the initial resilience-building module, which will be replaced by watching 15 minutes of educational video on topics such as health, nature or travel.
cognitive training
Play games that trains attention, memory and planning using the services provided by CogniFit.
physical exercise
Engage in age-appropriate physical exercises.
social interaction
Engage in social discussion with peers in the group.
Workshop training (WT)
The "workshop training" (WT) control condition involves workshops following the same 4-week schedule on aging-related topics.
workshop series
Watch a series of workshops targeting the older adult population.
Interventions
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Resilience training
Receive mini course on what is resilience and how to use different exercises to be more resilient in life.
cognitive training
Play games that trains attention, memory and planning using the services provided by CogniFit.
physical exercise
Engage in age-appropriate physical exercises.
social interaction
Engage in social discussion with peers in the group.
workshop series
Watch a series of workshops targeting the older adult population.
Eligibility Criteria
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Inclusion Criteria
1. Aged 65 or over and healthy
2. Chinese migrant (e.g., Canadian citizens, immigrants, visitors that are born and raised in the Chinese culture)
3. Can speak, read and write Mandarin
4. Having access to a computer that has internet and allows Zoom meeting attendance
Study 2(Canadian group):
1. Aged 65 or over and healthy
2. White Canadian citizen
3. Can speak, read and write English
4. Having access to a computer that has internet and allows Zoom meeting attendance
Exclusion Criteria
2. Unfit for light physical exercises
3. Without access to a computer and internet
4. With current or previous mental health diagnosis
65 Years
ALL
Yes
Sponsors
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Social Sciences and Humanities Research Council of Canada
OTHER
AGE-WELL and the Canadian Frailty Network
UNKNOWN
Cogniciti
UNKNOWN
Cognifit
UNKNOWN
Aging in Cloud
UNKNOWN
Toronto Metropolitan University
OTHER
Responsible Party
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Lixia Yang
Professor
Principal Investigators
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Lixia Yang, PhD
Role: PRINCIPAL_INVESTIGATOR
Toronto Metropolitan University
Locations
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Cognitive Aging Lab
Toronto, Ontario, Canada
Countries
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Central Contacts
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Facility Contacts
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References
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Related Links
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Choose to Move at Home video modules
23 resilience building activities \& exercises for adults. Resilience \& Coping, Positive Psychology
Other Identifiers
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SSHRC-PEG2023-AAT
Identifier Type: -
Identifier Source: org_study_id
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