Physical Inactivity Clinical Trial
Official title:
The Healthy Aging Brain Study: A Remote Behavioral Intervention to Enhance Physical Activity in Older Adults.
This is a twelve-week pilot randomized controlled trial of a behavioral intervention in older adults at risk for Alzheimer's disease. Older participants are a subgroup from the PREVENT-AD longitudinal cohort. We will test whether a four-week intergenerational social motivation using a technology-based platform (intervention group) enhances physical activity relative to a control group. After a washout period, the two groups will be offered the opportunity to cross-over into the alternate condition.
This study is a two-arm, single site randomized controlled trial to test whether a four-week technology-based intergenerational social motivation intervention enhances physical activity in 60 cognitively normal older adults with a first-degree history of Alzheimer's disease. These at-risk older adults will be recruited as a subgroup from a longitudinal cohort at McGill University, PREVENT-AD. At the outset, half of the participants will be randomized to the intergenerational social motivation condition (intervention group) and the other half will be randomized to the control group (1:1). A multimodal Alzheimer's disease (AD) risk score based on older participants' already acquired AD biomarker, health and cognitive data will be used as strata for randomization to ensure equal assignment of high-risk participants to Intervention and control groups, using a permuted block method with random blocks. The primary measure of interest is increased physical activity as measured by accelerometry (average minutes in sedentary behavior/day, average steps per day, and average minutes in moderate-to-vigorous physical activity/day). After an initial visit consisting of behavioral testing and structural and functional MRI, participants in the Intervention Group will be paired with younger adults (14 to 40 years) to form intergenerational dyads. Younger adults are either a family member of the older adult or a younger adult recruited from the community. Participants in the intervention group will receive personalized, positive daily messages over a four-week period via their device using a technology platform. These daily messages combine (1) pro-social goals, (2) intergenerational social engagement and (3) positive personalized messages from their younger study partners. This study will have 6 visits over a 2-month period in addition to the four-week intervention period (3 months total). Cognitive and behavioral data will be collected at each visit and physical activity data will be collected over the intervention period. All participants will be offered the opportunity to cross-over, after a washout period, to ensure that all participants have access to the intervention, into the alternate condition in order to ensure access to the intervention in all participants and longer-term follow up. The primary endpoint is defined as the end of the initial period. Data collected are stored in one of three ways; (1) Physical activity monitoring data are extracted from their respective software packages and uploaded directly to a secure data storage environment at a high-performance computing facility. All pen-and-paper psychosocial and neuropsychological assessments are scored and entered in REDCap. Computerized psychosocial assessments are collected directly in REDCap and computerized neuropsychological assessments are entered in REDCap. The oTree library is used to distribute the daily intervention messages and collect survey data. This system runs on a Heroku server, a cloud-based system that sends and receives hash-encrypted links. Collected anonymized data are stored on the messaging site behind an administrative login on the Heroku server. All data from RedCAP will be exported to CSV files using the data de-identification feature for subsequent analysis with R and SPSS statistical analysis packages. After compiling all data across the 3 different data servers, data will be checked for completeness and correctness using frequency distributions (for missing data and out-of-range values). For the final dataset, the multiple imputation by chained equations (MICE) will be used for imputing missing values with 10 imputations. ;
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