The Healthy Aging Brain Study: A Remote Behavioral Intervention to Enhance Physical Activity in Older Adults.
Phase: NA
Conditions: Physical Inactivity
Sponsor: Douglas Mental Health University Institute

 
 
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FULL PROTOCOL 
 
THE HEALTH AND AGING BRAIN STUDY (HABS): A PREVENT-AD OPTIONAL PILOT STUDY 
“An intergenerational behavioural intervention to enhance physical activity in older adults at risk 
for Alzheimer’s disease” 
 
Principal Investigator:       Maiya R. Geddes, MD, FRCPC 
*Assistant Professor,  
Department of Neurology and Neurosurgery, McGill University 
 
*Associate Researcher, 
 
McGill Centre for Research Studies in Aging (MCSA),  
 
The Douglas Mental Health University Institute 
 
CIUSSS de l'Ouest-de-l'île-de-Montréal 
*Behavioral Neurologist and Clinician Scientist, 
Montreal Neurological Institute-Hospital (The Neuro) 
3801 University Street, Montreal, QC H3A 2B4 
514-398-8751 
maiya.geddes@mcgill.ca 
 
Co-Investigator: 
Judes Poirier Ph.D., Professor,  
Department of Psychiatry, Douglas Hospital, McGill University 
Sylvia Villeneuve Ph.D., Assistant Professor,  
    Department of Psychiatry, Douglas Hospital, McGill University 
Arthur F. Kramer Ph.D., Professor, 
Center for Cognitive and Brain Health, Northeastern University 
Adrián Noriega de la Colina M.D. Ph.D.  
Montreal Neurological Institute-Hospital, McGill University 
Caitlin Walker, PhD Candidate,  
Montreal Neurological Institute-Hospital, McGill University 
 
Collaborators:  
      
Jennifer Tremblay-Mercier M.Sc., Research Coordinator 
 
The Douglas Mental Health University Institute, McGill University 
Christine Déry M.Sc., Research Assistant 
Montreal Neurological Institute-Hospital, McGill University 
Meishan Ai B.Sc., Ph.D. Candidate, Psychology, Department of 
Health Sciences, Northeastern University 
Nagashree Thovinakere B.Sc., graduate student, McGill University 
Linda Li, Undergraduate student, McGill University 
Sarah Elbaz, Medical Student, Université Laval  
Helen Pallett-Wiesel, Graduate student, McGill University 
Nicolas Lavoie, Medical student, Université Laval 
Garance Barnoin, Undergraduate student, McGill University 
Johanie Victoria Piché, Medical student, McGill University 
Ying Wen, Medical Student, McGill University 
Adelina Dobromir Angheluta, Medical student, McGill University 
Ryan Kara, Medical student, McGill University 
 
 
 

 
 
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Source of Support: PI Startup funding from Brain Canada/Alzheimer Society; National Institutes of 
Health (NIH) Roybal Award “Under Review” 
 
Executive Summary      
Physical inactivity increases the risk for multiple chronic diseases, early mortality, and 
accelerated cognitive decline in aging adults. Interventions to enhance physical activity 
among older adults are needed to improve health outcomes and reduce the burden on 
healthcare systems. We propose a remotely administered behavioural intervention that uses 
social motivation manipulation, and self-transcendence messages to effectively enhance 
physical activity in older adults. This randomized controlled trial consists of daily messaging 
delivered via smart-phone over 4 weeks in 120 healthy but ‘at risk’ older adults over the age 
of 60 years from the PResymptomatic EValuation of Experimental or Novel Treatments for AD 
(PREVENT-AD) cohort. Participants are randomly assigned to one of two groups: an 
intervention group, who are recruited with a child or grandchild (14 years or older) and 
receive socially motivating feedback, and an active control group, who are recruited without 
a family member. The primary outcome is the change in physical activity as measured by 
accelerometers following the intervention compared to a pre-intervention baseline. 
Recruitment takes place among current participants of the PREVENT-AD cohort as an optional 
sub-study. These participants have already undergone MRI and Alzheimer’s disease 
biomarker assessment as part of the PREVENT-AD cohort. During the present sub-study, these 
participants will be assessed remotely using telephone/videoconference and computerized 
neuropsychological tests, computerized behavioural measures, and psychosocial surveys at 
baseline and after the intervention. Assessment of cognition, affect and fitness will serve as 
secondary outcome measures. Participants in each group will be offered the opportunity to 
participate in a cross-over second period of the study, to ensure that participants in the active 
control group have access to a potentially beneficial intervention and to serve as a longer-
term follow-up of both groups. This study will assess the effectiveness of a novel behavioural 
intervention at enhancing physical activity in older adults and examine the neurobehavioural 
mechanisms underlying any such behavioural change. 
 
1. Introduction 
There is overwhelming evidence that increased exercise in older age improves cognitive, 
affective and physical well-being, and may prevent the progression of age-related illnesses 
[1]. Already, previous findings from the FINGER study, a large, long-term, randomized 
controlled trial suggests that multidomain interventions (targeting diet, exercise, cognitive 
training, vascular risk monitoring) could improve or maintain cognitive functioning in at-risk 
elderly people from the general population [2]. Nevertheless, despite the overwhelming 
health benefits of physical activity, many older adults are sedentary [3]. The Public Health 
Agency of Canada (PHAC) reports that on average adults spent 9.6 hours per day being 
sedentary [4]. The COVID-19 pandemic made it more difficult for older adults to stay 
physically active, as they were disproportionately impacted by the severity of the disease [5]. 
Isolation from other individuals including friends and family members further compounds the 
challenges to engage in physical activity [6]. Developing and understanding techniques that 
motivate older adults to engage in physical activity has the potential to impact a spectrum of 
health-related behaviours and to improve brain health and quality of life [7]. Motivational 
processes change across the lifespan [8]. Despite a decline in the neurobehavioral influence 

 
 
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of motivation on learning, older adults demonstrate relatively preserved reward sensitivity 
compared to younger adults [9].  
 
Social rewards may be particularly salient for older adults and offer a promising avenue for 
physical activity engagement [10]. Social motivation constitutes an evolutionary adaptation 
encompassing a set of psychological dispositions and biological mechanisms that bias the 
individual to preferentially orient to the social world, to seek and take pleasure in social 
interactions, and to work to foster and maintain social bonds [11]. In younger adults, the 
presence of peers or friends has proven effective in motivating them to stay physically active 
[12]. In older adults, similar strategies seem to be effective; bringing a friend to group 
exercises, walking while talking with a friend, walking to a colleague’s office rather than 
emailing, etc. [13]. Thus, there is reason to postulate that interventions that tap into these 
motivational processes would be effective in reducing time spent sedentary in older adults.  
 
Self-transcendence convenes a change in an individual’s mindset to focus on the well-being 
of others rather than self-interest [14]. Focusing on values and activities that transcend the 
self can allow people to see that their self-worth is not tied to a specific behaviour in question, 
and in turn become more receptive to subsequent, otherwise threatening health information. 
Health message interventions in older adults using self-transcendence priming were 
associated with increased activity in subregions of the ventromedial prefrontal cortex, 
implicated in self-related processing and positive valuation, which predicted later decreases 
in sedentary behaviour [14]. These findings suggest that having a positive self-transcendent 
mindset can increase behaviour change, in part by increasing neural receptivity to health 
messaging [14]. Moreover, health messaging is another potential way to bolster physical 
activity [15]. The framing of health messages matters. Therefore, in this study, we will use a 
social motivation manipulation combined with self-transcendence messaging to take 
advantage of both of these techniques to enhance physical activity in vulnerable older adults 
who have a family history of Alzheimer’s disease, and thus, stand to benefit from a lifestyle 
change. 
 
2. Objectives and Hypothesis      
This remotely administered multidisciplinary pilot proposal focuses on examining the efficacy 
of factors that have shown promise in motivating sedentary older adults to become more 
physically active as well as to investigate changes in patterns of activation of the neural 
networks, as indexed by MRI and fMRI, that support these factors and changes in physical 
activity. Brain imaging data has already been collected as part of the PREVENT-AD longitudinal 
cohort. We will not acquire any new brain or biomarker data but rather capitalize the dataset 
on these participants that already exist. 
 
Aim 1: To determine the efficacy of a novel motivational intervention to enhance physical 
activity in at-risk older adults. In a four-week two-arm randomized controlled trial with 
cognitively normal older adults at-risk for AD, we hypothesize that social motivation 
combined with positively-framed health messaging + home-based physical training will 
increase physical activity compared to positively-framed health messaging + home-based 
physical training. We will examine the extent to which any differential physical activity 
engendered in the two groups is maintained at the longer-term crossover baseline period 
post-intervention or active control. In addition, we will test the extent to which participants 

 
 
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at higher risk of AD differentially benefit from the intervention and changes in physical 
activity. The primary outcome will be objectively-measured physical activity, secondary 
outcomes will be cognitive performance and functional brain connectivity, and tertiary 
outcomes will be fitness, mood and quality of life. 
 
Aim 2. To determine the individual differences in cognitive processes that moderate 
behavioural change in older adults. We hypothesize that individual differences in cognitive 
processes moderate behaviour change in older adults. Therefore, we will test the extent to 
which differences in adaptive decision-making (i.e., reward-effort computations) and 
dimensional measures of motivational traits (i.e., grit and growth mindset) moderate the 
effects of the intervention on change in physical activity. We will capture individual 
differences in motivation to exert effort for rewards using the Effort Expenditure for Rewards 
Task (EEfRT): This is an established computerized cognitive paradigm that maps onto the 
reward valuation/effort construct in the Research Domain Criteria (RDoC) framework. This 
approach will provide a novel, mechanistic understanding of how dimensional constructs of 
motivation influence adaptive decision-making and behavioural change.  
 
Aim 3: To define brain markers that predict successful real-world behavioural change in 
aging. We will test the hypothesis that successful behavioural change (i.e., increased physical 
activity post-intervention versus baseline) is associated with enhanced activation of self-
referential (i.e., ventromedial prefrontal cortex) and reward valuation (i.e., ventral striatum, 
ventral tegmental area) brain networks as indexed by task-based and resting-state fMRI. 
Acquisition of baseline brain imaging data will allow us to ask whether and what 
neuromarkers predict successful behavioural change as a function of the intervention.  
      
     The hypotheses that will be investigated in this study are: 
 
(1) Social-Motivation combined with self-transcendence messaging will increase physical 
activity in older adults, compared to an active control condition. 
 
(2) Enhanced brain network modularity at baseline will predict exercise-related executive 
function gains. 
 
(3) Individual differences in structural and functional network connectivity at baseline will 
predict change in physical activity.  
 
To investigate hypotheses 2 and 3, we will be using previously acquired brain imaging data 
from the PREVENT-AD cohort study. The overarching goals of this work are to identify and 
understand novel strategies to enhance physical activity in sedentary older adults and to 
characterize individual brain and neuropsychological differences that predict behavioural 
change. Our ultimate goal is to develop personalized behavioural interventions in older adults 
that tailor persuasive health-related messaging based on an individual’s neurobehavioral 
profile. 
 
We believe that our intervention will provide valuable, novel information about the efficacy 
of promising factors to enhance physical activity, and in turn cognitive and brain health, in 

 
 
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sedentary older adults as well as the functional brain changes and individual differences that 
support these potential changes in physical activity. 
 
3. Method 
 
3.1 Recruitment 
3.1.1 Initial Contact 
Older adult participants will be recruited through the PREVENT-AD cohort as an optional sub-
study, by reaching out to potentially eligible participants by phone and email. Screening 
procedures will involve verbally screening potential participants over the phone. A staff 
member doing the screening will begin with an overview of the HABS project. The screener 
will then obtain verbal consent (see telephone script). The telephone script will ask questions 
concerning inclusion and exclusion criteria. The total time to administer all screening 
questions is approximately 40 minutes. The telephone screen will also assess the level of 
physical activity via self-reported physical activity. If eligibility is verified, a date and time will 
be scheduled for a virtual meeting between the participant and a researcher where the 
formal study consent will be signed. Those individuals that are deemed ineligible from the 
screening call will have their forms kept in a separate file on REDCap. This information will be 
used to quantify how many were ineligible from the screening call and the reasons for 
ineligibility. 
 
The criteria will be assessed by one of the listed study personnel. No special expertise is 
required to evaluate screening responses. If a participant requires exclusion due to 
information received during a session, they will be contacted via telephone or email and 
informed that they have been excluded from further study, nevertheless remaining part of 
the PREVENT-AD cohort. The reason provided for their exclusion will be brief and will include 
a statement such as, "Based on the data collected in your last session, we will not require any 
further testing. As indicated in the beginning, participation depends on several factors and 
not all participants qualify for the entire study."  
 
3.1.2 Consent Process for Participants 
Participants’ consent will be obtained remotely before they begin participating in research 
activities. The consent process will be administered by experimenters (i.e., research 
personnel described above). Individuals who agree to participate after the phone screen will 
receive a copy of the consent document in advance by email and will schedule a time to speak 
with an experimenter via videoconference. They will be asked to read, but not sign, the 
consent document before the phone call, and the experimenter will coordinate with the 
participant so they have enough time to read the document before the call. During the call, 
the experimenter will explain the study and answer any questions the participant has. If the 
participant wants to take part in the study, they will then sign the consent document 
electronically in the REDCap platform; this format is secure and easy for participants to use. 
The informed consent process will be completed while a researcher is videoconferencing with 
the participant and can answer any questions they may have. Participants will be made aware 
that their participation is completely voluntary, and they may quit the experiment at any time. 
 

 
 
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Participants in the intervention arm will be invited to participate in a social motivation 
manipulation involving a younger study partner. The intervention group will be asked to invite 
an interested younger child/grandchild 18 years and older but younger than 40 to join them 
at the time of consent. The social motivation intervention represents the younger generation 
family member dyad. The study partner will sign as well informed consent during session T0, 
follow the same timeline as their older relative, receiving feedback on their relative’s 
accelerometer data. Study partners have a streamlined intervention whereby they do not 
undergo accelerometry testing and only have two videoconferenced sessions and one phone 
session. Study partners partake in the 4 weeks of daily messages and receive feedback on 
their relative’s performance. The study partner will complete an overlapping, but briefer 
battery of pre and post compared to their older adult family members. Study partners will 
not undergo a remote physical assessment evaluation and will not be required to have 
physical or virtual contact with their older adult family members other than their regular 
interactions.  
 
3.1.3 Consent process for minors aged 14 up to before 18 years old.  
 
Younger study partners between the ages of 14 and up before their 18th birthday, will be 
required to provide remote written assent for their participation in the study by using a 
unique consent form and the remote written consent of their parent or legal guardian. This 
special group of intrafamilial study partners will be the grandchildren of the main participant 
younger than 18 years old. Older participants in the intervention group who do not have 
grandchildren will be assigned an extrafamilial study partner aged 18 years or older. Written 
assent from the minor participant and the written consent of their parent or legal guardian 
will be obtained during session T0. Contact will be through the main study participant who 
will provide the contact details for their younger study partner (grandchild or child). These 
study partners will follow the same timeline as their older relatives, receiving feedback on 
their relative’s accelerometer data. Study partners have a streamlined intervention whereby 
they do not undergo accelerometry testing and only have two videoconferenced sessions and 
one phone session. Study partners partake in the 4 weeks of daily messages and receive 
feedback on their relative’s performance. The study partner will complete an overlapping, but 
briefer battery of pre and post compared to their older adult family members. Study partners 
will not undergo a remote physical assessment evaluation and will not be required to have 
physical or virtual contact with their older adult family members other than their regular 
interactions.  
 
**The study will recruit up to 120 younger study partners including individuals between 18-
40 years old and between 14 and up to 18 years old.  
 
3.2 Eligibility/ Inclusion Criteria 
Participants will not be excluded based on sex, race, or ethnicity. If a participant is excluded 
for any reason, they will be immediately informed that they have not met all criteria and their 
participation will be discontinued. All interested participants will be selected to participate 
until the desired number (n = older adults) is reached. We recognize that women in this age 
group are over-represented relative to men and are also more likely to volunteer for health-
related studies. However, we will attempt to have a diverse sample of participants across 
cultural, gender, language and educational factors in our sample. Participants will be 

 
 
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randomized to one of the two study conditions and be assigned a coded subject number using 
REDCap after signing the consent form. Study partners will be over the age of 1 year.  
 
• Men and women of all ethnicities/races and socio-economic status, older than 60 years 
• Adequate vision to complete the cognitive tasks 
• Able to speak, read, and write English or French 
• Ambulatory without a significant increase in pain or the assistance of walking devices 
• No diagnosis of a neurological disease 
• Wants to engage in more physical activity. 
• Regular access to a computer with internet or a smartphone 
• Having a child, grandchild older or friend aged 14 years or older that is considered ‘close’. 
 
3.3 Exclusion Criteria 
• Current or previous formal diagnosis of a DSM-V Axis I or II disorder including Major 
Depression (not including postpartum depression or anxiety) 
• History of major psychiatric illness including schizophrenia 
• Current treatment for cancer – except non-melanoma skin cancer 
• Neurological condition (MS, Parkinson’s, Dementia, Stroke) or moderate to severe 
traumatic brain injury. 
• Current alcohol or substance abuse 
• Current treatment for congestive heart failure, angina, uncontrolled arrhythmia, DVT or 
other cardiovascular condition 
• Myocardial infarction, coronary artery bypass grafting, angioplasty or other cardiac event 
in the six months before enrollment. 
• Regular use of an assisted walking device or significant increase in pain when walking 
• Use of any antipsychotic, anti-depressant, anti-anxiety, and ADD/ADHD medications, other 
than for sleep. 
• Not fluent in English or French 
• No regular access to a smartphone or computer with internet 
• Involvement in conflicting research studies currently or recently 
 
3.4. Participants ineligible due to physical activity criteria 
Participants who do not want to increase their physical activity levels and are thus ineligible 
for the main study would have the option to join the study for the first 3 sessions up to 
before the 4-week intervention. This would allow for the acquisition of behavioural 
measures up to yellow visits in ineligible participants. The objective would be to understand 
physical activity as it relates to Alzheimer’s disease risk and its related motivational factors. 
This piece of the study would follow the same parameters, cognitive measures, and 
questionnaires as the one collected for the main study for the first three sessions up to 
before the intervention window. Compensation would be provided accordingly.  
 
3.5 Study Partner inclusion criteria 
• Can be identified as child or grandchild of participant (biological or adopted), 14 years or 
older. 
• Can be a young adult (18 years or older) who is not a relative of the main participant, in case 
a grandchild or child is not available. 
• Stable on psychoactive medications for more than 6 months. 

 
 
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• In contact with the primary participant more than once per 12 months at baseline  
• Lives anywhere accessible by mail in Canada if 18 years and older, or anywhere accessible 
by mail in Quebec if 14 years and older but younger than 18 years.  
• Adequate vision to complete the cognitive tasks 
• Able to speak, read, and write English or French 
• No diagnosis of neurological disease or unstable health condition 
• Regular access to a computer with internet or a smartphone 
 
3.6 Study Partner exclusion criteria 
• Not in contact with the primary participant more than once per 12 months at baseline  
 
3.7 Extrafamilial study partners 
 
Young adults (aged 18 to 40) will be recruited from the community to participate as 
extrafamilial study partners. These participants will be paired with an older adult participant 
who does not have a child or grandchild that can participate but is otherwise eligible. Young 
adults will be recruited through flyers posted around the McGill University campus as well as 
an advertisement posted on the Department of Psychology’s SONA participant pool. 
Participants will receive either 2 SONA credits or $40 CAD for their participation. The study 
timeline for extrafamilial study partners will consist of one additional, remote visit 
approximately one week after the formal consent form is signed. This visit will consist of a 1 
hour Zoom call with the older adult participant, the extrafamilial study partner, and a member 
of the research team. 
The purpose of this visit will be to introduce the older adult to the younger study 
partner and provide the participants with an opportunity to get to know one another. This 
conversation will allow the extrafamilial study partner to create the personalized messages 
(“kudos”) for the social messaging application. The younger study partner will be asked to 
lead the conversation and will be provided with a list of questions that they can ask in order 
to get to know the older adult. After the conversation, the older adult will be asked to log off 
the Zoom call and the younger study partner will be asked to provide the 30 personalized 
messages. 
 
3.8. Financial compensation 
Financial compensation will be offered as follows:       
 
3.8.1. Intervention Group 
 
Participant 
Remote Meeting 
Pay 
Session 1 
$20 
Session 2 
$20 
Session 3 
$20 
Session 4 
$20 
Accelerometry Completion  
$20 
TOTALS 
$100 for all sessions and device 
returned 
 

 
 
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Study partner 
REMOTE Session 
Pay 
TOTALS 
$40 for study completion 
 
3.8.2. Control Group 
Remote Meeting 
Pay 
Session 1 
$20 
Session 2 
$20 
Session 3 
$20 
Session 4 
$20 
Accelerometry Completion  
$20 
TOTALS 
$100 for all sessions and device 
returned  
 
3.8.3 Cross-over segment 
 
3.8.3.a Crossed to Intervention Group 
 
Participant 
Remote Meeting 
Pay 
Session 1 
$20 
Session 2 
$20 
Session 3 
$20 
Session 4 
$20 
Accelerometry Completion  
$20 
TOTALS 
$100 for all sessions and device 
returned 
 
Study partner 
REMOTE Session 
Pay 
TOTALS 
$40 for study completion 
 
3.8.3.b Crossed to Control Group 
Remote Meeting 
Pay 
Session 1 
$20 
Session 2 
$20 
Session 3 
$20 
Session 4 
$20 
Accelerometry Completion  
$20 
TOTALS 
$100 for all sessions and device 
returned  
 
 
3.8.3.c Donation to the Alzheimer’s Society 
 

 
 
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Based on the participant’s physical activity performance and their pre-set goals (# of steps 
increase or amount of time increase being active) during the 4-week intervention period, a 
maximum amount of 3.00$ per week would be saved to be donated to the Alzheimer’s society 
at the end of the intervention (up to 18.00$ for the whole intervention).  
 
Week 
Donation 
Week 1 
Up to 3.00$ 
Week 2 
Up to 3.00$ 
Week 3 
Up to 3.00$ 
Week 4 
Up to 3.00$ 
Total Amount 
Up to 12$ 
 
The 3.00$ will be saved for donation if the participant achieves 100% of their goal on a given 
week.  
 
3.8.3.d Donation to the Alzheimer’s Society of Montréal for the cross-over segment 
 
The donation to the Alzheimer’s Society of Montréal will follow the same principle than for 
the first segment of the study for those participants who cross into the intervention: 
 
Week 
Donation 
Week 1 
Up to 3.00$ 
Week 2 
Up to 3.00$ 
Week 3 
Up to 3.00$ 
Week 4 
Up to 3.00$ 
Total Amount 
Up to 12$ 
 
The 3.00$ will be saved for donation if the participant achieves 100% of their goal in a given 
week.  
 
4. Methods/Assessments      
4.1 Overview 
In 120 sedentary and cognitively asymptomatic older adults (60 years and older) we will test 
whether a behavioural intervention combining social motivation, and self-transcendence 
messages decreases the amount of time participants are sedentary, as measured by 
accelerometry. We will use a stratified randomization scheme to ensure that half of the 
participants in each group will be randomized and stratified by their risk of developing 
Alzheimer’s disease: to the social motivation + self-transcendence messaging (intervention) 
and the other half will be randomized to a daily activity monitoring group (active control). 
Participants will not be explicitly told to exercise as part of the study, but during the 
experiment they will receive messages that encourage walking or decreasing sedentary time. 
The primary measure of interest is decrease in sedentary behavior. All participants will be 
recruited from the PREVENT-AD cohort (STOP-AD Centre) at the Douglas Mental Health 
University Centre. Participants will be screened remotely by researchers affiliated with McGill 
University under the direction of Dr. Geddes.  
 
4.2. Study design 

 
 
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The HABS study is a remote behavioural intervention that is conducted as a single-blinded 
randomized controlled trial. Recruited participants will be categorized as either high or low 
risk for Alzheimer’s disease, in accordance with Aim 1 to determine the extent to which the 
behavioral intervention improves physical activity in at-risk older adults. Participant 
classification into high and low risk is based on their already known biomarker and cognitive 
status available  from PREVENT-AD using a multimodal risk score. Note, that this does not 
involve collection of any new data and this data is not shared with participants as per the 
PREVENT-AD protocol. For participant classification into high risk, an individual’s score is 
taken from a two-tier system of variables. The first tier involves variables where a positive 
result involves higher risk for Alzheimer’s disease: Amyloid Tau Index (ATI) <1, and p-tau in 
cerebrospinal fluid, β-Amyloid, and Total tau in PET, or APOE-ε4/ε4 or ε4/ε3status. A single 
positive value in any of these variables classifies the participant into the higher risk group. 
The second tier involves variables that independently are not sufficient for higher risk 
classification but together with a second variable might indicate higher risk: Overall cognitive 
performance (i.e., Repeatable Battery for the Assessment of Neuropsychological Status 
[RBANS]), episodic memory (i.e., Rey Auditory Verbal Learning Test [RAVLT]), hippocampal 
volume on MRI, APOE ε4/ε2 status, Framingham Risk Score, and history of depression or 
consumption of psychotropic medication. Any combination of two variables from this tier 
classifies the participant into the higher risk group. Participants that are not classified into the 
higher risk group either because they had negative results to all risk variables or because they 
had a positive score to only one risk variable from the second tier, will be randomized into 
the low-risk group. We expect that approximately 50% of our participants will be in the high-
risk group. We are using stratified randomization to ensure that each higher risk participant 
will be equally distributed across the intervention and control groups. The participants in each 
risk group are randomized to either a social motivation group (intervention) or control with a 
ratio of 1:1. The stratified randomization scheme is prepared by the Harvard Catalyst 
Biostatistical Group using a permuted block method with random blocks [16]. The 
randomization scheme will be uploaded in the REDCap randomization module. At the end of 
the first study period, participants will be offered to participate in a follow-up to ascertain 
maintenance which will consist of a cross-over into the alternative arm to which they initially 
were randomized. The study consists of two 4-week study periods with at least a 6-week 
washout period in between. This trial is registered on clinicaltrials.gov with an identifier 
NCT04315363. This study received ethical approval from Northeastern University Institutional 
Review Board (IRB). 
 
NOTE ON STUDY DESIGN AND SINGLE-BLINDING: It is important to note that in order maintain 
the single-blind nature of the study, participants will not be specifically told that the daily 
messages are the study intervention.  Therefore, the consent form will simply mention that 
some participants may receive motivational messages, but will not elaborate further.  
 
Hence, in terms of the cross-over design, it will be described as a long-term follow up in the 
ICF in order to maintain the single-blind and not bias the participants.  A debriefing session 
will be held at the end of period 1 to explain to the participants that the motivational 
messages were the intervention and they will be offered to cross-over into the opposite arm. 
See section 5.6 for more information regarding the cross-over.  
 
PERSONNEL: 

 
 
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All staff and personnel associated with screening, collecting data, and analyzing data will have 
been trained and will have undergone all necessary research modules for safety and research 
ethics. Dr. Geddes will meet with all staff on a regular basis to ensure that they are conducting 
research protocols appropriately. In addition, all staff who interact with participants are 
certified in Automatic External Defibrillator (AED) and CardioPulmonary Resuscitation (CPR). 
All staff who administer remote study sessions will be familiar with an emergency protocol 
(including calling emergency services) to prepare for the unlikely event that a participant has 
a medical emergency during a video or phone appointment.  
 
RESEARCH ACTIVITIES: 
After obtaining informed consent, participants will complete screening measures for anxiety, 
depression, and cognitive impairment. If they pass these screenings, they will be randomized 
into the intervention (social motivation + self-transcendence messaging or control group. 
After randomization, participants complete a baseline non-exercise cardiorespiratory fitness 
(CRF) estimation (using heart rate measurement), short virtual physical assessments involving 
walking and sitting-to-standing, and neuropsychological and behavioural assessment during 
the ‘Consent Session’ and at ‘Time 1” (Figure 1).  
 
5 Intervention      
5.1 Study timeline      
An illustration of the study timeline can be seen in Figure 1. Informed consent is obtained at 
the initial video-conferenced meeting. Each participant undergoes a baseline session (T1) one 
week before the beginning of the intervention. As a baseline, participants wear a wrist-worn 
accelerometer on their non-dominant hand to assess physical activity (see physical activity 
monitoring). Physical assessments will be administered at baseline. The accelerometer is 
worn for a week. The intervention lasts 4 weeks, during which participants receive daily 
intervention messages via email or phone. Participants are fitted with the accelerometers 
again for a one-week mid-intervention period. The post-intervention session (T3) is scheduled 
at the beginning of the last intervention week (week 4), during which participants repeat 
psychosocial surveys and neuropsychological tests. All sessions are administered remotely 
through online surveys and computer tasks (please see timeline document).  
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

 
 
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Figure 1. Main participant’s timeline (2 arms, Intervention and Control) with Cross-over 
design.  
 
5.2 Social Motivation Intervention      
Participants in the intervention arm will be invited to participate in a social motivation 
manipulation involving a study partner. The same number of study participants will be 
recruited as the number of older adults in the study given that older adults in the active 
control group will be offered the opportunity to participate in the intervention after the 
washout period. The intervention group will be asked to invite an interested younger 
child/grandchild over the age of 14 years to join them at the time of consent. The social 
motivation intervention represents the younger generation family member dyad. These 
individuals will be either a child or a grandchild of the participant in this arm who is older than 
14 years old but younger than 40. The study partner will sign as well informed consent, follow 
the same timeline as their older relative, receiving feedback on their relative’s accelerometer 
data. The younger adult study partner will complete an overlapping, but briefer battery of pre 
and post assessments compared to their older adult family member. Study partners will not 
undergo a remote physical assessment evaluation. Minor participants aged 14 years to up 
before their 18 birthday need to provide written assent by a parent or legal guardian. All study 
partners will not be required to have physical or virtual contact with their older adult family 
members other than their regular interactions. Because of the nature of this intervention 
which involves adolescents, it minimal the risk for minors participatinga,b and the potential 
benefits to their well-being of intergenerational social interactions.  
 
aNational 
Commission. Report 
and 
Recommendations: 
Research 
Involving 
Children. Washington, DC: U.S. Government Printing Office; 1977. 
bFernández C; Canadian Paediatric Society (CPS), Bioethics Committee 
Paediatr Child Health 2008;13(8):707-12 
cSantini S, Tombolesi V, Baschiera B, Lamura G. Intergenerational Programs Involving 
Adolescents, Institutionalized Elderly, and Older Volunteers: Results from a Pilot Research-
Action in Italy. Biomed Res Int. 2018;2018:4360305. Published 2018 Dec 5.  
 
 
5.3 Daily messaging       
The 4-week intervention consists of daily self-transcendence messages via email using the 
encrypted online software oTree, an open-source platform for implementing messaging 
surveys, which allows for accessibility via desktop or smartphone [17]. Unique, coded links 
are assigned to each participant at enrollment. Participants will be requested to: “For the next 
30 seconds contemplate the warm feelings you have towards a loved one as vividly as you 
can. Think about a situation where the following wish comes true for your loved one: May 
you be well”. Examples of daily self-transcendence prompts rotate among: 
 
- 
May you be well 
- 
May you be happy 
- 
May you be safe 
- 
May you be at ease 
- 
May you be healthy 

 
 
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- 
May you be peaceful 
- 
May you find wholeness 
- 
May you be joyful 
 
Each day if they reach their physical activity goal, the main participants will receive messages 
from a pre-set list of messages composed at the consent session by their study partners (see 
Annex A – time capsule). The participant will then rate their mood and confidence in 
implementing the health tips, the goal of which is to examine the changing in well-being and 
self-efficacy of physical activity throughout the intervention. During weeks 2 and 4, they also 
receive daily reminders to continue wearing their accelerometer. This daily message survey 
setup is displayed in Figure 2. The researcher’s contact information is displayed on each 
survey page to enhance compliance. Participants’ responses are tracked and those that do 
not complete the survey by a specified time of day are contacted the following day by 
research assistants to prevent technical failures. 
 
In addition to self-transcendence health messages, participants in the intervention arm will 
receive feedback about their daily physical activity using the CentrePoint encrypted software 
package from Actigraph (https://actigraphcorp.com/cdh/). The CentrePoint data hub is a 
home-based communication gateway that securely transmits data captured by the Actigraph 
activity monitors to provide near real-time feedback to participants about daily physical 
activity. 
 
Figure 2. Messaging system setup and logic. Each participant (represented by Px, where x designates 
the participant number) receives their unique link. In that link, they follow a series of pages each day 
that contain their unique questions and parameters based on the inputted comma-separated values 
(CSV) file. The system does not initiate until the participant begins on their first day and then repeats 
for 28 days (4 weeks) for the duration of the daily messaging intervention. The process occurs 
synonymously for all other participants. Links that are not activated simply remain idle until a 
participant is assigned that link 
 
5.4 Non-exercise cardiorespiratory fitness estimate 

 
 
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At baseline, participants will be asked to wear an accelerometer and have their 
cardiorespiratory fitness (CRF) estimated. The assessment of cardiorespiratory fitness (CRF) 
is associated with burdens of time, cost, risk and resources. To address this concern, we will 
take advantage of a non-exercise estimate of CRF. CRF will be estimated by a method 
developed by Jurca et al. (2005) [18] and validated by Mailey et al. (2010) [26]. The estimation 
uses a regression equation that includes age, sex, body mass index, resting heart rate, and 
self-reported physical activity. We will obtain a non-exercise CRF estimation before and four 
weeks after the intervention. To perform the CRF estimation, we will collect the resting heart 
rate after participants have rested quietly for ten minutes. 
 
5.5 Neuropsychological Assessment      
If participants pass this second screening, they will complete neuropsychological and 
behavioural inventories. We expect testing to take about 3 hours and will administer the 
assessments with breaks every ~40 minutes to reduce fatigue. They will complete behavioural 
inventories that capture individual differences in traits potentially predicting responsiveness 
to the intervention. These measures (listed in the attached spreadsheet) include validated 
questionnaires to assess factors like motivation for physical activity, self-efficacy for exercise, 
self-efficacy for walking, barriers to exercise, mood, conscientiousness and grit, growth 
mindset, loneliness, future time perspective, and purpose in life. Participants’ educational 
attainment and total personal income levels will also be collected to create a measure of 
socioeconomic status, as described by Hartanto et al. (2019) [19]. These questionnaires will 
be administered through REDCap, a “secure, HIPAA-compliant, web-based application… 
housed in a secure local data center, behind the Tufts Medical Center firewall, and all web-
based information is encrypted” (tuftsctsi.org/research-services/informatics/redcap-
research-electronic-data-capture/).  
 
Participants will also complete a cognitive battery (also listed in the attached spreadsheet) 
that examines important cognitive constructs that have been associated with changes in 
physical activity and aging including executive function (i.e., the Brief Test of Adult Cognition 
by Telephone [BTACT]), working memory (n-back, WAIS-IV Digit Span Forwards and 
Backwards), sustained attention and motor speed (WAIS-IV Coding test, simple reaction 
time), verbal fluency (Category and Phonemic Fluency tests), and episodic memory (Hopkins 
Verbal Learning Test – Revised (HVLT-R). Neuropsychological measures will be administered 
remotely via telephone encrypted videoconferencing (using HIPAA compliant Zoom software) 
and secure, coded platforms such as Test My Brain (testmybrain.org). Additional paradigms 
are described below:  
 
The Intrinsic Motivation Effort Expenditure for Rewards Task (EEfRT), captures the construct 
of Reward Valuation and Effort. This multi-trial computerized task presents participants with 
a (variable) level of reward and a (variable) amount of work (effort) to win that reward. For 
each trial, the participant must accept or reject the proposal based on whether they think the 
reward is worth the effort. If they accept the trial, they have a 1/3 chance of then being asked 
to perform that work. The “work” is fast key presses on the left and right arrow keys, using 
the right-hand index and middle fingers. The amount of work is communicated using a vertical 
rectangle with a horizontal line through it at different heights; the higher the line, the more 
key presses are required. Participants are given visual feedback during the trial as the line is 
moved to the bottom and is progressively raised with each button press, with the goal of 

 
 
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raising the line up to its original height for that trial. Rewards come from three domains: 
monetary rewards (hypothetical money), social rewards (hypothetical time with loved ones), 
and intrinsic rewards from curiosity (the answers to trivia questions). There are 6 “levels” of 
reward in each of the three domains, and 5 levels of work. 
 
The Option Generation Task [22] measures participants’ fluency and ability to generate 
options for future behaviour. In each trial, the experimenter will present the participant with 
a hypothetical “open” (e.g., It’s a rainy and cold Sunday. What could you do?) or “problem-
solving” situations (e.g., You are in a foreign city and you are lost. What could you do?).  
 
The participant will be given 2 minutes to generate options for action. They will be 
encouraged to describe each option briefly, mainly using keywords. 
 
The Delay Discounting Task is a measure of temporal discounting; the tendency for people to 
prefer smaller, immediate monetary rewards over larger, delayed rewards. Participants will 
respond to a series of 27 questions that ask them to choose between a smaller, immediate 
reward (e.g., $25 today) versus a larger, later reward (e.g., $35 in 25 days). The 27 items are 
divided into three groups according to the size of the larger amount (small, medium, or large). 
Modeling techniques are used to fit the function that relates time to discounting. The main 
dependent measure of interest is the steepness of the discounting curve such that a more 
steeply declining curve represents a tendency to devalue rewards as they become more 
temporally remote (Science of Behavior Change, Columbia University). 
 
The Future Time Perspective Task [24, 25] assesses the length of individuals’ views of the 
future, where more limited views of the future have been linked with pathological impulsive 
behavior like drug use. Participants will be asked to generate a list of five future life events 
and respond orally, without a time limit. After the events are generated, the experimenter 
will ask the participant to estimate how far into the future each event might occur. The two 
dependent measures for this task are the ‘extension’, which is the maximum length of time 
generated by each subject, and the mean future time period for all five items. 
 
In the simple reaction time task, the participant will be presented with a blank white screen 
and asked to press a button as quickly as possible each time a large, black “X” appears. The 
“X” will always appear in the same spot in the center of the screen. This measures the 
participant’s reaction times. 
 
In summary, in order to understand the variability in participants’ responses to persuasive 
messaging, we will explore a rich dataset of individual differences across behavioural traits 
and cognitive, structural, and functional brain measures. All brain imaging and biomarkers 
have been already collected under the auspices of the ongoing PREVENT-AD study, of which 
the PI, Dr. Geddes, is a formal collaborator. Some of these tests will be administered verbally 
by adapting in-person, pen and paper versions to phone calls or video conferencing formats. 
Certain phone-based tasks require researchers to collect audio recordings of participant 
responses for timing and other scoring purposes.  Online replacement tests will be 
administered using TestMyBrain.org and Pavlovia.org.  
 

 
 
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TestMyBrain was developed by Dr. Laura Germine and colleagues in 2008 and is updated 
continuously. TMB provides online alternatives to classic pen-and-paper neuropsychological 
assessment tools and has normative data from thousands of online test subjects aged 12 to 
90. TMB only provides tests that have been validated online and shown to be comparable to 
hard-copy versions. The TMB Neuropsychology Toolkit follows HIPAA regulations and does 
not collect personal identifiable data or demographic information. They retain test 
performance data for quality assurance and temporarily store access information (IP address, 
access URL, timestamp, and user agent) for 14 days to help prevent or identify security 
breaches or other fraudulent behaviour. 
 
Pavlovia was created by John Pierce and colleagues at the University of Nottingham and is 
now run by Open Science Tools LTD. It is fully GDPR, or General Data Protection Regulation, 
compliant. The GDPR concerns data protection and privacy in the European Union and the 
European Economic Area. Source: https://pavlovia.org/docs/home/ethics 
 
Participants will be assessed remotely with accelerometers and have their cardiorespiratory 
status estimated. The estimation uses a regression equation that includes age, sex, body mass 
index, and resting heart rate. We will obtain a non-exercise CRF estimation before and after 
the four-week intervention. To perform the CRF estimation, which will be remote, we will ask 
participants to report their supine resting heart rate after they have rested quietly for ten 
minutes. Participants will also complete a remote physical assessment focused on their basic 
walking speed, their ability to transition repeatedly from sitting to standing, and their balance. 
 
Accelerometers, chargers, and related materials will be sent to participants through the mail 
after the consent meeting and will be returned after the end of the first study period. 
Accelerometry data will be recorded during wakefulness and sleep, with the exception of 
bathing or swimming, for the week between T1 and T2 (before the intervention begins; i.e., 
baseline), for two separate weeks during the 4-week intervention (with additional days during 
this timeframe for any participant who does not wear the devices consistently during the 
original period). This will characterize changes in physical activity from baseline and 
maintenance. It will be assessed using two accelerometers worn simultaneously. The first is a 
wrist-worn tri-axial accelerometer (ActiGraph GT3X Link, Pensacola, FL). This accelerometry 
data will be downloaded in 60-second epochs (ActiLife software, ActiGraph, Pensacola, FL) 
and will be screened for wear time using standard methods [26]. The second device is a tri-
axial accelerometer and inclinometer and will be worn on the thigh using an adhesive.  
 
Physical activity will be measured with an ActiGraph accelerometer model GT9X Link 
(ActiGraph LLC, Pensacola, FL). The ActiGraph GT9X Link is a small (3.5 x 3.5 x 1 cm) and light 
(14 g) device that measures acceleration in three planes: vertical, anteroposterior and 
mediolateral. Participants will wear the device on their wrists 24 hours a day to improve 
compliance. The 24-hour protocol has resulted in greater compliance over waking time wear 
protocol [27]. Participants will be instructed to take the device off for swimming, showering 
and bathing. Data from this device will be synced with the CentrePoint app (HIPAA compliant, 
also through ActiGraph) on the participant’s phone or computer. Raw data will be reduced 
and processed using ActiLife software (http://www.actigraphcorp.com). Participants will fill 
in sleep and activity logs.  
 

 
 
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The physical assessment administered at T1, T3, and T4 will involve the 2-minute walking test 
adapted from the NIH Motor Battery, a 20-second sitting-to-standing test (also used in the 
CDC’s STEADI toolbox), and observations of balance while doing everyday activities like 
putting on shoes. We will record these physical assessments using Zoom. These are sensitive 
measures often used with older adults that reflect their fitness, especially their lower-body 
strength. Choosing these sensitive measures makes it more likely that we will be able to 
detect fitness changes post-test if the intervention results in the behaviour changes we 
expect. 
 
 
5.6. Cross-over design 
 
In order to ensure that participants in the active control group have the opportunity to enroll 
in the intervention, a cross over period 2 is in place. Enrolled participants who complete the 
first period of the study will be offered, the possibility to participate in a follow-up assessment 
to ascertain a maintenance effect. While the primary endpoint is at the completion of period 
1 for all participants, an identical schedule of acquisition is implemented for period 2. Both 
groups are offered the opportunity to crossover into the other arm of the study (intervention 
to active control; active control to intervention). This follow-up will consist in a cross-over to 
the opposite study arm to which they were initially randomized. The study will include two 
periods of 4 weeks separated by a washout period of at least 6 weeks. 
 
 
5.6. Study partner 
 
The study partner (grandchild, child or friend) of the main participant will undergo a shorter 
cognitive battery and questionnaires. The timeline for the study partner’s participation is 
provided in Figure 3. Their participation will involve two main sessions T1s (pre) and T2s 
(post). Each session will take between 1.5-2 hours. During the 4-week intervention, each day 
if they reach their physical activity goal, the main participants will receive self-transcendence 
messages from a pre-set list of messages composed at the consent session with the study 
partner. The study partners will receive feedback on their relative’s accelerometer 
performance.  
 
Study partner’s participation is limited to the study period where the main participant is 
taking part in the intervention arm. This means the study partner will only be involved in one 
of the study periods. If the main participant starts with the intervention arm, the study 
partner will only be part of study period 1 (Figure 1), and end its participation before the 
washout period. If the main participant starts in the control arm, the study partner’s role will 
start after the washout period, i.e. during study period 2, when the main participant crosses 
over to the intervention arm.   

 
 
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Figure 3. Timeline study participants (Intervention Arm in Periods 1 and 2).  
 
6a. Data management 
All research data are coded and only the research coordinator has access to identifiable 
information stored in a secure location. Data are stored electronically on password-protected 
servers behind university-protected firewalls. Data collected are stored in one of three ways; 
(1) MRI data (including tasks) and 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. (2) All pen-and-paper psychosocial and 
neuropsychological assessments are scored and uploaded to REDCap [28]. Computerized 
psychosocial assessments are collected directly in REDCap and computerized 
neuropsychological assessments are uploaded to REDCap [29]. 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. 
 
6b Data analysis      
Outcome measures outside of the neuropsychological assessment battery are as follows: 
 
Outcome measure 
Type 
Timeframe 
Brief description 
 
Total step count (average steps/day)  
Primary 
Week 
0 
(baseline); 
Week 
2; 
Week 4.  
This metric quantifies the 
change in the average number 
of steps taken each day, from 
the baseline, Week 2, and 
Week 4. It is a marker of 
change in habitual ambulatory 
activity. 
Sedentary behavior (average min/day) 
Primary 
Week 
0 
(baseline); 
Week 
2; 
Week 4.  
This metric quantifies the 
change in the average amount 
of time spent sedentary each 
day, from the baseline, Week 

 
 
20 
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2, and Week 4. It is a marker of 
time spent inactive. 
Moderate-vigorous activity (average 
min/day) 
Secondary 
Week 
0 
(baseline); 
Week 
2; 
Week 4.  
This metric quantifies the 
change in the average amount 
of time spent engaged in 
moderate-to-vigorous 
physical activity each day, 
from the baseline, Week 2, 
and Week 4. It is a marker of 
physical activity.  
Walking Cadence 
Secondary 
Week 
0 
(baseline); 
Week 
2; 
Week 4 
This 
metric 
reflects 
the 
participant’s average steps 
per minute. We will examine 
change from baseline over the 
course of the intervention. 
Walking Bouts 
Secondary 
Week 
0 
(baseline); 
Week 
2; 
Week 4 
This measures the number of 
‘bouts’ of physical activity (in 
our case, steps). We will have 
two counts: the number of 5+ 
minute bouts and the number 
of 10+ minute bouts of 
walking. We will examine 
changes from baseline over 
the course of the intervention. 
 
A spreadsheet holding the list of neuropsychological assessments to be used, with brief 
descriptions, is attached. They will be administered at T1 (Week 0), T2 (Week 1), and T3 (Week 
4). 
 
To test our main hypothesis that social motivation + self-transcendence messaging + home-
based physical training will produce the largest increase in physical activity over the course of 
the 4-week intervention compared to the active control, we will perform repeated measures 
ANCOVAs (with group as a between-subject factor and pre-post session as a within-subject 
factor). This hypothesis will be examined by analyzing total number of steps and percent time 
sedentary. We will analyze structural/functional MRI connectivity to test the hypothesis that 
increased physical activity following the intervention is associated with enhanced brain 
connectivity between brain regions in reward valuation (i.e., ventral tegmental area and 
ventral striatum) and social processing (vmPFC). We will conduct seed-based functional 
connectivity analyses using methods as in our prior research [9, 29-31]. To mitigate the 
influence of motion, we will identify and address artifactual motion outliers in data modeling, 
and employ quality assurance software to mitigate head motion artifacts and physiological 
aliasing (https://www.nitrc.org/projects/artifact_detect). We will control for the effects of 
demographic variables (e.g., age, sex, education, diet, mood, socioeconomic status, alcohol, 
vascular risk factors and sleep). We apply a whole-brain height threshold of p < 0.001 (T = 
3.24) and false discovery rate cluster threshold of p < 0.05. We will examine brain modularity, 
which indexes the segregation between networks, and has previously been shown to predict 
cognitive gains after a physical exercise intervention [20]. In addition to these hypothesis-
driven analyses, we will perform an agnostic, data driven multi-voxel pattern analysis of 
resting-state data using an approach published by our collaborator [21]. 

 
 
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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 A B values). Group differences at baseline are examined for variables including 
demographic factors (i.e., age, sex, educational level, socioeconomic status, culture), baseline 
sedentary time, self-report sitting time, and estimated fitness, in order to detect potential 
confounding factors. For the primary hypothesis that social motivation + self-transcendence 
messages decrease sedentary time more than an active control, all outcome measures about 
sedentary behaviour are first quantified using available software. Changes in sedentary 
behaviour (% daily sitting and lying time, minutes/per day in physical activity, count of steps) 
over time (3-time points) are analyzed using linear mixed effect models to account for the 
correlated data and likely heterogeneous variability.  
 
Non-linear changes across 3-time points are also examined by including quadratic effects. 
These models will include a random intercept and slope to account for subject-specific 
changes as well as a group (2) x time (3) interaction fixed effect. This allows for modelling of 
the effect of our intervention as a function of both groups and time as well as accounting for 
potentially confounding covariates. All model assumptions will be tested both visually and 
formally and associations between covariates will be assessed to protect against 
multicollinearity. 
 
Analyses on the resting state and task-based fMRI analyses are considered secondary. Briefly 
they will be modeled using the general linear model approach. First-level analyses will include 
all necessary nuisance regressors to minimize motion artifacts influence, spatial smoothing 
kernel and high pass filtering, as well as physiological aliasing for the low-frequency 
fluctuations in resting state data. To answer questions about the intervention effect and 
prediction of behavioural change, both a priori ROI seed-based analyses of functional 
connectivity are performed as well as data-driven whole-brain multi-voxel pattern analysis, 
modularity analyses and graph theory per several previous publications using data-driven 
approaches to predict clinical outcomes. Besides the primary outcomes, adherence and drop-
outs are also included in the prediction model as outcome variables, to examine what 
individual characteristics affect participation in the current intervention. Robust-prediction 
models of MRI data and psychosocial measures will be generated using cross-validation 
methods to improve the generalization of the results. 
 
Selection bias will also be considered in our study by comparing characteristics between the 
source population (i.e., PREVENT-AD participants) and the study sample. For eligible 
participants invited to participate in the study, we will document the proportion of those who 
decline and agree to participate. We will compare demographic information (age, sex, 
education, ethnicity, socioeconomic status, smoking status, and self-reported physical 
activity) between those who agree and those who refuse to participate using t-tests and chi-
square tests of independence. Multivariate logistic regression models will be used to 
determine whether these characteristics are associated with acceptance relative to refusal to 
participate in the study. 
 
 
7. Data confidentiality and protection 

 
 
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To reduce the risk of breach of confidentiality we will separate all information obtained during 
the screening period from identifying documents. All research data will be anonymized. These 
documents will be stored in a separate location from the data and the screening information 
on REDCap, in a project file to which only lab personnel have access. Data that is saved 
electronically (computer system) is protected by the REDCap firewalls. During data collection 
from participants, staff will converse with participants and have knowledge of names, but will 
be encouraged to maintain a first-name basis whenever possible. All data will be blinded and 
only used in aggregate to understand physical activity effects on the brain and cognition. 
 
We will ensure participant confidentiality by using PREVENT-AD’s coding for all participants' 
data according to their numbering system and separating it from the informed consent. All 
informed consent documents and data files pertaining to subject data information will be 
kept in encrypted, password-protected files on an encrypted, password-protected flash drive 
that only researchers involved in the project will have access to. Multiple levels of password 
protection (e.g., record, file, directory, server, and computer levels) are employed to ensure 
data security. All personnel involved in the study will be approved through the IRB and agree 
to protect the security and confidentiality of identifiable information. All data pertaining to 
the individual will be stripped of all identifying information. Paper copies of data will be 
destroyed 7 years from the date of study completion. Trial results will be uploaded to 
Clinicaltrials.gov in compliance with the NIH standards of reporting. 
 
 
8. Incidental findings 
If any study results are revealing a direct implication of the health and safety of the participant 
(i.e. requiring immediate medical intervention or in the near future), the incidental findings 
will be transmitted to the physician of the participant indicated on the informed consent 
form. In cases where the physician is not reachable or not indicated on the informed consent 
form, the clinical staff of the Douglas Hospital will inform the participant as soon as possible. 
This procedure will be followed for all participants whether or not they wish to be contacted 
for less serious incidental findings. 
 
 
9. Risks      
The procedures, techniques, equipment, and measures to be used in the proposed study are 
commonly used in educational and research settings involving human subjects, and are not new, 
untested, or of questionable safety. Experimenters are aware of the potential for serious adverse 
events to occur with any type of moderate-intensity exercise, but such risks are considered 
minimal in this population. In addition, the primary focus of this study is the decrease in sedentary 
behavior and an increase in walking rather than moderate to vigorous exercise. There is a risk of 
physical injury during exercise, particularly if participants have little to no previous experience. 
Fatigue and muscle soreness may also occur in participants who do not normally engage in 
physical activity. Exercise is associated with a very small risk of serious medical complications 
including heart attack and sudden death, although this risk is particularly small in healthy older 
adults. Lastly, protocols currently exist to respond to any adverse events by contacting emergency 
response personnel and facilitating their arrival to the correct rooms (if the event occurs at the 
Center).  

 
 
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Participants will have contact information for study personnel should they have an unexpected 
adverse effect or question. The daily health messages contain information on how to contact 
study personnel if needed. Participants also receive a recruitment packet detailing contact 
information for study personnel to avoid technical failure (e.g., with accelerometers). We will 
send biannual safety reports to an independent safety officer, Dr. Etienne de Villers-Sidani, a 
neurologist and neuropsychologist who is not involved in the study. If an unexpected adverse 
event arises, the study team will alert the PI, Dr. Geddes and Dr. Geddes will inform Dr. Etienne 
de Villers-Sidani. The PI will be made aware of any adverse outcomes. All research personnel will 
be trained in good clinical practice ethics modules.  
 
Access to private health information 
There is a potential risk of breach of confidentiality that is inherent in all research protocols. 
There is a possibility that if research data were to become generally known, this knowledge 
could potentially impact a subject's future insurability, employability, or reproduction plans, 
or have a negative impact on family relationships, and/or in paternity suits or stigmatization. 
 
Exercise  
There are several common risks associated with exercise participation including injury to 
muscles or joints, especially when initiating an exercise program after a period of being 
sedentary. Further, there is a minor risk of dehydration or heat exhaustion. More commonly, 
there is a risk of falling. Based on our considerable experience in walking and balance-based 
research assessments and interventions in adults, many of whom are much older than the 
cohort anticipated for enrollment into this study, we are confident that this risk is rare, meaning 
that it will occur in less than .001% (less than 1 out of 100000) of people in the otherwise 
healthy adults targeted for this study. This risk will be minimized as we are focusing on walking 
and reductions in sedentary behaviour rather than exercise training. Adverse or unstable 
cardiovascular or pulmonary response to exercise, including disorders of heart rhythm, heart 
attack, stroke, or sudden death will be minimized, because assessment of vital signs and history 
of heart disease are included in our screening procedures, and only those adults with 
satisfactory results as detailed in our eligibility criteria will be allowed to participate in 
experimental procedures for this study. As such, we anticipate that this risk is rare. According 
to American College of Sports Medicine (ACSM), guidelines published in 2000, the risk of 
myocardial infarction (MI) in symptomatic (categorized with males and females having 
ventricular arrhythmias) and asymptomatic (without any signs or symptoms indicative of 
ischemic heart disease) individuals during exercise is less than 0.04%. The risk of death in the 
same population is less than or equal to 0.01%, and the risk of needing hospitalization (including 
acute heart attack and/or serious arrhythmia) is less than or equal to 0.2%. The risk of 
cardiovascular complications occurring during exercise is rare (occurs in less than 1% of people). 
A retrospective survey by the YMCA revealed 1 death and 1 cardiac arrest per 2,897,057 and 
2,253,267 person-hours. To minimize the risk, we are using a non-exercise estimation of 
cardiorespiratory fitness that requires BMI and heart rate measurement only.  
 
Cognitive assessment and questionnaires 
Some inconvenience and/or anxiety may occur due to time required to complete formal 
rating scales and questionnaires. The cognitive assessments impose some risk of emotional 
discomfort. Fatigue is associated with performing the cognitive tasks. The Geriatric 

 
 
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Depression Scale and the Geriatric Anxiety Inventory may warrant a follow-up if the subject 
receives a clinically significant score on any of these items (e.g., >5 on the GDS). These items 
will be scored immediately after completion by the subject. 
 
ActiGraph physical activity monitor  
Participants may experience red skin or discomfort from wearing the device around the waist 
wrist too tightly or for an extended period of time. 
 
PERSONNEL: 
All staff and personnel associated with screening, collecting data, and analyzing data will have 
been trained in their laboratory and will have undergone all necessary research modules for 
safety and research ethics. Dr. Geddes will meet with all staff on a regular basis to ensure that 
they are conducting research protocols appropriately.  
 
Regarding use of the physical activity monitoring devices, participants will be guided through 
the use of the devices at T1 and will be reminded repeatedly throughout the study. We will 
help participants through the fitting process of the device and alert them to the sound the 
device will make when it is properly adjusted and ready to collect data. We will ensure that 
participants understand how the device works and how to correctly wear it to avoid any 
discomfort or incorrect usage. We will also instruct participants to notify us if any discomfort 
occurs. If any discomfort does arise as a result of wearing either of the physical activity 
monitoring devices, we will instruct participants to discontinue the use of the device. 
 
Cognitive assessments: To alleviate any fatigue that may occur, participants are offered 
breaks during testing periods. They will also be provided with a referral for psychiatric 
consultation upon request or if their scores on the GDS and GAI are clinically significant, 
according to each evaluation’s scoring guide. Any person scoring highly on the depression, 
anxiety, or cognitive impairment items will be referred back to their PCP for consultation. 
 
 
10. End of Study 
There is the potential for direct benefit to participants randomized to the social motivation + 
self-transcendence health messaging arm of the study. Participants may experience direct 
benefits from participation such as improved cognition, mood, quality of life, physical fitness 
or decreased sedentary behaviour as a result of participating in the behavioural intervention 
over 3 months. There may be a reduction in central adiposity and cardiovascular benefits. In 
addition, we are hoping that participants will maintain reductions in sedentary behaviour 
beyond the completion of the study. The findings of this study provide information regarding 
the effect of simple and cost-effective behavioural intervention in reducing sedentary 
behaviour and improving brain health in a population at risk for cognitive decay. As such, the 
dissemination of this information stands to improve public health. 
 
 
11. Transfer of Knowledge 
As part of the goals of this study, we intend to publish the results of these trials through 
scientific articles engaging in open science platforms, as well as through scientific conferences 
both locally and internationally. We believe that this intervention could be the first step 

 
 
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towards behavioural counselling with a precision medicine goal. This could potentially be a 
feasible way how to positively influence people’s behaviour, especially patients at risk. 
Furthermore, positive results could potentially be translated into providing the active control 
group of this trial with the actual intervention. Moreover, if demonstrated that the 
intervention is successful in fulfilling its goals, we intend to offer it to a wider group of older 
adults, as we consider it a cheap, scalable, and effective way of motivating physical activity in 
sedentary older adults. 
 
 
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List of Annexes: 
 
Annex A. Time Capsule. 
 
Annex B. Study Partner cognitive battery and list of questionnaires. 
 
Annex D. The Benefits of Physical Activity for Older Adults (informational material). 
 
Annex F. Extrafamilial Study Partner Recruitment File. 
 
Annex H. Extrafamilial study partner – script for partnering.  
 

 
 
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