Intervention to Reduce Sitting Time in Mild Cognitive Impairment
Phase: NA
Conditions: Mild Cognitive Impairment
Sponsor: University of Kansas Medical Center

 
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University of Kansas Medical Center  
RESEARCH PROTOCOL INVOLVING HUMAN SUBJECTS  
 
Study Title: Intervention to Reduce Sitting Time in Mild Cognitive Impairment (ReST-MCI) 
NCT#: 02878486 
Principal Investigator: Amber Watts 
 
Co- Investigator(s): John Thyfault, Christie Befort 
Version date: May 5, 2016 
 

 
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University of Kansas Medical Center  
RESEARCH PROTOCOL INVOLVING HUMAN SUBJECTS  
 
I. 
Purpose, Background and Rationale 
A. Aim and Hypotheses  
Older adults are highly sedentary, spending more than 60% of waking time sitting. Independent of 
physical activity, daily sitting time is a risk factor for poor glycemic control and type 2 diabetes. Glycemic 
control and insulin sensitivity are inexorably linked to Alzheimer’s disease (AD) and cognitive decline. 
Individuals with mild cognitive impairment (MCI) and AD display physiological differences in insulin and 
glucose regulation compared to older adults without cognitive impairment. Reducing sitting time and taking 
frequent breaks from sitting have resulted in improved glycemic control and insulin sensitivity within hours. 
Studies are beginning to suggest that time spent in seated activities (e.g., TV) is associated with poorer 
global cognitive function and risk of AD independent of physical activity. 
The proposed study directly addresses the recommendations of an NIH sponsored workshop on 
“Physiology of Sedentary Behavior and its Relationship to Health Outcomes.” 1) We will investigate the 
physiological correlates of sedentary behavior by assessing glycemic control and insulin sensitivity. 2) We 
will focus on the impact of lack of movement as distinct from the effects of movement by objectively 
measuring both simultaneously. In individuals with MCI, we will evaluate whether a behavioral intervention 
to reduce sitting can alter physiological processes known to contribute to disease pathology. 
          Cardiorespiratory fitness changes that occur with moderate or vigorous aerobic exercise may not be 
essential for improving brain health and cognition, as demonstrated by studies of activities that do not 
robustly improve fitness (Tai Chi, resistance training, Wii fit), but still show improvements in brain health and 
cognition. Even low intensity, non-exercise activity is associated with reduced risk of cognitive decline and 
healthier cardiometabolic measures. In fact, non-exercise activity accounts for the vast majority of daily 
activity, while exercise accounts for only 2-5%. More evidence is needed to determine whether reductions in 
sitting time are sufficient to produce changes in cognitive performance, brain volume, or neurogenesis as 
seen in aerobic exercise interventions.  
Interventions targeting sedentary behavior can effectively reduce sitting time (average 42 min/day), 
but few studies have evaluated whether these reductions result in clinically meaningful outcomes and none 
have been conducted in older adults with MCI. We propose a feasibility study of a 12-week home based 
behavioral intervention to reduce sitting time among sedentary older adults with MCI and their 
caregivers. The intervention is designed to break up prolonged bouts of sitting and replace sitting behavior 
with standing and light or moderate intensity activities associated with improved cognitive performance 
among people at risk for AD. Our proposed intervention adds innovative elements that are empirically 
rigorous compared to previous studies: 1) it uses objectively assessed electronic postural monitoring, 2) it 
provides electronic feedback to promote sitting times <30 minutes, 3) it assesses insulin sensitivity and 
glycemic control which are sensitive to changes in sitting after a short duration and which few previous 
interventions have measured, 4) it is conducted in the home and targeted to individual habits and physical 
environments that reinforce sitting behaviors, 5) it targets sedentary older adults with MCI, which has not 
been done before, and 6) it capitalizes on the caregiver/patient dyad to help improve adherence to the 
behavioral change regimen. 
Specific Aim 1: Determine feasibility of a 12-week home and telephone based intervention in 
older adults with mild cognitive impairment targeting both the impaired individual and their study 
partner to help initiate and maintain behavior change. We will recruit KUADC registry participants with 
MCI and their caregivers (as study partners). Behavioral interventions are more effective when there is built 
in social support. We will evaluate feasibility in terms of successful recruitment and retention of participants, 
10% or less of technological failures, rate of participant concerns addressed by phone and at home visits, 
acceptability of the intervention to participants (measured by questionnaires during home visits). 
Specific Aim 2: Determine whether a 12-week home and telephone based intervention results 
in reduced total sitting time and shorter bouts of sitting in older adults with MCI and their 
caregivers. Electronic postural monitors will record sitting time for a duration of one week at three time 

 
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points (pre-intervention, mid-intervention, and post-intervention). The intervention includes 1) feedback from 
baseline monitoring, 2) educational and goal setting session with the participants and research staff, 3) wrist 
worn monitors that alert wearers to sitting times >30 minutes, 4) home and telephone visits to address 
physical, psychological, and home environment barriers to behavior change. Changes in sitting time and 
breaks from sitting will be compared between baseline, mid-intervention, and post-intervention 
measurement occasions.  
Specific Aim 3: Determine whether sedentary behavior intervention results in improved 
insulin sensitivity and glycemic control. To evaluate whether reduced sitting results in meaningful 
metabolic changes, we will measure postprandial insulin and glucose, and body composition, and evaluate 
changes from pre- to post- intervention adjusting for relevant covariates.  
 
The PI is an early-career investigator who has completed KU-ADC funded pilot work using objective 
activity monitoring and has the necessary foundation for the proposed research on physical activity and 
sedentary behavior in older age and AD. She has several published papers on biomarkers associated with 
cognitive decline and dementia. She has successfully collaborated with the KU-ADC since 2008 to build a 
program of research measuring physical activity in naturalistic settings in older adults with and without AD. 
She has experience in use, interpretation, and analysis of objective activity monitoring data in ADC 
participants. Her pilot work found that participants with mild AD did not differ from older adult controls in 
their levels of moderate physical activity, but differed in sedentary and light intensity activities. This supports 
the idea that sedentary behavior is a valuable target for this population.  
 
B. Background and Significance 
     Older adults are highly sedentary, spending more than 60% of waking time sitting.1,2 Independent of 
physical activity, daily sitting time is a risk factor for poor glycemic control, unhealthy body composition, 
elevated lipid levels,3–5 and Type 2 diabetes.6,7 An NIH sponsored workshop identified research priorities 
and recommendations for understanding the “Physiology of Sedentary Behavior and its Relationship to 
Health Outcomes.”8 The proposed study addresses these recommendations directly. 1) We investigate the 
physiological correlates of sedentary behavior by assessing glycemic control and insulin sensitivity. 2) We 
focus on the impact of lack of movement as distinct from the effects of movement by accurately and 
objectively measuring both simultaneously. In individuals with mild cognitive impairment (MCI), we will 
evaluate whether a behavioral intervention can alter physiological processes that contribute to disease 
pathology. 
     Glycemic control and insulin sensitivity are highly modifiable through changes in activity and sitting9 and 
are inexorably linked to Alzheimer’s disease (AD) and cognitive decline.10,11 Individuals with MCI and AD 
display physiological differences in insulin and glucose regulation compared to older adults without cognitive 
impairment.12 Reducing total sitting time and taking frequent breaks from sitting have resulted in improved 
glycemic control and insulin sensitivity.4,13 Reduced insulin sensitivity has been shown to occur within hours 
after a transition to sedentary behavior.14 Time spent in seated activities (e.g., TV) is associated with poorer 
global cognitive function15 and risk of AD16 independent of physical activity.  
     Cardiorespiratory fitness changes that only occur with moderate or vigorous aerobic exercise may not be 
essential for improving brain health and cognition, as demonstrated by studies of activities that do not 
robustly improve fitness (Tai Chi, resistance training, Wii fit), but still show improvements in brain health and 
cognition.17,18 Even low intensity, non-exercise activity is associated with reduced risk of cognitive 
decline19,20 and healthier cardiometabolic measures.21,22 In fact, non-exercise activity accounts for the 
majority of daily activity, while exercise accounts for only 2-5%.23,24 More evidence is needed to determine 
whether reductions in sitting time are sufficient to produce changes in cognitive performance and 
neuroanatomy as seen in aerobic exercise interventions.18,25  
     A recent meta-analysis reports that interventions targeting sedentary behavior can effectively reduce 
sitting time in adults (average 42 min/day), but few studies have evaluated whether these reductions result 
in clinically meaningful health outcomes.26 Furthermore, few interventions have been conducted in older 
adults. One intervention to reduce sitting time in older adults included one on one goal setting and 
individualized feedback on objectively derived sitting time.27 Participants successfully reduced sitting time, 
increased breaks in sitting, and increased light and moderate intensity activities. Our 12 week intervention 

 
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adds new elements to strengthen this design: 1) objective postural monitoring, 2) electronic reminders when 
sitting >30 minutes (real time reminders are more effective than education alone in reducing sitting28), 3) 
assessment of insulin sensitivity and glycemic control which are sensitive to changes in sitting after a short 
duration.  
     The proposed intervention is ecologically valid—it can be done in any setting. It uses participants’ goals 
and preferences to guide behavior changes instead of defining goals for them.29 The intervention is 
designed to break up bouts of prolonged sitting and replace sitting behavior with standing, light and 
moderate intensity activities (e.g., walking, household activities, and resistance exercise) which have been 
associated with improved cognitive performance among people at risk for AD.25  
     Preliminary Results: The PI is an early-career investigator with a foundation for the proposed research 
on physical activity, sedentary behavior, and associated biomarkers in older age and AD.21,30–42 Pilot 
research allowed us to establish expertise in use, interpretation, and analysis of activity monitoring data. In 
100 participants, we had excellent retention (99%) and low rates of technological problems that prevent 
valid data collection (5%). We found that participants with mild AD did not differ from older adult controls in 
their levels of moderate physical activity, but differed in sedentary and light intensity activities.42 This 
supports the idea that sedentary behavior is a valuable target for this population. We discovered that 
patterns of activity variability differ between men and women (i.e., women are more consistently active 
across days), but did not differ by dementia status.35 Understanding within-individual variability helps target 
interventions toward individual habits to result in tailored behavior change approaches. We conducted a 
focus group with the KU-ADC Ambassadors and consulted with experts (Gardiner, Befort, Thyfault, 
Rosenberg, & Carlson) to develop our intervention.  
 
C. Rationale 
Our proposal is innovative in 6 ways compared to previous studies: 1) it is conducted in the home and 
targeted to individual habits and physical environments that reinforce sitting behaviors, 2) it uses objectively 
assessed electronic postural monitoring, 3) it provides electronic reminders to reduce sitting, 4) it targets 
sedentary older adults with MCI, which has not be done before, 5) it assesses glycemic control and insulin 
sensitivity which are sensitive to changes in sitting after a short duration and which few previous 
interventions have measured, and 6) it capitalizes on the caregiver/patient dyad to help improve adherence 
to the behavioral change regimen. 
 
 
II. 
Research Plan and Design 
 
A. Study Objectives:  
We propose a feasibility study of a 12-week home based behavioral intervention to reduce sitting time 
among sedentary older adults with MCI and their caregivers.  
 
B. Study Type and Design:  
The proposed pilot study will include individuals with MCI and their caregivers as a dyad. We will use a 
multi-level model to evaluate the change in our outcome variables across three time points. Level 1 is time 
of observation (baseline, mid-study, follow up). Level 2 is the individual (with or without MCI), and Level 3 
is the level of the dyad. This model includes the non-independence in the estimation of the two members 
of the dyad as well as repeated observations for each individual. This model also allows us to compare 
whether individuals with MCI are equally or less responsive to the intervention than the study partners 
within the context of the dyadic relationship. Future funding applications will include an RCT design with a 
control group of dyads who do not receive the intervention or a double baseline design to establish within 
person change with and without the intervention. We chose an intervention duration of 12 weeks. A 
previous intervention study in middle-aged adults observed changes in glucose and insulin within 2 hours of 
reduced sitting replaced by light walking.13 A 6-month intervention in adults improved insulin levels and 
waist circumference.43 

 
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Sample Size, Statistical Methods, & Power 
We will enroll 15 dyads of older adults (N=30 individuals; 15 with MCI and 15 non-impaired caregivers). 
Aim 1: We will evaluate feasibility in terms of 1) successful recruitment and retention of 
participants, specifically how many months did it take to recruit an adequate sample of participants, 2) 10% 
or less of technological failures, calculated as the number of failures divided by the total number of 
participants enrolled, 3) rate of participant concerns addressed by phone and at home visits, as measured 
by numerical counts of concerns successfully or unsuccessfully addressed and percent of participants 
having concerns, and 4) acceptability of the intervention to participants (measured by questionnaires 
during home visits), we will describe these data using descriptive statistics. 
            Aims 2 and 3:  Our proposal is underpowered to detect significant effects, however we will focus on 
finding a meaningful effect size for the treatment (which is not affected by sample size). We feel this is 
acceptable given the feasibility focus of our pilot study. A previous RCT of an intervention to reduce sitting 
in multiple sclerosis47 reported a statistically significant main effect, Cohen’s d = 0.49, for intent-to-treat 
analysis. 
            We will use a multi-level model to evaluate the change in our outcome variables across three time 
points. Level 1 is time of observation (baseline, mid-study, follow up). Level 2 is the individual (with or 
without MCI), and Level 3 is the level of the dyad. This model includes the non-independence in the 
estimation of the two members of the dyad as well as repeated observations for each individual. This 
model also allows us to compare whether individuals with MCI are equally or less responsive to the 
intervention than the study partners within the context of the dyadic relationship. Constraining estimates 
to be equivalent provides a test of the significance of the difference in the estimates between the MCI 
patients and the study partners. We are primarily interested in the change in outcome measures (listed 
below) from pre-intervention to post-intervention (i.e., is the intervention effective), thus we are testing for 
a growth model with an intercept change, indicating a mean change after the intervention, this type of 
model can estimate discontinuous processes with longitudinal data. With regard to the multiple time 
points, we hypothesize an improvement in outcomes from baseline to mid-point and a maintenance effect 
from mid-point to follow up. Outcomes are (1) average daily sitting time (2) number of sitting bouts >30 
min (3) insulin and glucose, adjusting for baseline values and relevant covariates (disability status, 
medications, age, education, etc.). Data will be validated for wear time (i.e. remove periods of sleep or 
monitor removal). A valid day of wear is > 10 hours of waking wear time and a valid week of wear 
includes > 4 valid days of wear (>1 weekend day). 
 
 

 
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D. Participant criteria. We will enroll 15 dyads of older 
adults (N=30 individuals; 15 with MCI and 15 non-impaired 
caregivers) per Table 1 criteria. We will recruit additional 
participants in the event of screen failure or technological problems 
to reach our enrollment goal. MCI status will be determined by CDR 
in the most recent KU Alzheimer’s disease center (ADC) Registry 
visit (See Appendix I: Vulnerable Populations). Inactive status will 
be determined by the Measure of Older Adults’ Sedentary Time 
(MOST), a 7-item questionnaire about sitting activities common in 
older adults.27 There is no guidance from the literature for cutoffs 
for self-reported sitting times. Self-reports consistently 
underestimate sitting times compared to objective measures and 
we do not wish to exclude the majority of individuals screened. 
Thus, we will use a cutoff of self-reported sitting time of >7 hours 
per day not counting time spent sleeping or napping. This is 
roughly the average time spent sitting per self-reports using this 
questionnaire in a previous study of older adults (Gardiner et al. 2011). The MOST scale can be found in 
Appendix II. We will include individuals with glucose in the normal or pre-diabetic range. No participant who 
is eligible to participate based on inclusion/exclusion criteria will be denied based upon race, gender, or 
ethnicity. 
E. Methods 
Measures 
     Sitting. Our primary outcome measures are the average number of minutes sitting per day and the 
number of sitting bouts >30 minutes during waking hours over one week measured with activPAL 
(PalTechnologies, Glasgow, Scotland). ActivPAL is superior in estimation of postural changes (sitting vs. 
standing) compared to other monitors44 partly due to thigh placement. It is waterproofed for 7+ days by 
placing in a nitrile sleeve and wrapping in medical adhesive before attaching to the thigh with medical 
adhesive (i.e., can be worn while bathing). The device estimates time in sitting, standing, or stepping 
postures and transitions (sit-to-stand, stand-to-sit) in 15 second epochs. It is small, lightweight, and 
unobtrusive. Its rechargeable batteries last up to 14 days. We have successfully collected pilot data from 
100 older adults establishing safety and feasibility including adhesive integrity for the study duration. 
Participants will be educated on use of the device before recording data. Logs will be used to record 
waking/sleeping times and problems with or removal of monitors (see appendices).  
     Biomarkers. Fasting and postprandial glucose and insulin will be collected to determine whether 
changes in sedentary behavior impact glycemic control and insulin sensitivity. Postprandial glucose and 
insulin responses will be determined as reported previously.45 Briefly, an IV catheter will be placed for 
sampling by a nurse. Fasting baseline blood will be drawn. Subjects will then consume a liquid mixed meal 
(Ensure drink containing 57% carbohydrate, 28% fat, and 15% protein). Blood will then be collected at 15, 
30, 45, 60, 90, and 120 minutes after consumption of the drink. The total amount of blood will not exceed 92 
cc which is safe for adults over 100 lbs. Glucose will be measured in all samples immediately after 
collection with a glucose analyzer (YSI 2300 Stat plus). Remaining blood will be processed with 
centrifugation and serum separated and stored at -80 until time of analysis. Insulin will be measured in 
serum using Enzyme-Linked Immunosorbent Assay (ELISA; Alpco Diagnostics). Glucose and insulin area 
under the curve calculations will quantify postprandial responses. We will calculate insulin sensitivity via the 
Matsuda index as reported previously.9,45 Body mass will be measured using a digital scale. Height will be 
measured by stadiometer with shoes off. Waist circumference will be reported as the average of 3 
measures. 
     Covariates. Covariates include age, sex, education, marital status, physical functional limitations, health 
history, self-reported pain, and medications that may influence insulin sensitivity and glycemic control. We 
will classify medications into categories of drugs used to treat diabetes or to induce weight loss, and use 
them as covariates in the model to determine the effect of the intervention on biomarkers after adjusting for 
use of these classes of medications. 
Table 1. 
Inclusion Criteria 
 
Exclusion Criteria 
1) Person with MCI 
enrolled in KU ADC 
Registry 
1) Unable to stand or 
walk unassisted  
2) Clinical Dementia 
Rating (CDR) = 0.5 
for the impaired 
partner 
2) Inadequate visual, 
auditory, or English 
language capacity  
3) Inactive status on 
MOST questionnaire 
(both partners) 
3) Adhesive allergy  
4)  Retired or <20 
hrs/wk in an office 
(both partners) 
4) Current Type 2 
diabetes 
5) Live together in a 
a community 
dwelling setting (both 
partners) 
5) Unwilling to change 
sitting behavior   

 
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Procedures  
     Pre-Intervention (T0). Eligibility will be determined via chart review and telephone screening.  
     Baseline Visit (V1). Participants (both the individual with MCI and the study partner) will arrive fasting 
for baseline insulin and glucose testing. Weight, height, and waist circumference will be measured for both 
partners. Postural monitors will be attached by study staff to participants’ dominant thigh. Participants will be 
asked not to remove the monitor for 7- 24 hour periods. They will receive instructions on use of the monitors 
and sleep/wake logs.  
 
 
 
 
 
 
 
 
 
 
 
     Baseline Postural Monitoring (BL). Participants will wear monitors for 1 week and return it at the home 
visit (HI1). They are encouraged to call the clinic regarding questions about monitors or sleep logs. 
     Home and Telephone Intervention Visits (HI1-3, TI1-2). A series of home visits and telephone calls 
will be used to administer the behavioral intervention for both members of the dyad together. Study staff will 
be trained on intervention procedures by Dr. Gardiner via two 1-hour Skype training sessions and a written 
handbook based on his expertise in sitting reduction interventions. At the first intervention visit (HI1), 
participants will receive preliminary feedback on baseline monitoring (i.e., graphical & verbal feedback, 
attention to times of day when sitting occurred), and will be mailed a more detailed account of their sitting 
behavior to review at TI1. The education and goal setting session will consist of 1) education on 
demographic trends, harms of sitting, contexts in which prolonged sitting occurs, recommendations for 
reduced sitting, 2) guided completion of a workbook that: a) asks participants to reflect on their habits, b) 
sets realistic and measureable goals, describes expectations for change in sitting and barriers to reducing 
sitting, c) evaluates perceived benefits of reducing inactivity, reinforcement strategies for rewarding change 
and enjoyable nonsedentary activities to pursue, ratings of confidence in ability to make changes, d) tips for 
ways to reduce sitting time (targeted to individual habits and home environments), and ways to make sitting 
time more active when sitting cannot be avoided.30 In the home, interventionists and participants will identify 
specific environmental cues that promote sitting and devise plans to integrate nonsedentary activity into 
typical routines. The workbook was originally developed by Gardiner et al.27 based on Social Cognitive 
Theory46 and Behavioral Choice Theory.29 
Both members of the dyad will receive a water resistant activity monitor to wear on the non-dominant 
wrist (Jawbone Up, San Francisco, CA). Monitors will be programmed to provide vibrations (“idle alerts”) to 
encourage activity after inactive periods of >30 minutes and to shut off during hours when participant is 
normally asleep. We chose Jawbone for programmability and vibration reminders (vs. auditory). Jawbone 
batteries last 10 days. Participants and study partners will be trained in their home on how to recharge them 
and can be assisted via telephone and during home visits if needed. Participants and study partners will 
indicate in logs during which activities they most frequently received alerts to assist in goal setting during 
subsequent visits.  
      TI1 (wk2) will focus on problems and adherence with idle alerts, monitor wear, success of limiting sitting 
to 30 minutes, and goals for other cues to limit sitting. HI1 (wk5) will focus on setting goals for replacing 
sitting with standing/light activity, maintenance of goals, and reduction of barriers. Study staff will attach 
activPAL monitors for mid-intervention assessment of changes in sitting time in both partners (M) measured 
during week 6 of the intervention. After the weeklong assessment, participants will mail monitors in a pre-
addressed stamped padded envelope. TI2 (wk8) will check on success of goal maintenance and barrier 
reduction. HI2 (wk12) will be the final follow up visit to address barriers and discuss progress toward 
Table 2. 
Pre- 
Pre- 
Pre- 
Int 
Int 
Int 
Int 
Int 
Int 
Post- 
Post- 
 
 
 
Wk0 
Wk1 
Wk2 
Wk5 
Wk 6 
Wk8 
Wk12 
Wk13 
Wk14 
Study Timeline 
T0 
V1 
BL 
HI1 
TI1 
HI2 
M 
TI2 
HI3 
FU 
V2 
Eligibility Screening 
X 
 
 
 
 
 
 
 
 
 
 
Insulin & Glucose  
 
X 
 
 
 
 
 
 
 
 
X 
Postural monitoring 
 
 
X 
 
 
 
X 
 
 
X 
 
Postural feedback 
 
  
 
X 
 
 
 
 
 
 
X 
Education & goals  
 
 
 
X 
 
 
 
 
 
 
 
Wrist worn alert 
 
  
 
X 
X 
X 
X 
X 
X 
 
 
Intervention Visit 
 
 
 
X 
X 
X 
 
X 
X 
 
 
T- telephone; V- clinic visit; BL- Baseline; HI- Home intervention visit; M-Mid-Study; FU- Follow up 

 
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maintaining goals. Questionnaires will be used to assess the acceptability of the intervention to participants. 
Study staff will attach activPAL monitors for post-intervention assessment of changes in sitting time 
(measured week 13). 
     Follow up (V3). Participants will return monitors to the clinic and complete follow up biomarker testing 
(glycemic control, insulin resistance, BMI, and waist circumference). Participants will receive feedback from 
postural monitoring during the waiting period of glucose testing.  
 
F. Risk/benefit assessment:   
Physical risk: Blood tests usually result in some discomfort during the blood draw and may result in mild 
bruising at the site of the blood draw. Fasting before blood testing may result in some discomfort and feeling 
hungry. Some people experience dizziness or feel faint after having blood drawn. The medical tape used to 
attach the monitor to the thigh may cause redness or stick to leg hair.   
Psychological risk: It is possible that wearing activity monitors, keeping a diary, or filling out 
questionnaires will be tiring or annoying.  
Social & Economic risk: We do not foresee any social or economic risk to participating in the study.  
 
Potential benefit of participating in the study  
a. Individual subject: The participant may learn about his/her own activity and sedentary 
habits and they may learn strategies to make them healthier. This information may 
benefit health and well-being.  
b. Study Population: We do not expected to the population from which the subject is 
drawn to benefit in any particular way.  
c. Science, society, and humanity in general: The new information that will be obtained 
may benefit future patients by providing new insights into healthy aging and 
prevention of Alzheimer’s disease or Mild Cognitive Impairment (MCI). 
G. Location where study will be performed: Participants will visit the Clinical Translation Science 
Unit in Fairway, KS for study visits. Activity monitoring, home visits, and telephone calls will take 
place in the participant’s home and community environment. Data will be stored at the KU 
Alzheimer’s Disease Center and the PI’s research lab at the University of Kansas in Lawrence.  
H. Collaboration (with another institution, if applicable): NA 
I. Single IRB Review for a Multi-site study (if applicable):  NA 
 
J. Community-Based Participatory Research (if applicable): NA 
 
K. Personnel who will conduct the study, including: 
1. Indicate, by title, who will be present during study procedure(s): Study Coordinator, Research 
Assistants 
2. Primary responsibility for the following activities, for example:  
a. Determining eligibility: Study Coordinator, PI, Research Assistants 
b. Obtaining informed consent: Study Coordinator, Research Assistants 
c. Providing on-going information to the study sponsor and the IRB: NA 
d. Maintaining participant's research records: Study Coordinator, Research Assistants, 
PI 

 
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e. Completing physical examination: N/A 
f. Taking height, weight: CTSU staff 
g. Drawing / collecting laboratory specimens: CTSU staff  
h. Performing / conducting tests, procedures, interventions, questionnaires: Study 
Coordinator, Research Assistants 
i. Completing study data forms: Study Coordinator, Research Assistants 
j. Managing study database: PI, Research Assistants 
 
L. Assessment of Subject Safety and Development of a Data and Safety Monitoring Plan 
 
1. Elements of the plan include: 
a. Persons/groups who will review the data: CTSU and research staff 
b. Data/events that will be reviewed: Reports from participants to study staff will be 
recorded during study visits and telephone calls. 
c. Frequency of review:  quarterly 
d. Types of analyses to be performed: assess frequency and severity of reported 
events 
e. Safety-related triggers that would cause the PI to stop or alter the study: No 
anticipated safety-related events 
Eligibility criteria screen for health risks prior to study enrollment, and we will immediately report to 
PI any adverse events. Postprandial glucose and insulin testing is the only procedure that increases risk to 
participants above the risks in daily life and that portion will be continuously monitored in the CTSU. Home 
visits and telephone calls to study participants from study staff occur frequently during the study period to 
monitor any additional unforeseen problems. We will record and review any reported adverse events for 
severity. If deemed, severe, participation will be discontinued. 
 
III. 
Subject Participation 
 
A. Recruitment: 
1. We will recruit and collect data from participants currently participating in the KU-ADC 
Registry. This is a large registry of well characterized patients that has demonstrated an 
excellent ability to identify, recruit, and characterize individuals with mild AD and healthy 
older adults and retain them for investigator initiated research studies. Participants with MCI 
have had a full physical and neurological examination and review of medical history as part 
of the Alzheimer’s Disease Center Registry evaluation before being recruited into the present 
study. No subject who is eligible to participate based upon the inclusion/ exclusion criteria; 
desires to participate is this study; is eligible for the study will be denied based upon race, 
gender or ethnicity. 
2. The study coordinator and/or research assistants will identify potential participants via chart 
review and telephone screening. 
3. Recruitment letters will be mailed to potentially eligible participants. Copies of recruitment 
letter, website description, and pocket card for recruitment are attached. The pocket card is 
used as a tool for study coordinators to have handy information to inform participants they 
contact in person or over the phone about the study. 
 

 
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B. Screening Interview/questionnaire: As members of the KU Alzheimer’s Disease Center 
Registry, potential participants have previous consented to being contacted for future 
research. During eligibility screening, the study coordinator or research assistants will 
contact potential participants by telephone. They must meet the inclusion/exclusion criteria 
given in Table 1. Clinical Dementia Rating scores will have been determined in a previous 
registry visit for those with MCI. Additional questions will include work/retirement status, 
availability of a willing study partner, able to stand or walk unassisted, adequate English 
language, auditory, and visual capacity, adhesive allergy, current uncontrolled Type 2 
diabetes, and willingness to change sitting behavior. To evaluate eligibility for sedentary 
behavior, we will use the MOST questionnaire which is shown in Appendix II below.  
C. Informed consent process and timing of obtaining of consent 
1 
The study coordinator who is experienced in working with participants from the KU- 
ADC participant Registry, will give subjects detailed and comprehensive information 
about the study and obtain their written consent.  
2 
For all study participants, consent forms will be reviewed and signed in a private, clinic 
room at the Alzheimer's Disease Center or CTSU/GCRC. The potential subjects will be 
given the consent form to fully review prior to signing.  
3 
Both caregivers and persons with cognitive impairment who are potential participants for 
the study will be given details about the study as stated in the consent form. Both the 
caregiver and the person with impairment will be asked to describe what they will do to 
participate in the study, the risks and benefits of participation, and what they would do if 
they decided they wanted to discontinue participation in the study. Their ability to relay 
back key information about the study will be used to determine whether they have 
capacity for consent. We will not enroll participants who are unable to consent for 
themselves. We will obtain written consent from all participants. 
D. Alternatives to Participation: Participation in the study is entirely voluntary. Participants 
may withdraw at any time and no care or services will be denied on the basis of participation 
or lack thereof.  
E. Costs to Subjects: There are no costs to participants.  
F. How new information will be conveyed to the study subject and how it will be 
documented: Participants will be notified verbally and in writing if any new information is 
determined that might alter the participant’s wish to participate in research. 
G. Payment, including a prorated plan for payment: Participants will not be paid to 
participate in the study. Upon study completion they will be able to keep their wrist worn 
activity monitors (value about $100). 
H. Payment for a research-related injury: If participants have research-related injuries, they 
will be provided treatment at the usual charge. Treatment may include first aid, emergency care 
and follow-up care, as needed. Claims will be submitted to their health insurance policy, 
government program, or other third party, but they will be billed for the costs that are not covered 
by the insurance. 
IV. 
Data Collection and Protection 
A. Data Security 

 
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Data Sharing, Management, & Quality Control: We have signed a formal data use agreement specifying the 
terms of data use and protection. Data collection and sharing for this project was funded by the KUADC 
(NIH P30AG035982). KUADC has a designated Data Management Core that provides support for data 
collection, management and secure storage. All data are entered on standardized forms during the clinical 
visits and entered into a central database. Data are doubly entered to minimize data entry errors. Upon 
completion, we conduct logic, edit, and range checks. Queries are sent to the study coordinator for 
resolution. Data are downloaded and locked in a secure dataset. The database is backed up in an off-site 
location. Data security is ensured by managing all data on a secure server that has role-based access that 
is password protected.  All files that are modified are backed up daily, with complete backups of the server 
on a weekly basis. Confidentiality is strictly safeguarded by HIPAA-compliant standards and all data are 
stored in a HIPAA compliant manner. All paper records will be kept in locked files in the research offices to 
which only our research personnel have access and filed by number in accordance with professional 
standards of privileged information. Any information on the subjects which may be shared will only be 
identifiable through a code number and will not have any personal information attached. Empathetic and 
professional staff mitigates risk of embarrassment. There are no plans to have ongoing third party 
monitoring. 
 
B. Sample / Specimen Collection: At the CTSU, fasting and postprandial glucose and insulin will 
be collected to measure glycemic control and insulin sensitivity. An IV catheter will be placed for sampling 
by a nurse. Fasting baseline blood will be drawn. Subjects will then consume a liquid mixed meal (Ensure 
drink containing 57% carbohydrate, 28% fat, and 15% protein). Blood will then be collected at 15, 30, 45, 
60, 90, and 120 minutes after consumption of the drink. Glucose will be measured in all samples 
immediately after collection with a glucose analyzer (YSI 2300 Stat plus). Remaining blood will be 
processed with centrifugation and serum separated and stored at -80 until time of analysis. Insulin will be 
measured in serum using Enzyme-Linked Immunosorbent Assay (ELISA; Alpco Diagnostics). Samples will 
be stored in a secure location within the CTSU to which only CTSU and study staff have access. The 
samples will not be shared outside this research, but will be sent to an external site for processing.  
 
C. Tissue Banking Considerations: NA  
D. Procedures to protect subject confidentiality: The researchers will protect the participant’s 
information as required by law.  Researchers cannot guarantee absolute confidentiality. Efforts will be made 
to keep your personal information confidential. If the results of this study are published or presented in 
public, information that identifies participants will be removed. The privacy of health information is protected 
by a federal law known as the Health Insurance Portability and Accountability Act (HIPAA).  By signing this 
consent form, you are giving permission (“authorization”) for KUMC to use and share health information 
about the participant for purposes of this research study. If you decide not to sign the form, you cannot be in 
the study. The researchers will only use and share information that is needed for the study. To do the study, 
they will collect health information from the study activities and from your medical record that relates to 
study participation. You may be identified by information such as name, address, phone, date of birth, or 
other identifiers. Your health information will be used at KUMC by Dr. Watts, members of the research 
team, The University of Kansas Hospital Medical Record Department, the KUMC Research Institute and 
officials at KUMC who oversee research including members of the KUMC Human Subjects Committee and 
other committees and offices that review and monitor research studies. By signing this form, you are giving 
the research team permission to share information about you with persons or groups outside KUMC. Your 
information will be shared by Dr. Watts with KU Lawrence campus, and U.S. agencies that oversee human 
research (if a study audit is performed). These groups or agencies may make copies of study records for 
audit purposes. The purpose for using and sharing the information is to make sure the study is done 
properly. The HIPAA privacy law may not apply to everyone who receives your health information. Your 

 
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health information might not be protected by HIPAA if persons outside KUMC disclose it. In some cases, 
there may be other laws that protect your information from improper use. Your permission to use and share 
the participant’s health information will not expire unless you cancel it. No research information will be 
placed in your medical record. Some research-specific information is kept only by the researcher. Access to 
all of the research-specific information may not be available until the end of the study.   
E. Quality Assurance / Monitoring 
We have signed a formal data use agreement specifying the terms of data use and protection. Data collection and 
sharing for this project was funded by the KUADC (NIH P30AG035982). KUADC has a designated Data Management 
Core that provides support for data collection, management and secure storage. All data are entered on standardized 
forms during the clinical visits and entered into a central database. Data are doubly entered to minimize data entry 
errors. Upon completion, we conduct logic, edit, and range checks. Queries are sent to the study coordinator for 
resolution. Data are downloaded and locked in a secure dataset. The database is backed up in an off-site location. 
Data security is ensured by managing all data on a secure server that has role-based access that is password 
protected.  All files that are modified are backed up daily, with complete backups of the server on a weekly basis. 
Confidentiality is strictly safeguarded by HIPAA-compliant standards and all data are stored in a HIPAA compliant 
manner. All paper records will be kept in locked files in the research offices to which only our research personnel have 
access and filed by number in accordance with professional standards of privileged information. Any information on the 
subjects which may be shared will only be identifiable through a code number and will not have any personal 
information attached. Empathetic and professional staff mitigates risk of embarrassment. 
There are no plans to have ongoing third party monitoring.  
 
V. 
Data Analysis and Reporting 
Statistical and Data Analysis:       
 Data Analysis:             We will use a multi-level model to evaluate the change in our outcome variables 
across three time points. Level 1 is time of observation (baseline, mid-study, follow up). Level 2 is the 
individual (with or without MCI), and Level 3 is the level of the dyad. This model includes the non-
independence in the estimation of the two members of the dyad as well as repeated observations for each 
individual. This model also allows us to compare whether individuals with MCI are equally or less 
responsive to the intervention than the study partners within the context of the dyadic relationship. 
Constraining estimates to be equivalent provides a test of the significance of the difference in the estimates 
between the MCI patients and the study partners. We are primarily interested in the change in outcome 
measures (listed below) from pre-intervention to post-intervention (i.e., is the intervention effective), thus 
we are testing for a growth model with an intercept change, indicating a mean change after the 
intervention, this type of model can estimate discontinuous processes with longitudinal data. With regard 
to the multiple time points, we hypothesize an improvement in outcomes from baseline to mid-point and a 
maintenance effect from mid-point to follow up. Outcomes are (1) average daily sitting time (2) number of 
sitting bouts >30 min (3) insulin and glucose, adjusting for baseline values and relevant covariates (disability 
status, medications, age, education, etc.). Outcome: Milestones for achieved feasibility include successful 
recruitment and retention of participants, 10% or less of technological failures, rate of participant concerns 
addressed by phone and at home visits, acceptability of the intervention to participants (measured by 
questionnaires HI3), and few adverse events. Effectiveness of the intervention will be evaluated based on 
change of moderate effect size in the average amount of time spent in sitting and duration of sitting bouts as 
demonstrated in previous studies. Two previous intervention studies reported a decline in sitting time of 
about 3 - 4%.27,43 We will use this range as our target for success.  

 
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Study results to participants: Participants will learn their individual results from activity monitoring as part 
of the intervention at home visit 1 and clinical visit 2. These results are used as educational and motivating 
agents to modify the participants’ behavior. 
Publication Plan: Our plan is to use the results from this pilot study to support an NIH R21 application to 
fund a larger RCT of our intervention to reduce sitting time. We will publish results in a peer reviewed 
manuscript.  
 
 
VI. 
References 
1. 
Harvey, J. A., Chastin, S. F. & Skelton, D. A. Prevalence of sedentary behavior in older adults: a 
systematic review. Int. J. Environ. Res. Public. Health 10, 6645–6661 (2013). 
2. 
Matthews, C. E. et al. Amount of time spent in sedentary behaviors in the United States, 2003–2004. 
Am. J. Epidemiol. 167, 875–881 (2008). 
3. 
Owen, N., Healy, G. N., Matthews, C. E. & Dunstan, D. W. Too Much Sitting. Exerc. Sport Sci. Rev. 
38, 105–113 (2010). 
4. 
Hamilton, M. T., Healy, G. N., Dunstan, D. W., Zderic, T. W. & Owen, N. Too Little Exercise and Too 
Much Sitting: Inactivity Physiology and the Need for New Recommendations on Sedentary Behavior. 
Curr. Cardiovasc. Risk Rep. 2, 292–298 (2008). 
5. 
Mikus, C. R. et al. Lowering physical activity impairs glycemic control in healthy volunteers. Med. 
Sci. Sports Exerc. 44, 225 (2012). 
6. 
Booth, F. W., Roberts, C. K. & Laye, M. J. Lack of exercise is a major cause of chronic diseases. 
Compr. Physiol. (2012). 
7. 
Hu, F. B. et al. Physical activity and television watching in relation to risk for type 2 diabetes mellitus 
in men. Arch. Intern. Med. 161, 1542–1548 (2001). 
8. 
Thyfault, J. P., Du, M., Kraus, W. E., Levine, J. A. & Booth, F. W. Physiology of sedentary behavior 
and its relationship to health outcomes. Med Sci Sports Exerc (2014). 
9. 
Mikus, C. R. et al. Lowering physical activity impairs glycemic control in healthy volunteers. Med. 
Sci. Sports Exerc. 44, 225 (2012). 
10. 
Yaffe, K. et al. Diabetes, impaired fasting glucose, and development of cognitive impairment in older 
women. Neurology 63, 658–663 (2004). 
11. 
Luchsinger, J. A. Type 2 diabetes and cognitive impairment: linking mechanisms. J. Alzheimers Dis. 
30, (2012). 
12. 
Morris, J. K. et al. Cognitively impaired elderly exhibit insulin resistance and no memory 
improvement with infused insulin. Neurobiol. Aging 39, 19–24 (2016). 
13. 
Dunstan, D. W. et al. Breaking up prolonged sitting reduces postprandial glucose and insulin 
responses. Diabetes Care 35, 976–983 (2012). 
14. 
Heath, G. W. et al. Effects of exercise and lack of exercise on glucose tolerance and insulin 
sensitivity. J. Appl. Physiol. 55, 512–517 (1983). 
15. 
Hamer, M. & Stamatakis, E. Prospective study of sedentary behavior, risk of depression, and 
cognitive impairment. Med. Sci. Sports Exerc. 46, 718 (2014). 
16. 
Lindstrom, H. A. et al. The relationships between television viewing in midlife and the development 
of Alzheimer’s disease in a case-control study. Brain Cogn. 58, 157–165 (2005). 
17. 
Mortimer, J. A. et al. Changes in brain volume and cognition in a randomized trial of exercise and 
social interaction in a community-based sample of non-demented Chinese elders. J. Alzheimers Dis. 
30, 757–766 (2012). 
18. 
Lövdén, M., Xu, W. & Wang, H.-X. Lifestyle change and the prevention of cognitive decline and 
dementia: what is the evidence? Curr. Opin. Psychiatry 26, 239–243 (2013). 
19. 
Buchman, A. S. et al. Total daily physical activity and the risk of AD and cognitive decline in older 
adults. Neurology 78, 1323–1329 (2012). 
20. 
Middleton, L. E. et al. Activity energy expenditure and incident cognitive impairment in older adults. 
Arch. Intern. Med. 171, 1251–1257 (2011). 

 
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21. 
Watts, A. S., Vidoni, E. D., Loskutova, N., Johnson, D. K. & Burns, J. M. Measuring physical activity 
in older adults with and without early stage Alzheimer’s disease. Clin. Gerontol. 36, 356–374 (2013). 
22. 
Gando, Y. & Muraoka, I. in Physical Activity, Exercise, Sedentary Behavior and Health 51–61 
(Springer, 2015). 
23. 
Craft, L. L. et al. Evidence that women meeting physical activity guidelines do not sit less: an 
observational inclinometry study. Int J Behav Nutr Phys Act 9, 122 (2012). 
24. 
Dunstan, D. W., Howard, B., Healy, G. N. & Owen, N. Too much sitting–a health hazard. Diabetes 
Res. Clin. Pract. 97, 368–376 (2012). 
25. 
Voss, M. W., Nagamatsu, L. S., Liu-Ambrose, T. & Kramer, A. F. Exercise, brain, and cognition 
across the life span. J. Appl. Physiol. 111, 1505–1513 (2011). 
26. 
Martin, A. et al. Interventions with potential to reduce sedentary time in adults: systematic review 
and meta-analysis. Br. J. Sports Med. bjsports–2014 (2015). 
27. 
Gardiner, P. A., Eakin, E. G., Healy, G. N. & Owen, N. Feasibility of reducing older adults’ sedentary 
time. Am. J. Prev. Med. 41, 174–177 (2011). 
28. 
Evans, R. E. et al. Point-of-choice prompts to reduce sitting time at work: a randomized trial. Am. J. 
Prev. Med. 43, 293–297 (2012). 
29. 
Rachlin, H. Judgment, decision, and choice: A cognitive/behavioral synthesis. (WH Freeman/Times 
Books/Henry Holt & Co, 1989). 
30. 
Rhyner, K. T. & Watts, A. Exercise and depressive symptoms in older adults: A Systematic Meta-
Analytic Review. J. Aging Phys. Act. (2015). 
31. 
Watts, A., Ferdous, F., Moore, K. D. & Burns, J. M. Neighborhood Integration and Connectivity 
Predict Cognitive Performance and Decline. Gerontol. Geriatr. Med. 1, 2333721415599141 (2015). 
32. 
Watts, A. et al. A combined measure of vascular risk for white matter lesions. J. Alzheimers Dis. 45, 
187–193 (2015). 
33. 
Watts, A. S., Loskutova, N., Burns, J. M. & Johnson, D. K. Metabolic syndrome and cognitive 
decline in early Alzheimer’s disease and healthy older adults. J. Alzheimers Dis. JAD 35, 253 
(2013). 
34. 
Burns, J. M., Johnson, D. K., Watts, A., Swerdlow, R. H. & Brooks, W. M. Reduced lean mass in 
early Alzheimer disease and its association with brain atrophy. Arch. Neurol. 67, 428–433 (2010). 
35. 
Watts, A., Walters, R., Hoffman, L. & Templin, J. Intra-individual variability of physical activity in 
older adults with and without mild Alzheimer’s disease. (under review). 
36. 
Vidoni, E., Watts, A. & Burns, J. Feasibility of a memory clinic-based physical activity prescription 
program. (under review). 
37. 
Watts, A., Ferdous, F., Diaz Moore, K. & Burns, J. Neighborhood Spatial Configuration and 
 
Metabolic Function in Older Adults with and without Alzheimer’s Disease. (under review). 
38. 
Watts, A., Ferdous, F. & Diaz Moore, K. Perceived neighborhood characteristics differentially impact 
sedentary behavior in older adults with and without Alzheimer’s disease. (Nov 2016). Paper to be 
presented at the annual meeting of the Gerontological Society of American, New Orleans, LA. 
39. 
Watts, A., Anstey, K., Andrews, S. & Dixon, R. BDNF interacts with physical activity to predict 
cognitive function and  declines. (in preparation). 
40. 
Breda, A., Liebmann, E., Ferdous, F., Diaz Moore, K. & Watts, A. Neighborhood Characteristics and 
Dementia Status Predict Physical Functioning in Older Adults. (Nov, 2015). Paper presented at the 
annual meeting of the Gerontological Society of American, Orlando, FL. 
41. 
Khou, C., Rendzia, B., Bevan, A. & Watts, A. Evaluation of waist-worn actigraphy monitors for the 
assessment of sleep and physical activity in older adults with and without Alzheimer’s disease. (Oct, 
2015). Poster presented at the Berg Symposium, St. Louis, MO. 
42. 
Varma, V. & Watts, A. Differences in accelerometer-derived peak physical activity between older 
adults with and without mild AD. (in preparation). 
43. 
Aadahl, M. et al. Motivational counseling to reduce sitting time: a community-based randomized 
controlled trial in adults. Am. J. Prev. Med. 47, 576–586 (2014). 
44. 
Kozey-Keadle, S. et al. Validation of wearable monitors for assessing sedentary behavior. Med Sci 
Sports Exerc 43, 1561–1567 (2011). 

 
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45. 
Young, C. N. et al. Influence of endurance training on central sympathetic outflow to skeletal muscle 
in response to a mixed meal. J. Appl. Physiol. 108, 882–890 (2010). 
46. 
Bandura, A. Social foundations of thought and action: A social cognitive theory. (Prentice-Hall, Inc, 
1986). 
47. 
Klaren, R. E., Hubbard, E. A. & Motl, R. W. Efficacy of a behavioral intervention for reducing 
sedentary behavior in persons with multiple sclerosis: a pilot examination. Am. J. Prev. Med. 47, 
613–616 (2014). 
 

 
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APPENDIX I: VULNERABLE POPULATIONS 
Both caregivers and persons with cognitive impairment who are potential participants for the study will 
be given details about the study as stated in the consent form. Both the caregiver and the person with 
impairment will be asked to describe what they will do to participate in the study, the risks and benefits 
of participation, and what they would do if they decided they wanted to discontinue participation in the 
study. Their ability to relay back key information about the study will be used to determine whether 
they have capacity for consent. We will not enroll participants who are unable to consent for 
themselves. We will obtain written consent from all participants. 

 
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APPENDIX II: Screening Questionnaire 
 
Measuring Older Adults Sedentary Time (MOST) Questionnaire 
 
I am going to ask you about activities you did over the last week while sitting or lying down. Don’t count the time you spent in 
bed.  
 
Today is ____________. I want you to think about the time from last ____________ to yesterday.  
 
For each of the activities only count the time when this was your main activity. For example if you are watching television and 
doing a crossword, count it as television time or crossword time but not as both. 
 
During the last week, how much time in total did you spend sitting or lying down and…… 
SEDENTARY ITEM 
TIME 
1. Watching television or videos/DVDs  
 ______ hours 
______ minutes 
2. Using the computer/Internet 
 ______ hours 
______ minutes 
3. Reading 
 ______ hours 
______ minutes 
4. Socializing with friends or family 
 ______ hours 
______ minutes 
5. Driving or riding in a car, or time on public transport 
 ______ hours 
______ minutes 
6. Doing hobbies, e.g. craft, crosswords 
 ______ hours 
______ minutes 
7. Doing any other activities 
 ______ hours 
______ minutes