Computerized Cognitive Training to Improve Cognition in Diabetic Elderly Veterans
Phase: PHASE4
Conditions: Diabetes Mellitus, Type 2
Sponsor: VA Office of Research and Development

Computerized Cognitive Training to Improve Cognition in Diabetic Elderly 
Veterans 
IIR 11-285 
 Funding Agency: Department of Veterans Affairs 
Principal Investigator/Study Chair: Jeremy Silverman, Ph.D. 
01.06.2017 

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Abstract 
Project Background: Diabetes mellitus (DM) has consistently been associated with increased 
risk for cognitive decline, mild cognitive impairment, and dementia in the elderly. Even minor 
cognitive impairments in nondemented individuals dramatically affect disease self-management. 
This, in turn, is associated with poor glycemic and blood pressure control in diabetes, which by 
themselves increase the risk of dementia, provoking a reinforcing cycle of disease. Thus, it is 
imperative to find interventions to delay or prevent cognitive compromise in diabetic patients, 
that can be relatively easily and rapidly implemented, and that are not cost prohibitive. This is 
especially true in the VA, in view of the high incidence of both diabetes and dementia in our 
growing population of elderly Veterans. 
Epidemiologic evidence suggests modifiable life-style factors, including cognitive activity, 
may prevent or delay the onset of cognitive decline. Computerized cognitive training (CCT) is an 
intervention that has shown promising results in the improvement of cognitive functioning, more 
consistently in non-demented elderly, with additional benefits from booster training sessions. To 
date, studies of CCT have typically only examined cognitive outcomes, and only shortly after the 
intervention. The proposed CCT program, Personal Coach from Cognifit, is designed to improve 
cognition of elderly persons by targeting their weak cognitive functions, using a personally 
tailored training plan. The proposed study will provide the first evaluation of the effects of CCT 
on DM self-management behavior and clinical outcomes, in addition to cognition. 
Project Objectives: Aim 1A: To determine whether the CCT, relative to the active control 
games program, improves cognition (memory and executive functions/attention), DM-related 
behavior (DM self-management and medication adherence), and clinical outcomes (glycemic 
and blood pressure control), 6 and 12 months after the intervention. Aim 1B: To demonstrate 
efficacy by improvement in behavioral outcomes (DM self-management and medication 
adherence) 6 months after the intervention. Aim 2: To document the effects of CCT on the 
successive changes in memory and executive functions/attention, DM self-management and 
medication adherence, and glycemic and blood pressure control. Aim 3: To explore the impact 
of demographic (age, education, ethnicity, site) and health (ADL/IADL, health literacy, 
depression, dementia family history, lifestyle factors) characteristics, on the intervention effects. 
Project Methods: Non-demented DM elderly from the James J. Peters (Bronx, NY) and Ann 
Arbor (MI) VAMCs will be randomized to CCT or games intervention and perform the respective 
program 3 days per week (every other day), for 20 minutes, for 24 total sessions. Four months 
after the intervention, subjects will receive a 1-week booster training. Subjects will be assessed 
at baseline; and immediately, 6 months, and 12 months after the intervention. At each time 
point, assessments will be cognitive function, DM self-management, and blood pressure; blood 
will be drawn forHbA1c measurement. VA records will be used to monitor medication 
adherence. Longitudinal mixed model analyses will assess the effects of the intervention on 
change in outcomes overtime. Path analyses will evaluate the inter-relationships among 
changes in cognition, DM self-management, and clinical outcomes for each intervention at 6 
and 12 months. 
 

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List of Abbreviations 
Provide a list of all abbreviations used in the protocol and their associated meanings. 
Activities of Daily Living/ Instrumental Activities of Daily Living (ADL/IADL 
Advanced Cognitive Training for Independent and Vital Elderly (ACTIVE) 
Alzheimer‘s disease (AD) 
Clinical Dementia Rating (CDR) 
Computerized cognitive training (CCT) 
Dementia Rating Scale (DRS) 
Diabetes mellitus (DM) 
Geriatrics Research, Education, and Clinical Center (GRECC) 
James J. Peters VA Medical Center (JJP VA) 
Mild cognitive impairment (MCI) 
Mini Mental State Examination (MMSE) 
Unified Data Set (UDS) 
Wechsler Adult Intelligence Scale (WAIS) 
 
 

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Contents 
Protocol Title: ............................................................................................................................. 5 
1.0 
Study Personnel .............................................................................................................. 5 
2.0 
Introduction ..................................................................................................................... 6 
3.0 
Objectives ....................................................................................................................... 9 
4.0 
Resources and Personnel ..............................................................................................10 
5.0 
Study Procedures ...........................................................................................................13 
5.1 Study Design ...................................................................................................................13 
5.2 Recruitment Methods..................................................................................................... 116 
5.3 Informed Consent Procedures .........................................................................................17 
5.4 Inclusion/Exclusion Criteria ..............................................................................................18 
5.5 Study Evaluations ............................................................................................................19 
5.6 Data Analysis ..................................................................................................................22 
5.7 Withdrawal of Subjects ....................................................................................................25 
6.0 
Reporting ........................................................................................................................25 
7.0 
Privacy and Confidentiality .............................................................................................25 
8.0 
Communication Plan ......................................................................................................26 
9.0 
References .....................................................................................................................27 
 
 
 

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Protocol Title: Computerized Cognitive Training to Improve Cognition in Diabetic Elderly 
Veterans 
 
 
1.0 
Study Personnel 
 
Principal Investigator/Study Chair:  
Jeremy Silverman, Ph.D., Professor, Mount Sinai School of Medicine and Research Scientist 
and Clinical Psychologist, James J. Peters VAMC, 718-584-9000 ext 1700, 
jeremy.silverman@va.gov and jeremy.silverman@mssm.edu 
 
Co-Investigators: 
Hillel Grossman, M.D., Team Leader Geriatric Psychiatrist, James J. Peters VA Medical Center, 
718-584-9000 ext 5752, hillel.grossman@va.gov 
 
Joan Penrod, Ph.D., Health Science Specialist, James J. Peters VA Medical Center, 718-584-
9000 ext 3814, joan.penrod@va.gov 
 
Mary Sano Ph.D., ACOS R&D, James J. Peters VA Medical Center, 718-584-9000 ext 6009, 
mary.sano@va.gov 
 
James Schmeidler, Ph.D., Assistant Clinical Professor Psychiatry, Mount Sinai School of 
Medicine,212-659-8838, james.schmeidler@mssm.edu 
 
Elizabeth Guerrero-Berroa, Assistant Professor, Icahn School of Medicine at Mount Sinai, 718-
584-9000 x5182 elizabeth.guerrero-berroa@mssm.edu 
 
Pearl Lee, MD., Physician Scientist, VA Ann Arbor Healthcare System, 734-769-7100, 
pearl.lee2@va.gov 
 
Neil Alexander, M.D. Co-investigator, GRECC director, , VA Ann Arbor Healthcare System, 734-
845-3048, vhacogreccwm@va.gov   
Director 
Sarah Krein, PhD, RN, Research Scientist, VA Ann Arbor Healthcare System, 734-845-3502, 
sarah.krein@va.gov 
 
Collaborator: (Consultant) 
Michal Schnaider Beeri, Ph.D., Associate Professor, Mount Sinai School of Medicine, Director, 
Joseph Sagol Neuroscience Center, Sheba Medical Center, 212-659-8807, 
michal.beeri@mssm.edu 

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2.0 
Introduction 
BACKGROUND 
 
 
Diabetes is a risk factor for dementia and cognitive decline. There are numerous studies 
demonstrating consistently higher risks of dementia, mild cognitive impairment (MCI), and 
cognitive decline in persons with diabetes. Diabetes or impaired fasting glucose may be 
present in up to 80% of persons with Alzheimer‘s disease (AD)1. This is a significant health 
concern not only for the general population, but also specifically for our Veterans since the 
incidence of dementia is as high or higher in elderly Veterans2 as in the population at large and 
diabetes prevalence is also accelerating3. A systematic review of the effect of diabetes on 
dementia and cognitive decline concludes that cognitive impairment should be considered a 
consequence and disabling manifestation of diabetes4, and the 2010 NIH Consensus 
Development Conference Statement on Preventing Alzheimer’s Disease and Cognitive 
Decline listed diabetes first as a risk factor4. Thus, interventions to prevent cognitive  impairment 
and dementia in diabetic elderly patients are imperative in order to halt this  devastating 
epidemic that affects the patients, their families, and the society as a whole  emotionally and 
financially. Furthermore, increased MCI and dementia have been associated even with pre-
diabetes5. This is significant from a public health perspective, since it suggests that the 
mechanisms underlying the increased risk of cognitive compromise in diabetes may be 
generalizable to non-diabetic individuals. Thus, this study may shed light into potential therapies 
to prevent dementia in all elderly.   
 
The current lack of disease-modifying treatment for Alzheimer‘s disease (AD), and the 
robust epidemiologic evidence suggesting modifiable protective life-style factors (eg. cognitive 
and physical activity6) have led to particular interest in life-style interventions that may delay the 
onset or slow the progression of cognitive decline. The Alzheimer‘s Association ―Maintain Your 
Brain‖ campaign recommends staying mentally active as one of the key components of a 
―brain healthy lifestyle. In addition, the Alzheimer‘s Association has recently partnered 
with the Centers for Disease Control and Prevention to develop the ―Healthy Brain Initiative‖, 
which recommends studying the effects of mental activity as part of its road map for maintaining 
or improving the cognitive performance of adults. The Institute for the Study of Aging chose to 
specifically promote neurogenesis—which is induced by cognitive enrichment—rather than 
treatment to address neuropathology, as a therapeutic strategy for cognitive aging and AD7. 
These recommendations are based on studies demonstrating that the brain is highly plastic and  
capable of generating new synaptic connections and neurons throughout life8, particularly when 
activated by enriched environments. Enriched environments that target sensorimotor modalities9 
have been shown to improve cognitive function10, facilitate recovery from injury or stroke11, and 
prevent age-related decrease in synaptic density in the aged brain12. Such enriching 
environments have also been shown to increase  brain weight13, cortical thickness14, 15, and 
neurotrophic factors16. Mice raised in an enriched environment—that includes access to mental 
activities such as colorful toys and tunnels—generate more neurons in the  hippocampus17, an 
area playing a central role in memory formation and severely affected in AD. These animals 
also experience reduced cerebral deposition of β-amyloid, a pathological hallmark of AD18. 
Moreover, neurogenesis has been reported also in the brains of old animals, both in the 
hippocampus19 and in the forebrain20. In humans, several prospective longitudinal studies have 
shown that elderly who engage in more mental activity, such as reading or playing games, are 
less likely to develop dementia and AD.21,22 
 
As described above, the presence of neurogenesis and neuroplasticity into old and even 
very old age is the underlying rationale for cognitive training as a therapeutic venue to enhance 
cognition. A variety of interventions, including mnemonic training, group learning sessions, 
individual piano instruction, audiotape memory training, and more recently computerized 
training, have been suggested to delay cognitive decline in non-demented elderly23. Cognitive 

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interventions have been shown relatively consistently to improve cognitive functioning in 
individuals with no cognitive impairment24,25. Results for cognitively impaired individuals are less 
consistent. For MCI two studies using global cognition as the outcome measure showed 
cautious but positive results22, 26 while another study found that MCI subjects improved in 
reasoning and speed of processing but not in memory when trained in these respective 
functions27. Similarly, some studies have shown positive results for early AD28, although a 
Cochrane review concluded that methodological limitations precluded a strong demonstration of 
efficacy29. These improvements are found both in general cognition and in specific cognitive 
domains30-34,  including attention, executive functioning, explicit memory, reasoning, speed of 
processing, and spatial orientation35. Of note, a recent investigation of the effects of a 6-month 
cognitive intervention program on brain metabolism in MCI and mild AD patients found that MCI 
patients had cognitive benefits from the training that were accompanied by attenuated decline of 
glucose metabolism in cortical regions affected by AD36. This pattern was not present in AD 
patients, suggesting that the cognitive and neuronal metabolism benefits derived from 
cognitive interventions are more effective before the dementing process has been broadly 
established. The Advanced Cognitive Training for Independent and Vital Elderly (ACTIVE) trial, 
the largest randomized trial published so far, found that cognitive training results in cognitive 
improvements specifically for the trained cognitive function (e.g., memory)37. The ACTIVE study 
also found that cognitive training reduces functional decline in self-reported IADLs33 as well as 
increases health-related quality of life37. Importantly, these improvements persisted five years 
after the initiation of the intervention. Similar to the ACTIVE trial, cognitive training has been 
shown to affect areas beyond cognition, such as increased quality of life perception38, health-
related quality of life37, improved driving behavior39, and improved gait40. In contrast to the 
ACTIVE trial, other studies have shown that training generalizes to cognitive functions beyond 
what was trained37 (but see34) and to have durable benefits31. These promising findings, in addition 
to the various advantages of nonpharmacological interventions (such as lack of physiological 
side-effects so common in the cholinesterase inhibitors), are a basis for the recent emphasis on 
cognitive activity and specifically cognitive training in the fight against cognitive decline and AD 
(see section B2). Computerized cognitive training (CCT) is currently one of the most commonly 
used forms of cognitive intervention. Although a concern of providing CCT to the elderly is the 
lack of familiarity with the technology, there has been a dramatic increase in the number of older 
adults buying and using computers24, a trend that is accelerating. Census estimates of the US 
population 65+ years of age ―having internet access in the household increased from 29.4% in 
2001 to 45.7% in 2007 and then to 53.3% in 2009. The rates of ―using the internet at any 
location similarly increased from 19.8% to 34.9% and then to 41.5%. CCT programs have the 
advantages of being multimedia and interactive, performed at the residence of the participant, 
having flexible hours of use, and being available for continued use after the intervention period 
ends. They also avoid the need for a live instructor throughout the training period reducing 
costs. Further, some CCT programs have the capability of adjusting the content or level of 
difficulty of the tasks to the user. For research contexts, every response by a participant is 
recorded and saved automatically, maximizing opportunities for assessing change while 
minimizing data entry mistakes and difficulties. The CCT proposed in this study, Personal 
Coach, improved both cognitive (visuospatial working memory) and non-cognitive outcomes 
(gait30) primarily when using CCT before the development of overt dementia, with ―large effect 
sizes. Since diabetic patients are at particularly high risk for developing dementia, the proposed 
randomized trial will examine the immediate (2 months after initiation of training), short-term (8 
months) and longer-term (14 months) effects of CCT in nondemented diabetic elderly Veterans. 
 
In diabetes, medication adherence is typically considered a central component of 
disease self-management44 because pharmacological therapy is a cornerstone of treatment, 
both for glycemic control and for managing cardiovascular risk factors such as blood pressure. 
Nonetheless, approximately 50% of diabetic patients are not adherent to diabetes medications45, 

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46. Multiple factors influence poor medication adherence, which is associated with more severe 
disease progression, avoidable hospitalizations, disability, and death47,48. While the implications 
of dementia for medication adherence are obvious, even non-demented elderly individuals with 
the mildest cognitive impairment have increased risk for poor medication adherence. In a study 
of independently living healthy elders, those with lower cognitive scores had significantly worse 
adherence (measured using an electronic 7-day pillbox; relative risk of ≥20% of days non-
adherent = 4.1)49. Similarly, executive functions and working memory were predictors of 
medication adherence in another study of community dwelling cognitively normal elderly50. 
Higher scores on verbal memory and executive functions were associated with successfully 
setting up a medication schedule and with medication adherence in another study of community 
dwelling elderly51. This supports our choice of memory and executive  functions/attention as 
primary cognitive outcomes and suggests that CCT may enhance medication scheduling and 
adherence. Performance in cognitive function tests, among non-demented elderly referred to a 
geriatric assessment unit, was significantly poorer in those demonstrating lack of basic 
knowledge of their medication regimen52. More generally, cognitive performance predicts poor 
medication adherence in many contexts and diseases. In the Framingham study, among 
hypertensive subjects who had previously been prescribed medication, cognitive deficits were 
associated with reduced medication adherence53. Specifically, those in the lowest 10th percentile 
of education-adjusted cognitive performance were over three times as likely to have stopped 
treatment than those in the normal performance group. Non-adherence behavior after hospital 
discharge was examined in a sample of a general clinical population and poor memory was one 
of the significant predictors54. Cognitive deficits predicted poor medication adherence in patients 
taking anticoagulants55 and in rheumatoid arthritis56 and COPD57 patients. In older patients with 
schizophrenia, cognitive functioning predicted medication adherence above and beyond age, 
gender, education level, symptom severity, and attitudes towards medication58. In a review of 
treatment adherence studies in older patients with Parkinson‘s disease it was concluded that 
―neuroprotective regimens may give rise to better adherence59. Cognitively impaired patients 
are more likely to have poorly controlled blood pressure due non-adherence60. Diabetic patients 
have higher prevalence of white matter hyperintensities61, which have been associated with 
poor medication adherence62 suggesting an underlying biological substrate for low medication 
adherence in diabetes. Thus, healthy cognition is a critical factor for successful medication 
adherence in other diseases, as well as diabetes. The literature on general self-management in 
diabetes is more limited, but the relationships with cognition are in the same direction as for 
medication adherence. Cognitive impairment (Mini Mental State Exam<23) was associated with 
poor diabetes self-management (eye, foot, and dietician assessments) in diabetic elderly 
subjects above the age of 7563. Similarly in a population-based study of 1398 diabetic patients 
aged 55 and older, subjects with mild and moderate cognitive impairment (based on the 
Telephone Interview for Cognitive Status) were significantly less adherent to exercise and to 
diet64. These studies provide evidence for 1) diabetic patients having high non-adherence to 
medications; 2) cognitive functioning, and specifically memory and executive functions, being 
associated with self-management and medication adherence; and 3) this relationship occurring 
even with the mildest cognitive dysfunction and consistently across several diseases and 
conditions. Thus, they support this investigation of the effects of CCT on medication adherence 
and self-reported diabetes self-management, in a sample of non-demented diabetic elderly 
Veterans. They also support the examination of the clinical manifestations, glycemic and blood 
pressure control. 
 
In the absence of CCT, diabetes increases risk for cognitive compromise, which 
increases the risk for poor medication adherence and other disease self-management 
behaviors, which in turn increases poor glycemic and blood pressure control, increasing the risk 
for cognitive  compromise65, and thus developing a reinforcing cycle of disease ultimately 
resulting in increased diabetes complications, hospitalizations, and death. The model implies 

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that improvement in cognition, due to CCT, impedes formation of this cycle, by counteracting 
the cognitive compromise that initiates the cycle. Aim 1 examines the effects of CCT on 
cognitive, behavioral, and clinical outcomes, in diabetic elderly. Aim 2 goes beyond assessment 
of efficacy to validate the linkages among these outcomes in the conceptual model, by 
evaluating the associations through which CCT affects the successive cognitive, behavioral, and 
clinical changes. 
 
3.0 
Objectives 
 
 
Diabetes mellitus (DM) has consistently been associated with increased risk for cognitive 
decline, mild cognitive impairment (MCI), and dementia. Our prior research shows that 1) 
subjects with diabetes in midlife had a 3-fold increased risk of dementia three decades later, 2) 
diabetic elderly with the earliest signs of cognitive compromise have a faster rate of cognitive 
decline, 3) glycemic control is associated with cognitive decline even in non-diabetic individuals, 
and 4) diabetes medications are associated with fewer neuritic plaques, a hallmark Alzheimer‘s 
disease (AD) neuropathological feature. Additionally, numerous studies have shown that in non-
demented individuals, even minor cognitive impairments dramatically affect their adherence 
to medications and disease self-management in general. Those in turn, are associated with 
poor glycemic and blood pressure control in diabetes, which by themselves increase the risk of 
dementia, provoking a reinforcing cycle of disease. Importantly, there is evidence indicating that 
the brain itself regulates systemic glycemic control. Thus, it is imperative to find interventions for 
diabetic patients that prevent impaired self-management by maintaining a healthy brain, and 
that can be relatively easily, rapidly, and cost-effectively implemented. This is especially true in 
the VA, given the high incidence of both diabetes and dementia in our ever growing 
population of elderly veterans in treatment. The current lack of disease-modifying treatment for 
AD and dementia, and epidemiologic evidence suggesting modifiable protective life-style factors 
(e.g. cognitive activity), have provoked investigations of lifestyle interventions to delay the onset 
of or to prevent cognitive decline. The Alzheimer‘s Association ―Maintain Your Brain campaign 
recommends mental activity as a key component of a ―brain healthy lifestyle. In 
addition, the Alzheimer‘s Association recently partnered with the Centers for Disease Control 
and Prevention to develop the ―Healthy Brain Initiative, which recommended studying the 
effects of mental activity on maintaining/improving cognitive functioning. The Alzheimer‘s Drug 
Discovery Foundation promotes neurogenesis, rather than treatment for neuropathology, as a 
preventive strategy for cognitive compromise. Computerized cognitive training (CCT) is an 
intervention that has shown promising results in the improvement of cognitive functioning, more 
consistently in the elderly who are not demented. To date, CCT studies have typically examined 
only cognitive outcomes, and only shortly after the intervention. 
 
The proposed study will assess longer-term as well as short-term effects of a CCT 
program, compared with an active control, ―classic computerized games. Participants will be 
non-demented elderly veterans with diabetes mellitus, who are at particularly high risk of 
developing cognitive impairment, recruited from two VAMCs: James J. Peters, Bronx, NY and 
Ann Arbor, MI. Six primary outcomes on three levels will be: cognition (memory and executive 
functions/attention), behavioral (self-reported DM self-management and medication adherence 
from VA records), and clinical outcome (glycemic and blood pressure control). CCT programs 
have major advantages: they are multimedia, interactive, performed at flexible hours at the 
subject‘s residence without a live instructor, and available for use after the training period. 
Responses are recorded to monitor progress, without data entry problems. The proposed CCT 
program, Personal Coach from Cognifit (Seattle, WA), is designed to improve cognition of 
elderly persons by targeting their weak cognitive functions, using a personally tailored training 
plan. The active control games program provides similarly structured tasks, but was not 

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designed to improve cognition. The proposed study will further innovate with booster training 
sessions, which have been found to provide additional cognitive benefits in non-computerized 
cognitive training programs. 
 
The proposed study initiates an untapped area of research: the evaluation of short-term 
(6 months) and longer-term (12 months) health benefits of this promising intervention. This 
study focuses on elderly diabetic veterans, who are at particularly high risk for dementia. If 
successful, the results will be invaluable for designing a large scale multi-site study to justify 
clinical implementation of CCT throughout the VA for diabetics, and perhaps eventually for other 
elderly veterans who are vulnerable to cognitive compromise. The specific aims of this 
randomized, controlled trial on non-demented elderly veterans with diabetes are: Aim 1. A) To 
determine whether the CCT intervention, relative to the active control games program, improves 
cognition (memory and executive functions/attention), DM-related behavior (DM self-
management and medication adherence), and clinical outcomes (glycemic and blood pressure 
control), 6 and 12 months after the intervention. B) To demonstrate efficacy by improvement in 
behavioral outcomes (DM self-management and medication adherence) 6 months after the 
intervention. Aim 2. To document the effects of CCT on the successive changes in memory and 
executive Functions/attention, DM self-management and medication adherence, and glycemic 
and blood pressure control. Aim 3. To explore the impact of demographic (age, education, 
ethnicity, site) and health (ADL/IADL, health literacy, depression, family history of dementia, 
lifestyle factors) characteristics, on the intervention effects. 
 
4.0 
Resources and Personnel 
The James J. Peters VA Medical Center 
 
The James J. Peters VA Medical Center (JJP VA) in the Bronx has a longstanding and 
active research program, supported by a strong R&D office directed by Dr. Mary Sano, 
internationally known clinical investigator in Alzheimer’s disease and a co-investigator in the 
proposed study.  
The VA Ann Arbor Healthcare System 
 
The VA Ann Arbor Healthcare System has provided state-of-the-art healthcare 
services to more than 153,000 veterans living in a 15-county area of Michigan and northwest 
Ohio.  
JJP and Ann Arbor GRECCs 
 
Dr. Penrod is an investigator with the JJP GRECC and Dr. Lee is an investigator 
with the Ann Arbor GRECC, and Dr. Alexander is its director. The Centers’ goals are to increase 
capacity for conducting state-of the- art health services research on care for veterans with 
complex conditions, such as diabetes, with particular emphasis on care for the elderly. Thus, the 
proposed project is well within the theme of these centers and the project will be supported by 
the centers for items such as office space, computer hardware and software for investigators 
and staff. Desktop computers linked to secure VAMC servers behind VA firewall are available to 
investigators for data management and analyses with no data kept on individual computers. 
 
We anticipate that most subjects will be assessed at the two VAMCs, where we have 
rooms for clinical/medical assessments fully equipped with examining beds, sinks, etc. as well 
as desks for the neuropsychological assessments. Please note that many of these outpatient 
veterans visit relatively frequently the VA. However, since these are elderly diabetic veterans, 
who may have difficulties ambulating into the hospital, we will examine them at their residences 
if they prefer so. All research coordinators will be required to have a car. 
 
Jeremy Silverman, Ph.D., Principal Investigator, is a Clinical Psychologist at the JJP-VAMC 
with 30 years of experience at the VA. He is also a Professor of Psychiatry in the Department of 
Psychiatry at the Mount Sinai School of Medicine. Dr. Silverman will be responsible for 
constructing and implementing ascertainment strategies, monitoring their progress, and 

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ensuring the quality of the project. He is responsible for the design, and will lead the analysis, 
interpretation of results, planning of implementation and dissemination processes, and 
preparation of papers. Dr. Silverman will supervise the recruitment and data collection at the 
JJP-VAMC. He will lead bi-weekly meetings (the Ann Arbor staff will join on a conference call) to 
discuss all day-to-day aspects of the study (recruitment, reasons for refusals and ways to 
overcome them, data entry and missing data, staffing and coordination issues, etc.). Dr. 
Silverman will confer with the senior staff of the project at least monthly. Dr. Silverman will have 
access to PHI. 
Hillel Grossman, M.D., Co-investigator, is the Director of the Memory Disorders Clinic at the 
JJP VAMC, an Associate Professor in the Department of Psychiatry at Mount Sinai School of 
Medicine, and the Co-PI of the Clinical Core in the ADRC. Dr. Grossman will use similar 
methods to review each case at both sites to ensure that the veterans do not have dementia 
and meet memory functioning for participation. Dr. Grossman will also be responsible for 
identification of adverse events at the JJP VAMC. Dr. Grossman will have access to PHI.  
Elizabeth Guerrero-Berroa, Ph.D., Co-investigator, is a clinical neuropsychologist by training. 
She is an Assistant Professor in the Department of Psychiatry at the Icahn School of Medicine 
at Mount Sinai. Dr. Guerrero-Berroa will be responsible for assisting the PI with training and 
supervision of research coordinators at the JJP VAMC for the successful implementation of the 
study procedures. She will assist with study participant recruitment, grants management, and 
database management. Dr. Guerrero-Berroa will supervise administration, scoring, and data 
entry of neuropsychological tests at the JJP VAMC and the Ann Arbor VAMC, attend senior 
investigator meetings, and participate in manuscript preparation. She will have access to PHI.     
Joan Penrod, Ph.D., Co-investigator, is Director of the HSR&D REAP “Center for Research 
on Health Care Across Systems and Sites of Care” housed at the JJP VA. She will be 
instrumental in the integration of CPRS and other VA databases into the study, particularly for 
Aim 3, where historical CPRS information will be examined in order to identify sub-groups of 
veterans that respond best to the CCT. She will be involved in manuscript writing and will 
participate in the monthly senior investigators’ meetings. Dr. Penrod will have access to PHI. 
Mary Sano Ph.D., Co- investigator, is a nationally recognized neuropsychologist with a 
longstanding research interest in cognitive functioning in the aged. Dr. Sano is the Associate 
Chief of Staff for Research and Development at the JJP VAMC, a Professor in the Department 
of Psychiatry at the Mount Sinai School of Medicine, and the Director of the Mount Sinai ADRC. 
She is the PI of several major clinical trials of Alzheimer’s disease and will provide this expertise 
to the proposed study. Dr. Sano worked closely with the PI in the development of the design 
and the primary and secondary outcome measures for the proposed study. She also advised on 
the composition of the cognitive assessment battery. Dr. Sano already meets regularly with the 
PI to discuss projects involving the ADRC and will join the monthly senior staff meetings for this 
project. Dr. Sano will be involved in manuscript preparation. Dr. Sano will have access to PHI. 
To Be Hired, Research Coordinator, will have a psychology or related degree. She/he will be 
the instructor for the proposed study, training subjects in the use of PCT and computer game 
programs. She/he will be on call for technical assistance, and will contact participants weekly to 
identify and resolve technical problems, and record adverse events. The research coordinator 
will also perform the duties of the JJP-VAMC research assistant described below, but 
approximately 2 baseline assessments per week. She/he will also recruit, validate the data entry 
by the JJP-VAMC research assistant, will perform informed consents, and will have access to 
PHI.  
To Be Hired, Research Assistant, will have a psychology or related degree. She/he will be 
involved in the recruitment effort and the scheduling of participants. He/she will be trained and 
certified in the CDR and all neuropsychological tests. She/he will participate in the meeting to 
discuss eligibility of potential participants for the proposed study. She/he will perform 
approximately 3 baseline or follow up assessments per week and enter the data. She/he will 

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also validate the data entry by the JJP-VAMC research coordinator. She/he will recruit, perform 
informed consents, and will have access to PHI. 
Pearl Lee, MD., Co-investigator, will be the Ann Arbor site PI for the proposed study. Dr. Lee 
is a Physician Scientist in the GRECC and Attending Physician in the Geriatric Medicine Clinic 
at the Ann Arbor VAMC. She is also an Assistant Professor at the Department of Internal 
Medicine in the Division of Geriatric Medicine, University of Michigan School of Medicine. Dr. 
Lee will take overall responsibility for the successful implementation and performance of the 
study at the Ann Arbor site. She will supervise the Ann Arbor VAMC research coordinator and 
research assistant to ensure smooth implementation of all methods, from recruitment through 
data entry. She will confer with Dr. Silverman on a weekly basis to monitor progress, and ensure 
homogeneity in all methods among the two sites. Dr. Lee will lead the Ann Arbor staff meetings, 
attend the senior investigator meetings, and participate in manuscript preparation. Dr. Lee will 
have access to PHI. 
Neil Alexander, M.D. Co-investigator, is the GRECC director at the VA Ann Arbor Healthcare 
System. Dr. Alexander will be involved in developing the recruitment strategy at the Ann Arbor 
site. Dr. Alexander will participate in the joint Clinical Core 
Sarah Krein, PhD, RN, Co-investigator, is a Research Scientist at the VA Ann Arbor Center 
for Clinical Management Research, a Health Services Research and Development (HSR&D) 
Center of Excellence and a Research Associate Professor in the Department of Internal 
Medicine at the University of Michigan. She is an experienced investigator who is co-Director of 
the VA’s Quality Enhancement Research Initiative for Diabetes (QUERI-DM) Research 
Coordinating Center. She will be involved in interpretation of the study data, and participate 
in senior investigator meetings and manuscript writing. In Year 1, Dr. Krein will be involved in 
setting up the clinical trial. In Year 4 Dr. Krein will also lead dissemination and implementation 
activities. Dr. Krein will have access to PHI. 
To Be Hired, Research Coordinator, will have a psychology or related degree. She/he will be 
the instructor for the proposed study, training subjects in the use of PCT and computer game 
programs. She/he will be on call for technical assistance, and will contact participants weekly to 
identify and resolve technical problems, and record adverse events. The research coordinator 
will also perform the duties of the Ann Arbor VAMC research assistant described below, but 
approximately 2 baseline assessments per week. She/he will recruit, validate the data entry by 
the Ann Arbor VAMC research assistant, will perform informed consents, and will have access 
to PHI. 
To Be Hired, Research Assistant, will have a psychology or related degree. She/he will be 
involved in the recruitment effort and the scheduling of participants. She/he will be trained and 
certified in the CDR and all neuropsychological tests. She/he will participate in the meeting to 
discuss eligibility of potential participants for the proposed study. She/he will recruit, perform 
approximately 3 baseline or follow up assessments per week and enter the data. She/he will 
perform informed consents, and will have access to PHI. 
Consultants 
Michal Schnaider Beeri, Ph.D., is an Associate Professor in the Department of Psychiatry at 
the Mount Sinai School of Medicine. Dr. Beeri was the PI of the original submission of this 
proposal, but left the VA to become the Director of the Joseph Sagol Neuroscience Center at 
Sheba Medical Center in Israel. Dr. Silverman will consult with Dr. Beeri on all aspects of this 
project. 
James Schmeidler, Ph.D., Co-investigator, statistician, is an Assistant Clinical Professor of 
Psychiatry at the Mount Sinai School of Medicine, where he has collaborated with the PI for 
over 20 years. He devised the experimental design of this study. In year 1, he will design and 
write the data management programs. He will supervise data management and statistical 
analyses by Ms. West. In year 4, he will perform the longitudinal analyes, and interpret cross-
sectional and longitudinal statistical results together with Dr  Silverman, 

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and the other senior investigators, and participate in the senior investigator meetings and writing 
papers. Dr. Schmeidler will have access to PHI. 
Rebecca West, M.A., Statistical Programmer, In year 1, she will train the research 
coordinators and assistants at both sites on instruction of the interventions, and will supervise 
those activities. She will be responsible for data management, and will oversee acquisition of 
data from CogniFit, the company providing the computerized interventions. She will produce 
quarterly reports to be presented in the staff meetings. In year 3, she will perform cross-
sectional statistical analyses of the baseline data and the results of the intervention at two 
months, immediately after treatment. In year 4, she will perform statistical analyses, and prepare 
tables and figures. Ms. West will be supervised by Dr. Schmeidler, and will have access to PHI. 
 
5.0 
Study Procedures 
 
5.1 
Study Design 
 
 
Upon receiving a list of the potential subjects who meet eligibility criteria according to 
initial screen using the CPRS , we contact their primary care physicians or the chief of the 
diabetes clinic and ask for their permission to contact their patients. It should be noted that in 
our prior studies of elderly Veterans, all physicians approved approaching their patients. 
Subjects will be then sent a letter describing the study, inviting them to get in touch with us by 
phone or mailing in a postage paid card.  Unless a subject replies telling us not to call, the 
research coordinators will call the subject. That phone call will include a short screening 
procedure. In this screening, subjects are asked if 1) a doctor has ever told them that they have 
a memory problem/dementia/Alzheimer‘s disease, and 2) if they have ever received medication 
to treat a memory problem (the names of all FDA approved medications for Alzheimer‘s disease 
are presented to the subjects). Additionally, in this phone conversation subjects are asked about 
all other inclusion and exclusion criteria (availability of an informant to complete brief 
questionnaires, computer and internet access, familiarity with computer, ability to see and hear 
computer, information about the computer [operating system]. Potential subjects also complete 
the diabetes self-management questionnaire on the telephone. Then subjects are scheduled for 
a face-to-face interview that includes the informed consent procedure. After informed consent, 
the interview will continue with baseline cognitive assessments, blood draws, and blood 
pressure measurement (see measures described later). This can occur in one visit or over more 
than one visit, as preferred by the participant. Subjects will be assessed at their residences or 
come to their respective VAMCs, according to their preference. Participants are then 
randomized to their treatment group, and receive a visit (during which they are instructed in how 
to use the program, and complete the first session of the program. Participants then continue 
use of the program for a total of 24 sessions, 3 days per week (one session every other day). 
Once the program is completed, participants are again assessed with cognitive assessments, 
blood draws, and blood pressure measurement (identical to baseline visit). Four months after 
completion of program, participants complete a 3-session booster session. Six months and 
twelve months after completion of the program, they again complete the cognitive assessments, 
blood draws, and blood pressure measurement (identical to baseline visit).  
 
Procedures:  
             Cognitive testing- After informed consent, the interview will continue with baseline 
cognitive assessments, blood draws, and blood pressure measurement. Subjects will be 
assessed at their residences or come to their respective VAMCs, according to their preference. 
The Clinical Dementia Rating (CDR) scale, Mini Mental State Exam (MMSE), and  
Neuropsychological evaluation will be utilized for cognitive testing (see details of these tests 
below). 

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Interventions- Randomization and training for use: At each site, a computer program 
will randomize the order of the CCT and the games program, within 100 consecutive pairs of 
eligible subjects. At an initial home visit, an instructor will install the computer program and 
provide individual instruction with a single standardized script for both programs. The instructor 
will be a research coordinator who is proficient in installation and adjustment of computer 
equipment and software. The instructor will verify that subjects are capable users of the mouse 
and keyboard, can read the screen effectively, hear the auditory signals, and perform all 
procedures. During the training, the instructor will contact subjects weekly, to identify and 
resolve technical problems and record adverse events, and also be available for technical 
assistance by phone, 8am to 6pm, seven days a week, and at home if necessary. The Personal 
Coach software company, Cognifit, provides technical support for the instructor 24 hours a day 
seven days a week. Subjects and assessors, who administer and score the outcome measures, 
will be blinded to the intervention. Subjects will be asked not to discuss their computer program 
with the assessors; the instructor will not be involved in assessment. Since occasional 
participants may be deemed ineligible after assignment due to inability to perform the computer-
based tasks, the next eligible recruit will be the replacement. Thus, randomization will continue 
until 100 participants in each intervention at each site begin training. 
Programs- 
 
Personal Coach- This software package creates, administers, and scores an individually 
tailored program that emphasizes training to address the cognitive weaknesses of the 
participant that were assessed prior to training. Thus, it determines the composition of cognitive 
tasks to be presented throughout the training sessions, based on participants‘ relative 
performance in the Neuropsychological Examination (NE). The NE is a two-session assessment 
of a profile of 14 cognitive domains trained by the program: awareness, inhibition, spatial 
perception, visual short term memory, working memory, hand-eye coordination, visual scanning, 
response time, divided attention, time estimation, visual perception, shifting, naming, and 
planning. . Personal coach uses an algorithm that adjusts and customizes the training program 
by scoring the 14 cognitive domains, based on the pre-training NE, and assigning task 
frequencies so that the cognitive domains with the lowest NE scores are relatively over-
represented. For example, a subject who demonstrates weakness in spatial perception, but 
scores high in response time in the pre-training NE, will be provided with training sessions 
including more tasks intended to improve spatial perception, and fewer tasks intended to 
improve response time. Personal Coach also adjusts the difficulty level for each task, to reflect 
the participant‘s capability and performance in the previous session. This adaptive-interactive 
system focuses on cognitive domains with the greatest potential for improvement, and also 
avoids frustration due to tasks that are consistently too difficult or easy. 
Subjects‘ training sessions are 20 minutes in duration. Subjects are instructed to have sessions 
3 days per week (every other day), with a day rest between sessions, for a total of 24 sessions.. 
Personal Coach utilizes 21 tasks.  
 
The NE is an evaluation used by Personal Coach to customize the training for 
participant‘s need, and also assessed after the eight-week training on the same measures, as a 
built-in component of the Personal Coach CCT package. We emphasize that the NE is NOT one 
of the outcome measures of this study—which were independently selected by the investigating 
team.  
 
Active control classic games program- The proposed control intervention is comprised of 
games commonly at community centers for  seniors, on the internet, or on home computers. 
The active comparison intervention, unlike a passive comparison or paper and pencil games, 
was chosen so that the procedures for the two groups would be as similar as possible, 
facilitating blinding of subjects. The proposed games program is provided by the same software 
company, Cognifit, as Personal Coach. In both the CCT and the active control, participants 
receive identical pre-training instruction; are assessed with the NE at the beginning and end of 

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the program; and complete 20-minute cognitive training sessions, 3 days a week (every other 
day), with one day rest between sessions, for 24 sessions. The number, distribution, and length 
of the active control sessions are identical to the CCT; as in the CCT program, computerized 
feedback and encouragement are provided in each control session. A research coordinator will 
be available for technical assistance – at home if necessary, and will telephone subjects weekly 
to ask if they needed any help and if they are performing the intervention. In contrast to the 
CCT, the active control is not personalized, so the twelve classic computer games included in 
the control program are presented in a predefined order for all participants with three games in 
each session. 
Booster week- A booster week will be performed at 6 months after baseline (4 months 
after completion of training), to maintain the improvement in cognitive and other abilities. All 
subjects will perform a regular training week, i.e. three sessions of 20 minutes each. The CCT 
subjects will perform the last week of the training and the control games subjects will similarly 
perform the last week of games they have played during the training. 
 
Blood draw and blood pressure-  
Glycemic control will be assessed by drawing bloods from subjects at every 
assessment. 5 uL will be drawn and assessed using the same machine readings used in our 
studies both at the JJP and at Ann Arbor (Siemen's DCA Vantage Analyzer). Change from 
HbA1c at baseline will be calculated at each of the three subsequent assessments. Change in 
status will be evaluated relative to baseline (same, lower, higher).  
Blood pressure measurements will also be performed at every assessment by the 
research coordinators, using the same machine readings used in our studies both at the JJP 
and at Ann Arbor (Omron HEM-780). The outcome measures will be changes in blood pressure 
(systolic and diastolic) from baseline to each subsequent assessment. 
 
Additional assessments: Diabetes self-management and medication adherence, 
Cognitive Self-Report Questionnaire, Prospective memory tasks, Activities of daily living (ADL) 
and instrumental ADL, The Geriatric Depression Scale, Sociodemographic characteristics, 
Health Literacy, Family history review, Lifestyle assessments, Historical data from CPRS, Prior 
experience with computers , and gait assessments. 
 
             There is minimal risk in this study, and no reasonable steps to further reduce harm 
could be taken. The overall risks of this proposal are slight. Protection of patient confidentiality 
and privacy will be rigorously guarded by the assignment of coded numbers to each file in the 
computer database. Professional treatment will not be altered or modified for research 
purposes. Subjects will be told that all information obtained is confidential and that their 
participation or non-participation will not affect their treatment. 
Subjects will be told that information which identifies the subject will not be shared with 
any collaborator, parties outside of our immediate research laboratory, nor family member. 
Subjects are informed that they may terminate testing or training at any time should they find 
any aspect objectionable. The interviewers and research assistants will be clinically trained and 
will be sensitive to signs of stress, anxiety and/or fatigue. 
 
Interviews and assessments will be terminated should any subject show signs of 
discomfort. We will make every effort to protect the subject’s confidentiality. However, subjects 
will be told that should such information be accidentally disclosed to the wrong party, it could 
possibly have adverse consequences for the subject in terms of liability in legal proceedings, or 
discrimination in obtaining life or health insurance. 
 
Adverse events will be monitored weekly through phone calls of the instructor to the 
subjects. The risks in this study are minimal and it is highly unlikely that the proposed protocol 
will contribute to any adverse outcome. However, the participants will be of advanced age so it 

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is possible that a participant may die or be hospitalized during the course of the study. Adverse 
events will be reported according to the timeline in the Table of Reporting Requirements.  
As a result of the cognitive assessment at baseline, potential subjects may be excluded from the 
study due to impaired cognition (by MMSE or CDR) or dementia diagnosis. Similarly, at follow 
up interviews, subjects may show impaired cognition. With patient permission, we will confer 
with the primary care physician on any potential medical or cognitive problems.  
 
Risks of this project to the subjects are judged to be very slight. Important new 
knowledge on the effect of cognitive interventions on cognitive functioning is expected to be 
gained. It is anticipated that this information will lead to highly beneficial interventions for the 
diabetic aging population, for whom cognitive decline is a significant concern as well as a public 
health issue. 
The possible direct benefits to those participating in this study are those that might arise 
from a comprehensive cognitive examination, and from cognitive training. The assessment may 
provide clinically relevant information and lead to referrals for otherwise unrecognized cognitive 
problems that may require treatment. The training may provide improvements in cognitive 
functioning. For these reasons, the slight risks to subjects are reasonable in relation to the 
anticipated benefits to subjects and others. 
 
Four hundred subjects will be assessed for participation in an 24 session computerized 
cognitive training program (Personalized Computer Training- PCT) or computer games 
program.  Subjects will be elderly veterans 55+ years old, nondemented, and diagnosed with 
type 2 diabetes with less than optimal diabetes self-management (i.e. 18 or less on the self 
management scale). Subjects will not have neurological or psychiatric conditions that might 
affect cognition (such as Parkinson’s disease or Schizophrenia). Subjects must have sufficient 
vision and hearing to be able to perform the training programs. 
Informants: For each subject, we require identification of an informant with contact 
averaging weekly, who can knowledgeably answer a questionnaire about the subject’s day-to-
day function and ability to take care of his or her diabetes management. Approximately 400 
informants will be contacted via telephone.  
Family members: Subjects will be questioned about their family history, including parents 
and siblings, regarding mental and physical health.  These family members will not be contacted 
in any way.  
 
Research data may be used in the future to develop larger projects, so data will be 
stored indefinitely. Blood samples will not be banked.  
 
5.2 Recruitment Methods 
 
 
400 total veterans will be recruited for this study.  
In the proposed study, we will take advantage the following methods to recruit subjects: 
Upon receiving a list of the potential subjects via CPRS (using a method already with IRB 
approval at the local VAMC of the PI: James J Peters VAMC) who meet eligibility criteria 
according to initial screen using the CPRS, we contact their primary care physicians and ask for 
their permission to contact their patients. It should be noted that in our prior studies of elderly 
Veterans, all physicians approved approaching their patients. Subjects will be then sent a letter 
describing the study, inviting them to get in touch with us by phone or mailing in a postage paid 
card. Unless a subject replies telling us not to call, the research coordinators will call the 
subject. That phone call will include a short screening procedure—with no preserved 
documentation of these responses, a procedure already approved by the local VAMC IRB—in 
order to minimize recruitment of subjects with more than mild cognitive impairment. In this 
screening, subjects are asked if 1) a doctor has ever told them that they have a memory 
problem/dementia/Alzheimer‘s disease, and 2) if they have ever received medication to treat a 
memory problem (the names of all FDA approved medications for Alzheimer‘s disease are 

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presented to the subjects). Additionally, in this phone conversation subjects are asked about all 
other inclusion and exclusion criteria, such as diabetes management and computer use. Then 
subjects are scheduled for a face-to-face interview that includes the informed consent 
procedure. 
 
Potential participants will be identified using data from VISTA/CPRS.  In addition, at Ann 
Arbor VA there is a registry as part of PACT demo lab activities as well as the capacity to 
automatically extract the requisite data to compile a list if needed.  
Research team members may also approach the doctors and other staff and ask them for 
referrals. Finally, we will post flyers and, possibly, advertise in local newspapers, and will 
sponsor educational programs regarding the cognition and diabetes directed to Veterans. 
 
Participants will be reimbursed for their time and effort devoted to the study with a check, 
$50 for the baseline neuropsychological assessment, $35 for the third visit, $50 for the fifth visit 
and $50 for the 6th. The local VAMCs: the James J Peters VAMC  in the Bronx NY and the Ann 
Arbor VAMC will individually dispense payment to their participants.  Participants will be 
reimbursed for their time and effort after each neuropsychological assessment. Checks will be 
requested for each participant immediately after completion of an assessment, to limit wait time. 
Informants will not be reimbursed, due to budget restrictions and the brief nature of their 
involvement. 
 
5.3 Informed Consent Procedures 
 
Participants will provide information in person in their homes, or at the local VAMC. 
Participants will provide information through the memory and cognitive assessments, and only 
research staff members will receive and use that information. Participants are not likely to feel 
any stigma in entering the VAMC or hospital, or within their own homes. In nearly all cases, the 
participant will already be a patient at that VAMC and will regularly be seen by doctors there. 
The information collected is not likely to cause any discomfort, but efforts will be made to clearly 
communicate to the participants that their information is confidential. Participants will  also be 
informed that they may refuse to answer any questions that make them uncomfortable. Only 
investigators and staff listed on this project will be allowed to view any identifiable information 
about the participants. These individuals will have completed their IRB certifications. All efforts 
will be made to make participants comfortable in the research setting. Most participants will be 
seen in their homes or at the VAMC where they are regular patients; this should help ensure 
their comfort. We will inform all participants that they may refuse to answer any questions that 
make them uncomfortable. Research coordinators and assistants, who will have completed all 
required human subjects protections training and will have met with the PI regarding how to 
collect informed consent, will be obtaining consent, and as we are only recruiting and enrolling 
those with capacity to consent, we do not anticipate any issues with regards to capacity to 
consent. Each local site PI will meet with their research team members to discuss the consent, 
the information provided in the consent, and how to properly review the consent with 
participants, at an "informed consent procedures" meeting prior to the start of the research 
study.    
 
 
We are requesting a waiver of documentation of informant consent and a waiver of 
HIPAA authorization. In order to perform a CDR (Clinical Dementia Rating Scale) informant 
interview and diabetes management interview over the telephone. Our procedure is as follows:  
1. We meet with the participant, consent them, and request permission to speak with an 
informant.  
2. The participant contacts their informant and asks this informant to contact us by 
telephone, or to agree to be contacted by us, to complete the informant interview; name 
and telephone of the informant are collected to be in contact with the informant.  

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3. The informant completes the consent form over the phone (as there is no need to see 
the informant in person), with a waiver of signature.  
 
Please note that subjects will be informed prior to signing the consent that an informant is 
required, so that any participant not interested in providing an informant will know before 
signing a consent, so that they may choose not to participate.  
 
 
Further, this study includes a family history assessment that collects information about memory 
disorders and ages of relatives (living and deceased) of the participants in this study. It would 
be impractical to attempt to contact all first-degree relatives, and some of these relatives are 
deceased. We will be gathering information about family members (both demented and not), 
through the participants themselves, that would be collected during a routine complete medical 
history, only collecting first initials and no other identifying information. We are requesting a 
waiver of HIPAA authorization and of informed consent.  
 
5.4 Inclusion/Exclusion Criteria 
1. 55 years old or above. 
2. A diagnosis of type 2 diabetes. 
Inclusion criteria 1 and 2 are major foci of the study- a study of cognitive training in the elderly 
with diabetes.  
3. Does not have dementia or prescribed AD medications. This is to aid in confirmation of 
cognitive health 
4. Does not have major medical, psychiatric, or neurological conditions that affect cognitive 
performance. This will ensure time and ability to take part in the study.  
5. Home access to computer and internet. 
6. Has an informant. This is to aid in confirmation of cognitive health. 
7. Self-management score 18 or below. Self-management is a focus of the study.  
8. Does not have severe impairment of vision or hearing. This will ensure ability to take part in 
the study.  
 
Anyone not meeting the above inclusion criteria will not be enrolled. 
 
5.5 Study Evaluations 
 
The below-described materials are included as an appendix to this document.  
 
In the pre- screening, subjects are asked if 1) a doctor has ever told them that they have 
a memory problem/dementia/Alzheimer‘s disease, and 2) if they have ever received medication 
to treat a memory problem (the names of all FDA approved medications for Alzheimer‘s disease 
are presented to the subjects). Additionally, in this phone conversation subjects are asked about 
all other inclusion and exclusion criteria.  
 
             Cognitive testing- After informed consent, the interview will continue with baseline 
cognitive assessments, blood draws, and blood pressure measurement. Subjects will be 
assessed at their residences or come to their respective VAMCs, according to their preference. 
1. Clinical Dementia Rating (CDR) scale: Severity of cognitive and functional impairment is 
assessed from subject information and an informant (someone with contact averaging weekly, 
who can knowledgeably answer a questionnaire about the subject’s day-to-day function and 
ability to take care of his or her diabetes management).Only non-demented subjects, with a 
CDR of 0 (no dementia) or 0.5 (questionable dementia), are eligible. 
2. Mini Mental State Exam (MMSE): This 30-item questionnaire assesses orientation,  
concentration, memory, and language. A score 25 is an exclusion. 

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3. Neuropsychological evaluation: Cognitive performance is assessed by the Unified Data Set 
(UDS 2.0) neuropsychological battery used by the ADRC with some additional tests. This 
battery was designed independently of the Personal Coach neuropsychological exam (the NE) 
and has been used in many of our studies of cognitive aging.  The neuropsychological 
evaluation can be conducted in approximately 60 minutes and includes the following tests 
(organized by cognitive domain): 
i. Memory. There are two types of verbal memory tasks; word list and paragraph recall. 
(1) Word List Memory- This is a free recall memory test that assesses learning ability for new 
verbal information. Participants are presented 10 unrelated items on printed cards to read aloud.  
Immediately following presentation of all 10 words, the participant is asked to recall as many as 
possible. On each of the three learning trials, the 10 words are presented in a different order. 
The maximum score on each trial is 10. The maximum total score for immediate recall is 30. 
Delayed recall tests the ability to recall, after 15 minutes, the 10 words given in the word list 
memory test. The maximum number of correct responses is 10. Word list recognition counts the 
number of 10 words presented in the word list memory task correctly recognized (Rec-yes). 
These words are presented among 10 distracter words. The number of distracter words 
correctly identified (Rec-no) is also counted. The maximum score for each is 10. 
(2) Paragraph recall: this task is the Logical Memory subtest of the Wechsler Memory Scale-III. 
We will use the 2 stories for immediate recall and for delayed recall, 20 minutes later. The 
maximum score for each is 25. 
ii. Attention/Executive Functions. 
(1) Target Cancellation Tests: These tests will be used to assess vigilance and speeded 
attention. They require subjects to identify target stimuli randomly interspersed among distractor 
stimuli on a sheet of 8.5-by- 11 paper. One task requires the subject to identify diamonds 
among other geometric figures, and another to identify a specific triple of letters (TMX) among 
other triples of letters. The measures are the numbers of correct targets identified in four 
minutes. 
(2) Trail Making Test: The Trails tests measure timed attention, mental flexibility and 
sequencing. Part A entails connecting randomly ordered numbers by drawing a line in 
sequence. Part B entails connecting numbers and letters in alternating order (i.e. 1, A, 2, B, 
etc.). Although number of errors in each part will be recorded, the analysis will include only the 
two time measures. 
(3) Digit Symbol Substitution Test: The subject is given a key grid of numbers and matching 
symbols and a test section with numbers and empty boxes. The test consists of filling as many 
empty boxes as possible with a symbol matching each number. Time is 90 seconds, and the 
score is the number of correct number-symbol matches. 
(4) Digit Span: This is a subtest of the WAIS-III. The Digit Forward section assesses attention by 
reading sequences of digits to the subject for immediate verbatim repetition. Then the Digit 
Backwards section consists of sequences to be repeated in reverse order. The numbers of 
correct answers in the sections will be the two measures used for the analysis. 
iii. Language 
(1) Similarities. Similarities is a subtest from the WAIS-Revised. The test measures abstract 
thinking by asking the subject to state how pairs of words (e.g., egg/seed) are alike. The number 
of correctly answered pairs is the single measure from this test with maximum score 33. 
(2) Boston Naming Test: It assesses the ability to name 15 black and white line drawings 
representing a range of high to low frequency English words. The number of correctly identified 
drawings is the single measure. 
(3) Category fluency: Subjects will be asked to generate exemplars in two categories: animals, 
and fruits and vegetables; 60 seconds are allowed for each category. The score is the sum of 
the numbers of correct exemplars in the two categories. 

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(4) Controlled Oral Word Association Test (COWA): In three one-minute trials, this test of 
phonemic fluency assesses the ability to name as many words as possible beginning with three 
letters—F, A, S. The single measure is the sum of words in all three trials. 
 
Blood draw and blood pressure- Glycemic control will be assessed by drawing bloods from 
subjects at every assessment. 5 uL will be drawn and assessed using the same machine 
readings used in our studies both at the JJP and at Ann Arbor (Siemen's DCA Vantage 
Analyzer). Change from HbA1c at baseline will be calculated at each of the three subsequent 
assessments. Change in status will be evaluated relative to baseline (same, lower, higher).  
Blood pressure measurements will also be performed at every assessment by the research 
coordinators, using the same machine readings used in our studies both at the JJP and at Ann 
Arbor (Omron HEM-780). The outcome measures will be changes in blood pressure (systolic 
and diastolic) from baseline to each subsequent assessment. 
 
Diabetes self-management and medication adherence- A self-report scale of diabetes self-
management collects five separate areas of diabetes self-care (medication adherence, 
exercising, following an eating plan, blood glucose monitoring, and foot care), subjects will be 
asked ―"Over the past year, how difficult has it been for you to do each of the following, exactly 
as the doctor who takes care of your diabetes suggested?". Labels on the five response 
categories (scored 0 – 4) range from ―"So difficult that I couldn‘t do it at all" to ―"Not difficult, I 
got it exactly right." Subjects can also respond that the area of diabetes care is ―Not applicable 
for them. Possible scores for the scale range from 0 to 20, with higher scores meaning greater 
self-management in the five domains.  Like the assessment of the CDR, which is based on both 
subject and informant interviews, the DM self-management questionnaire will also be 
administered to the informant and the scores for each item – averaged from both sources – will 
be summed.  
Cognitive Self-Report Questionnaire- This questionnaire assesses perceptions of cognitive 
abilities and will be administered before and after training (together with each 
neuropsychological assessment). The CSRQ-25 consists of 25 statements about cognition and 
mood in everyday life over the past 2 weeks, answered using a 5-point Likert scale.  
Prospective memory tasks-  Since diabetes medication is taken at specified times, we will 
employ time-based prospective memory items from the Rivermead Behavioural Memory Test 
(3rd Edition) to assess this type of memory. 
Activities of daily living (ADL) and instrumental ADL- The ADL questionnaire has eight 
yes/no items covering the following activities: dressing, grooming, rising, eating, walking, 
hygiene, reaching, and gripping. Similarly, the IADL questionnaire has three yes/no items 
covering the following activities: making financial transactions such as paying the bills, running 
errands and shopping, doing chores such as vacuuming and yard work. For each questionnaire 
the total number of items endorsed will be split at the median to define sub-groups. 
The Geriatric Depression Scale- The Geriatric Depression Scale (GDS) is a 30-item self-
report yes/no questionnaire on feelings of general satisfaction with life, expectations of the 
future, boredom, activity levels, anxiety, fearfulness, ability to concentrate, energy levels, and 
sadness. A score above 14 is interpreted as indicating clinically significant symptoms and will be 
used to define sub-groups1.  
Sociodemographic characteristics- Education and age will be collected. 
Health Literacy. The Short Test of Literacy Functional Health Literacy in Adults (S-TOFHLA) 
will be used to assess health literacy. In this test, subjects read passages in which every fifth to 
seventh word has been deleted and subjects are asked to insert the correct word from a choice 
of four words. The short version involves only two reading comprehension sections. 
Family history review- we use the well validated dementia family history questionnaire. 
Information regarding the birth year, age or age of death, cause of death, and any physical or 

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mental illness is collected for all first-degree relatives. If the subject reports that a first-degree 
relative has/had dementia or memory problems, the Dementia Questionnaire is then used to 
clarify a diagnosis of dementia.  
Lifestyle assessments- Smoking history will be collected, and the physical activity 
questionnaire provides six levels of activity, from mostly sitting to strenuous exercise several 
times a week.  
Historical data from CPRS- Directly measured HbA1c and blood pressure will be clinical 
outcome measures. We will additionally take advantage of CPRS data and explore whether 
historical HbA1c and blood pressure, i.e. the average HbA1c and blood pressure in the last 
three years prior to the intervention, predict benefits from the CCT. 
Prior experience with computers- Prior experience with computers will be assessed at 
baseline.  
Diabetes Care Profile-The Diabetes Care Profile is a self-administered instrument that 
assesses the social and psychological factors related to diabetes and its treatment. For this 
study, we have adapted the approximately 40-page questionnaire to 13 pages. Participant 
responses are scored using various scales including understanding, support, attitude, and care 
ability. This is administered everytime the neuropsychological assessments are completed.  
Vision Screen-To formalize the assessment of the veteran’s capability to use the computer, we 
implemented the Vision Screen, which seeks to determine whether or not the veteran has any 
visual issues, and if so, if there issues have been addressed by a medical doctor or affect daily 
tasks that require adequate vision. In addition, we also use this form, to gauge the participant’s 
ability to adequately use the computer and the CCT program—that is, to use the mouse, and to 
understand the instructions.  
End of Program Survey- This survey captures the participants’ experiences with the 
computerized cognitive training program.  
 
Gait assessments: 
WALKING WHILE TALKING (WWT) 
The WWT is a cognitive-motor divided attention task (Dual Task) that has been shown to 
uncover “subclinical” gait deficits, by increasing the complexity of the walking condition.  
Participants are asked to walk while reciting alternate letters of the alphabet.  The test measures 
both the time (seconds) taken by an individual to walk a distance of 6 meters, and the accuracy 
of the cognitive responses (#correct responses/total responses) during the walk.  It consists of 3 
components: Single Task Cognitive; Single Task Walk; and Dual Task Walking while Talking.  
Participant should wear their regular footwear and use their customary walking aid (none, cane, 
or walker).  No physical assistance is given.   
 
Single Task Cognitive 
Description:  Single task cognitive performance is assessed by asking participants to recite 
alternate letters of the alphabet(i.e. a, c, e,…etc), while standing still for 10 seconds.  Two trials 
are performed, the first beginning with the letter ‘A’ and the second with the letter ‘B’.   
Record for each trial:  Responses generated within each 10 seconds interval.  Response 
accuracy is the single task cognitive outcome and is calculated by dividing the number of correct 
responses by the total number of responses.   
 
Single Task Walk: 
Description:  Single task walking performance is assessed by timing. The participantstands 
behind  the walkway start line,and at the command “GO”, walks down the walkway at their 
normal, comfortable pace, stopping after crossing the deceleration line.  For safety, the 

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examiner walks to the side and slightly behind the participant, being careful not to pace the 
participant. 
Record for each trial: Time, in seconds, to complete the central, 6 meter portion of the 
walkway.  Timing begins when the participant’s foot crosses over the 1stwhite line and ends 
when their foot crosses the 2nd white line. Note whether an assistive device is utilized to perform 
the task. Speed (meters per second) is the single task walk outcome and is calculated by 
dividing the distance (6 meters) by the time taken to walk it. A value is calculated for each trial. 
 
Dual Task Walking While Talking: 
The WWT consists of walking the designated walkway while simultaneously reciting alternate 
letters of the alphabet. The participant walks down the 8 meter walkway, at their normal, 
comfortable pace, while reciting alternate letters of the alphabet.  The participant is instructed to 
pay equal attention to both the walking and cognitive task. Testers do not advise or encourage 
subjects during the task, intervening only in situations where subject safety is an issue. The 
initial letter in the cognitive  task is randomly varied between (C-E-G) in the first trial and  (B-D-
F) in the second trial at subsequent time-points to reduce learning effects. Participants continue 
reciting letters until they have completed the walking task-they do not end when they reach the 
end of the alphabet. For safety, the examiner walks to the side and slightly behind the 
participant, being careful not to pace the participant. 
Record for each trial: Time, in seconds, to complete the central, 6 meter portion of walkway 
and the letter responses generated during the duration of the walk.  
 
 
5.6 Data Analysis 
 
Data analysis 
 
We will examine all variables for errors. Substantially non-normal distributions will be 
transformed to reduce the influence of extreme values. SPSS or SAS will be used aims 1 and 3, 
and Mplus will be used for Aim 2. 
 
 Linear mixed model analyses for Aims 1 and 3- These analyses will be intent-to-treat 
(ITT) comparisons of the 150 subjects randomized to the CCT with the 150 randomized to the 
control intervention, with four observations — baseline, at 2 (end of treatment), and 8 and 14 
months afterwards (post-treatment). Linear mixed models (LMM) will be fitted for two endpoints, 
the 8 and 14 month observations. Missing data will be accounted for using iterative full 
information maximum likelihood estimation of the relevant model parameters. For Aim 1, each 
model will include intervention group and time as fixed factors, subjects as a random factor, and 
– most importantly – the intervention group by time interaction, which indicates whether the 
change in outcome over time differs between the intervention groups. To reduce variation 
attributable to subject differences, and to control for possible unbalanced randomization by age, 
sex, education, or baseline MMSE, these will be included as primary covariates. With regard to 
other, secondary covariates, such as ethnicity, health literacy, or computer experience, if any 
correlates with an outcome at p<0.05, it will be used as a covariate in a secondary analysis, to 
reduce within-group variation. The number of intervention sessions completed will be a 
covariate in secondary analyses. To confirm the results, for each post-intervention assessment, 
ANCOVAs will test group differences in changes from baseline to the post-intervention 
observation, using the baseline score as a covariate. 
 
For Aim 3, the LMM model will also be used to explore the contributions of 
demographics (age, education, ethnicity) and health-related characteristics (health literacy, 
ADL/IADL, depression, family history of dementia, smoking and physical activity habits; see 
section D13 of the grant) to the effects of CCT on each of the primary and secondary outcomes, 
by including them in the analyses. We will add the characteristic as a covariate, and also its 

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interactions with the intervention group by time interaction and lower order interactions. 
Identifying the contributions of such characteristics may suggest underlying mechanisms of CCT 
efficacy, in addition to targeting subgroups of subjects for whom the intervention is most 
efficacious. This may guide planning of dissemination and implementation of a CCT program 
(see section E). For descriptive purposes, we will compare the interventions using dichotomized 
subgroups of the characteristics (e.g., low and high education).  
Significance levels for multiple outcomes and for efficacy analysis. The six primary outcome 
measures for Aim 1A are memory and executive functions/attention, diabetes self-management 
scale and medication adherence, and glycemic and blood pressure control. Each of these 
variables will be a dependent variable in two LMM analyses, for follow ups at 6 and 12 months 
after the intervention. Although demonstration of benefit of CCT beyond that of the active control 
is directional, tests of significance will be two-sided, for sensitivity to the possibility that CCT is 
substantially inferior to the active control. Each of these results will be critical for designing a 
large scale multi-site study to justify clinical implementation of CCT throughout the VA, so each 
will be tested at the 0.05 level. Similarly, each of the Aim 3 analyses will be tested at the 5% 
level, since they are all exploratory, for the purpose of identifying Veterans who are most likely 
to benefit from CCT. For the specific purpose of demonstrating efficacy in Aim 1B, a test of 
significance of CCT efficacy for noncognitive outcomes, we have selected two of these LMMs, 
the behavioral outcomes (DM self-management and medication adherence) at 6 months after 
the intervention, which are intervening variables for the clinical and longer-term outcomes. For 
this evaluation of efficacy, each of these two LMMs will have a one-sided test, at the 0.025 level 
of significance. By the Bonferroni inequality, this has a 0.05 upper limit for probability of rejection 
by chance if the null hypothesis, equivalent to a single two-sided test at the 0.05 level. Path 
analyses for Aim 2. To compare the linkages through which the two interventions successively 
affect changes in cognition, behavior, and clinical outcomes, four parallel path analyses (for 
CCT and active control interventions, at six and 12 months after the intervention) will be 
performed for the model . Comparisons of the coefficients in the models will indicate whether 
the CCT has different linkages from the active control intervention. 
 
Power analysis is provided for Aim 1 based on the LMM model, calculated using Equation 15 in 
Oakes and Feldman. In a study finding significant differences between Personal Coach and a 
computer games program in a sample of patients with MS25, the effect size for the memory 
composite was the strongest, 0.97, and most of the effect sizes for other cognitive assessments 
(tests and composite scores) were between .25 and .30. In addition to the effectiveness of CCT, 
the power reflects the postulated R2, the proportion of the total variance among the post-test 
scores that is explained by the pre-test scores. When the pre-test scores predict the post-test 
scores well (high R2), there is relatively little ―noise‖ so one can clearly discriminate between 
the two interventions. When R 2 is small, a larger effect is required for detectability. Table 9 in 
the protocol (grant) displays the effect sizes (differences between the post-test z-score mean in 
intervention group and the post-test z-score mean in the control group, adjusted for pre-test 
scores) that are detectable with 80% power using a 2-sided α=0.05 with n=112 participants in 
each of the two groups. These power analyses demonstrate satisfactory detectability for these 
effect sizes and R2 values. Thus, samples of n=112 subjects who complete all four 
assessments provide at least 80% power to detect an effect size for a cognitive outcome in the 
range of .25 to .30 if R2 is no less than 0.35. Based on a 14-month attrition rate of 25%, a 
conservative sample of 112 with complete data implies an initial sample of 150 in each group. 
With such a large sample size, it is seen that the effect size does not depend much on R2, so 
that even for lower R2=0.30, the detectable effect size is only 0.32. If the effect size is larger, as 
was observed for memory, the power will exceed .80. To the best of our knowledge, disease 
self-management and the other behavioral and clinical measures have never been examined as 
outcomes in the context of CCT, so data suggesting effect sizes is lacking. (Among all other 

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innovations, the proposed study will also provide data on this.) Effect sizes for a variety of other 
non-cognitive outcomes in other cognitive training studies (0.50 for gait velocity three months 
after initiation of the program, in a Personal Coach study, 0.21 for health-related quality of life 
two years after training in the ACTIVE study, and 0.25 on average, depending on the training 
modality, for an ADL outcome five years after training in the ACTIVE study) suggest that the 
effect sizes anticipated for the primary cognitive outcomes will be broadly applicable to the 
noncognitive outcomes of Aim 1 as well, so power will be comparable. This power analysis for a 
two-sided test at the 0.05 level also applies to each of the one-sided tests for efficacy in section 
D16b of the grant. Since this power is based on only one of the two outcomes being efficacious, 
it provides a conservative power estimate for efficacy based on testing two outcome measures. 
Although M-Plus also calculates power for comparison path coefficients, the specification of 
estimates would require an additional level of speculation beyond the speculation for the power 
analysis of Aim 1. The present proposal will provide the first empirical results on the 
relationships among changes in cognition, diabetes-related behavior, and clinical outcome in a 
CCT and in an active control. 
Missing data from training dropouts- Since few subjects refuse to continue our 
longitudinal studies, we anticipate almost all subjects who start the intervention will complete the 
identical neuropsychological follow up assessments for this study, at the same follow up times, 
even if they drop out of the intervention. 
Statistician James Schmeidler, with the assistance of Rebecca West, will complete data 
analysis during and after the study, from offices at the JJP VAMC and Mount Sinai School of 
Medicine.  
 
 
5.7 Withdrawal of Subjects 
 
Although normal cognitive functioning is a requirement at the start of the study, 
participants who experience cognitive decline during the course of the study will not be removed 
from use of the cognitive training program.. If the worsening of cognitive functioning brings a 
participant to the point of potentially impaired decision-making capacity, they will be 
discontinued from the study. We have changed the documentation to explain that if decision-
making capacity is lost, the follow-up memory and thinking tasks, blood draw and blood 
pressure tests, and other assessments will not continue. However, a participant may continue 
using the cognitive training program, they will not be required to stop use of the program. The 
cognitive data up to the point of potential loss of decision-making capacity will be retained, and 
when data analysis is conducted, the participant will be marked as having declined in cognitive 
functioning. Data analysis procedures will be conducted such that it is clear that these 
individuals, even if they go on to complete the cognitive training, had declined in cognitive 
functioning and lost capacity. Information regarding actual use of the program by these 
participants will be incorporated into the analysis. 
Subjects are informed that they may terminate testing or training at any time should they find 
any aspect objectionable. The interviewers and research assistants will be clinically trained and 
will be sensitive to signs of stress, anxiety and/or fatigue. 
 
6.0 
Reporting 
 
Safety monitoring for adverse events (AEs) will be conducted in real time by the 
PI, research coordinators, and the Central, and JJP and Ann Arbor VAMCs IRBs. All adverse 
events (serious adverse events (SAEs), unexpected AEs, and expected AEs) will be indicated 
on the source documentation for the study, and on the specific VA Central IRB adverse event 
report form. All AEs will be reported to the VA CIRB within according to the Table of Reporting 
Requirements (within 5 business days when required of the investigative team learning about 
them, otherwise in summary at continuing review) . The following information about adverse 

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events will be collected: 1) the onset and resolution of the AE, 2) an assessment of the severity 
or intensity (use existing grading scales whenever possible), 3) an assessment of the 
relationship of the event to the study (definitely, probably, possibly or not related), and 4) action 
taken (e.g., none, referral to MD, start or increase concomitant medication). The PI together with 
Dr. Grossman at the JJP and Dr. Lee at Ann Arbor will determine the severity of the event, will 
assign attribution to the event, and will monitor the event until its resolution. 
 
Research staff will maintain communication with participants as part of the study, and will 
record any reports of an AE, and will ask about any adverse events the participants are 
experiencing during participation, via regular telephone calls with the participants and at follow-
up visits. 
 
After informed consent, participants will be seen in person at baseline, immediately 
following training (7-8 weeks after baseline), 4 months after completion of training, 6 months 
after completion of training,  and 12 months after completion of training. Participants will be 
contacted weekly during training. At each of these points, safety data will be collected. 
 
7.0 
Privacy and Confidentiality 
 
PHI will be obtained directly from project participants. Upon receiving a list of the 
potential subjects who meet eligibility criteria according to initial screen using the CPRS, we will 
contact their primary care physicians and ask for their permission to contact their patients. 
Subjects will be then sent a letter describing the study, inviting them to get in touch with us by 
phone or mailing in a postage paid card. Unless a subject replies telling us not to call, the 
research coordinators will call the subject. Names, SSNs, medical records, ages and birth 
dates, and telephone numbers and addresses will be collected. The company that makes the 
two programs, CogniFit, will not have access to personally identifiable information of the 
participants.   
            All study data will be securely stored on an approved VA server behind the VA firewall in 
a folder with restricted access. Only authorized project staff members have access to the folder, 
and once personnel are no longer a part of the research team, their access to this folder will be 
removed. Additionally, any identifiable data stored in a crosswalk file are stored in a folder that 
is separate from datasets to be used for analysis. All analyses files contain a study ID only. Any 
data to be transferred are transferred using PKI or an encrypted CD, both of which are VA 
approved methods of transmission. Note that the CCT data is directly sent to the software 
company every time a subject logs in and off. This data will be connected with an ID number 
and the training data only and the informed consent will include language that clearly informs 
the subject this data from the training will be stored at the software company, which is outside 
the VA. The software provides us with information on number of times the subject logged in, 
average time on the software, the percent of time subjects performed each task (this variable 
provides us with information about the cognitive function that was identified by the software 
algorithm as the weakest and thus was trained the most). Finally, the investigators will NOT 
provide the software company any information collected by the investigators (such as the 
neuropsychological assessments performed by the investigating team, medication adherence 
information, etc.).  
Data will also be stored and managed using REDCap (Research Electronic Data 
Capture). REDCap is currently approved for use, with constraints, by the U.S. Department of 
Veterans Affairs. We will ensure that we adhere to the constraints outlined by the decision on 
1/31/016: http://www.va.gov/TRM/ToolPage.asp?tid=6453&tab=2&minYear=2016.     
De-identified will be placed on a regular CD and snail mailed or emailed to Dr. 
Schmeidler, whose offices are at the Mount Sinai School of Medicine, for data analysis.  The PI 
will ensure that data is backed-up in the event that these de-identified data are lost in transit. 
Protection of patient confidentiality and privacy will be rigorously guarded by the assignment of 
coded numbers to each file in the computer database.  

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       Participants will provide information in person in their homes, or at the local VAMC. 
Participants will provide information through the memory and cognitive assessments, and only 
research staff members will receive and use that information. Participants are not likely to feel 
any stigma in entering the VAMC or hospital, or within their own homes. In nearly all cases, the 
participant will already be a patient at that VAMC and will regularly be seen by doctors there. 
The information collected is not likely to cause any discomfort, but efforts will be made to clearly 
communicate to the participants that their information is confidential. Participants will  also be 
informed that they may refuse to answer any questions that make them uncomfortable. Only 
investigators and staff listed on this project will be allowed to view any identifiable information 
about the participants. These individuals will have completed their IRB certifications. All efforts 
will be made to make participants comfortable in the research setting. Most participants will be 
seen in their homes or at the VAMC where they are regular patients; this should help ensure 
their comfort. We will inform all participants that they may refuse to answer any questions that 
make them uncomfortable. 
 
 
8.0 
Communication Plan 
 
Two VA sites are involved in this study, and the study PI and local sites will be in contact 
regularly regarding any required approvals. Dr. Silverman will lead bi-weekly meetings (the Ann 
Arbor staff will join on a conference call) to discuss all day-to-day aspects of the study (adverse 
events or problems, recruitment, reasons for refusals and ways to overcome them, data entry 
and missing data, staffing and coordination issues, and IRB issues including modifications and 
ensuring that research is conducted fully within the bounds of the approved IRB protocol). Dr. 
Silverman will confirm with both local sites that IRB-approval has been fully obtained prior to any 
conduction of research, or prior to any enacting any modifications of research. Any changes 
made to IRB documentation will be shared between sites, and IRB paperwork for local sites will 
be sent to both sites for their records.  
 
9.0 
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3. Miller et al. Who has diabetes? Best estimates of diabetes prevalence in the Department of 
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5. Xu et al. The effect of borderline diabetes on the risk of dementia and Alzheimer's disease. 
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37. Wolinsky et al. The effects of the ACTIVE cognitive training trial on clinically relevant 
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44. Heisler et al. How well do patients' assessments of their diabetes self-management correlate 
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51. Stoehr et al. Factors associated with adherence to medication regimens in older primary 
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52. Sela-Katz et al. Basic knowledge of the medication regimen correlates with performance on 
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55. Platt et al. Risk factors for nonadherence to warfarin: results from the IN-RANGE study. 
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62. Insel et al. White matter hyperintensities and medication adherence. Biol Res Nurs 2008; 
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