Supporting Habit Formation to Attenuate Prefrailty in Elders: a Pilot Study
Phase: NA
Conditions: Frailty
Sponsor: Wayne State University

 
 
Supporting Habit Formation to Attenuate 
Prefrailty in Elders (SHAPE) Pilot Study  
Protocol  
 
 
 
 
 
 
Version 1, July 9th, 2019 (original) 
 
 
 
Clinical Trial # NCT04140890 
 
Funding from the Michigan Health Endowment Fund: R-1707-141644 
  

1 
 
Table of Contents 
 
List of tables ............................................................................................................................... 2 
List of figures .............................................................................................................................. 2 
 
The SHAPE Pilot Study ........................................................................................................ 4 
1.1 Objectives and Hypotheses ........................................................................................................... 4 
1.2 Background ................................................................................................................................... 4 
1.3 Study design .................................................................................................................................. 5 
1.3.1 Participants eligibility.............................................................................................................. 5 
1.3.2 Phone screening ..................................................................................................................... 7 
1.3.3 Consent visit ........................................................................................................................... 7 
1.3.4 Baseline evaluation ................................................................................................................. 7 
1.3.5 Randomization and Blinding ................................................................................................... 8 
1.3.6 Recruitment ........................................................................................................................... 8 
1.3.7 Intervention period ................................................................................................................ 8 
1.3.8 Follow-up data collection ........................................................................................................ 9 
 
Data analysis plan ............................................................................................................. 11 
2.1 Data analysis ............................................................................................................................... 11 
2.2 Sample size estimation ............................................................................................................... 11 
2.3 Assessments................................................................................................................................ 11 
 
Potential Benefits, Risks and Alternatives ........................................................................ 12 
3.1 Benefits ....................................................................................................................................... 12 
3.2 Risks ............................................................................................................................................ 12 
3.3 Minimization of Risks .................................................................................................................. 12 
3.4 Adverse events ........................................................................................................................... 13 
 
References ........................................................................................................................ 14 
 
 

2 
 
List of tables  
Table 1 Overview of measurements and testing time ................................................................ 10 
 
List of figures 
Figure 1. Trial conceptual model ................................................................................................. 5 
Figure 2. Overview of the SHAPE pilot study................................................................................ 6 
Figure 3. Breakdown of baseline evaluation by tasks ................................................................... 7 
 
 
 

3 
 
 
Contact for Public 
Queries 
 
Heather Fritz, PhD, OTR/L 
heather.fritz@wayne.edu 
Department of Occupational Therapy 
Wayne State University 
259 Mack Ave. Room# 2204 
Detroit, MI 48202 
United States  
 
Contact for Scientific 
Queries 
Heather Fritz, PhD, OTR/L 
heather.fritz@wayne.edu 
Department of Occupational Therapy 
Wayne State University 
259 Mack Ave. Room# 2204 
Detroit, MI 48202 
United States  
 
Or  
Yi-Ling Hu, PhD 
ha1124@wayne.edu 
Department of Occupational Therapy 
Wayne State University 
259 Mack Ave. Room#3112 
Detroit, MI 48202 
United States  
 
Countries of 
Recruitment 
United States 
 
 

4 
 
 The SHAPE Pilot Study  
1.1 Objectives and Hypotheses   
The main objective of the SHAPE pilot study is to determine the feasibility of using Habit 
Formation (HF) treatment to increase Physical Activity (PA) (reduction in daily in hours of 
sedentary time), and dietary among prefrail African Americans. This study will test two 
hypotheses:  
Hypothesis 1: The SHAPE study will demonstrate good feasibility with high recruitment 
rate and successfully administrating all of measures among the target population.   
 
Hypothesis 2: Treatment group participants will demonstrate greater increases in 
primary outcomes (sedentary time and dietary quality) and secondary outcomes 
(prefrailty reduction, lower extremity strength, balance, and quality of life) at 
intervention completion.  
 
1.2 Background  
Frailty among older African Americans is common, detrimental and costly. Approximately 50% 
of older adults are pre-frail, 1-2 which makes them 2-3 times more likely to develop frailty within 
3-7 years than non-frail elders.2-5 Frailty, is defined as a decline in resilience across one or more 
domains of functioning that reduces an individual’s ability to respond to or recover from 
stressors (e.g., illness or loss of a loved one).6 In the context of frailty, acute social or health 
stressors can trigger a cascade of negative sequelae. Frail older adults are more likely to 
experience premature morbidity (as high as a 50% increase in relative risk), 4 mortality, and 
institutionalization.1-2, 4, 7-8 African Americans have an especially high risk of becoming frail. 
African Americans are 2-4 times more likely to develop frailty than their European American 
counterparts, to do so at a younger ages, and to experience worse outcomes as a result.1, 9-10 
Moreover, correlates of frailty such as having less formal education and lower income,12 living 
in lower quality neighborhoods,12-15 higher rates of comorbid chronic diseases, obesity, and of 
disability are more prevalent in African American populations.16-21 
 
Effective frailty reduction interventions delivered to older African Americans during the 
prefrailty stage could reduce or delay frailty and improve health outcomes among older 
African Americans. For prefrail older adults, the progression to frailty is neither inevitable nor 
irreversible. Pre-frail elders can regain non-frail resilience and are significantly more likely to do 
so than frail elderly.5, 22-24 Moreover, pre-frailty represents an important, time-limited window 
of opportunity to intervene in the progression to frailty.25 A recent study suggested that 
individual’s spend approximately 7.4 years in the prefrail stage versus only 3.4 in the frail stage 
(before progressing to death or disability).25 Interventions delivered during prefrailty may also 
require less intensive treatment than those delivered during frailty. Resilience-bolstering 
behaviors such as consuming adequate nutrition and increasing physical activity (PA) levels are 
currently the frontline non-pharmacological treatment for frailty reduction. Adequate nutrient 
intake (e.g., protein, vitamin D, fatty acids and minerals) protects against frailty by improving 
cell metabolism and anabolic signaling.26 PA is considered frailty-protective through the effect 
that it has on attenuating sarcopenia,26-27 stimulating muscle protein synthesis,28-29 and 

5 
 
increasing muscle strength, and physical performanc.26-27 Thus, intervening to increase physical 
activity and improve dietary quality among older adults during the prefrailty stage has the 
potential to reduce prefrailty and significantly improve both current and future health. 
 
A novel, evidence-based habit formation program is used the SHAPE study to improve dietary 
quality and decrease total sedentary time (ST) could reverse prefrailty or delay its progression 
among older adults. The habit formation program consists of 12 treatment sessions over 12 
weeks. In each session, an occupational therapist will deliver educational content, and use HF 
techniques and behavioral skills to facilitate frailty protective behaviors. The conceptial 
treatment model approach to improve dietary quality and reduced ST among frail older adults 
(Error! Not a valid 
bookmark self-
reference.). HF 
approaches are 
effective across a 
range of behaviors, 
easy to implement, 
satisfactory to 
participants, 
tailorable to the 
individuals’ unique 
context, and 
correlated with key 
health outcomes.54, 
63-65  
 
1.3 Study design 
The SHAPE pilot study is a two-armed, single blinded, randomized control trial study (Figure 2). 
Community dwelling prefrail African Americans ages 55 and older is the target population to 
account for accelerated aging among African Americans.66 The sampling frame are Afiracan 
American adults who register in the Healthier Black Elders Center’s Participant Resource Pool 
(PRP). The screening, consent, and enrollment procedures will follow a strict IRB-approved 
protocol over 16 weeks. Eighty prefrail African Anericans will be randomized to the treatment 
or control group.  
 
1.3.1 Participants eligibility 
The inclusion criteria of participants includes: (a) English-speaking, (b) community dwelling, (c) 
members of PRP registry, (d) prefrail (evaluated by the Fried’s Frailty Criteria Index), (e) self-
identify as African Americans, (f) aged 55 and older. The exclusion criteria include: (a) 
diagnosed psychiatric disorders, (b) moderate or severe cognitive impairment (verified using 
the validated 6CIT and operationalized as score of ≥ 10),68-69  the use of prescription drugs that 
could affect cognition and functioning (e.g., neuroleptics), (c) individuals with typical daily pain 
ratings of ≥ 7/10, (d) plan to change residences during the study period; (b) rely on a wheelchair 
for home or community mobility; (e) are actively receiving home care services, occupational, or 
Educa&on about 
resilience bolstering 
ac&vi&es 
Strategies to increase 
self eﬃcacy 
Habit forma&on 
behavioral skills 
training 
Prefrailty reduc&on, 
Improved strength, 
balance, and QOL 
Conscious inﬂuences on 
behavior decrease over &me 
Environmental inﬂuences on 
behavior increase over &me 
Increased objec&ve PA, 
Improved dietary 
quality 
Habit 
Forma&on 
Figure 1. Trial Conceptual Model 
Figure 1. Trial conceptual model 

6 
 
physical therapy; (f) are on dialysis or who have an end stage disease (e.g., stage IV heart 
failure); (g) are enrolled in a health promotion program focused on PA and diet; and (h) those 
who have a baseline dietary quality score of ≥ 85/100 as their diet would already be very close 
to ideal (average score for U.S. population = 59).   
 
Figure 2. Overview of the SHAPE pilot study.  
Raters will conduct the activities in the navy boxes.  
 
 
Week 0 
Follow-up evaluation 
Treatment group  
Control group 
Allocation 
Follow-Up 
Randomized 
Enrollment 
Consent 
Phone screening 
(confirm eligibility) 
Baseline evaluation 
Week 0 
Week 1-2 
Week 3-14 
Week 15 

7 
 
1.3.2 Phone screening  
The study coordinator calls potential participants from the participant resource pool (PRP) 
registry to screen for exclusion criteria (a)-(g). If potential participants passed the phone 
screening, the coordinator will schedule consent/baseline evaluation visit and assign 1-2 raters 
for the visit.  
 
1.3.3 Consent visit  
Consenting visits will take place at participants’ home. Raters should call potential participants 
1 day ahead of time to confirm if they are still available. During the visit, raters will explain and 
help participants understand the SHAPE study procedure. All components of the consent form 
should be clearly delivered (see 2.3 consenting procedure). Consent forms must be attained 
before any data collection activities started. Both potential participants and the raters will sign 
two copies of consent forms, one for the potential participants to keep and one for the lab.  
 
1.3.4 Baseline evaluation 
Ideally, once potential participants consented, raters will immediately start the baseline 
evaluation. However, if the potential participant need time to think about joining the study or 
are unwilling to do the baseline evaluation immediately after consent, raters should reschedule 
another time for baseline evaluation visit (figure 2).  
 
At baseline evaluation visit, the raters will 
collect potential participants’ sociodemographic 
characteristics and anthropometrics. A series of 
psychometric and performance-based measurers 
will also be conducted for eligibly confirmation 
and primary/secondary outcomes (table 2; see 
1.4.2 for procedure of measurement 
administration). Most of the measures will be 
conducted in the baseline evaluation visit, except 
for ActivPal activity-tracking device (measures 
sedentary time) and Automated Self-Administered 
24-hour (ASA24) dietary recall (measures dietary 
quality).  
 
Sedentary time is measured by Community 
Healthy Activities Model Program for Seniors 
(CHAMPS) and the ActivPal activity-tracking 
device. At baseline evaluation visit, the rater will 
teach potential participants to use the ActivPal 
activity-tracking device. The potential participant 
will wear the ActivPal sensor for seven 
consecutive days to collect baseline activity data. 
At the end of the tracking period, the rater will schedule an  
Figure 3. Breakdown of baseline evaluation by tasks 
Baseline evaluation 
•Administer all psychometric and 
perfomance-based assesments 
•Apply and teach participants to 
use ActivPal
Baseline 
evalulation 
visit
•Administed the second ASA24 
dieatary recall with participants
2nd ASA24 
phone 
follow-up
•Pick up ActivPal sensor 
•Deliver gift card
ActivPal pick-
up visit

8 
 
ActivPal pick-up visit to retrieve the tracker from the participant.  
To evaluate potential participants’ dietary quality, the rater will administer two ASA24 dietary 
recalls in two non-consecutive days. The ASA24 is a web-based tool that enables multiple, 
automatically coded, self-administered 24-hour recalls for multiple meals. At baseline 
evaluation visit, raters will log in to the ASA24 system respondent website to go collect recalls 
of meals dietary from the previous day. A 2nd ASA24 phone follow-up will be scheduled two 
days after the baseline evaluation will be conducted to collect another day of participants’’ 
dietary intake.   
 
After completing consent/baseline evaluation visit, all files and tools should be returned to the 
Fritz lab in the same day. If raters need to return the tools overnight, please remember not to 
leave the tools in raters’ car, some tools need to be in certain temperature.  
 
1.3.5 Randomization and Blinding 
After consent/baselinve evaluation visit. The study coordinator will check participants’ 
eligibility. Randomization was carried out by a coordinator not involved in data collection or 
analysis activities. Data collectors were blinded to arm assignment. 
 
Participants will be allocated using a 1:1 ratio via adapted randomization sequences generated 
a priori by the study statistician, Dr. Hu, using an online tool 
(https://www.sealedenvelope.com/simple-randomiser/v1/lists) to form a randomization table 
with a variable block size (2,4, or 8). Randomization sequence concealment will be achieved by 
query of the REDCap (Research Electronic Data Capture) system.  
  
1.3.6 Recruitment 
Participants are recruited through PRP list from the Healthier Black Elders Center (HBEC). A 
preidentified list was screened by the center coordinator. Raters cold call people on the list to 
invite potential participants to join our study.  
 
1.3.7 Intervention period 
The treatment group will receive habit formation intervention for 12 weeks. The HF 
intervention is delivered by an experienced geriatric occupational therapist. The 12-week long, 
intervention is delivered to each participant during 12 face-to-face, home based sessions (each 
lasting ~60 minutes). An initial session (week 2) focuses on welcoming the participant to the 
program, and delivering educational content about prefrailty, frailty protective behaviors, and 
the concept of HF. In preparation for the sessions covering ST reduction and MVPA the next 
session (week 3) focuses on pain, its management, and the relationship between pain and 
activity (described below). Weeks 3-11 include weekly HF sessions focused on ST reduction, 
MVPA and dietary behaviors (see Table 2 for session content). A closing session occurs in week 
12 to review program progress and create maintenance plans.  
 
The control group will receive 12 weeks of newsletters focused on general healthy aging 
topics. Within 4 days of mailing the newsletter, the coordinator will call the participant, verify 
receipt of the newsletter, and ask them if they have any questions about the materials. Phone 

9 
 
call will last ~15 minutes. Control condition participants receive no further intervention. 
 
1.3.8 Follow-up data collection 
When the 12-week intervention period is over, the coordinator will assign raters for follow-up 
evaluation. Most of the measures will be re-administered.  
 

10 
 
Table 1 Overview of measurements and testing time  
Evaluation time point 
(week) 
Variable  
Measure 
Screening  
Phone screening (w0) 
Eligibility  
1. Phone screening eligibility form  
Frailly status 
2. Paulson Lichtenberg Frailty Index (PLFI) 
Cognitive impairment 
3. The Six Item Cognitive Impairment Test 
(6CIT) 
Primary outcome*  
Baseline (w1),  
follow-up (w15) 
Sedentary time 
4. Community Healthy Activities Model 
Program for Seniors (CHAMPS)  
Baseline evaluation (w1-
2),  follow-up (w15) 
Sedentary time 
5. ActivPal kcal expenditure 
Baseline (w1, 2nd phone 
follow-up), 
follow-up (w15, 2nd 
phone follow-up) 
Dietary quality 
6. Automated Self-Administered 24-hour 
(ASA24) dietary recall 
Secondary outcome  
Baseline (w1),  
follow-up (w15) 
 
Frailty status 
7. The Fried’s Frailty Criteria  
• Grip strength with dynamometer 
• 15 ft walking test 
Lower extremity muscle 
strength 
8. Short Physical Performance Battery (SPPB)  
• 3-meter walking test 
 
Balance 
Quality of life 
9. The World Health Organization Quality of 
Life- BREF (WHOQOL-BREF) 
Habit formation 
(Treatment group only) 
Habit formation 
10. The self-reported habit index subscale 
Demographics and other mediators 
Baseline (w1) 
Comorbidities   
 
11. Comorbidity Checklist  
 
Sociodemographic  
12. Sociodemographic Form  
Baseline (w1),  
follow-up (w15) 
Participants 
anthropologies 
13. Participants anthropologies forms 
• Weight 
• Height 
• Waist circumference  
Depressive symptoms  
14. Geriatric Depression Short form (GDS) 
Treatment session 
1,3,5,7,9  
(w 3, 5,7,9,11) 
Habit formation 
15. Self-report habit index (SRHI) 
Note. *Both primary outcomes will be used for screening potential participants’ eligibility.  
 
 

11 
 
 Data analysis plan   
2.1 Data analysis  
Feasibility outcomes such as recruitment, retention, and attendance data were presented by 
descriptive statistics. Differences in baseline characteristics between the two groups were 
tested by independent t tests or chi-square/Fisher’s exact tests. For the primary and secondary 
outcomes , effect sizes were be represented by Cohen’s D, where 0.2 indicates small, 0.5 as 
moderate, and 0.8 as large effects. As for mechanisms of behavior change, pre and post habit 
formation effect sizes are estimated by Cohen’s D. All statistical analyses were conducted by 
IBM SPSS software, version 26.0 (SPSS Inc., Chicago, IL).  
 
2.2 Sample size estimation  
We did not use power analysis to estimate study sample size for determine efficacy. We aim to 
recruit 15 participants in per group suggested for feasibility pilot study.  
 
2.3 Assessments 
Primary outcomes (measured at week 0 and 1 week post intervention). Sedentary Time (ST) 
was measured via the ActivPal wireless activity tracker. ActivPal is a validated tool with a 
commercialized program to generate mean minutes of total ST (min/day), sum of 30-minute 
bouts ST, and sum of 60-minunite bouts ST, as well as the number of 30-min bout ST and 60-
munites bout ST per day. Participants wore the ActivPal device on their thigh for seven days 
during their waking hours. Dietary Quality was measured using the Healthy Eating Index (HEI) 
and operationalized as the total HEI score generated from the National Cancer Institute’s ASA 
24®.  
 
Secondary outcomes (measured at week 0 and 1 week post intervention). Pre-frailty status was 
measured using the current gold standard, the Cardiovascular Health Study frailty criteria as 
composite index consisting of the following components: (a) self-reported weight maintenance; 
(b) walking speed (the mean time of two trials for the time taken to walk 15 ft. reported in 
seconds); (c) grip strength, (mean score of grip strength reported in Lbs. of three trials on the 
dominant hand using a calibrated Jaymar dynamometer); (d) exhaustion, measured as a 
response of “All of the time” or “Most of the time” to the following two questions reported on 
a 4 point Likert scale, “I felt that everything I did was an effort in the last week,” and “I could 
not get going in the last week”; and (e) total Kcals of energy expended over a 7 day period, 
measured via Community Healthy Activities Model Program for Seniors (CHAMPS) 
questionnaire. Change of all PA and MVPA duration (minutes/week) measured by CHAMPS. We 
also used Activpal to estimate the cumulated MVPA duration. We cumulated MVAP minutes by 
selecting activity intensity greater than 3 METs. Physical Function was measured via the Short 
Physical Performance Battery (SPPB) subtests for lower extremity strength and balance. 
Depressive symptoms were measured using the Geriatric Depression Scale (Kieffer & Reese, 
2002). Participant anthropometry such as weight circumference (inch) was measured by a 
girthometer, height (cm) by a stadiometer, and weight (pound) by medical scales. Body mass 
index (BMI) was also calculated based on participant anthropometry. Quality of life was 
measured using the 26-item validated WHOQOL-BREF. Occupational performance was 

12 
 
measured by the Canadian Occupational Performance Measure (COPM), but only among 
treatment group participants. Habit Formation was measured using the validated, 4-item, Self-
Report Behavioral Automaticity Index (SRBAI). The SRBAI measures perceptions of behavioral 
automaticity for an identified behavior. To track habit formation during the intervention, the 
SRBAI was administered to treatment condition participants every 2 weeks from sessions 3-11 
to assess changes in automaticity for their self-selected habits.   
 Potential Benefits, Risks and Alternatives  
3.1 Benefits 
There will be considerable benefits to the participants enrolled in the proposed study. All 
participants will receive information about how to reduce cardiovascular disease risk, and how 
to increase physical activity or improve your diet. In addition, participants in the active treatment 
group will receive free health coaching, while participants in the attention control group will have 
a trained research assistant deliver health related education. 
 
3.2 Risks 
Potential risks of research participation-physical, psychological, financial and legal risks among 
others-are considered minimal. In-home evaluations and assessments of barriers may result in 
fatigue or aggravation. In addition, some questions may touch on emotionally-sensitive issues 
that could cause anxiety or other forms of emotional stress. The performance-based testing 
involves observation of everyday activities, which may result in fatigue or embarrassment.  
 
Participants will be told that their involvement in this research study is voluntary and that they 
may choose not to participate or withdraw their consent at any time. Withdrawal from the study 
will not at any time affect the commitment of the clinician to administer care, and there will be no 
penalty or loss of benefits to which participants are otherwise entitled. Participants who undergo 
the study visits will be given the option to reschedule the visit or take a break at any time during 
the study if necessary. There is little legal risk to participating in this research. All research-
related information will be kept confidential and accessible only to authorized members of the 
research team. 
 
3.3 Minimization of Risks  
We are a HIPPA covered entity and comply with all HIPPA regulations. To protect against and 
minimize potential risks, participants will be carefully screened and evaluated for eligibility by 
research coordinator. 
 
To avoid or minimize symptoms of fatigue, agitation, or emotional distress due to testing, 
participants will be instructed to notify the rater or interventionist if they experience any 
discomfort. They will also be periodically questioned about their tolerance for the 
tests/intervention. Testing and interviews will be terminated if participants develop fatigue, 
agitation, or emotional distress.  
 
An ID number will be assigned to each participant. All data collected from a participant will be 
labeled with the ID number. All participant electronic and hard-copy data will be kept under 
double-lock protection. All hard copy forms that contain personal identifiers (e.g., name, 
address, phone numbers) will be stored in a separate locked file drawer under double-lock 
protection. No publication or presentation of the study data will uniquely identify or provide 
sufficient information to uniquely identify participants. 
 

13 
 
Risks during the home visit will be minimized by having licensed and trained interventionists 
available to monitor safety during intervention.  
 
To guard against unauthorized data access, all shared-use computer systems at the lab are 
protected with passwords, which are changed at 4-month intervals. Only individuals with a 
particular "need to know" status are given access, and system privileges are carefully restricted. 
All personal computers to be used in the Administrative Unit are located within a secure area, 
and the system is locked when not in use. SPSS software packages will be used for data 
management and analysis. Datasets generated from these programs will not contain any HIPPA 
data.  
 
Data will be entered into a REDCap database. REDCap servers are securely housed in an onsite, 
limited-access data center managed by the Wayne State University IT. All data are stored on a 
private, firewall protected network. All users are given individual user IDs and passwords, and 
their access is restricted on a role-specific basis. REDCap was developed specifically around 
Health Insurance Portability and Accountability Act security guidelines and is implemented and 
maintained according to Washington University guidelines. Study data will be collected via 
tablet in the field and managed using REDCap electronic data-capture tools hosted at 
Washington University. REDCap is a secure, Web-based application designed to support data 
capture for research studies.  
 
3.4 Adverse events  
• What is an adverse event?  
An adverse event is any reaction, side effect or untoward event that occurs 
during the course of the study. Adverse events are categorized as serious (see 
below) or non-serious, as related or not related to the study intervention, and as 
expected or unexpected.  For the purpose of the present trial, clinically insignificant 
events will be excluded from any type of AE documentation. These include colds, flu, 
cuts, scrapes, coughs, headaches, stomach complaints, general fatigue and mild 
symptoms. Behavioral AEs that will be tracked in this trial include increases in 
emotional distress and problems managing everyday activities (functional changes). 
Serious adverse events (SAEs) are defined as deaths, life-threatening events, 
permanently or substantially disabling events, congenital anomalies, events 
requiring an initial hospitalization or prolonging a current hospitalization, or events 
that require intervention to prevent permanent impairment or damage. SAEs in this 
trial could include inpatient hospitalization for cardiovascular or other cardio-
metabolic disease related problems. 
• In the visit, if there is an SAE that is emergent, call 911.  
• Document AE in rater’s log in Redcap.  
• Notify Study coordinator immediately if there is an AE or SAE.  
 

14 
 
 References 
1. Fried, L. P., Tangen, C. M., Walston, J., Newman, A. B., Hirsch, C., Gottdiener, J., ... & 
McBurnie, M. A. (2001). Frailty in older adults evidence for a phenotype. The Journals of 
Gerontology Series A: Biological Sciences and Medical Sciences, 56(3), M146-M157. 
2. Bandeen-Roche, K., Xue, Q. L., Ferrucci, L., Walston, J., Guralnik, J. M., Chaves, P., ... & 
Fried, L. P. (2006). Phenotype of frailty: characterization in the women's health and 
aging studies. The Journals of Gerontology Series A: Biological Sciences and Medical 
Sciences, 61(3), 262-266.  
3. Song, X., Mitnitski, A., & Rockwood, K. (2010). Prevalence and 10-Year Outcomes of 
Frailty in Older Adults in Relation to Deficit Accumulation. Journal of the American 
Geriatrics Society, 58(4), 681-687.  
4. Shamliyan, T., Talley, K. M., Ramakrishnan, R., & Kane, R. L. (2013). Association of frailty 
with survival: a systematic literature review. Ageing research reviews, 12(2), 719-736. 
5. Gill, T. M., Gahbauer, E. A., Allore, H. G., & Han, L. (2006). Transitions between frailty 
states among community-living older persons. Archives of internal medicine, 166(4), 
418-423. 
6. Bergman, H., Ferrucci, L., Guralnik, J., Hogan, D. B., Hummel, S., Karunananthan, S., & 
Wolfson, C. (2007). Frailty: an emerging research and clinical paradigm—issues and 
controversies. The Journals of Gerontology Series A: Biological Sciences and Medical 
Sciences, 62(7), 731-737. 
7. Rockwood, K., Howlett, S. E., MacKnight, C., Beattie, B. L., Bergman, H., Hébert, R., ... & 
McDowell, I. (2004). Prevalence, attributes, and outcomes of fitness and frailty in 
community-dwelling older adults: report from the Canadian study of health and 
aging. The Journals of Gerontology Series A: Biological Sciences and Medical 
Sciences, 59(12), 1310-1317. 
8. Ensrud, K. E., Ewing, S. K., Taylor, B. C., Fink, H. A., Stone, K. L., Cauley, J. A., ... & Study of 
Osteoporotic Fractures Research Group. (2007). Frailty and risk of falls, fracture, and 
mortality in older women: the study of osteoporotic fractures. The Journals of 
Gerontology Series A: Biological Sciences and Medical Sciences, 62(7), 744-751. 
9. Bandeen-Roche, K., Seplaki, C. L., Huang, J., Buta, B., Kalyani, R. R., Varadhan, R., ... & 
Kasper, J. D. (2015). Frailty in older adults: a nationally representative profile in the 
United States. The Journals of Gerontology Series A: Biological Sciences and Medical 
Sciences, 70(11), 1427-1434. 
10. Hirsch, C., Anderson, M. L., Newman, A., Kop, W., Jackson, S., Gottdiener, J., ... & 
Cardiovascular Health Study Research Group. (2006). The association of race with frailty: 
the cardiovascular health study. Annals of epidemiology, 16(7), 545-553.  
11. Hayward, M. D., Miles, T. P., Crimmins, E. M., & Yang, Y. (2000). The significance of 
socioeconomic status in explaining the racial gap in chronic health conditions. American 
sociological review, 910-930. 
12. August, K. J., & Billimek, J. (2016). A theoretical model of how neighborhood factors 
contribute to medication nonadherence among disadvantaged chronically ill 
adults. Journal of Health Psychology, 21(12), 2923-2933.   
13. Johnson, B. L., & Coulberson, S. L. (1993). Environmental epidemiologic issues and 
minority health. Annals of Epidemiology, 3(2), 175-180. 

15 
 
14. Zilioli, S., Slatcher, R. B., Fritz, H., Booza, J. C., & Cutchin, M. P. (2017). Brief report: 
Neighborhood disadvantage and hair cortisol among older urban African Americans. 
Psychoneuroendocrinology, 80, 36-
38. http://dx.doi.org/10.1016/j.psyneuen.2017.02.026 
15. Fritz, H., & Cutchin, M. P. (2017). Changing neighborhoods and occupations: Experiences 
of older African-Americans in Detroit. Journal of Occupational Science, 24, 
doi:10.1080/14427591.2016.1269296 
16. Arias E. United States life tables. Natl Vital Stat Rep 2004. 2007;56:1–39. 
17. Bibbins-Domingo, K., Pletcher, M. J., Lin, F., Vittinghoff, E., Gardin, J. M., Arynchyn, A., ... 
& Hulley, S. B. (2009). Racial differences in incident heart failure among young 
adults. New England Journal of Medicine, 360(12), 1179-1190. 
18. Miller, D. K., Wolinsky, F. D., Malmstrom, T. K., Andresen, E. M., & Miller, J. P. (2005). 
Inner city, middle-aged African Americans have excess frank and subclinical 
disability. The Journals of Gerontology Series A: Biological Sciences and Medical 
Sciences, 60(2), 207-212. 
19. Minority Health: Recent Findings (2013). Agency for Healthcare Research and Quality, 
Rockville, MD. 
http://www.ahrq.gov/research/findings/factsheet/minorityfind/index.html 
20. Mendes de Leon, C. F., Barnes, L. L., Bienias, J. L., Skarupski, K. A., & Evans, D. A. (2005). 
Racial disparities in disability: recent evidence from self-reported and performance-
based disability measures in a population-based study of older adults. The Journals of 
Gerontology Series B: Psychological Sciences and Social Sciences, 60(5), S263-S271. 
21. Rooks, R. N., & Whitfield, K. E. (2004). Health disparities among older African Americans: 
Past, present, and future perspectives. Closing the gap: Improving the health of minority 
elders in the new millennium, 45-54. 
22. Song, X., Mitnitski, A., & Rockwood, K. (2010). Prevalence and 10-Year Outcomes of 
Frailty in Older Adults in Relation to Deficit Accumulation. Journal of the American 
Geriatrics Society, 58(4), 681-687. 
23. Espinoza, S. E., Jung, I., & Hazuda, H. (2012). Frailty transitions in the San Antonio 
longitudinal study of aging. Journal of the American Geriatrics Society, 60(4), 652-660. 
24. Kojima, G., Taniguchi, Y., Iliffe, S., Jivraj, S., & Walters, K. (2019). Transitions between 
frailty states among community-dwelling older people: a systematic review and meta-
analysis. Ageing research reviews.  
25. Herr, M., Arvieu, J. J., Ankri, J., & Robine, J. M. (2018). What is the duration of life 
expectancy in the state of frailty? Estimates in the SIPAF study. European journal of 
ageing, 15(2), 165-173. 
26. Bosaeus, I., & Rothenberg, E. (2016). Nutrition and physical activity for the prevention 
and treatment of age-related sarcopenia. Proceedings of the Nutrition Society, 75(2), 
174-180. 
27. Cruz-Jentoft, A. J., Landi, F., Schneider, S. M., Zúñiga, C., Arai, H., Boirie, Y., ... & Sieber, 
C. (2014). Prevalence of and interventions for sarcopenia in ageing adults: a systematic 
review. Report of the International Sarcopenia Initiative (EWGSOP and IWGS). Age and 
ageing, 43(6), 748-759. 

16 
 
28. Glover, E. I., Phillips, S. M., Oates, B. R., Tang, J. E., Tarnopolsky, M. A., Selby, A., ... & 
Rennie, M. J. (2008). Immobilization induces anabolic resistance in human myofibrillar 
protein synthesis with low and high dose amino acid infusion. The Journal of 
physiology, 586(24), 6049-6061. 
29. Bowen, T. S., Schuler, G., & Adams, V. (2015). Skeletal muscle wasting in cachexia and 
sarcopenia: molecular pathophysiology and impact of exercise training. Journal of 
cachexia, sarcopenia and muscle, 6(3), 197-207. 
30. Fanning, J., Rejeski, W. J., Chen, S. H., Nicklas, B. J., Walkup, M. P., Axtell, R. S., ... & 
McDermott, M. M. (2019). A Case for Promoting Movement Medicine: Preventing 
Disability in the LIFE Randomized Controlled Trial. The Journals of Gerontology: Series A. 
31. Denison, H. J., Cooper, C., Sayer, A. A., & Robinson, S. M. (2015). Prevention and optimal 
management of sarcopenia: a review of combined exercise and nutrition interventions 
to improve muscle outcomes in older people. Clinical interventions in aging, 10, 859 
32. Cermak, N. M., de Groot, L. C., Saris, W. H., & van Loon, L. J. (2012). Protein 
supplementation augments the adaptive response of skeletal muscle to resistance-type 
exercise training: a meta-analysis. The American journal of clinical nutrition, 96(6), 1454-
1464.  
33. Finger, D., Goltz, F. R., Umpierre, D., Meyer, E., Rosa, L. H. T., & Schneider, C. D. (2015). 
Effects of protein supplementation in older adults undergoing resistance training: a 
systematic review and meta-analysis. Sports medicine, 45(2), 245-255. 
34. Beaudart, C., Dawson, A., Shaw, S. C., Harvey, N. C., Kanis, J. A., Binkley, N., ... & Rizzoli, 
R. (2017). Nutrition and physical activity in the prevention and treatment of sarcopenia: 
systematic review. Osteoporosis international, 28(6), 1817-1833. 
35. Denison, H. J., Cooper, C., Sayer, A. A., & Robinson, S. M. (2015). Prevention and optimal 
management of sarcopenia: a review of combined exercise and nutrition interventions 
to improve muscle outcomes in older people. Clinical interventions in aging, 10, 859. 
36. Levine, M. E., & Crimmins, E. M. (2014). Evidence of accelerated aging among African 
Americans and its implications for mortality. Social Science & Medicine, 118, 27-32. 
http://doi.org/10.1016/j.socscimed.2014.07.022 
37. Fritz, H., Cutchin, M. P., & Cummins, E. R. (2018). Loss of trust in the neighborhood: The 
experience of older African Americans in Detroit. Journals of Gerontology, Series B: 
Psychological Sciences and Social Sciences. 
38. Gwyther, H., Bobrowicz-Campos, E., Luis Alves Apóstolo, J., Marcucci, M., Cano, A., & 
Holland, C. (2018). A realist review to understand the efficacy and outcomes of 
interventions designed to minimise, reverse or prevent the progression of frailty. Health 
psychology review, 12(4), 382-404. 
39. Dedeyne, L., Deschodt, M., Verschueren, S., Tournoy, J., & Gielen, E. (2017). Effects of 
multi-domain interventions in (pre) frail elderly on frailty, functional, and cognitive 
status: a systematic review. Clinical interventions in aging, 12, 873.Middleton, K. R., 
Anton, S. D., & Perri, M. G. (2013). Long-term adherence to health behavior 
change. American journal of lifestyle medicine, 7(6), 395-404. 
40. Apóstolo, J., Cooke, R., Bobrowicz-Campos, E., Santana, S., Marcucci, M., Cano, A., ... & 
Holland, C. (2018). Effectiveness of interventions to prevent pre-frailty and frailty 

17 
 
progression in older adults: a systematic review. JBI database of systematic reviews and 
implementation reports, 16(1), 140. 
41. Kehler, D. S., Hay, J. L., Stammers, A. N., Hamm, N. C., Kimber, D. E., Schultz, A. S., ... & 
Duhamel, T. A. (2018). A systematic review of the association between sedentary 
behaviors with frailty. Experimental gerontology. 
42. Ekelund, U., Steene-Johannessen, J., Brown, W. J., Fagerland, M. W., Owen, N., Powell, 
K. E., ... & Lancet Sedentary Behaviour Working Group. (2016). Does physical activity 
attenuate, or even eliminate, the detrimental association of sitting time with mortality? 
A harmonised meta-analysis of data from more than 1 million men and women. The 
Lancet, 388(10051), 1302-1310. 
43. Nilsen, W. J., Haverkos, L., Nebeling, L., & Taylor, M. V. (2010). Maintenance of long-
term behavior change. American journal of health behavior, 34(6), 643-646. 
44. Noar, S. M., & Zimmerman, R. S. (2005). Health Behavior Theory and cumulative 
knowledge regarding health behaviors: are we moving in the right direction?. Health 
education research, 20(3), 275-290. 
45. Soysal, P., Veronese, N., Thompson, T., Kahl, K. G., Fernandes, B. S., Prina, A. M., ... & 
Lin, P. Y. (2017). Relationship between depression and frailty in older adults: A 
systematic review and meta-analysis. Ageing research reviews, 36, 78-87. 
46. Arai, H., Satake, S., & Kozaki, K. (2018). Cognitive Frailty in Geriatrics. Clinics in geriatric 
medicine, 34(4), 667-675. 
47. Brown, M. T., & Bussell, J. K. (2011, April). Medication adherence: WHO cares?. In Mayo 
clinic proceedings (Vol. 86, No. 4, pp. 304-314). Elsevier. 
48. Shah, K., Hilton, T. N., Myers, L., Pinto, J. F., Luque, A. E., & Hall, W. J. (2012). A new 
frailty syndrome: central obesity and frailty in older adults with the human 
immunodeficiency virus. Journal of the American Geriatrics Society, 60(3), 545-549. 
49. Ferrucci, L., & Fabbri, E. (2018). Inflammageing: chronic inflammation in ageing, 
cardiovascular disease, and frailty. Nature Reviews Cardiology, 1. 
50. Morante, J. J. H., Martínez, C. G., & Morillas-Ruiz, J. M. (2019). Dietary Factors 
Associated with Frailty in Old Adults: A Review of Nutritional Interventions to Prevent 
Frailty Development. Nutrients, 11(1), 102. 
51. Mañas, A., del Pozo-Cruz, B., Guadalupe-Grau, A., Marín-Puyalto, J., Alfaro-Acha, A., 
Rodríguez-Mañas, L., ... & Ara, I. (2018). Reallocating accelerometer-assessed sedentary 
time to light or moderate-to vigorous-intensity physical activity reduces frailty levels in 
older adults: an isotemporal substitution approach in the TSHA study. Journal of the 
American Medical Directors Association, 19(2), 185-e1. 
52. Cohen, Sarah S., Charles E. Matthews, Lisa B. Signorello, David G. Schlundt, William J. 
Blot, and Maciej S. Buchowski. "Sedentary and physically active behavior patterns 
among low-income African-American and white adults living in the southeastern United 
States." PloS one 8, no. 4 (2013): e59975. 
53. Evans, J. S. B. (2008). Dual-processing accounts of reasoning, judgment, and social 
cognition. Annu. Rev. Psychol., 59, 255-278. 
54. Gardner, B. (2014). A review and analysis of the use of ‘habit’ in understanding, 
predicting, and influencing health-related behavior. Health Psychology Review, 1–19, 
doi: 10.1080/17437199.2013.876238 

18 
 
55. Orbell, S., & Verplanken, B. (2010). The automatic component of habit in health 
behavior: Habit as cue-contingent automaticity. Health Psychology, 29(4), 374–383. 
doi:10.1037/a0019596  
56. Gardner, B., Abraham, C., Lally, P., & de Bruijn, G. (2012). Towards parsimony in habit 
measurement: Testing the convergent and predictive validity of an automaticity 
subscale of the self-report habit index. International Journal of Behavioral Nutrition and 
Physical Activity, 9(1), 102–102. doi:10.1186/1479-5868-9-102 
57. Wood, W., Tam, L., & Guerrero, M. (2005). Changing circumstances, disrupting habits. 
Journal of Personality and Social Psychology, 88(6), 918–933. doi: 10.1037/0022-
3514.88.6.918 
58. Pimm, R., Vandelanotte, C., Rhodes, R. E., Short, C., Duncan, M., & Rebar, A. (2015). Cue 
consistency associated with physical activity automaticity and behavior. Behavioral 
Medicine. doi:10.1080/08964289.2015.1017549 
59. Verplanken, B., Walker, I., Davis, A., & Jurasek, M. (2008). Context change and travel 
mode choice: Combining the habit discontinuity and self-activation hypotheses. Journal 
of Environmental Psychology, 28(2), 121–127. doi:10.1016/j.jenvp.2007.10.005 
60. Verplanken, B., & Wood, W. (2006). Interventions to break and create consumer habits. 
American Marketing Association, 25(1), 90–103. doi:10.1509/jppm.25.1.9 
61. Gollwitzer, P. M. (1999). Implementation intentions: Strong effects of simple 
plans. American Psychologist, 54, 493–503. doi:10.1037/0003-066X.54.7.493 
62. Adriaanse, M. A., Gollwitzer, P. M., De Ridder, D. T., de Wit, J. B., & Kroese, F. M. (2011). 
Breaking habits with implementation intentions: A test of underlying processes. 
Personality and Social Psychology Bulletin, 37(4), 502–513. 
doi:10.1177/0146167211399102 
63. Lally, P., Chipperfield, A., & Wardle, J. (2008). Healthy habits: efficacy of simple advice 
on weight control based on a habit-formation model. International Journal of Obesity, 
32(4), 700–707. doi: 10.1038/sj.ijo.0803771 
64. McGowan, L., Cooke, L., Gardner, B., Beeken, R., Croker, H., Wardle, J. (2013). Healthy 
feeding habits: Efficacy results from a cluster-randomized, controlled exploratory trial of 
a novel, habit-based intervention with parents. American Journal of Clinical Nutrition, 
98, 769–777. doi: 10.3945/ajcn.112.052159  
65. Mullan, B., Allom, V., Fayn, K., & Johnston, I. (2014). Building habit strength: A pilot 
intervention designed to improve food-safety behavior. Food Research International, 66, 
274–278. doi:10.1016/j.foodres.2014.09.027 
66. Hanlon, P., Nicholl, B. I., Jani, B. D., Lee, D., McQueenie, R., & Mair, F. S. (2018). 
Frailty and pre-frailty in middle-aged and older adults and its association with 
multimorbidity and mortality: a prospective analysis of 493 737 UK Biobank 
participants. The Lancet Public Health, 3(7), e323-e332. 
67. Abdel-Aziz, K., & Larner, A. J. (2015). Six-item cognitive impairment test (6CIT): 
pragmatic diagnostic accuracy study for dementia and MCI. International 
psychogeriatrics, 27(6), 991-997. 
68. Upadhyaya, A., Rajagopal, M., & M Gale, T. (2010). The six item cognitive impairment 
test (6-CIT) as a screening test for dementia: comparison with mini-mental state 
examination (MMSE). Current aging science, 3(2), 138-142.