A Culturally Adapted, Social Support-Based, Physical Activity Interventions for South Asian Indian Women in the United States: A Feasibility Study
Phase: NA
Conditions: Sedentary Behavior
Sponsor: The University of Texas Health Science Center, Houston

1 
IRB NUMBER: HSC-SN-23-0576 
IRB APPROVAL DATE: 02/15/2024 
 
 
 
 
 
 
 
 
 
 
 
A Culturally Adapted, Social Support-Based, Physical Activity Interventions for South 
Asian Indian Women in the United States: A Feasibility Study 
 
NCT05966506 
 
Version Date: 02/15/2024 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

2 
IRB NUMBER: HSC-SN-23-0576 
IRB APPROVAL DATE: 02/15/2024 
 
 
Protocol Title: A Culturally Adapted, Social Support-Based, Physical Activity Interventions 
for South Asian Indian Women in the United States: A Feasibility Study 
 
Principal Investigator: Nitha Mathew Joseph, PhD, RN, CNE 
 
Co-Investigators: Larkin Strong, PhD, MPH 
 
Study Coordinator: Sheeba John (Graduate Research Assistant) 
 
Health Coach: Sara Lewandowski, DNP, MS, BA, BS, RN, CNE, HNB-BC, NC-BC, RYT 
 
Population: Participants will be 10 dyads of South Asian Indian (SAI) women aged 40-65 years 
living in Houston, Texas; insufficiently active (Physical activity (PA) <150 minutes/week); 
physically able to engage in moderate PA; and Blood pressure reading <160/100 mm Hg, or with 
medical clearance. 
 
Number of Sites:South Asian Indian Churches/faith organizations and community organizations 
 
Study Duration: one year 
 
Subject Duration: Three months 
 
 
General Information (Abstract) 
South Asian Indians (SAIs) are diverse and come from different cultures, backgrounds, 
immigration histories, geographic regions, and experiences. Despite being the fastest growing 
ethnic/racial group in the U.S., Asian Americans have not been a focal group of scientific interest 
in psychological research and high-impact medical research studies, with only 0.17% of National 
Institutes of Health (NIH) expenditures allocated to projects since 1992. Most importantly, SAIs 
disproportionately experiences cardiometabolic health disparities, including a high prevalence of 
type 2 diabetes (T2D) and increased mortality from atherosclerotic cardiovascular disease (CVD) 
compared to non-Hispanic, White and other Asian American groups, despite having a lower 
body mass index (BMI) than other racial/ethnic minority groups. The objective of the proposed 
research is to adapt and evaluate a dyadic social support intervention to increase PA in SAI 
women. Social support, self-efficacy and behavioral skills are recognized correlates of PA across 
racially, ethnically, and socioeconomically diverse populations. Nonetheless, research is needed 
to better understand the most effective approaches for delivering social support interventions to 
increase PA in SAI women. The proposed research is able to leverage the knowledge and 
infrastructure from two ongoing studies of this research team, one involving qualitative focus 
groups with SAI women regarding barriers and facilitators to PA including the role of social 
support, and a large R01 efficacy trial testing a dyadic health coaching PA intervention in 
inactive Hispanic and African American women) in Houston, TX. Women will enroll with an 
eligible partner of their choosing (e.g., family member, friend). The intervention will consist of 6 
dyad-based health coaching sessions, a Fitbit device for women to monitor their own and their 
partners’ PA, and 6 electronic newsletters with PA-related health education.  The health 
coaching will be delivered over Zoom by a certified holistic nurse using a motivational 

3 
IRB NUMBER: HSC-SN-23-0576 
IRB APPROVAL DATE: 02/15/2024 
 
 
interviewing approach to promote social support between dyad members as they practice how to 
be supportive partners. Participants will be recruited by leveraging the PI’s relationships with 
community- and faith-based organizations, through advertisement flyers, on-site recruitment, 
presentations during/before church services, social media, email list-serves, local SAI 
newspapers, health fairs, and health screenings targeting SAIs in Houston. Participants will be 
eligible for inclusion in the study if they satisfy all the inclusion criteria including inactive SAI 
women aged 40-65 years living in Houston, Texas. Participants will be assessed at baseline and 
immediately post-intervention. Physical activity will be assessed using self-reported and 
objective measures. Detailed screening log and record consent rates including refusal reasons, 
retention rates including attrition reasons, and completion of questionnaires will be tracked. We 
will also monitor session attendance, and participants will complete brief, open-ended 
evaluations of their overall satisfaction of the program at the follow up to determine intervention 
acceptability. 
 
 
Background and Significance 
 
Asian Indians from the Indian subcontinent are at high risk for CVD and type 2 diabetes (T2D). 
Asian Indian immigrants are at greater risk for morbidity and mortality from these chronic 
diseases compared with whites and other immigrant groups in the U. S.1-5. Central obesity 
(accumulation of abdominal fat) is a significant risk factor for CVD, T2D and metabolic 
syndrome in Asian Indians, despite the fact that they have an average lower body mass index 
(BMI) than Whites6. Morbidity and mortality from CVD and T2D are higher in people of Asian 
Indian descent who live in the U.S. than those who reside in India7 due to the metabolic impact 
of a westernized diet, sedentary lifestyle and unhealthy dietary habits. 8 Importantly, SAIs 
experience cardiometabolic health disparities, including a high prevalence of type 2 diabetes 
(T2D) and increased mortality from atherosclerotic cardiovascular disease (CVD) 
disproportionately compared to non-Hispanic, White and other Asian American groups, despite 
having a lower body mass index (BMI). 9-17 In addition, clinical consequences such as 
myocardial infarction and stroke tend to appear at an earlier age in this group than in any other 
ethnical/racial groups18-20.The prevalence of diabetes among first generation Asian Indian 
immigrants is estimated to be two-to three-fold higher than in the general US population.2 
Moreover, risk factors are present in Asian Indians at a younger age compared to other 
populations, resulting in coronary artery disease at a younger age.21 Because Asian Indians are 
one of the fastest growing populations, the population-attributable risk of these conditions is 
expected to increase over time. Asian Indians are the second largest Asian American group (4.6 
million) after Chinese Americans (5.4 million) with a much faster growth rate.22 Regular PA is 
essential for reducing the risk factors for CVD23, T2D24, obesity and metabolic syndrome25. 
Studies conducted in the U.S. and other western countries have shown a reduced level of PA 
among Asian Indians26-31 and thus, increased risk for CVD, T2D and metabolic syndrome5,8,31-33 
in this population. 
 
The major precursor to T2DM is abdominal obesity, which is associated with the most dangerous 
risk factors for CVD events and premature deaths in Asian Indians, e.g., insulin resistance, high 
cholesterol, and hypertension (HTN)4,34.In the Diabetes Prevention Program (DPP),35 moderate 
physical activity, i.e., ≥150 minutes per week of activity similar in intensity to brisk walking, and 

4 
IRB NUMBER: HSC-SN-23-0576 
IRB APPROVAL DATE: 02/15/2024 
 
 
losing a minimum of 7% of body weight through reduced caloric intake resulted in the largest 
reduction in diabetes risk (58%) in persons with impaired glucose tolerance (IGT). These 
findings were consistent across other ethnic groups, both genders, and all age groups. In other 
ethnic groups, small weight reductions (7%−10%) enhance insulin sensitivity and glycemic 
control and: (1) may reduce the need for medications in those diagnosed with T2DM or delay 
diabetes onset in those who are at high risk but not yet diagnosed. 
 
Asian Indians are significantly different from the average values of body mass index for the 
world. World Health organization (WHO) modified BMI criteria for Asians as having normal 
weight (BMI of less than 23(BMI ≥23 kg/m2) as compared with normal WHO criteria (BMI ≥25 
kg/m2)36 because of the additional fat content, and a difference of fat distribution on the body in 
Asians and thus increasing tendency toward metabolic syndrome37. Recent study findings on the 
causality link between BMI and T2D, postulated that obesity may be involved in the etiology of 
T2D through interaction with ethnic-specific genetic factors in Asian Indians as compared other 
Asian subgroups37and other related complications at a much early age38. Most importantly, 60% 
of the world’s diabetic population is Asians39. Moreover, Centers for Disease Control and 
Prevention (CDC) identified south Asian subgroups are at higher risk for diabetes and also 
changed the criteria of screening for T2D as Asian heritage with a BMI of 23 should be tested for 
type 2 diabetes40,41. 
 
Gender influences levels of PA. Worldwide data of PA levels for adults confirm that women are 
generally less physically active than men. 29 A national survey indicated that women had a higher 
percentage of inactivity (22% to 47%) than men (14% to 32%).30 With advancing age, women 
are less likely to participate in PA. PA is unusually low in this at-risk population11,32-34 Studies 
conducted in the U.S. and other western countries have shown a reduced level of PA among 
Asian Indians.4 ,24-26 It is also found that lower levels of PA are also associated with the 
development of diabetes, coronary artery disease,7, 27- 28 and metabolic syndrome in Asian Indian 
women.18 The high prevalence of chronic disease in Asian Indian women and their low PA level 
emphasize the need for developing culturally sensitive interventions that promote regular PA in 
these at-risk minority women. 
 
Low PA among Asian Indian women is rooted in cultural factors that are unique to this 
population. Promoting PA among Asian Indian women poses a particular challenge, as the 
barriers to recreational PA may be culturally derived.42-45 Presumably, Asian Indian women 
participate in less PA and recreational exercise than other women owing to the cultural barriers 
of religious modesty, avoidance of mixed-gender activities, fear of going outside alone and thus 
PA remains a function relegated to normal daily duties rather than for enjoyment.43,46,47 
Furthermore, Asian Indian women come from a patriarchal and collectivistic society and bear the 
responsibility of holding, teaching, and transmitting cultural traditions, values, and beliefs to 
their families48,49. Findings from a study in the U.K. showed that Asian Indian women were 
under considerable physical demands, including caregiving, housekeeping, and workday 
activities. This, in turn, resulted in less supplemental time for exercise, and activities such as 
aerobics classes were not seen as an acceptable part of family duties. The notion of exercise for 
oneself beyond daily work was perceived by some as a selfish activity or given little priority in 
the context of family and community expectations and needs.47 Moreover, acculturation among 
Asian Indian women does not necessarily lead to greater PA, as is seen in other ethnic groups. 

5 
IRB NUMBER: HSC-SN-23-0576 
IRB APPROVAL DATE: 02/15/2024 
 
 
Earlier research by the PI found that lower levels of leisure time PA that were well below the 
recommended weekly exercise level in this at-risk population. Furthermore, the PI’s secondary 
analysis of data from a national sample of Asian Indians showed that PA mediated the 
relationship between acculturation and cardiovascular risk factors.8 in both in Asian Indian men 
and women. 
 
Physical inactivity and increased sedentary time are major risk factors for obesity, CVD and T2D 
and are important contributors to preventable morbidity and mortality. Studies conducted in the 
U.S. show a reduced level of physical activity (PA) among SAIs, and that lower levels of PA are 
associated with T2D in SAI women in particular. These findings underscore the importance of 
developing culturally sensitive interventions to promote regular PA in these at-risk minority 
women. As a SAI woman and nurse researcher, PI understands that low PA among SAI women 
can be rooted in cultural and social factors that are unique to our population. Moreover, 
acculturation among SAI women does not necessarily lead to greater PA, as seen in other ethnic 
groups. In our previous study from a national sample of SAIs, PA mediated the relationship 
between acculturation and CVD risk factors in SAI women, suggesting an important role for 
community health care providers to improve the PA of SAI women in the U.S. 
 
Social Environments and PA. Social environments are widely recognized to have an important 
impact on critical health behaviors.50-53 Individuals are embedded within social networks, 
creating spheres of influence. Decisions about and participation in PA often involve other social 
network members, producing opportunities for behavioral impact, both positive and negative. 
Social support for PA, conceptualized as encouragement to be active, actions taken by others that 
facilitate being active, and having someone with whom to engage in PA, is positively associated 
with PA across racially, ethnically, and socioeconomically diverse groups of women.53-57 
Research has also shown that PA is heavily associated with social and cultural norms,54,58-61 such 
as gender role expectations and cultural appropriateness of PA in adult women. Moreover, the 
potentially influential role of friends is illustrated by the finding that having a close friend who 
becomes obese increases an individual’s chances of becoming obese by 57% within the same 
time period.62 These findings underscore the notion that individuals’ behaviors are strongly 
influenced by the actions and beliefs of others around them, pointing to social environments as 
an important lever for behavior change. 
Despite this recognition, few studies intervene on the social contexts in which these behaviors 
occur.63,64 Most interventions remain focused on individuals. Although empirical evidence 
supports the efficacy of individually focused strategies that address key behavior change 
constructs (e.g., goal setting, self-monitoring), effects tend to be short-lived and maintenance is 
poor.63,65-69 Studies of racially/ethnically diverse women provide support for the potential appeal 
of approaches that involve existing members of one’s social network. These studies report that 
women desire encouragement and support for PA from important people in their lives; that they 
seek to exercise with others; that tangible support in the form of direct help or assistance can 
facilitate engagement in PA activities; and that seeing others in their communities and their 
social networks be active is important to feeling comfortable and confident about 
exercising.53,54,56,69-72 Although some interventions aim to create social support for PA by 
bringing unconnected individuals together, research indicates that support tends to diminish upon 
the conclusion of the intervention.73 This highlights a potentially unique and critical contribution 
of intervention approaches designed to enhance support within women’s existing social networks 

6 
IRB NUMBER: HSC-SN-23-0576 
IRB APPROVAL DATE: 02/15/2024 
 
 
OUTCOME MEASURES (a.k.a. ENDPOINTS), 
with TIMEPOINTS for each 
OBJECTIVES 
to promote health behavior change. 
Social support, self-efficacy and behavioral skills are recognized correlates of PA across racially, 
ethnically, and socioeconomically diverse populations. However, research is still needed to better 
understand the most effective channel(s) for delivering social support interventions to increase 
PA in SAI women. Research is also needed to determine whether and how dyadic behavioral 
interventions can create supportive interpersonal environments to yield greater increases in 
PA in sedentary SAI women. 
 
Objectives and Outcome Measures 
 
The objective of the proposed research is to adapt and evaluate a peer based dyadic social 
support health coaching PA intervention to increase PA in SAI women. Social support, self- 
efficacy and behavioral skills are recognized correlates of PA across racially, ethnically, and 
socioeconomically diverse populations74-78 and motivational interviewing can enhance lifestyle 
behavioral change79,80. Nonetheless, research is needed to better understand the most effective 
approaches for delivering social support interventions to increase PA in SAI women. The 
proposed research is able to leverage the knowledge and infrastructure from two ongoing studies 
of this research team, one involving qualitative focus groups with SAI women regarding barriers 
and facilitators to PA including the role of social support, and a large R01 efficacy trial testing a 
peer based dyadic social support health coaching PA intervention in inactive Hispanic and 
African American women. 
 
Hypothesis: We hypothesize that this innovative culturally adapted, social support-based 
intervention will be feasible and acceptable among sedentary population of SAI women in the 
U.S. 
Specific Aims: This project is built on evidence that peer-based social support, motivational 
interviewing, and mobile technologies can be utilized to strengthen self-efficacy and social 
supports to promote increased PA in minority women. This study is able to leverage two ongoing 
studies, one that involves qualitative focus group research specifically with SAI women 
regarding barriers and facilitators to PA, and a large R01(R01HL155310) efficacy trial testing a 
dyadic health coaching intervention in inactive Hispanic and African American women. 
Aims are: 1) Assess the feasibility of recruitment, retention outcomes, intervention engagement 
(i.e., number of counseling sessions completed, use of Fitbit, review of newsletters), and 
completion of study procedures in a preliminary group of a social network-based 12-week dyadic 
behavioral PA intervention in sedentary SAI women. 2) Explore preliminary effects of receiving 
the intervention on intermediate outcomes: self-reported and objective moderate-to-vigorous 
physical activity (MVPA), social support, and self-efficacy at 12 weeks. 
 
 
 
 
 

7 
IRB NUMBER: HSC-SN-23-0576 
IRB APPROVAL DATE: 02/15/2024 
 
 
 
Primary 
Assess the feasibility of 
recruitment, retention 
outcomes, intervention 
engagement (i.e., number of 
counseling sessions completed, 
use of Fitbit, review of 
newsletters), and completion of 
study procedures in a 
preliminary group of a social 
network-based 12-week dyadic 
behavioral PA intervention in 
sedentary SAI women 
The feasibility of the intervention will be determined 
by comparing the percentages for overall recruitment 
and retention at week 12 to their target values of 80% 
and 70%, respectively. 
A secondary feasibility assessment will determine the 
proportion of intervention participants who take part in 
each of the intervention components (i.e., number of 
counseling calls completed, use of Fitbit, receipt and 
review of newsletters). 
In addition, every attempt will be made to query 
subjects lost to follow-up to ascertain the reason for 
drop out or barriers to participation. 
Feasibility will be measured by calculating the rates of 
enrollment, retention, assessment completion, and 
treatment adherence. 
The enrollment rate will be the proportion of those 
meeting inclusion criteria that enrolled, while the 
retention rate will be the proportion enrolled that 
complete the study. 
Assessment completion will be calculated as the 
proportion of assigned data collection forms that were 
completed. Treatment adherence will be calculated as 
the proportion of intervention sessions attended. 
Secondary 
Explore preliminary effects of 
receiving the intervention on 
intermediate outcomes: self- 
reported and objective 
moderate-to-vigorous physical 
activity (MVPA), social 
support, and self-efficacy at 12 
weeks. 
Secondary outcome measure(s) should be clearly 
specified, and a timepoint should be listed for each 
secondary outcome measure). 
Secondary outcome measure(s) are those that may 
provide supportive information about the study 
intervention’s effect on the primary outcome measure 
or demonstrate additional effects on the disease or 
condition. 

8 
IRB NUMBER: HSC-SN-23-0576 
IRB APPROVAL DATE: 02/15/2024 
 
 
Study Design 
 
The proposed single-arm pilot study will test the feasibility of recruitment, retention, 
acceptability and implementation of study procedures of a 12-week dyadic behavioral 
intervention to promote positive and sustained change in MVPA, social support, and self- 
efficacy among inactive SAI women in Houston, TX. The intervention will target 10 dyads of 
inactive SAI women and will include dyad-based Zoom coaching delivered by a certified holistic 
nurse coach using a motivational interviewing approach to promote social support between dyad 
members as they practice how to be supportive partners; employing a Fitbit device to monitor 
one’s own and one’s exercise partner’s PA; and dissemination of PA-related health education. 
Study Population and Eligibility 
 
For this study, participants will be SAI women aged 40-65 years living in Houston, Texas; 
insufficiently active (PA<150 minutes/week); physically able to engage in moderate PA; speak 
and read English; able to enroll with an eligible adult female partner who does not live in the 
same household; willing to use the Fitbit app/device; own a smartphone that is compatible with 
Fitbit software (up to 223.3 MB on iPhone or 165 MB on Android) 9); able and willing to send 
and receive text messages; and Blood pressure reading <160/100 mm Hg, or with medical 
clearance. Exclusion criteria include SAI women with a current/planned pregnancy; cannot speak 
and read English, those participating in a PA or weight loss program, and those diagnosed with a 
physical disability that interferes with their ability to be physically active. 
 
Recruitment: To facilitate sustainability, we will pilot this intervention with SAI women 
recruited from religious organizations. Faith is a significant component of many SAIs, and 
churches are an important element of SAI community. The Houston metropolitan area is home to 
many Asian Indian females in a close-knit community. According to the 2020 census data, Texas 
is one of the top three states in the U.S. with the largest number of Asian Indians (n=245,981, 
i.e., 0.9% of 25,145,561)81. The majority of the Asian Indian population resides in Houston 
(1.21% of 2,571,090), Stafford (7.35% of 27,677), Sugar Land (7.20% of 108,607), Missouri 
City (3.4% of 65,701), and surrounding neighborhoods of Houston82. The study will use 
purposive sampling of women who meet the study eligibility criteria. IRB approval will be 
obtained from the Committee for the Protection of Human Subjects (CPHS) at the University of 
Texas Health Science Center at Houston. Study participants will be recruited from Indian 
community churches that the PI used previously to successfully recruit the population of interest 
and we anticipate no challenges to recruiting for this study given previous experience and 
established contacts27,83. Participants also will be recruited through advertisements through flyers 
(Appendix-A) on-site recruitment, presentations during/before church services, email list-serves, 
health fairs, and health screenings targeting Asian Indians in Houston. As the study progresses, 
snowball sampling may be employed in cases where a study participant wishes to recommend 
other Asian Indian women to ensure that the sample is not limited to those who are socially 
engaged and attend religious facilities. 
Trained research staff will screen potentially eligible participants. Screening may be performed 
in person or over the phone. At this time, staff will explain the study, assess interest in 
participation, and for those interested, screen for inclusion/exclusion criteria. Determination of 
preliminary eligibility will be based on participants’ self-reported responses to the screening 

9 
IRB NUMBER: HSC-SN-23-0576 
IRB APPROVAL DATE: 02/15/2024 
 
 
questions (Appendix -B). Participants will be informed that eligibility will be finalized with the 
measurement of blood pressure at the in-person baseline visit. Prospective participants will select 
their study partners. Screening of both dyad members is required prior to enrolling in the study. 
Informed consent (Appendix -C) will be collected from both partipcants and their study partners. 
 
 
 
Data Collection and Study Procedures 
Intervention: The intervention draws from social cognitive theory, self-determination theory, 
and interdependence theory, which informed the individual and interpersonal constructs of 
importance for behavior change within a dyadic context. Intervention components include dyad- 
based Zoom coaching delivered by a certified nurse coach who is certified in holistic nursing 
using a motivational interviewing approach to promote positive communication between dyad 
members as they learn and practice how to be a supportive partner; a Fitbit device to monitor 
one’s own and one’s partner’s PA; and electronic newsletters to disseminate PA-related health 
education. Holistic care in nursing is important to enhance the health of all populations, improve 
preventive care, and reduce treatment costs. Motivational interviewing by a certified holistic 
nurse health coach in a dyad-centered behavioral intervention can create supportive interpersonal 
environments to yield greater increases in PA. If results are meaningful, this nurse-driven 
intervention could be used as a guide for health researchers in areas of preventive research for 
enhancing minority health and ultimately reduce health inequities. 
The goal of the intervention is to increase participants’ PA, working towards meeting national 
PA guidelines for adults that recommend 150 minutes of at least moderate intensity activity per 
week, by building behavioral skills and increased social support through social network dyads. 
The intervention will draw upon Social Cognitive Theory (SCT), a robust framework for 
behavior change that explains behavior within a dynamic and reciprocal model where a person’s 
behavior, personal factors, and the environment continuously interact. The intervention design 
was informed by the literature highlighting the importance of social support and enhanced 
behavioral skills and motivation, while incorporating the use of a mobile app to reflect the new 
ways in which PA-related information can be tracked and how women communicate with social 
network members. The intervention builds off of women’s existing social networks, enrolling 
women as dyads to enhance the social support provided and received. The 12-week intervention 
will focus on behavior change strategies and principles derived from SCT, with a particular 
emphasis on developing skills related to the constructs of self-efficacy, and social support. 
Specific skills that will be targeted include goal setting, self-monitoring, problem solving, and 
drawing upon one’s social networks to both receive, and provide, social support. 
Dyad-based Zoom health coaching: Zoom based coaching is selected because it demonstrates 
more feasibility in diverse populations with busy life schedule and thus it can help people initiate 
PA. Trained holistic nurse health coach will provide 6 sessions of Zoom health coaching over 12 
weeks to dyads, biweekly (weeks 1, 3, 5,7, 9 &11) for 45 minutes, and dyad members do not 
need to be physically together; they can both participate via zoom meeting. Moreover, PI’s 
ongoing qualitative focus group study explores how natural dyads of women can help each other 
to promote greater PA, and in particular, how mobile phone technology can facilitate the 
provision of support for PA within women’s social networks, how women can share information 

10 
IRB NUMBER: HSC-SN-23-0576 
IRB APPROVAL DATE: 02/15/2024 
 
 
within their social networks, how they provide support to one another, as well as potential 
challenges that may arise in an intervention that emphasizes mobile technology to promote PA 
within dyads of women. This component of the intervention will be adapted and modified based 
on the qualitative data collected from the PI’s ongoing focus group study and it is intended to 
help women gain the knowledge and skills needed for behavior change and maintenance, and to 
build women’s capacity to act as sources of support to facilitate PA participation among dyad 
members. Dyad based Zoom coaching will be delivered by a certified nurse coach who is also 
certified in holistic nursing with specific training and experience in motivational interviewing 
(MI). MI is a collaborative, goal-oriented, person-centered approach designed to elicit and 
strengthen autonomous motivation for change.84,85 Consistent with SCT, MI represents an 
orientation or interpersonal style in which the health coach respects the client’s autonomy and 
freedom of choice regarding her own behavior. The primary purpose of the coaching calls will be 
to increase autonomous motivation for positive behavior change and promote self- 
efficacy/competence to make change. Coaching calls will address constructs aligned with the 
guiding theoretical frameworks using established techniques for PA behavior change.86 Zoom 
coaching will focus chronologically on goal-setting, self-monitoring, identification of barriers 
and facilitating factors, social support, and problem solving. The nurse health coach will first 
inquire about participants’ past and present experiences with PA including barriers and 
facilitators to get to know participants, build rapport, and inform future discussions. The nurse 
health coach will explore participants’ personal motivations for PA, identify outcome 
expectancies, and connect motivation for PA with personal values. Participants will work with 
the coach to develop a Wellness Plan that outlines what participants want to work on and will 
serve as a guide throughout the intervention. To promote self-efficacy, nurse health coach will 
work with participants to build key behavioral skills such as self-monitoring of PA with the 
Fitbit, setting incremental and achievable goals to facilitate mastery and competence, and 
problem solving to overcome identified barriers. Each zoom meeting will include discussion 
about progress since the last call, strategies that worked well and those that did not, possible 
modification of participants’ goals, and continued problem solving. During all sessions, the nurse 
health coach will provide positive feedback and reinforcement using MI techniques such as 
active listening, asking rather than making assumptions, offering empathy, and speaking in a 
non-judgmental manner. These positive communication strategies will serve as a guiding 
framework for discussions during coaching calls and will be encouraged between partners on 
their own. Nurse health coaches will model these approaches, and participants will practice them 
during calls, beginning with role play scenarios and later in discussions of their own progress. 
Role play scenarios will provide examples of both positive (e.g., asking open questions, 
reflection, support for partners’ decisions) and negative (e.g., interruption, telling partner what to 
do, critical and pressuring language) communication patterns to illustrate differential reactions 
and outcomes. Dyads will also develop a mutual support plan that describes each participant’s 
support needs and ways for the partner to be supportive. Partner support actions may include 
those that provide direct/tangible support (e.g., actions that facilitate a partner being active) as 
well as autonomy support (e.g., expressing support for her partner’s behavior change plans). On 
each zoom meeting, the nurse health coach will check in with participants regarding 
communication between dyad members, support that has been helpful, support or actions that 
have not been helpful, and support needs. Mutual support plans will be reviewed and modified as 
needed. Recognizing that relationships may encounter challenges, the nurse health coach will 
also reach out to participants individually throughout the study to see if they would like to speak 

11 
IRB NUMBER: HSC-SN-23-0576 
IRB APPROVAL DATE: 02/15/2024 
 
 
privately. Finally, the nurse health coach will encourage dyads to engage in at least one PA- 
related activity together each week (or on a regular basis agreed on by participants). Consistent 
with SCT, dyads can choose from a menu of options or develop an activity on their own. Options 
may include exercising together, planning to be active during the same day/time even if 
physically apart, participating in a challenge or friendly competition together (e.g., through the 
Fitbit app), and trying a new type of activity or exercise class. Nurse health coach will encourage 
dyads to engage in a virtual or in-person activity together one time per week to promote 
interaction and enjoyment and will record women’s experiences and satisfaction. During 
coaching zoom meeting calls, nurse health coaches will record the activity engaged in, overall 
enjoyment, and aspects participants liked and did not like to inform future activity planning. 
Participants will also be advised to set small, achievable PA goals to promote mastery and build 
self-efficacy. All calls will be digitally recorded to monitor coaching procedures and for future 
evaluation. Zoom audio recordings will be erased once the data have been published. Nurse 
health coach will communicate with participants using institutionally-managed devices (e.g., 
iPhones managed with institutional information security software). For reminders and 
rescheduling of calls, nurse health coach may communicate with participants over the zoom and 
via text messaging. Text messages will include information about the time and date of calls but 
names will not be used. No protected health information will be included in the text messages. 
Messaging history will be deleted at weekly intervals. 
Fitbit activity monitor. Fitbits have been used extensively in research with adequate feasibility. 
Fitbits will be provided to all participants to ensure consistency in devices and data monitoring. 
The increasing availability of wearable activity monitors (e.g., Fitbit, wearable devices) limits 
the expectation of a dyad group that lacks access to this form of monitoring. Participants in the 
dyadic intervention will be instructed to use the Fitbit to monitor their partners’ PA in addition to 
their own. All participants will be instructed to “friend” their health coach to enable real-time 
monitoring of PA to inform coaching zoom calls. Women will receive an activity tracker/Fitbit 
and instruction in their use to facilitate monitoring of PA. The Fitbit will provide feedback on 
steps, active minutes, and calories burned. Participants will be instructed in how to use the Fitbit 
to monitor their PA. Participants will be asked to wear the device on most days and while they 
sleep. Fitbit physical activity data will be collected through a secure system called Fitabase. 
Although studies suggest that activity monitors can lead to increased PA, these effects tend to be 
short term, with multifaceted interventions that include monitors and personalized coaching 
leading to greater, sustained effects.87,88 Researchers have suggested that activity monitors like 
Fitbit should be integrated within a lifestyle intervention to yield meaningful benefits.89-91 
Electronic newsletters. Newsletters will be sent twice monthly during months 1-3 via email or 
text with an online link. Newsletters will be designed to share educational PA-related 
information from publicly available resources (e.g., the Physical Activity Guidelines for 
Americans, 2nd edition,92 the Centers for Disease Control and Prevention, “Move Your Way” 
campaign materials). Newsletters will also contain tips for overcoming barriers to PA that may 
be common in our target population, e.g., finding time to exercise, low-cost ways to be active, 
being active with kids. Newsletters will also contain links to brief exercise routines that 
participants can do in their homes and information on low cost/free exercise classes in the 
community, which may help to overcome perceived access barriers. Participants who do not use 
email and do not want to receive the newsletter link via text will be sent newsletters in the mail. 
Cultural sensitivity. The proposed intervention integrates cultural values and norms of South 

12 
IRB NUMBER: HSC-SN-23-0576 
IRB APPROVAL DATE: 02/15/2024 
 
 
Asian Indians into aspects of the design and delivery to enhance intervention relevance, appeal, 
and engagement. This includes “surface structure” approaches that emphasize the importance of 
having intervention materials and research/intervention staff reflect the characteristics of the 
target population (e.g., availability of Indian language materials, images of SAI women, 
bilingual and bicultural staff).93 In addition, the intervention aims to address “deep structure” 
elements by focusing on issues of salience to the target population including cultural values and 
beliefs pertinent to health generally and PA in particular and these specific knowledge will be 
incorporated from the PI’s ongoing qualitative focus group research with SAI women regarding 
barriers and facilitators to PA. Examples of deep structure elements for SAI women include the 
importance of family and the role of women as caregivers, religion/spiritualism, perceived norms 
around women exercising, body image, concerns regarding safety and access to PA 
opportunities. Although the intervention does not intervene directly on potential barriers such as 
access to opportunities for PA, MI is well-suited for problem solving to address the varied 
barriers that participants may face. The nurse health coach will be well trained to delve deeper 
into potential barriers and engage dyads to elicit participant-identified solutions. In addition, PI 
who represent SAI women will be involved in the planning process and will help to identify 
other possible cultural factors of relevance. An in-depth understanding of the factors associated 
with PA engagement and common barriers in our target population will be an important 
component of nurse health coach training. 
Quality Control. Nurse health coach have a masters and doctorate degree in nursing (DNP) and 
is – is or are double certified in holistic nursing and health coaching. The nurse health coach will 
receive 20 hours of training in MI, which combines didactic and experiential activities. The nurse 
holistic health coach will also receive training in cultural competency and cultural and behavioral 
factors relevant to SAI women. 
Data collection and study procedures are shown in Table 1 (Appendix -D). Data collection will 
take place at baseline and immediately post-intervention (approximately 3-months after 
baseline). Each participant will be compensated for their time with $40 (at baseline) and $50 (at 
12-week follow-up) in gift cards upon completing study procedures and parking (as needed) for 
each visit. 
All participants will also be provided with a Fitbit device that will enable participants to monitor 
their own and their partner’s PA, and will also allow research staff and the nurse health coaches 
to monitor participants’ PA. Data collection will be conducted in-person by UTHealth staff 
(research assistant) at community sites (e.g., Indian community center, churches, other religious 
organizations, health fairs, and health screenings targeting Asian Indians in Houston etc.) 
depending on participants’ preference. 
At baseline study staff will first request permission to take participants’ blood pressure to 
confirm eligibility. Following the measurement, all participants will be provided with health 
education on blood pressure. Participants with elevated and high blood pressure (≥120/80 mm 
Hg), as defined by the 2017 American College of Cardiology and American Heart Association, 
will be encouraged to see a healthcare provider. Participants with BP readings ≥160/100 mm 
Hg will be informed that they can participate in the study only with a letter from a healthcare 
provider clearing them for participation. If participants do not have a healthcare provider, a list 
of low-cost clinics in Harris County will be provided. Participants with pressure readings 
≥180/120 mm Hg will be informed that study staff must contact 911 due to their BP being 

13 
IRB NUMBER: HSC-SN-23-0576 
IRB APPROVAL DATE: 02/15/2024 
 
 
dangerously high. If participants decline to have 911 called, they will be required to sign a 
waiver indicating this decision. Participants will be advised to seek medical care immediately. 
Research Electronic Data Capture (REDCap), a secure, HIPAA-compliant web application for 
managing online surveys and databases, will be used to administer questionnaires. For 
participants who are eligible, study staff will describe the study and obtain informed consent. 
Participants will complete questionnaires on a laptop/tablet device, provide anthropometric 
measures, complete the fitness measures. Anthropometric measures include measured height, 
weight, waist circumference, and percent body fat. Height and weight will be measured using a 
stadiometer and digital scale, respectively. During the baseline assessment, study staff will 
work with participants to create a Fitbit account. 
Process Evaluation. Process evaluation will be used to monitor and document program 
implementation via assessment of intervention dose (amount of intervention delivered and 
received), reach (extent of intervention participation by the target population), and fidelity 
(extent to which the intervention was implemented as planned). For dose, we will track the 
extent to which coaching session was completed, intended content was covered, and 
newsletters were received and read. Reach will be assessed by tracking participation of dyad 
members for each session (0, 1, or both) along with barriers to participation, dyad interaction, 
and use of the Fitbit, including frequency of monitoring partner’s PA. Individual participants’ 
Fitbit data from Fitabase dashboard will be used by intervention coaches to review participants’ 
data and aid them with providing feedback. We will also use this information to evaluate 
participants’ adherence to self-monitoring. To assess fidelity, all coaching sessions will be 
digitally recorded. Holistic nurse health coach will be required to keep detailed implementation 
logs showing the date and start and end times of sessions, individuals present, the content 
discussed, goals set by participants that will be followed up on the next session, dyad support 
plans, and any qualitative observations. 
Measures: Surveys will be administered using Research Electronic Data Capture (REDCap), a 
secure, HIPAA- compliant web application. Table 1 (Appendix-D) shows the schedule of study 
procedures and constructs to be assessed, proposed measures, and the timing of assessment. 
Physical Activity. Fitbit data include daily step counts, floors climbed, activity intensity, heart 
rate, and sleep data along with wear/usage data. If participants do not wear the Fitbit as 
recommended, this will not be recorded as a deviation Fitbit data will be PA will be described in 
terms of step count per minutes and total minutes being in moderate, and vigorous PA. Self- 
reported PA will be assessed with the Godin Leisure Time Exercise Questionnaire,94 which 
assesses episodes, intensity, and duration of PA during a typical 7-day period. Good test-retest 
reliability has been observed, with test-retest correlation coefficients ranging from 0.48 for light 
activity to 0.94 for strenuous activity.94 
Anthropometry. Non-fasting weight in light clothing, height without shoes, waist (at the iliac 
crest) circumference, and percent body fat will be measured by trained staff. Measurements will 
be assessed in duplicate or until two measurements are within the permitted variance (weight, 0.2 
kg; height and waist circumference 0.3 cm) using a calibrated digital floor scale, a stadiometer, 
and a Gulick tape measure with a 6 oz. tension meter. Percent body fat is assessed using the 
digital Tanita scale. 
Blood Pressure (BP). Participants will have their BP taken by a trained staff member with an 
arm blood pressure monitor. Participants will be provided with a written recording of their 

14 
IRB NUMBER: HSC-SN-23-0576 
IRB APPROVAL DATE: 02/15/2024 
 
 
blood pressure and will be referred to the information sheet (see “Participant Measures and BP 
Report”) regarding recommendations. Participants with elevated and high blood pressure 
(≥120/80 mm Hg), as defined by the 2017 American College of Cardiology and American 
Heart Association, will be encouraged to see a healthcare provider. Participants who do not 
have a regular healthcare provider will be provided with a list of low-cost clinics in Harris 
County. Participants with BP readings ≥180/120 mm Hg will be informed that study staff must 
contact 911 due to their BP being dangerously high. If participants decline to have 911 called, 
they will be required to sign a waiver indicating this decision. Participants will be advised to 
seek emergency care or follow up with their healthcare provider immediately. 
Questionnaires. Questionnaires to be completed by participants are listed in Table 2 (Appendix- 
E) and briefly described below. REDCap (Research Electronic Data Capture) will be used to 
administer questionnaires. 
Screening 
• The Physical Activity Readiness Questionnaire (PAR-Q) is a pre-activity screening tool 
recommended by the American College of Sports Medicine as a minimal standard for 
entry into low and moderate intensity exercise programs.95 The PAR-Q serves to 
identify individuals who should consult a medical practitioner prior to participation in 
an exercise program. 
• The Godin Leisure Time Exercise Questionnaire94 assesses episodes, intensity, and 
duration of PA during a typical 7-day period. Good test-retest reliability has been 
observed, with test-retest correlation coefficients ranging from .48 for light activity to 
0.94 for strenuous activity.94 Other studies have confirmed reliability and validity,96 and 
this measure has been validated with accelerometers.97 
Demographics and Health 
• Demographic characteristics are drawn from the Behavioral Risk Factor Surveillance 
System and will include variables such as participants’ age, gender, race/ethnicity, 
country of birth, marital status, highest level of education, current employment status, and 
household income. 
 
• Chew’s one-item Health Literacy Screening Question98 assesses individuals’ self- 
reported ability to perform health literacy-related tasks. Participants respond to one 
question on a 5-point Likert scale (scores range from 1 to 5). Several studies have found 
that the question "How confident are you filling out medical forms by yourself" has the 
greatest accuracy in identifying individuals with limited and marginal health literacy.99,100 
 
• Self-Rated Health is a one-item measure that asks participants to rate their health on a 
continuum ranging from excellent to poor. Self-rated health has been shown to be a 
consistent predictor of mortality in diverse populations and sensitive to health indicators 
and social factors.101 
 
• Health History is a one-item measure that asks participants to indicate whether they have 
had specific medical problems in the past 12 months. These medical problems include 
diabetes, cancer, high blood pressure or cholesterol, stroke, asthma, thyroid problems, 
and heart, kidney, or lung disease. 

15 
IRB NUMBER: HSC-SN-23-0576 
IRB APPROVAL DATE: 02/15/2024 
 
 
 
• Online Access questions from the Pew Research Center assess the ways in which 
participants access the internet. 
 
 
• Value Assessment: At the baseline assessment, we will ask participants about their top 
three values from a pre-selected list of 22 values (e.g., good parent, responsible, caring). 
These values will be provided to the health coaches to inform the health coaching 
sessions. 
Social Context 
• The Interpersonal Support Evaluation List (ISEL-12) is a 12-item measure of perceived 
social support overall and within three dimensions: appraisal support, belonging support, 
and tangible support. The ISEL-12 and its subscales have demonstrated adequate test- 
retest reliability and internal consistency, and good convergent and criterion validity.102 
• The Social Support measure for PA assess family and friend social support specific to 
exercise behaviors.103 These scales exhibit good reliability (e.g., α=0.83) and have been 
used with minority populations.57,104 
• Important Others Climate Questionnaire (IOCQ; Autonomy Support) measures the 
perception of the autonomy supportiveness of an “important other” with respect to an 
identified behavior.105 In this study, we will assess perceived autonomy supportiveness of 
the study partner from the perspective of the participant, and the perceived autonomy 
supportiveness provided by the study participant to her study partner. 
 
• Partner Characteristics and Relationship Quality: We propose to ask a series of 
questions to collect information on participants’ study partners and to characterize the 
relationship between dyad members. This includes such information as the type of 
relation, frequency of interaction, strength of relationship, and content and format of 
communication. These questions were adapted from egocentric questions.106 Overall 
relationship quality will be assessed with a global rating item from the National Survey 
of Families and Households, with response options ranging from 1 (poor) to 5 
(excellent). 
 
PA-related Measures 
• Self-efficacy for PA assesses confidence in one’s ability to be physically active on a 
regular basis in the face of various barriers. This construct is one of the most consistent 
correlates of PA behavior in diverse samples of adults.107 
 
• The Stage of Change questionnaires for PA consists of 2 questions assessing readiness to 
engage regularly in PA,108-110 Participants can be classified into one of five stages of 
change: pre-contemplation, contemplation, preparation, action, and maintenance. 
Concurrent validity tests indicate strong validity evidence for this staging measure.111 

16 
IRB NUMBER: HSC-SN-23-0576 
IRB APPROVAL DATE: 02/15/2024 
 
 
• The Behavioral Regulation in Exercise (BREQ-3) questionnaire assesses motivation to 
exercise. The questionnaire contains 24 items within six subscales, all of which have 
acceptable internal reliability (α=0.73-0.86).112 
 
Physical Activity Outcomes 
• The Godin Leisure Time Exercise Questionnaire94 assesses episodes, intensity, and 
duration of PA during a typical 7-day period. Good test-retest reliability has been 
observed, with test-retest correlation coefficients ranging from .48 for light activity to 
0.94 for strenuous activity.94 Other studies have confirmed reliability and validity,96 and 
this measure has been validated with accelerometers.97 
 
• The Multi-Context Sitting Time Questionnaire (MSTQ) assesses time spent sitting on 
both work and non-work days.114 The MSTQ assesses common sedentary behaviors such 
as watching television, computer use, reading, socializing, and transport. Intraclass 
coefficients for the MSTQ demonstrated acceptable reliability (ICCs>0.70), and the 
MSTQ performed similarly to other measures of sedentary behavior. 
Other Behaviors 
• We will assess diet using items from the BRFSS. Six items assess fruit and vegetable 
intake. 
 
• We will also assess Cognitive function using Montreal Cognitive Assessment: MoCA 
Version 7.1 (Original Version)115(Appendix-E). The MoCA is a screening test assessing 
global cognitive function that assesses memory, visuospatial ability, executive function, 
attention, concentration, working memory and orientation. This can be used for screening 
for mild cognitive impairment (MCI). The MoCA takes approximately 10 minutes to 
administer. The total possible score is 30 points with a score of 26 or more considered 
normal. To better adjust the MoCA for lower educated individuals, 2 points should be 
added to the total MoCA score for those with 4-9 years of education and 1 point for 10- 
12 years of education. The score range for MCI is 19-25.2 and for Alzheimer’s dementia. 
The MoCA detected MCI with 90%-96% range sensitivity and specificity of 87% with 
95% confidence interval. The MoCA detected 100% of Alzheimer’s dementia with a 
specificity of 87%116. A trained research assistant who has successfully completed 
official MoCA training and certification module will administer this test. 
 
 
Ethics 
The study team will get approval from the Committee for the Protection of Human Subjects 
(CPHS) at the University of Texas Health Science Center at Houston before the recruitment of 
study participants. Potential participants will be informed regarding the overall goals of the study 
and stated that the data collected will remain confidential, and used strictly for research purposes 
and will get an informed consent (Appendix-C). 
Potential Challenges and Risks and Procedures for Minimizing Risks 
Risks associated with study participation are minimal as all data collection is non-invasive and 

17 
IRB NUMBER: HSC-SN-23-0576 
IRB APPROVAL DATE: 02/15/2024 
 
 
primarily non-personal. Minimal risk is defined as the probability and magnitude of physical or 
psychological harm that does not exceed that encountered in ordinary, everyday life or in the 
performance of routine medical or psychological examinations. Risks include: becoming 
fatigued when participating in sessions, feeling uncomfortable interacting with the study team 
during sessions, and breach of confidentiality. Participants will be notified of these risks during 
the informed consent process. If any concerns arise during study procedures, participants will be 
reminded that participation is voluntary and they may refuse to answer any questions, end the 
session, or withdraw from the study at any time without fear of repercussion. If a participant is 
too tired or ill to continue with a scheduled session, the session will be ended and if (and only if) 
the participant is willing and able the session will be rescheduled. All attempts possible will be 
made to minimize the risk that a participant’s data will become known to others outside the 
approved research team (see Data Management). The research team will ensure the anonymity of 
the participants by protecting personally identifiable information. The proposed study will be 
conducted in English; India is a linguistically diverse country with 22 languages recognized by 
the constitution of India117 and it is not feasible to conduct focus groups in multiple languages. 
However, English is also considered a popular second language in India 118 and is used as the 
language for communication in U.S. Asian Indians speak English very well (57.7%)117and 
limited English proficiency is fairly low (7.3%) and are bilingual since they speak another 
language at home117. 
 
Height/Weight/Waistline Measurements 
Having weight or waistline measurements taken may make participants feel uncomfortable. 
Participants may refuse to complete any procedure that makes them feel uncomfortable. 
Physical Activity Side Effects 
This study encourages increased participation in physical activity of a moderate nature. This 
activity may result in mild physical discomfort (e.g., sore muscles, stiffness) for some 
participants. These effects have no long-term negative health implications and are a normal 
consequence of activity. However, more serious potential risks include pulled muscles, heart 
problems, chest tightness or discomfort, shortness of breath, and accidental injuries, such as 
falling. Possible outcomes could include referral to the participant’s primary care physician 
and/or other physician. Our inclusion/exclusion criteria were designed to exclude participants 
who should not participate in regular light-to-moderate physical activity based on their responses 
to the PAR-Q and blood pressure measures without the authorization of a healthcare provider. 
Study Withdrawal/Discontinuation 
Participants may withdraw from this study at any point in time without repercussion, by simply 
indicating their desire to withdraw to a study team member. 
Criteria for Removal from the Study: 
• Participant or clinician request 
• Inability to contact the patient for 1 month (up to 6 attempts will be made) 
• Completion of study 
• Study team determined the patient was no longer eligible 

18 
IRB NUMBER: HSC-SN-23-0576 
IRB APPROVAL DATE: 02/15/2024 
 
 
• Sessions were not productive 
• Deceased 
• Health status declined 
 
All data captured from withdrawn participants will be considered evaluable and used for this 
study, unless a withdrawn participant requests to have their data destroyed. 
 
Data and Safety Monitoring 
Study team members will continuously monitor participant safety and data quality whenever 
conducting study activities. Study personnel will maintain quality assurance procedures for all 
data. Survey data will be collected and managed using REDCap (Research 
Electronic Data Capture). All protected health information (PHI) will be removed from the data 
when it is exported from REDCap for analysis. Those having access to the data file include the 
study Principal Investigator (PI) and research team personnel and will monitor recruitment, data 
quality, data management, and human subjects’ protection at least bi-weekly. Logs will be 
maintained of refusals during recruitment, any participant complaints, and other adverse events 
and will be reported according to Institution Review Board (IRB) requirements. Dr. Mathew 
Joseph will work to address and resolve any concerns in the most expeditious manner possible. 
In particular, participant responses to recruitment attempts will be tracked in terms of methods of 
contact, and reasons for refusal (if available) and contact attempts made by the study team. This 
information will be reviewed on a bi-weekly basis, and if any concerning trends are noted in 
recruitment refusals, the IRBs will be notified and adjustments made to recruitment strategies 
and / or study procedures (as indicated). 
 
Several procedures will be used to maintain the integrity of the data. Quality assurance 
procedures will include a data collection protocol documented in a protocol manual, and regular 
meetings among the investigators and project staff to review problems and solutions and discuss 
concerns. A specific audit trail system that identifies the date, time, and individual making 
changes on the database will be part of the data management system. 
No protected health information will be included in the text/email messages (as there will be no 
health information in the message). Although participants’ phone numbers and the content of the 
text messages will be disclosed to the automated text messaging service, no protected health 
information will be disclosed to the automated text messaging service. Participants will be 
informed that unencrypted text and email messages are not secure and may choose not to receive 
them. 
To minimize the possibility of a breach in confidentially, data for this study will only be 
accessible by study team members. Communication with participants may occur in-person or via 
electronic mail or telephone calls. Voice mails left for participants will contain just the 
information necessary to return the contact (no identifiable or confidential information). Only 
UTHealth or site institutional email addresses will be used to communicate with participants. 
Data Handling and Record Keeping 
 
Identifiable participant data will be kept in secure locked areas at the Cizik School of Nursing or 
in password-protected electronic files accessible only by study staff. All identifiable electronic 

19 
IRB NUMBER: HSC-SN-23-0576 
IRB APPROVAL DATE: 02/15/2024 
 
 
data (including original recordings and participant contact information) will be stored and 
managed in a secure, password-protected folder on a server approved for the storage of protected 
health information or in a secured Research Electronic Data Capture (REDCap™) database, per 
UTHealth policy. Participants’ names and identifiers will be linked to the study identification 
number in a database that will be password protected, with access restricted to the PI and 
designated research staff. Paper records (e.g., signed ICDs, completed screening forms) will be 
kept in a locked file room. All signed informed consent documents and/or HIPAA authorizations 
will be securely maintained for at least 6 years after the close of the study. Recruitment data will 
be stored separately from the data of participants who enroll in the study. In particular, a full list 
will be maintained of participant responses to recruitment attempts by site study team members 
on a secured and password-protected server managed by that site. 
Mr. Stan Cron, statistician of the study, will have access to identifiers needed for analysis such as 
date of birth (to calculate age) and assessment dates. Other collaborators will have access to de- 
identified data only. Participants’ residential addresses will be collected to access publicly 
available information about the area in which participants live. This can help us understand how 
their neighborhood is conducive to physical activity. Results from data analyses using this 
information will only be reported in aggregate form, and no participants will be identifiable from 
any research products resulting from this protocol. Participants’ residential addresses will never 
be released/published in any form (e.g., maps, graphs/charts). Addresses will be stored separately 
from other study data, and following the procurement of neighborhood information, access to 
participants’ addresses will be limited to the PI. Although every effort will be made to keep 
study data safe, there is a chance that personal health information could be lost or stolen. 
After the research described here is complete and the manuscript/s written, access to the de- 
identified data files will be limited to the PI and research staff/collaborators, who will maintain 
the files on the institutional server in case any questions emerge from peers or regulatory 
agencies regarding the resulting publications. Recordings of coaching sessions will be deleted 
following the completion of analysis. Following study termination, data and identifiers will be 
handled as per applicable policies and regulations. 
Statistics 
The feasibility of the intervention will be determined by comparing the percentages for overall 
recruitment and retention at week 12 to their target values of 80% and 70%, respectively. A 
secondary feasibility assessment will determine the proportion of intervention participants who 
take part in each of the intervention components (i.e., number of counseling calls completed, use 
of Fitbit, receipt and review of newsletters). In addition, every attempt will be made to query 
subjects lost to follow-up to ascertain the reason for drop out or barriers to participation. 
Feasibility will be measured by calculating the rates of enrollment, retention, assessment 
completion, and treatment adherence. The enrollment rate will be the proportion of those 
meeting inclusion criteria that enrolled, while the retention rate will be the proportion enrolled 
that complete the study. Assessment completion will be calculated as the proportion of assigned 
data collection forms that were completed. Treatment adherence will be calculated as the 
proportion of intervention sessions attended. 
To explore trends in the outcomes data, means and standard deviations will be calculated for the 
instrument scores at baseline and week 12. As hypothesis testing is not the objective of a pilot 

20 
IRB NUMBER: HSC-SN-23-0576 
IRB APPROVAL DATE: 02/15/2024 
 
 
study118, these descriptive statistics will only be used to inform effect size estimation. Since the 
effect sizes in a pilot study may overestimate or underestimate the true effect sizes 120 the 
obtained effect size estimates will be considered in combination with clinically significant effect 
sizes for the outcome variables in determining the sample size for a future trial. 
Power Analysis: The primary aims do not require power calculations given the focus on 
feasibility study. 
Anticipated Results: This study will provide the foundation for further large-scale efficacy 
testing of the dyadic social support PA intervention with the ultimate goal of improving the 
health and well-being of SAI women. The proposed intervention also integrates cultural values 
and norms into aspects of the design and delivery to enhance intervention relevance, appeal, and 
engagement of PA to yield long-term positive impact on the health of SAI women. The results of 
the study will be published in the scientific journals in a manner that will be accessible to other 
academic institutions and researchers. We also plan to model with SAI community organizations 
and health clinics that serve this population and would benefit from the study’s outcomes largely. 
Our project is timely and urgent for at risk SAIs women as it can improve PA to build healthy 
new habits that last a lifetime. Moreover, the nurse coach will help you learn new skills, 
encourage to set and meet goals, and keep motivated. Moreover, dyad partners can share ideas, 
celebrate successes, and work to overcome obstacles. Our study is related to current national 
priorities. The major goal of Healthy People 2030 is to reduce health disparities among racial and 
minority groups especially SAIs and to reduce obesity and diabetes by promoting physical 
activity. The National Institute of Health also encourages investigator-initiated research on 
minority health and health disparities. 
 
Publication Plans 
We will submit abstracts of the study findings for presentation at the conferences of Society of 
Behavioral Medicine and American Heart Association and plan to submit a manuscript for 
publication in the American Journal of Public Health and Journal Preventive Medicine Reports 
as second choice. 
 
Potential for Extramural Funding 
The data gathered in this study will allow us to understand the provides preliminary support for 
the feasibility and effectiveness of the peer-based dyadic behavioral intervention among SAI 
women. We will use the study findings as preliminary results to apply for National Institute of 
Health RO1 grant to test the effectiveness of a peer-based, dyadic behavioral intervention that 
emphasizes support between partners for promoting adoption and maintenance of PA 
intervention among SAI women. Major goals of Healthy People 2030 are to reduce health 
disparities among racial and other minority groups and obesity and diabetes by promoting PA. 
The National Institute of Health also encourages investigator-initiated research on minority 
health and health disparities. 

21 
IRB NUMBER: HSC-SN-23-0576 
IRB APPROVAL DATE: 02/15/2024 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
References 

22 
IRB NUMBER: HSC-SN-23-0576 
IRB APPROVAL DATE: 02/15/2024 
 
 
1. 
Venkataraman R, Nanda NC, Baweja G, Parikh N, Bhatia V. Prevalence of diabetes 
mellitus and related conditions in Asian Indians living in the United States. Am J Cardiol. 
2004;94(7):977-980. 
2. 
Enas EA, Mehta J. Malignant coronary artery disease in young Asian Indians: thoughts 
on pathogenesis, prevention, and therapy. Coronary Artery Disease in Asian Indians 
(CADI) Study. Clin Cardiol. 1995;18(3):131-135. 
3. 
Palaniappan L, Wang Y, Fortmann SP. Coronary heart disease mortality for six ethnic 
groups in California, 1990–2000. Ann Epidemiol. 2004;14(7):499-506. 
4. 
Misra A, Vikram NK. Insulin resistance syndrome (metabolic syndrome) and obesity in 
Asian Indians: evidence and implications. Nutrition. 2004;20(5):482-491. 
5. 
Misra KB, Endemann SW, Ayer M. Leisure time physical activity and metabolic 
syndrome in Asian Indian immigrants residing in northern California. Ethn Dis. 
2005;15(4):627-634. 
6. 
Yusuf S, Hawken S, Ounpuu S, et al. Effect of potentially modifiable risk factors 
associated with myocardial infarction in 52 countries (the INTERHEART study): case- 
control study. Lancet. 2004;364(9438):937-952. 
7. 
Mohanty SA, Woolhandler S, Himmelstein DU, Bor DH. Diabetes and cardiovascular 
disease among Asian Indians in the United States. J Gen Intern Med. 2005;20(5):474- 
478. 
8. 
Mathew Joseph N, Misra R, Wang J. Mediating Role of Acculturation and Lifestyle 
Behaviors on Cardiometabolic Risk Among a National Sample of U.S. Asian Indians. 
Journal of immigrant and minority health. 2020;22(4):727-735. 
9. 
Das A, Ambale-Venkatesh B, Lima JA, et al. Cardiometabolic disease in South Asians: A 
global health concern in an expanding population. Nutr Metab Cardiovasc Dis. 
2017;27(1):32-40. 
10. 
Bainey KR, Jugdutt BI. Increased burden of coronary artery disease in South-Asians 
living in North America. Need for an aggressive management algorithm. Atherosclerosis. 
2009;204(1):1-10. 
11. 
Volgman AS, Palaniappan LS, Aggarwal NT, et al. Atherosclerotic Cardiovascular 
Disease in South Asians in the United States: Epidemiology, Risk Factors, and 
Treatments: A Scientific Statement From the American Heart Association. Circulation. 
2018;138(1):e1-e34. 
12. 
Kanaya AM, Kandula N, Herrington D, et al. Mediators of Atherosclerosis in South 
Asians Living in America (MASALA) study: objectives, methods, and cohort 
description. Clin Cardiol. 2013;36(12):713-720. 
13. 
Kanaya AM, Kandula NR, Ewing SK, et al. Comparing coronary artery calcium among 
U.S. South Asians with four racial/ethnic groups: the MASALA and MESA studies. 
Atherosclerosis. 2014;234(1):102-107. 
14. 
Kanaya AM, Herrington D, Vittinghoff E, et al. Understanding the high prevalence of 
diabetes in U.S. south Asians compared with four racial/ethnic groups: the MASALA and 
MESA studies. Diabetes Care. 2014;37(6):1621-1628. 
15. 
Gujral UP, Kanaya AM. Epidemiology of diabetes among South Asians in the United 
States: lessons from the MASALA study. Ann N Y Acad Sci. 2021;1495(1):24-39. 
16. 
Kanaya AM, Herrington D, Vittinghoff E, et al. Understanding the High Prevalence of 
Diabetes in U.S. South Asians Compared With Four Racial/Ethnic Groups: The 
MASALA and MESA Studies. Diabetes Care. 2014;37(6):1621-1628. 

23 
IRB NUMBER: HSC-SN-23-0576 
IRB APPROVAL DATE: 02/15/2024 
 
 
17. 
Hastings KG, Jose PO, Kapphahn KI, et al. Leading Causes of Death among Asian 
American Subgroups (2003-2011). PLoS One. 2015;10(4):e0124341. 
18. 
Mangalmurti SS, Paley A, Gany F, Fisher EA, Hochman JS. South Asians and risk of 
cardiovascular disease: current insights and trends. Ethn Dis. 2010;20(4):474-478. 
19. 
Ardeshna DR, Bob-Manuel T, Nanda A, et al. Asian-Indians: a review of coronary artery 
disease in this understudied cohort in the United States. Annals of translational medicine. 
2018;6(1):12. 
20. 
Ye J, Rust G, Baltrus P, Daniels E. Cardiovascular Risk Factors among Asian Americans: 
Results from a National Health Survey. Ann Epidemiol. 2009;19(10):718-723. 
21. 
Joshi P, Islam S, Pais P, et al. Risk factors for early myocardial infarction in South Asians 
compared with individuals in other countries. JAMA. 2007;297(3):286-294. 
22. 
Ruiz NB, A. Key facts about Asian origin groups in the U.S. 2022; 
https://www.pewresearch.org/fact-tank/2021/04/29/key-facts-about-asian-origin-groups- 
in-the-u-s/. Accessed July 21, 2022. 
23. 
Kubota Y, Evenson KR, Maclehose RF, Roetker NS, Joshu CE, Folsom AR. Physical 
Activity and Lifetime Risk of Cardiovascular Disease and Cancer. Med Sci Sports Exerc. 
2017;49(8):1599-1605. 
24. 
Meisinger C, Löwel H, Thorand B, Döring A. Leisure time physical activity and the risk 
of type 2 diabetes in men and women from the general population. The MONICA/KORA 
Augsburg Cohort Study. Diabetologia. 2005;48(1):27-34. 
25. 
Strasser B. Physical activity in obesity and metabolic syndrome. Ann N Y Acad Sci. 
2013;1281(1):141-159. 
26. 
Daniel M, Wilbur J. Physical activity among South Asian Indian immigrants: an 
integrative review. Public Health Nurs. 2011;28(5):389-401. 
27. 
Mathew Joseph N, K. Hanneman S, L. Bishop S. Physical activity, acculturation, and 
immigrant status of Asian Indian women living in the United States. 2019. 
28. 
Misra R, Patel TG, Davies D, Russo T. Health Promotion Behaviors of Gujurati Asian 
Indian Immigrants in the United States. J Immigrant Health. 2000;2(4):223-230. 
29. 
Daniel M, Wilbur J, Fogg LF, Miller AM. Correlates of lifestyle: physical activity among 
South Asian Indian immigrants. J Community Health Nurs. 2013;30(4):185-200. 
30. 
Mohan S, Wilkes L, Jackson D. Lifestyle of Asian Indians with coronary heart disease: 
the Australian context. Collegian. 2008;15(3):115-121. 
31. 
Williams ED, Stamatakis E, Chandola T, Hamer M. Physical activity behaviour and 
coronary heart disease mortality among South Asian people in the UK: an observational 
longitudinal study. Heart. 2011;97(8):655-659. 
32. 
Misra R, Patel T, Kotha P, et al. Prevalence of diabetes, metabolic syndrome, and 
cardiovascular risk factors in US Asian Indians: results from a national study. J Diabetes 
Complications. 2010;24(3):145-153. 
33. 
Bhalodkar NC, Blum S, Rana T, Bhalodkar A, Kitchappa R, Enas EA. Effect of leisure 
time exercise on high-density lipoprotein cholesterol, its subclasses, and size in Asian 
Indians. Am J Cardiol. 2005;96(1):98-100. 
34. 
Abate N, Chandalia M. Ethnicity and type 2 diabetes: focus on Asian Indians. J Diabetes 
Complications. 2001;15(6):320-327. 
35. 
The Diabetes Prevention Program (DPP): description of lifestyle intervention. Diabetes 
Care. 2002;25(12):2165-2171. 

24 
IRB NUMBER: HSC-SN-23-0576 
IRB APPROVAL DATE: 02/15/2024 
 
 
36. 
Consultation. WHOWE. Appropriate body-mass index for Asian populations and its 
implications for policy and intervention strategies. The Lancet. 2004 363(9403):157–163. 
37. 
He L, Tuomilehto J, Qiao Q, et al. Impact of classical risk factors of type 2 diabetes 
among Asian Indian, Chinese and Japanese populations. Diabetes Metab. 
2015;41(5):401-409. 
38. 
Banerjee J, Dhas Y, Mishra N. Middle-Aged Indians with Type 2 Diabetes Are at Higher 
Risk of Biological Ageing with Special Reference to Serum CDKN2A. Journal of 
diabetes research. 2020;2020:7569259. 
39. 
Malik VS, Willett WC, Hu FB. Global obesity: trends, risk factors and policy 
implications. Nature Reviews Endocrinology. 2013;9(1):13-27. 
40. 
Cheng YJ, Kanaya AM, Araneta MRG, et al. Prevalence of Diabetes by Race and 
Ethnicity in the United States, 2011-2016. JAMA. 2019;322(24):2389-2398. 
41. 
Services USDoHH. Hispanic and Asian subgroups are at higher risk for diabetes. 2022; 
https://www.cdc.gov/diabetes/library/socialmedia/infographics/diabetes-race- 
ethnicity.html. Accessed October 27, 2022, 2022. 
42. 
Sriskantharajah J, Kai J. Promoting physical activity among South Asian women with 
coronary heart disease and diabetes: what might help? Fam Pract. 2007;24(1):71-76. 
43. 
Daniel M, Abendroth M, Erlen JA. Barriers and Motives to PA in South Asian Indian 
Immigrant Women. West J Nurs Res. 2018;40(9):1339-1356. 
44. 
Johnson MRD. Perceptions of Barriers to Healthy Physical Activity among Asian 
Communities. Sport, Education and Society. 2000;5(1):51-70. 
45. 
Kalra P, Srinivasan S, Ivey S, Greenlund K. Knowledge and practice: the risk of 
cardiovascular disease among Asian Indians. Results from focus groups conducted in 
Asian Indian communities in Northern California. Ethn Dis. 2004;14(4):497-504. 
46. 
Babakus WS, Thompson JL. Physical activity among South Asian women: a systematic, 
mixed-methods review. Int J Behav Nutr Phys Act. 2012;9:150. 
47. 
Lucas A, Murray E, Kinra S. Heath beliefs of UK South Asians related to lifestyle 
diseases: a review of qualitative literature. J Obes. 2013;2013:827674. 
48. 
Mann SK, Roberts LR, Montgomery S. Conflicting Cultural Values, Gender Role 
Attitudes, and Acculturation: Exploring the Context of Reproductive and Mental Health 
of Asian-Indian Immigrant Women in the US. Issues Ment Health Nurs. 2017;38(4):301- 
309. 
49. 
Rohit G. Women and Patriarchy in Indian Society. 2022; 
https://leaglesamiksha.com/2022/01/06/women-and-patriarchy-in-indian-society/. 
Accessed July 21, 2022. 
50. 
Emmons KM. Health Behaviors in a Social Context. In: Berkman L, Kawachi I, eds. 
Social Epidemiology. New York, NY: Oxford University Press, Inc.; 2000. 
51. 
Kawachi I, Berkman L. Social Cohesion, Social Capital, and Health. In: Berkman L, 
Kawachi I, eds. Social Epidemiology. New York, NY: Oxford University Press, Inc.; 
2000. 
52. 
McNeill LH, Kreuter MW, Subramanian SV. Social Environment and Physical activity: 
A review of concepts and evidence. Social Science & Medicine. 2006;63(4):1011-1022. 
53. 
Vrazel J, Saunders RP, Wilcox S. An overview and proposed framework of social- 
environmental influences on the physical-activity behavior of women. American Journal 
of Health Promotion. 2008;23(1):2-12. 

25 
IRB NUMBER: HSC-SN-23-0576 
IRB APPROVAL DATE: 02/15/2024 
 
 
54. 
Eyler AA, Baker E, Cromer L, King AC, Brownson RC, Donatelle RJ. Physical activity 
and minority women: A qualitative study. Health Educ Behav. 1998;25(5):640-652. 
55. 
Eyler AA, Matson-Koffman D, Vest JR, et al. Environmental, policy, and cultural factors 
related to physical activity in a diverse sample of women: The Women's Cardiovascular 
Health Network Project--summary and discussion. Women Health. 2002;36(2):123-134. 
56. 
Henderson KA, Ainsworth BE. A synthesis of perceptions about physical activity among 
older African American and American Indian women. American Journal of Public 
Health. 2003;93(2):313-317. 
57. 
Eyler AA, Brownson RC, Donatelle RJ, King AC, Brown D, Sallis JF. Physical activity 
social support and middle- and older-aged minority women: results from a US survey. 
Social Science & Medicine. 1999;49(6):781-789. 
58. 
Hartweg D, Isabelli-Garcia C, McEwen M, Piper R. Being Physically Active: Perceptions 
of Recent Mexican Immigrant Women on the ArizonaMexico Border. Hispanic Health 
Care International. 2012;10(3):127-136. 
59. 
Im EO, Lee B, Hwang H, et al. "A waste of time": Hispanic women's attitudes toward 
physical activity. Women Health. 2010;50(6):563-579. 
60. 
Ball K, Jeffery RW, Abbott G, McNaughton SA, Crawford D. Is healthy behavior 
contagious: associations of social norms with physical activity and healthy eating. Int J 
Behav Nutr Phys Act. 2010;7. 
61. 
Emmons KM, Barbeau EM, Gutheil C, Stryker JE, Stoddard AM. Social influences, 
social context, and health behaviors among working-class, multi-ethnic adults. Health 
Educ Behav. 2007;34(2):315-334. 
62. 
Christakis NA, Fowler JH. The spread of obesity in a large social network over 32 years. 
N Engl J Med. 2007;357(4):370-379. 
63. 
Greaves CJ, Sheppard KE, Abraham C, et al. Systematic review of reviews of 
intervention components associated with increased effectiveness in dietary and physical 
activity interventions. BMC Public Health. 2011;11:119. 
64. 
Johnson M, Jones R, Freeman C, et al. Can diabetes prevention programmes be translated 
effectively into real-world settings and still deliver improved outcomes? A synthesis of 
evidence. Diabetic medicine : a journal of the British Diabetic Association. 
2013;30(1):3-15. 
65. 
Yancey AK, Kumanyika SK, Ponce NA, et al. Population-based interventions engaging 
communities of color in healthy eating and active living: a review. Prev Chronic Dis. 
2004;1(1):A09. 
66. 
Goode AD, Reeves MM, Eakin EG. Telephone-delivered interventions for physical 
activity and dietary behavior change: an updated systematic review. Am J Prev Med. 
2012;42(1):81-88. 
67. 
Mailey EL, McAuley E. Impact of a brief intervention on physical activity and social 
cognitive determinants among working mothers: a randomized trial. J Behav Med. 2013. 
68. 
Marcus BH, Williams DM, Dubbert PM, et al. Physical activity intervention studies: 
what we know and what we need to know: a scientific statement from the American 
Heart Association Council on Nutrition, Physical Activity, and Metabolism 
(Subcommittee on Physical Activity); Council on Cardiovascular Disease in the Young; 
and the Interdisciplinary Working Group on Quality of Care and Outcomes Research. 
Circulation. 2006;114(24):2739-2752. 

26 
IRB NUMBER: HSC-SN-23-0576 
IRB APPROVAL DATE: 02/15/2024 
 
 
69. 
King AC, Castro C, Wilcox S, Eyler AA, Sallis JF, Brownson RC. Personal and 
environmental factors associated with physical inactivity among different racial-ethnic 
groups of U.S. middle-aged and older-aged women. Health Psychol. 2000;19(4):354-364. 
70. 
Young DR, Voorhees CC. Personal, social, and environmental correlates of physical 
activity in urban African-American women. Am J Prev Med. 2003;25(3):38-44. 
71. 
Ainsworth BE, Wilcox S, Thompson WW, Richter DL, Henderson KA. Personal, social, 
and physical environmental correlates of physical activity in African-American women in 
South Carolina. Am J Prev Med. 2003;25(3):23-29. 
72. 
Berg JA, Cromwell SL, Arnett M. Physical activity: perspectives of Mexican American 
and Anglo American midlife women. Health Care Women Int. 2002;23(8):894-904. 
73. 
Ickes MJ, Sharma M. A systematic review of physical activity interventions in Hispanic 
adults. J Environ Public Health. 2012;2012:156435. 
74. 
Garland M, Wilbur J, Fogg L, Halloway S, Braun L, Miller A. Self-Efficacy, Outcome 
Expectations, Group Social Support, and Adherence to Physical Activity in African 
American Women. Nurs Res. 2021;70(4):239-247. 
75. 
Anderson ES, Wojcik JR, Winett RA, Williams DM. Social-cognitive determinants of 
physical activity: the influence of social support, self-efficacy, outcome expectations, and 
self-regulation among participants in a church-based health promotion study. Health 
Psychol. 2006;25(4):510-520. 
76. 
Eyler AA, Brownson RC, Donatelle RJ, King AC, Brown D, Sallis JF. Physical activity 
social support and middle- and older-aged minority women: results from a US survey. 
Soc Sci Med. 1999;49(6):781-789. 
77. 
Vrazel J, Saunders RP, Wilcox S. An overview and proposed framework of social- 
environmental influences on the physical-activity behavior of women. Am J Health 
Promot. 2008;23(1):2-12. 
78. 
Wing RR, Jeffery RW. Benefits of recruiting participants with friends and increasing 
social support for weight loss and maintenance. J Consult Clin Psychol. 1999;67(1):132- 
138. 
79. 
Ismail K, Stahl D, Bayley A, et al. Enhanced motivational interviewing for reducing 
weight and increasing physical activity in adults with high cardiovascular risk: the 
MOVE IT three-arm RCT. Health Technol Assess. 2019;23(69):1-144. 
80. 
Copeland L, McNamara R, Kelson M, Simpson S. Mechanisms of change within 
motivational interviewing in relation to health behaviors outcomes: a systematic review. 
Patient Educ Couns. 2015;98(4):401-411. 
81. 
Hanna MB, J. Indian immigrants in the United States. 2022; 
https://www.migrationpolicy.org/article/indian-immigrants-united-states-2019. Accessed 
July 21, 2022. 
82. 
Atlas Z. Cities with the highest percentage of Indians (Asian) in Texas. 2022; 
http://zipatlas.com/us/tx/city-comparison/percentage-indian-population.htm. Accessed 
July 21, 2022. 
83. 
Mathew N. Exploring the Relationship between Physical Activity and Acculturation in U. 
S. Asian Indian Women Galveston, Texas , United States Graduate School of Biomedical 
Sciences University of Texas Medical Branch 2014. 
84. 
Miller WR, Rollnick S. Ten things that Motivational Interviewing is not. Behavioral and 
Cognitive Psychotherapy. 2009;37(2):129-140. 

27 
IRB NUMBER: HSC-SN-23-0576 
IRB APPROVAL DATE: 02/15/2024 
 
 
85. 
Miller WR, Rollnick S. Motivational Interviewing: Helping People Change. New York, 
NY: Guilford Press; 2013. 
86. 
Samdal GB, Eide GE, Barth T, Williams G, Meland E. Effective behaviour change 
techniques for physical activity and healthy eating in overweight and obese adults; 
systematic review and meta-regression analyses. Int J Behav Nutr Phys Act. 
2017;14(1):42. 
87. 
Brickwood KJ, Watson G, O'Brien J, Williams AD. Consumer-Based Wearable Activity 
Trackers Increase Physical Activity Participation: Systematic Review and Meta-Analysis. 
JMIR mHealth and uHealth. 2019;7(4):e11819. 
88. 
Van Hoye K, Boen F, Lefevre J. The Impact of Different Degrees of Feedback on 
Physical Activity Levels: A 4-Week Intervention Study. International journal of 
environmental research and public health. 2015;12(6):6561-6581. 
89. 
Hartman SJ, Nelson SH, Cadmus-Bertram LA, Patterson RE, Parker BA, Pierce JP. 
Technology- and Phone-Based Weight Loss Intervention: Pilot RCT in Women at 
Elevated Breast Cancer Risk. Am J Prev Med. 2016;51(5):714-721. 
90. 
Hutchesson MJ, Rollo ME, Krukowski R, et al. eHealth interventions for the prevention 
and treatment of overweight and obesity in adults: a systematic review with meta- 
analysis. Obes Rev. 2015;16(5):376-392. 
91. 
Patel MS, Asch DA, Volpp KG. Wearable devices as facilitators, not drivers, of health 
behavior change. Jama. 2015;313(5):459-460. 
92. 
U.S. Department of Health and Human Services. Physical Activiyt Guidelines for 
Americans, 2nd edition. Washington, DC: U.S. Department of Health and Human 
Services;2018. 
93. 
Resnicow K, Baranowski T, Ahluwalia JS, Braithwaite RL. Cultural sensitivity in public 
health: defined and demystified. Ethn Dis. 1999;9(1):10-21. 
94. 
Godin G, Shephard RJ. A simple method to assess exercise behavior in the community. 
Can J Appl Sport Sci. 1985;10(3):141-146. 
95. 
Thomas S, Reading J, Shephard RJ. REVISION OF THE PHYSICAL-ACTIVITY 
READINESS QUESTIONNAIRE (PAR-Q). Canadian Journal of Sport Sciences-Revue 
Canadienne Des Sciences Du Sport. 1992;17(4):338-345. 
96. 
Jacobs DR, Jr., Ainsworth BE, Hartman TJ, Leon AS. A simultaneous evaluation of 10 
commonly used physical activity questionnaires. Med Sci Sports Exerc. 1993;25(1):81- 
91. 
97. 
Miller DJ, Freedson PS, Kline GM. Comparison of activity levels using the Caltrac 
accelerometer and five questionnaires. Med Sci Sports Exerc. 1994;26(3):376-382. 
98. 
Chew LD, Bradley KA, Boyko EJ. Brief questions to identify patients with inadequate 
health literacy. Fam Med. 2004;36(8):588-594. 
99. 
Chew LD, Griffin JM, Partin MR, et al. Validation of screening questions for limited 
health literacy in a large VA outpatient population. J Gen Intern Med. 2008;23(5):561- 
566. 
100. 
Wallace LS, Rogers ES, Roskos SE, Holiday DB, Weiss BD. Brief report: screening 
items to identify patients with limited health literacy skills. J Gen Intern Med. 
2006;21(8):874-877. 
101. 
Idler EL, Benyamini Y. Self-rated health and mortality: a review of twenty-seven 
community studies. J Health Soc Behav. 1997;38(1):21-37. 

28 
IRB NUMBER: HSC-SN-23-0576 
IRB APPROVAL DATE: 02/15/2024 
 
 
102. 
Cohen S, Mermelstein R, Kamarck T, Hoberman H. Measuring the functional 
components of social support. In: Sarason IG, Sarason BR, eds. Social Support: Theory, 
Research, and Application. The Hague, Holland: Martinus Nijhoff; 1985. 
103. 
Sallis JF, Grossman RM, Pinski RB, Patterson TL, Nader PR. The development of scales 
to measure social support for diet and exercise behaviors* 1. Preventive Medicine. 
1987;16(6):825-836. 
104. 
Ball K, Timperio A, Salmon J, Giles-Corti B, Roberts R, Crawford D. Personal, social 
and environmental determinants of educational inequalities in walking: a multilevel 
study. J Epidemiol Community Health. 2007;61(2):108. 
105. 
Williams GC, Lynch MF, McGregor HA, Ryan RM, Sharp D, Deci EL. Validation of the 
"Important Other" Climate Questionnaire: Assessing autonomy support for health-related 
change. Families, Systems, & Health. 2006;24(2):179-194. 
106. 
Valente TW. Social Networks and Health: Models, Methods, and Applications. Oxford: 
Oxford University Press; 2010. 
107. 
Marcus BH, Selby VC, Niaura RS, Rossi JS. Self-efficacy and the stages of exercise 
behavior change. Res Q Exerc Sport. 1992;63(1):60-66. 
108. 
Laforge RG, Greene GW, Prochaska JO. Psychosocial factors influencing low fruit and 
vegetable consumption. J Behav Med. 1994;17(4):361-374. 
109. 
Norman GJ, Carlson JA, Sallis JF, Wagner N, Calfas KJ, Patrick K. Reliability and 
validity of brief psychosocial measures related to dietary behaviors. Int J Behav Nutr 
Phys Act. 2010;7:56. 
110. 
Yaroch AL, Tooze J, Thompson FE, et al. Evaluation of three short dietary instruments to 
assess fruit and vegetable intake: the National Cancer Institute's food attitudes and 
behaviors survey. J Acad Nutr Diet. 2012;112(10):1570-1577. 
111. 
Robinson AH, Norman GJ, Sallis JF, Calfas KJ, Rock CL, Patrick K. Validating stage of 
change measures for physical activity and dietary behaviors for overweight women. Int J 
Obes (Lond). 2008;32(7):1137-1144. 
112. 
Markland D, Tobin V. A modification to the behavioural regulation in exercise 
questionnaire to include an assessment of amotivation. Journal of Sport and Exercise 
Psychology. 2004;26(2):191-196. 
113. 
Sallis JF, Kerr J, Carlson JA, et al. Evaluating a brief self-report measure of 
neighborhood environments for physical activity research and surveillance: Physical 
Activity Neighborhood Environment Scale (PANES). J Phys Act Health. 2010;7(4):533- 
540. 
114. 
Whitfield GP, Gabriel KK, Kohl HW, 3rd. Assessing sitting across contexts: 
development of the multicontext sitting time questionnaire. Res Q Exerc Sport. 
2013;84(3):323-328. 
115. 
Doerflinger, Deirdre M. Carolan. "Mental Status Assessment in Older Adults: Montreal 
Cognitive Assessment MoCA Version 7.1 (Original Version)." The clinical 
neuropsychologist 25.1 (2012): 119-126. 
116. Berstein, I.H., Lacritz, L., Barlow, C.F., Weiner, M.F., & DeFina, L.F. (2011). 
Psychometric evaluation of the Montreal Cognitive Assessment (MoCA) in three diverse 
samples. 
 
117. 
Narayan H. India, a land of many tongues. Thread2017. 
118. 
India To. Indiaspeak: English is our 2nd language. March 14, 2010. 

29 
IRB NUMBER: HSC-SN-23-0576 
IRB APPROVAL DATE: 02/15/2024 
 
 
119. 
Rumbaut RG, Massey DS. Immigration and Language Diversity in the United States. 
Daedalus. 2013;142(3):141-154. 
120. 
Leon AC, Davis LL, Kraemer HC. The role and interpretation of pilot studies in clinical 
research. J Psychiatr Res. 2011;45(5):626-629. 
119. 
Kistin C, Silverstein M. Pilot Studies: A Critical but Potentially Misused Component of 
Interventional Research. JAMA. 2015;314(15):1561-1562.