Patient Centered Health Technology Medication Adherence Program for African American Hypertensives
Phase: NA
Conditions: Hypertension, Medication Non-Adherence
Sponsor: Medical University of South Carolina

 
Patient Centered Health Technology Medication Adherence Program for African 
American Hypertensives 
(9/6/2017) 

ABSTRACT/SUMMARY 
Efforts to improve medication non-adherence (MNA) and blood pressure (BP) control in patients with 
hypertension (HTN) have met with limited success. Innovative approaches are needed that are acceptable, 
sustainable, efficacious, and easily disseminated. There have been no randomized controlled trials (RCTs) 
evaluating the application of theory-driven, patient centered, mobile health (mHealth) technology programs 
among African Americans (AAs) with MNA and uncontrolled HTN. The proposed research will test and refine 
the Smart phone Medication Adherence Stops Hypertension (SMASH) program. SMASH includes multi-level 
components: 1) automated reminders from an electronic medication tray; 2) tailored text message/voice mail 
motivational feedback and reinforcement guided by self-determination theory and based upon adherence to 
daily medication and BP monitoring and 3) automated summary reports and direct alerts to providers. A 6-
month, 2-arm (SMASH vs. enhanced Standard Care [SC]) efficacy RCT will be conducted in 192 AAs (21-59 
years old) with electronic monitor derived MNA and repeated clinic and 24hr BP verified uncontrolled HTN. 
Evaluations will occur at baseline, months 3 and 6, and post-trial follow-ups at months 12 and 18. Specific aims 
are to test the hypotheses that, compared to the enhanced SC cohort, the SMASH cohort will demonstrate 
significantly improved and sustained changes in: 1) Primary Outcome Variables: a) Medication adherence: % 
with electronic monitor-derived adherence scores >0.90; b) BP control: % meeting JNC8 guidelines for BP 
control (resting BP <140/90 mmHg). 2) Secondary Outcome Variables: a) % reaching and sustaining 24-hr 
ambulatory BP<130/80 mmHg; b) % of provider adherence to JNC8 guidelines as measured by timing of 
medication changes and c) patient changes in Self-Determination Theory constructs (e.g., competence and 
autonomous motivation). 3) Exploratory Outcomes: a) moderators (e.g., gender, age, income) and mediators 
(e.g., perceived severity of disease, med side effects, depression symptoms, etc.) of medication adherence 
and BP control; b) cost effectiveness and c) physical risk factor changes (cholesterol, LDL, HgA1c, blood 
glucose). After final follow-up evaluations, focus groups with random sample of SMASH subjects (total n=32) 
and healthcare providers (total n=~12) will assess key user reactions including acceptability, usability, salience 
and aids/barriers to sustainability. Data from RCT and focus groups will be triangulated to further refine and 
optimize SMASH and prepare for a multi-site effectiveness RCT. Our long-term objective is to reduce 
premature mortality among AAs by developing effective and sustainable mHealth chronic disease medical 
regimen self-management programs including medication adherence, bio-function monitoring (e.g., BP) and 
timely bidirectional contact with healthcare providers.  
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

 
 
NARRATIVE 
Interventions that address medication nonadherence among chronic disease patients must be acceptable, 
sustainable, and easily disseminated by clinicians. We will test and further refine a smartphone delivered, tailored 
medical regimen self-management program for African Americans with uncontrolled hypertension that will 
facilitate medication adherence, BP control, and clinician oversight. With demonstrated effectiveness in future 
trials, the intervention will ameliorate the risk of future comorbidities (e.g., hypercholesterolemia, diabetes), 
cardiovascular events (e.g., kidney failure, stroke, heart attack) and associated premature mortality. 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

INTRODUCTION TO REVISED APPLICATION 
The thorough reviews guided our new pilot research on Smart Phone Medication Adherence (MA) Stops 
Hypertension (SMASH) developed for African Americans (AAs).We ran a 3rd feasibility trial (n=24), published 
3 articles (2nd mHealth attitudes survey and results of 2 feasibility trials), made SMASH refinements based 
upon subjects’ post trial feedback and made changes in our approach and analyses. Strengths: high clinical 
significance, no RCTs using mHealth in this domain, focus on both MA and BP control, use of 24-hr BP, rigor 
of using RCT design, time and attention control group and follow-up assessments, intervention theoretically 
driven, use of cultural tailoring and strategies for low literacy, promising preliminary data, cost effectiveness 
analyses, excellent environment and investigators. Weaknesses: Outlined below with Reviewer (R) comments 
in italics followed by our responses. Text changes are noted by a vertical line in the right margin. 
OVERALL IMPACT, SIGNIFICANCE, INVESTIGATOR(S) & INNOVATION: inclusion/exclusion criteria not in 
grant (R1&R2).We apologize for placing too much of that info in Human Subjects. It is now in section D.2 (and 
Human Subjects [1.a.]) Unclear how nonadherence due to smartphone service loss will be handled (R1): In our 
feasibility trials we observed high BP monitoring adherence via phone app (~88%), nonadherence tended to 
occur when cellular service was disrupted. We budgeted for 40% to receive a smart phone or data package to 
cover phone or service loss during the trial (in D.4.) Justify relatively limited age range (21-59 yrs) (R1): We are 
recruiting AAs from a federally qualified health center (FQHC) with sole diagnosis of HTN (n=2,619; mean age 
~45.3 yrs). Majority of those ≥ 60 had multiple comorbidities & JNC8 BP control goals differ for patients <60 vs 
≥60. Concern PI may not have time (25%FTE) to devote to project (R1): Within 2 mos of start date for this 
grant, Dr. Treiber will be covered 50% FTE on grants (R21 & RO1 will have expired; see bio). He has a long 
track record of running successful concurrent trials. An experienced full time project manager has been added, 
Dr. Chandler. Consider adding someone with usability testing background (R1): Dr. Ken Resnicow is a 
consultant with expertise in user centered, iterative design in web/app programs including use of various 
usability evaluation tactics (e.g., expert heuristic & end user think aloud evals, questionnaires; see bio & letter). 
SMASH not highly innovative, been used in other patient groups(R1): Our patient centered design revealed 
significant heterogeneity of influence of cultural heritage/acculturation and numeracy of chronic diseases 
(single vs multi-morbidities) upon MA and other health behaviors within & across ethnic groups. The mHealth 
program tailored to Hispanics is not culturally attuned for AAs. Our mHealth work with AA renal transplant 
patients with HTN, diabetes, etc. led to efforts to address poor MA before multi-morbidities develop. Our long-
term goal is to prevent common events (e.g., stroke, heart attack) & slow progression of common comorbidities 
(e.g., chronic kidney disease, diabetes) due to uncontrolled HTN. SMASH for transplant patients required ~2 
years of changes to become salient to AAs with solely uncontrolled HTN. We found those with only HTN often 
have greater MA problems (in C.1.3) & to be more challenging to establish sustained regimen adherence 
compared to HTNs with multi-morbidities. Experiences during trials & post trial interviews led to an iterative 
process of identifying highly salient motivational factors (values, beliefs, goals) not needed with multi-morbidity 
transplant patients (in C.1.5.) Others have observed similar challenges with single vs multi-morbidity HTN 
patients (in A.2.) This program (nor any earlier iteration) has not been nor is being tested using a fully powered 
RCT, much less within a low-income population & health system (i.e., FQHC). No focus on med nonadherence 
(MNA) mechanisms besides self-motivation or how other diseases & meds affect HTN MA; no lit review on co-
morbidities(R2): We clarified HTNs with comorbidities aren’t recruited (in D.2.) Exploratory analyses of MNA 
mechanisms now include med side effects, stress, depression symptoms, etc. (in D.10.) We added diabetes 
/CVD risk factor changes (e.g., TC, HgA1c) as exploratory outcomes. Recent trials show some newer HTN 
meds lower or at least do not increase these risk factors (in A.2.) APPROACH & ENVIRONMENT: Limited 
description of clinics (R1): 7 of 8 clinics have similar numbers of AAs with uncontrolled HTN and numbers of 
primary providers (MD, PA, NP; M=2.4). Lead site has 7.3 providers & generates ~45% of patient encounters 
(in Facilities & Resources). Clinic (=cluster) in our cluster RCT design will be a random effect in the analytic 
model & account for clinic site differences (in D.10). More details on SMASH focus group protocol stratification 
process (R1): We will identify 2 groups: 16 MA responders &16 partial/nonresponders stratified by clinic, age & 
sex. We will run 3-4 focus groups separately by group classification (in D.7.) Measures of numeracy, usability 
& project evaluation needed; SMASH & control condition descriptions a bit vague (R1): We added measures 
(in D.6.) & reworded SMASH & SC protocols for clarity (in D5-7.) No model to guide analytic approach; how will 
data be integrated to provide cohesive story (R1): We clarified in D.10 our conceptual model is built upon Self-
Determination Theory with competence & autonomous motivation as primary MA mediators. We now include 
socio-demographic (e.g., age, income) & biobehavioral (e.g., med side effects, stress, sleep quality, etc.) 
factors as potential moderators & mediators of MA. Those results will guide an integrated causal model using 
structural equation modeling that will identify key active ingredients of SMASH to guide future refinements.  

SPECIFIC AIMS 
Hypertension (HTN), a major risk factor for renal and cardiovascular disease (CVD), affects ~33% of US 
adults.1,2 Although blood pressure (BP) control (i.e., SBP/DBP <140/90 mmHg) has improved over the past 20 
years, large ethnic/racial disparities continue. African Americans (AAs) have earlier onset and highest 
prevalence rates compared to all other ethnic groups.3-6 Poor medication adherence (MA) remains the leading 
factor in uncontrolled HTN.7-10 Randomized control trials (RCTs) have found that BP self-monitoring, med 
reminding tactics and use of case managers each improve adherence, therapeutic inertia and BP levels (see 
reviews11-13). However, only 40-50% reached BP control and BP often deteriorated after trial cessation. 
Although 24hr BP control is vital for optimal reduction of CVD events,14 relatively few MA RCTs have evaluated 
24hr BP control.11,15,16 Our work and that of others indicate that HTN patients without comorbidities often 
experience greater MNA issues than HTNs with multi-morbidities in part due to lower motivation from low 
perceived disease severity.5,6,17-26 Culturally sensitive, efficacious and sustainable BP control programs are 
needed, especially for AAs with sole diagnosis of HTN before comorbidities ensue. To our knowledge, no RCT 
has monitored, in real time, MNA and resting and 24-hr BP control in this high-risk population.  
Formative Research: Our research with AAs with HTN found a high rate of cell phone use and high receptivity 
to mobile health (mHealth) technology.20,21 We found poor planning and forgetfulness as leading contributors to 
MNA. Health literacy, values and beliefs (e.g., “skipping meds ok if feeling good”, “Gullah root medicine works 
the best”; “I praise God by taking care of his gift of life”) were influential in medical regimen adherence.  
Feasibility RCTs: Feedback from AAs with HTN and their health care providers guided development, pilot 
testing and refinement followed by repeated feasibility RCT testing and refinements of a culturally tailored 
mHealth MA and BP control program for AAs called Smartphone MA Stops Hypertension (SMASH).20-26 
SMASH consists of multi-level components: Patient level components include: a) sequential automated 
reminders from an electronic med tray (blinking light, audio chime, automated call) and b) tailored SMS/voice 
mail that addresses: 1) motivational and social reinforcement to enhance and sustain adherence; 2) BP 
monitoring reminders; 3) HTN education and functional health literacy, tips on talking with doctor, etc. Provider 
level components include: a) weekly summary reports of subjects’ MA and BP levels with JNC8 stepped care 
guidelines and b) phone alerts to clinic nurse managers when verified out of range BPs occur. Our 3 feasibility 
trials (3 mos; 6 mos) with AAs with uncontrolled HTN demonstrated high acceptability, self-efficacy for 
following medical regimen, improved real-time MA, reduced emergency department use and higher 
percentages reaching JNC8 standard for BP control compared to standard of care (SC) cohorts.22-26 SMASH 
appears promising but requires further evaluation and refinement. PA-14-334, Practical Interventions to 
Improve MA seeks testing of novel, theory guided interventions to improve MNA (self-report & objective indices 
required) and inclusion of a biological indicator (e.g., BP) expected to be effected by changes in adherence. 
We propose to conduct a multi-site cluster efficacy RCT with 192 AAs (21-59 years old) with sole diagnosis of 
uncontrolled HTN and verified MNA randomly assigned to a 6-month intervention with 12-month follow-up. 
Evaluations will occur at baseline and months 3, 6, 12, and 18.The central hypothesis is, compared to an 
enhanced SC group, the SMASH group will exhibit significantly improved MA and resting and 24 hour BP 
control over the active treatment period (primary endpoint). 
Specific aims will assess the efficacy of the SMASH intervention on: 
AIM 1) Primary Outcomes: a) Medication adherence: % with electronic monitor-derived adherence scores 
>0.90; b) BP control: % meeting JNC8 defined BP control (resting BP<140/90 mmHg.)  
AIM 2) Secondary Outcomes: a) % provider adherence to JNC8 guidelines measured by timing of med 
changes; b) % meeting 24-hr BP control (BP<130/80 mmHg) and c) increases in self-determination theory 
constructs (i.e., competence & autonomous motivation).  
AIM 3) Exploratory Outcomes: a) moderators (e.g., gender, age, income, etc.) and mediators (e.g., 
competence, autonomous motivation, perceived disease severity, med side effects, depressive symptoms, 
etc.) of MA and BP control; b) cost effectiveness and c) physical risk factor changes (total cholesterol, LDL, 
blood glucose, HgA1c).  
AIM 4) SMASH Refinement: A mixed methods approach will be used including post-study questionnaires 
(e.g., patient/provider satisfaction, usability scales, etc.) and focus groups of 5-6 people with SMASH providers 
(n≈12) and SMASH subjects (16 responders and 16 partial/non-responders) will assess program acceptability, 
usability, salience and aids/barriers to sustainability. Data from the RCT and post trial multi-method evaluations 
will be triangulated to further optimize SMASH and prepare for a multi-site effectiveness RCT. 
Our long-term objective is to develop effective sustainable mHealth programs for HTN and other chronic 
diseases. Dissemination of such programs will help reduce burden of HTN associated health disparities.   

A. SIGNIFICANCE 
A.1. HTN and AAs: HTN, the most commonly diagnosed chronic disease in the US, is an independent risk 
factor for stroke, renal failure, and CVD events.1,2 Unfortunately, racial/ethnic disparities persist with AAs 
exhibiting earlier onset, higher prevalence rates than all other ethnic groups (~39% vs 19-28%) and higher 
rates of uncontrolled HTN(54-70 %) than Whites(47-54%),3-5,27-30 Risk factors for poor control of HTN include 
nonwhite ethnicity, poorer socioeconomic status, and residence in rural southeastern United States.29,30 These 
risk factors are all prevalent in South Carolina,30 and support need for culturally sensitive BP control programs 
for this population at significant risk for stroke, chronic kidney disease, type two diabetes and CVD events.31-36  
A.2. Medication Nonadherence (MNA) and Uncontrolled HTN: MA is defined as the extent to which a 
prescribed dose, frequency and timing of a med are followed.37 Around 20-32% of new prescriptions are never 
filled with HTN (28.4%) being a leading category.38,39 Sustained adherence to HTN meds can control HTN & 
reduce CV events (e.g., stroke, MI).40,41 Recent RCTs using newer HTN meds included in JNC8 guidelines 
(e.g., selective beta 1 blockers, lower dose diuretics, ACE inhibitors, etc.) report reductions in future 
comorbidity risk factors for diabetes and hypercholesterolemia (e.g., total cholesterol (TC), LDL, blood glucose, 
HgA1c).42-44 For example, newer selective beta 1 blockers increase peripheral blood flow which increases 
glucose uptake and disposal and lower dose thiazide diuretics produce less endogenous glucose; both 
promoting increased insulin sensitivity.45 Unfortunately, MNA remains the leading modifiable barrier to BP 
control.7-10 Around 50% of HTNs stop taking meds <12 mos after diagnosis and <65% remain in care after 3 
years.46 Across chronic diseases including HTN, MNA affects ~50% of patients (range: 20-75%).22,25,28,39-41,47,48 
Findings are mixed with some studies indicating HTN patients experience greater problems due to MNA with 
increasing number of comorbidities and meds.49-51 Our work22-26 and that of others5,6,17-19 find MNA is often a 
greater problem among patients with a sole diagnosis of HTN compared to those with comorbidities. 
When timing of dose is taken into account (e.g., meds taken within 3 hr window of designated times), our 
findings22,23 and others,52,53 indicate MNA is even higher. Most previous studies were limited to self-report or 
med possession ratio (MPR) to identify MNA, strategies that are less sensitive than electronic medication 
monitoring. For these reasons, electronic medication monitoring is regarded as the gold standard for 
measuring MNA.54,55 We will use electronic monitoring as a primary index of MNA, one of our primary 
outcomes. We will also explore effects of the SMASH program on changes in diabetes/ hypercholesterolemia 
risk factors (TC, LDL, blood glucose, HgA1c).  
A.3. Causes of MNA: World Health Organization distinguishes MA barriers as intentional (forgetfulness, poor 
planning, regimen complexity, costs, and access issues) or unintentional (adverse side effects, erroneous 
health beliefs).7-9,56 Several recent MA reviews found poor planning and forgetfulness to fill scripts/take meds, 
poor patient-provider communication, affordability, lack of motivation and erroneous health beliefs (e.g., HTN 
not permanent, can be healed) were common problems.55,57,58 Our studies indicate that local practice networks 
(e.g., Federally Qualified Health Centers: FQHCs) which focus upon lower socioeconomic status, underserved 
populations have reduced or eliminated some barriers (e.g., lowered med costs, decreased regimen 
complexity, transportation assistance, use low literacy novella based health education materials). However, 
poor planning and forgetfulness remained primary MA barriers in our studies involving AAs with HTN or 
additional comorbidities.20,21 Our recent work involving AAs with sole diagnosis of uncontrolled HTN revealed 
similar factors associated with MNA including low functional health literacy, poor planning, and forgetfulness, 
but also the need to more thoroughly explore motivating factors for establishing sustained regimen adherence. 
These factors will be used in self-determination theory (SDT) guided tailored SMS motivational and 
reinforcement messages linked to adherence levels to the regimen (in C.1.5; Appx.3). Roles of other known 
sociodemographic and biobehavioral MNA mediators among AAs and/or HTN patients will also be examined 
(e.g., age, income, med side effects, perceived disease severity, stress, patient satisfaction with provider, 
sleep quality, depressive symptoms, etc.)7-10,59-68 (in D6,Table3;D.10.AIM 3). 
A.4. Therapeutic Inertia and Uncontrolled HTN: Therapeutic inertia, the failure of clinicians to appropriately 
intensify therapy in a timely manner, explains, in part, why among adherent patients, HTN often remains poorly 
controlled.69-72 Although therapeutic inertia is a multifactorial problem, provider unawareness of best practice 
guidelines is a major culprit.71-74 Okonofua, et al.,72 monitored for 12 months 7,253 patients with uncontrolled 
HTN who attended ≥4 clinic visits from 44 primary practice sites primarily in SC. Med changes occurred on 
only 13% of the visits at which patients exhibited uncontrolled HTN. Additionally, lack of real-time data as to 
HTNs’ BPs at home and their degree of MNA means important medical decisions are often delayed until the 
next clinic visit that might be weeks or even months away. Thus, the SMASH program includes a practitioner 
component to reduce therapeutic inertia and follow JNC8 treatment guidelines (see D.5.b). 
A.5. RCT BP Control Efficacy Gaps: A number of interventions have addressed MNA among HTN 

populations. Reviews of 133 HTN RCTs ([37 RCTs],11 [78 RCTs],12 [18 RCTs]13) concluded MA reminder 
tactics (often live or automated phone calls), BP self-monitoring (readings brought/mailed/phoned in) and 
education/counseling, individually and/or in combination, often improved MA and resulted in small but 
significant BP declines. Unfortunately, only 40-50% reached BP control and improvements often deteriorated 
after the trial ended. Notably, although 24hr BP is a better predictor of CV morbidity and mortality than clinic 
BPs,14,27,75,76 relatively few MA BP control RCTs have included 24-hour BP.11,14-16 To our knowledge, besides 
our work, no other patient/practitioner guided program has been developed for AAs involving real time med 
reminder tactics, BP self-monitoring and HTN health literacy education guided by behavioral change theory 
using culturally tailored, personalized motivational/reinforcement messages. Although our pilot studies’ results 
are promising (in C1.4), sample sizes were very small and underpowered. In summary, there is a strong 
scientific premise for the proposed project. A significant need remains for evidence-based, cost effective 
strategies that show sustained improvement in MA and BP control among uncontrolled HTNs, 
especially AAs. Our mHealth intervention package requires testing in a fully powered RCT if this 
approach is to be adopted, disseminated and eventually reimbursed via CMS and insurance carriers. 
A.6. Role of mHealth in Adherence Enhancement: mHealth, the use of wireless technology in healthcare, is 
a rapidly growing field in preventive medicine and chronic disease management.77-80 mHealth capitalizes upon 
existing mobile technology infrastructure and the ubiquity of the mobile phone. Mobile phones are used by ~ 
94% of US adults and ~72% own a smart phone81 with ethnic minorities (e.g., AAs at 73%) slightly more likely 
to own a smartphone.81 Our preliminary work corroborated the high prevalence of standard feature and smart 
mobile phone usage among AAs and indicated that AAs are very receptive to mHealth programs.20,21 
Indirect monitoring using electronic devices (pill trays, vials, smart phone apps) provides various med 
intake reminders (e.g., blinking light, buzzer, SMS, voice mail). These devices have been found helpful among 
patients who are intent upon but forgetful about taking their meds or only moderately motivated.10 Research 
has verified indirect electronic monitoring methods (e.g., MEMS pill vial cap) reflect actual intake in such 
individuals and do not increase adherence artificially.82-85 A recent (2014) review of 37 MA electronic device 
trials (32 RCTs, 5 nonrandomized) involved 14 chronic conditions (e.g., HTN, diabetes, asthma, heart failure, 
COPD, etc.), and had a median trial duration of 5.5 mos.86 Compared to control groups, the majority of studies 
that provided solely reminder signals with or without additional feedback related to pill intake (e.g., LED with pill 
number to take, time elapsed since last dose, etc.) failed to show statistically greater improvements in MA.80 
Programs which integrated electronic device data with pertinent health related feedback by healthcare 
providers (e.g., relationship of MNA to physical risk factors) showed greater improvements than control groups 
(84.8% vs. 68.4 %, respectively). Other programs which focused upon intake reminders/educational 
information (e.g., phone alerts, SMS messaging), without monitoring med intake have, typically been 
unsuccessful in enhancing non self-report based MA and/or BP control.80,87-89 Our 3 SMASH feasibility studies 
involving AA HTNs included all of these components. All resulted in high acceptability, usability, improved MA 
and JNC8 BP control (in C.1.4) and if sustained, might ultimately improve long-term clinical outcomes.22,23 Our 
proposed 12-month follow-up will address the sustainability of SMASH.  
B. INNOVATION 
This revised application seeks to challenge and shift current clinical practice for HTN by testing and optimizing 
a mHealth program that is practical, sustainable and capable of large-scale dissemination. The research is 
innovative in several ways. To our knowledge it is the first mHealth program for AAs to: 1) focus upon those 
with sole diagnosis of uncontrolled HTN and poor MA in efforts to curtail HTN’s devastating cascade of 
damage to organ systems and vasculature contributing to future comorbidities and events (e.g., stroke, heart 
attack, CVD, diabetes, chronic kidney disease, etc.31-36); 2) Apply synergistic constructs from behavioral and 
technology application theories to develop a culturally tailored medical regimen self-management program via 
an iterative design process involving repeated guidance from AA patients and healthcare providers; 3) use 
real-time measurements of MA and BP data to facilitate immediate feedback, HTN educational messages, and 
automated, culturally tailored motivational/reinforcement messages aimed to enhance self-efficacy and 
sustained motivation for adherence; 4) include both resting BP and 24-hr BP monitoring as outcome variables 
and 5) provide healthcare providers personally designed, automated streamlined reports to enable faster 
changes in med regimens and achieve earlier sustained BP control. Since the first submission, we completed 
the third feasibility trial and further refinements including transitioning from generic SMS messages to an 
automated system that delivers culturally tailored, individually personalized motivational and reinforcement 
SMS and voice mail messages based upon degrees of MA with a library enhanced over the past year of >600 
messages (see C.1.5.) In summary, our proposal is both novel and timely offering a practical self-management 
program which will help establish sustained medical regimen adherence and control of HTN rather than waiting 

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autonomous motivation by linking subjects’ behavioral changes (i.e., increased MA) to their personal values, 
beliefs and goals, including culturally specific drivers such as faith, family and community. Autonomously 
motivated individuals exert more effort and persistence in their behavior change, which is vital for managing 
chronic diseases due to lifelong nature of the medical regimen behaviors. The patient must devote daily time 
and effort (e.g., taking correct meds on time, self-monitoring biofunctions) and exhibit persistent vigilance to 
sustain these efforts the rest of their life. Numerous studies have shown that, behavior changes rooted in 
autonomous motivation are more likely to be sustained than change stemming from controlled motivation via 
external or negative internal pressures.95-97  
There are reliable and valid instruments to measure SDT constructs that we will be using.97,101 Our health 
communications consultant, Dr. Ken Resnicow, has expertise in development of SDT messages and use of 
SDT measures102-104, as well as user centered, iterative design in development of web enabled programs and 
apps. This includes use of mixed method approaches such as expert heuristic and patient think aloud usability 
evals, key informant interviews, focus groups and questionnaires. He assisted us in the last 2 trials in these 
evaluations and subsequent refinements including expansion of our tailored motivational messages library. He 
will continue to do so and aid in analyses of potential moderators and mediators of adherence to SMASH (see 
biosketch and support letter). 
C.1.3 Mobile Phone and mHealth Technology Attitudes: We 
gave a brief survey to 3 groups of AAs with HTN (kidney 
transplant patients, FQHC patients, recent stroke patients).20,21 It 
assessed use of mobile devices and attitudes and preferences 
toward mHealth. As shown in Table 1, across the 3 groups, an 
average of 91% owned a cell phone and 50.6% owned a smart 
phone with internet activation, which mirrored the U.S. adult 
population at times of administration. They were facile in use of 
cell phones (i.e., collectively, 67% sent /received SMS, 36% 
browsed internet, 34% sent/received email,42% downloaded 
apps). Poor planning and forgetfulness were leading contributors 
to MNA; med side effects were not reported as a common cause 
of MNA.20,21 Only 69% reported 100% MA over previous 2 weeks 
using the Modified Morisky Scale,105 a scale we will use in this 
study (Appx. 1). Importantly, self-reported MNA progressively decreased as greater negative impact of 
uncontrolled HTN increased (e.g., MNA 4% among kidney transplant patients with HTN, chronic kidney 
disease, diabetes, etc. vs. 64.4% among Fetter FQHC HTN patients without history of CV related 
events).The groups also received a demo of the SMASH program (see Fig.1). Although only 10.8% had a 
priori knowledge of mHealth, 86% were receptive to using SMASH, especially if it was free. Most (79%) had 
someone at home who could help them use the system if needed. Most felt SMASH would help them follow 
their doctor’s directions (86%) and enable their doctor to make more rapid adjustments to their regimen 
(88%).20,21 Based on above findings and additional guidance from AAs with HTN and healthcare providers, we 
further refined the SMASH prototype guided by tenants of SDT to enhance competence and autonomous 
motivation for sustained adherence with med intake and BP monitoring. We then conducted 3 feasibility trials, 
each followed by post-trial interviews or focus groups with subjects and providers for refinement guidance. 
C.1.4 SMASH Feasibility RCTs:  
SMASH AA Kidney Transplant Patients with HTN Trial #1: We first ran a 3-mo feasibility RCT in 20 AAs 
with uncontrolled HTN who were also kidney transplant recipients. They were verified as having uncontrolled 
BP from clinic records followed by a BP screening. Majority had med possession ratios (MPRs) >0.85. Thus, 
we identified patients as nonadherent (i.e., adherence score <0.85) to their med regimen based on a month-
long screening using an electronic med tray (Maya MedMinder™) with reminder functions disabled. We used a 
modification of Russell et al.’s algorithm52 [see Appx. 2]) which considers dose timing in addition to dose 
taking, especially important when taking meds with especially short half-lives.20,21 We modified the algorithm to 
allow for dosing schedules other than twice daily. Subjects were instructed that to be fully adherent, their meds 
had to be taken within a 3 hr window centered on the prescribed dosing time (within 90 min before or 90 min 
after designated time.) A dose taken within the 3 hr window resulted in a full score for that dosing time; a dose 
taken outside the 3 hr window but within 6 hr window resulted in a half score for that dosing time; a missed 
dose resulted in a score of 0. Each subject received a score from 0-1.0 per day and scores averaged over the 
month. Despite self-reporting high MA, having MPRs often ≥0.85 for previous month and knowing their exact 
times of intake were being monitored, they had a mean adherence score of 0.63 (range 0.26-0.94.) Seventy-

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today and plan some special time with your grandkids”. For further examples of personalized messages based 
on patient responses, see Appx. 4. Positive feedback from SMS messages and phone delivered graphic 
representations of adherence patterns and BP control over time, intends to increase SMASHer’s perceived 
competence in engaging in the program and link their adherence behaviors with their values, beliefs and goals.  
D. Research Design and Methods  
D.1. Design and Randomization: Subjects will be drawn from Fetter Health Care Network (FHCN). It is the 
sole FQHC center in the 4-county area (8 clinics)and provides ~60% of routine AA healthcare in the 4 county 
area.107 A support letter from the FQHC network is included. EMR files indicated they have ~2,619 AAs (21-59 
yrs old; mean age=45.3yrs) with sole diagnosis of uncontrolled HTN. We will use the 8 practice sites in a 2 arm 
RCT design (n=192) with clinic as unit of randomization and patient as unit of analysis. All primary healthcare 
providers across the 8 clinics have agreed to participate if selected. Each clinic has a minimum of 2 primary 
providers (at least 1 MD and 1 or more NPs and/or PAs per clinic).Thus, 2 providers per site will be recruited. 
Each will have 12 of their patients recruited (24 per clinic). Given our ~90% participation rate in previous FQHC 
studies25,108,109 and 93% SMASH participation rate, we anticipate no recruitment problems.The Medical 
University of South Carolina  Family Medicine and Internal Medicine clinic  population will be an additional 
recruitment resource if needed. 
D.2. Participants: With consideration of the relevant biological variable of gender, we will recruit 192 AA 21-59 
yr old uncontrolled HTNs with equal numbers of males and females that meet the following inclusion/ exclusion 
criteria: 1) SBP ≥140 mmHg on most recent clinic visit over last 12 mos and at BP screening and recruitment 
visits; 2) MPR <0.85 over last 3 mos; 3) 24-hour SBP ≥130mmHg (HTN cutoff) to help rule out white coat 
HTN.76,110 SBP used as selection variable since most AA HTNs <60 have systolic or combination systolic/ 
diastolic HTN and for most patients, controlling SBP also results in DBP control;27,111,112 4) no other known 
chronic diseases (e.g., diabetes, chronic kidney disease (GFR <50ml/1.7 m2/min),cancer, renal dialysis, heart 
attack, coronary artery bypass, arterial stent, substance abuse (e.g., >21 drinks/week), psychiatric illness, 
Beck Depression Inventory113-115 >13, able to speak, hear and understand English; take own BP and meds; 6) 
owns smart phone with current data plan; 7) primary care MD’s assent patient able to participate and 8) no 
planned pregnancy or vulnerable population (e.g., pregnant or nursing women, prisoners).  
D.3. Recruitment: Proposed procedures were successful in our SMASH pilot trials.22,23,25,26 Practice sites will 
prepare a list of eligible patients and Dr. Chandler (project manager) will contact them, explain the study and, if 
interested, schedule the screening/recruitment visit. As part of design rigor, other MUSC staff will conduct the 
evaluations below using established protocols. They will remain blinded as to patients’ group status throughout 
study (i.e., baseline, 3 and 6 months, and post-trial follow-ups at 12 and 18 months).Subjects who develop any 
comorbidities over the study period will remain in the trial and all meds will be monitored.  
D.3.a. Resting and 24-hr BP screening: After obtaining informed consent, resting BP protocol will be 
conducted using our established protocol with the previously validated BpTRU device.116 If SBP≥140 mmHg 
from last 2 readings of 10 min protocol, they will continue with screening: height, weight and waist/hip ratio 
will be recorded (BP and anthros protocols in Appx. 5 and 6). Based on their preference, a set of 
questionnaires will be given orally or read on their own (see D.6 Measures; Table 3; copies in Appx. 7-21). 
They will have the option of using their smart phone, TACHL provided tablet, or paper copy version. They will 
then wear the previously validated117 SpaceLabs 90207 BP monitor for 24 hrs using our established 
protocol.118-120 Protocol and criteria for acceptable readings, generating 24-hr averages, etc. are in Appx. 22. 
Only those with 24hr SBP ≥130 mmHg will proceed to the MNA identification phase below.  
D.3.b. MNA Identification Phase: Subjects will be shown how MedMinder™ works and demonstrate 
proficiency in loading and activating the device. They will be told their doctors will receive summary reports on 
their med intake patterns. The tray plugs into a standard 110v outlet, has 28 compartments allowing up to 4 
dose times per day for 7 days, and is capable of providing escalating reminder signals (described in D.5.a). 
Reminder functions will be disabled for the 1-month screening phase. The nurse manager (or project 
manager, Dr. Chandler) and subject will program the MedMinder for dosing times (example of subject’s 24-hr 
MedMinder activity in Appx. 23). Subject will receive written and oral instructions on MA criteria (i.e., all meds 
taken within 180 min window centered on prescribed dosing time).SMASH app has auto call feature for TACHL 
service line for technical issues. Time and date stamped opening and closure of the tray’s compartments are 
relayed via GSM wireless cellular transmitter/receiver to MedMinder™ server for processing. The encrypted 
data are sent to a HIPPA-compliant server database housed in the TACHL center. The MA formula will be 
used to calculate MA scores.22,23,52,121(see Appx. 2) Only subjects with MA score <0.85 over the 4 week 
screening and whose subsequent resting and 24-hr SBP evaluations reconfirm uncontrolled HTN will 
be eligible for enrollment into the RCT. Dr. Mueller will randomly assign the 8 sites to either SMASH or 

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(internal validity) we will control for attention exposure by sending SC subjects automated SMS messages on 
topics related to healthy lifestyle behaviors (diet, physical activity) but not related to MA or HTN functional 
health literacy. Message length and frequency will be of same length as the personalized messages delivered 
to SMASHers. To account for time SMASHers measure their BP, the SC subjects will receive, every 3 days, an 
automated SMS directing them to different 2-3 minute video/YouTube™ clips on healthy lifestyles. For those 
who prefer hard copy material, brochures (esp. novella format) will be mailed weekly across the 6-month trial 
(examples of SMS, voice mails, video clip links and brochures can be found in Appx. 29).  
D.6. Measures: Table 3 presents all outcome variables, questionnaires and timing of administration. Most 
scales have been used with 21-59 yr old AAs and have established psychometrics. We provide brief 
psychometric information (e.g., internal consistency, test-retest reliability) (see Appx.1, 7-21, for copies and 
additional psychometrics). We will assess SDT constructs (competence/self-efficacy; MA Self-Efficacy Scale 
[Appx. 7]) 101,123,124 & autonomous motivation [Treatment Self-Reg. questionnaire; Appx. 8],97,125 cultural values, 
beliefs and life goals,106 (Appx. 14), self-reported MA (Morisky scale, Appx. 1),105,126,127 and MPR (formula in 
Appx.30).128 We will assess sociodemographic, biobehavioral and disease attitudes/knowledge variables which 
have been identified as potential mediators of MA7-10,60-68 including HTN knowledge (Appx. 9),129,130 health 
literacy and numeracy (Test of Functional Health Literacy scale, Appx.10),131-133 med side effects (Appx.11),134 
quality of life (SF-8, Appx 12),135 depression symptoms (Beck Depression Inventory, Appx.13),113-115 stress 
(Perceived Stress Scale, Appx.15),136,137 sleep quality (Pittsburgh Sleep Quality Index; Appx 16),138,139 
perceived disease severity (Illness Perception Questionnaire, Appx.17),140 and patient satisfaction with MD 
(Quality MD/Patient Interaction, Appx.18).141 These questionnaires will be given at baseline and mos 3, 6, 12 
and 18. Satisfaction and usability scales will be completed at mo 6 (System Usability Scale, Telemed. 
Satisfaction and Usability Scale, Mobile App Rating Scale, Appx. 19-21).142-147 All intervention tactics cease for 
both groups at end of 6-mo trial. Follow-up visits will occur at mos 12 and 18. Per SC, all subjects will have 
blood drawn for bioassays including TC, LDL, HgA1c and blood glucose at baseline, mos 6, 12 and18.  
D.7. Post-Trial Follow-up Focus Groups: Focus groups will be run after the final follow-up evaluations by 
Drs. Nemeth, Chandler & Treiber. To help ensure robust and unbiased results, purposive sampling will be used 
to recruit 32 SMASHers based upon MA, termed responders (MA score >.90) or non/partial responders (MA 
score <.90) based upon their cumulative adherence score (MedMinder 6 mo score & MPR level across follow-
up). Groups will also be stratified by sex, age group (<40; >40) and practice site (4 per site). The 16 subjects 
from each group will be divided into groups of 
4 to 5 (i.e., 3-4 focus groups). A semi-
structured interview guide with topic area 
probes will cover expectations, experiences, 
adherence, motivation, SMASK system 
usability and overall satisfaction. We will 
explore suggestions for improving the SMASK 
app content and features, tray/BP device 
usage, quality of SMS, and possible future use 
of motivational interviewing booster calls, etc., 
especially among non/partial responders. 
The 8 SMASH primary providers and 4 
nurse managers from the 4 SMASH sites will 
engage in a focus group (1 for providers; 1 for 
nurses). We will assess attitudes, beliefs, 
aids/barriers to use, feedback on retention, 
impact on therapeutic inertia and other practice 
considerations. Focus groups will be audio 
recorded and field notes written to note any 
reflexive findings and initial impressions. 
Recordings will be professionally transcribed, 
verified for accuracy and imported to NVivo 
11.0 (QSR International PTY, Doncaster, 
Victoria Australia) for analysis. 
D.8. Sample Size Justification & Power 
Calculations: For AIM 1: Sample size/power 
calculations were based on two-sided 
Table 3. Outcome Variables & Measurements/Instruments Used 
Outcome Variables  Measurements/Instruments Used (Cronbach’s α) 
Time points 
Primary Outcomes 
 
MA 
MedMinder (time-stamped) primary measure. 
Daily for 6 mos 
Self-report (Morisky Medication Adherence Scale [.76-.83] 
(Appx.1)). 
Baseline,3,6,12,18 mos 
Med Possession Ratio [MPR] (Appx.30). 
BP 
Resting SBP (Appx.5). 
Baseline,3,6,12,18 mos 
Secondary Outcomes 
Therapeutic Inertia 
Provider adherence to JNC8 goals: Timely med changes (date of 
med change following MA & BP feedback). 
weekly SMASH reports 
(SMASHers) and from clinic 
visits for all subjects 
Ambulatory BP 
24-hr Ambulatory BP with SpaceLabs 90207 (Appx.22). 
Baseline,3,6,12,18 mos 
SDT constructs 
TSRQ Autonomous Self-Motivation (α.81-.84)(Appx.8)97,122 
Baseline,3,6,12,18 mos 
Perceived Competence Scale (MASES-R) (.92, test-retest [3 
mos.] .51) (Appx.7).101,123,124 
Exploratory Outcomes  
Cost effectiveness 
Costs of additional personnel time, SMASH devices, ED visits, 
unplanned outpatient visits & hospitalizations, workdays lost. 
First 6 mos of trial & 
through post-trial follow-ups 
Physical Risk 
Factors 
TC, LDL, HgA1c, blood glucose from FQHC standard care via 
MedCorp (intra-assay variations all <5%; inter-assay variations 
3.3% to 6.6%) 
Baseline,6,12,18 mos 
Potential MA 
Mediators  
HTN Knowledge (.70) (Appx.9);129,130 Short Test of Functional 
Health Literacy (S-TOFHLA)(.68) (Appx.10);131-133 SF-8(α.87) 
(Appx.12);135 Med Side effects (Appx.11);134 Adverse events; 
Pittsburgh Sleep Quality Index (sleep quality) (.83; test-retest 
[1mo,12 mo] .85, .68) (Appx.16);138,139 Beck Depression 
Inventory (BDI) (0.82-0.92); (Appx.13);113-115 Perceived Stress 
Scale (PSS) (.84-.86; test-retest [2 day] .85)(Appx.15);136,137 
Illness Perception Questionnaire (IPQ-R; perceived disease 
severity);.84, test-retest [3 weeks,6 mos].74,.74)(Appx.17);140 
Questionnaire on Quality of Patient & Physician Interaction 
(QQPPI)(Appx.18).141 
Baseline,3,6,12,18 mos 
Values/Beliefs/Goals  Values, Beliefs, Goals (test-retest [1 mo].85) (Appx.14).106 
Baseline,3,6,12,18 mos 
Anthropometrics 
Ht./Wt./Girth (Appx.6). 
Sociodemographics Age, education level, income, type of healthcare insurance 
Baseline 
Feasibility 
Recruitment and Retention rates. 
End of trial 
System Usability 
System Usability Scale (Appx. 19);146,147 Patient/Provider 
SMASH/SC Treatment Satisfaction & Usability Scale (TSUQ) 
(α.82-.96, test-retest [1wk] .98) (Appx.20);144,145 User Version of 
Mobile App Rating Scale (uMARS) (.90, test-retest [2, 3 mos] .66, 
.70) (Appx.21).142,143 
At 6 mos (All subjects) 
After all subjects complete  
6 mos trial (Providers) 
Process/uptake 
Patient level (e.g., connection/reloads of MedMinder, BP uploads 
via phone & opening of messages /education info) & provider 
level (e.g., opening of patient summary reports & phone alerts). 
First 6 mos of trial 

Cochran-Mantel-Haentzel chi-square tests of differences in % of patients being >0.90 med adherent and % of 
patients within JNC8 guidelines for BP control (<140/90 mmHg) at the 6 month visit (primary endpoint) 
between the two groups (SMASH; enhanced SC). Type I error rate was 0.05 (two-sided). Sample size was 
adjusted to account for the cluster randomization scheme, using variance inflation factor (VIF) method.148 
Power and sample size estimates were performed for within-clinic sample sizes of 22 subjects for 4 clinics per 
group, assuming ICCs ranging from 0.0 to 0.05.The ICC from our feasibility trials for primary outcomes of 
electronic med tray based MA and SBP was estimated at 0.04. For an ICC of 0.04 the proposed sample size of 
22 per clinic and 4 clinics per group provides at least 90% power to detect a difference in the assumed 6-
month MA/BP control rates between the 2 groups (difference of ≥30% between SMASH and SC based on 
feasibility trials’ results).22,23,25,26 For the proposed study, for calculation of the VIF we used the conservative 
absolute ICC value of .04 for a final sample size 176. We inflated that by 10% (N=192) to account for greater 
than expected attrition across the trial. Conservative estimates for expected MA (or BP control) proportions 
were used for power calculations; proportions observed in our SMASH feasibility studies were 89% vs.0%, 
N=19 for MA based upon MedMinder22,23 and for resting SBP, an average of 90% vs. 10% for the three trials 
lasting 3 and 6 months and the recent 12-month follow-up (n=19,22 n= 22,25n= 24,23, n=19,22).For secondary 
continuous outcomes of 24-hr BP (and MPR derived MA scores) for longitudinal analyses [assuming 4 
intervention time points (months 3, 6, 12, and 18), level of significance = 0.05 (two-tailed), correlation among 
repeated measures (ICC ≤ 0.5)], we will have 90% power to detect a 0.48 standardized effect size (i.e., 
Cohen’s d effect size). A standardized effect size of 0.48 sd is equivalent to a raw effect size ranging from 2.4 
to 4.3 mmHg (raw scale units) for difference in SBP change from baseline between the groups for a range of 
sd from 5.0 to 9.0 mmHg, based upon our SMASH feasibility data.22,23,25,26 For resting DBP based upon our 
SMASH findings, this equates to a difference of 1.3 to 3.3 mmHg assuming sd ranging from 2.0-5.0 mmHg. 
SMASH findings for the tray derived monthly MA scores revealed a difference in MA score changes between 
the groups from baseline to 3 month of 28% (sd=6.2).22,23 Assuming similar adherence in both groups through 
the 6-month trial, we will have at least 94% power to detect differences in adherence change scores as small 
as 10% (with sd up to 15).  
For AIMs 2: secondary outcomes (changes in SDT constructs [i.e., competence & autonomous motivation], % 
reaching & sustaining 24-hr BP control [<130/80 mmHg], therapeutic inertia (i.e., % making med change in 
patient’s EHR & script delivery to patient or pharmacy within 24 hours of subject’s clinic visit and/or receiving 
BP info report)72 and AIM 3: exploratory outcomes (cost effectiveness; changes in TC,LDL,HgA1c, blood 
glucose) in the intent-to-treat sample, we have 80% power to detect a difference of 0.53 sd between the 2 
groups assuming  = 0.05 (Type I error rate), two sided; independent sample t-test comparison of means; 
equality of variance between groups. For 24-hour BP, we will have > 85% power to detect a 30% difference in 
% reaching 24-hr BP control between groups. Our 24-hr BP data from a subgroup (N=12) of FQHC AAs in the 
feasibility trial found 85% of the SMASH group vs 25% of the SC group achieved 24-hr BP control at 6 mos. 
D.9. Data Management & Quality Control: Quality control checks of anthropometrics/BP evaluations & 24-hr 
BP protocol delivery will be run on random selection of 10% of subjects per mo & protocol retraining conducted 
as needed. Questionnaire data will be directly captured via REDCap (HIPAA compliant, web-based app) & 
overseen by Mr. Patel and Dr. Mueller. Clinic data (e.g., anthropometrics, BP) & EMR derived data (e.g.TC, 
HgA1C) will be double entered with discrepancies resolved by Mr. Patel. Data will be reviewed on twice-
monthly basis. Outlying, inconsistent data values, as well as missing data, will be targets of the data quality 
review. Issues will be communicated to Drs. Treiber, Chandler and Mueller for resolution.  
D.10. Quantitative Analyses: AIM1 Primary outcome measures are % of subjects with >0.90 MA from 
MedMinder and % within JNC8 clinic resting BP guidelines (<140/90 mmHg). Secondary analyses will 
assess resting & ambulatory BP levels (e.g., 24-hr, daytime/nighttime BP level changes) & MA indices (i.e., 
MPR score changes). Intent-to-Treat (ITT) sample analyses will be used along with multiple imputation 
methods for missing end-of-study outcomes.149,150 To assess relationships between intervention outcomes and 
intervention status (SMASH or SC) at end of the active trial period (6-mo visit, primary endpoint), two-sided 
Cochran-Mantel-Haentzel chi-square tests for unadjusted differences in proportions will be used. Adjusted 
differences in proportions at the 6-mo visit will be compared using logistic regression. To assess relationships 
over time, we will use a generalized linear mixed models (GLMM; generalized estimation equation [GEE]–type 
models) analytic model with group (SMASH vs SC) & time (3, 6, 12 &18 months) included as fixed effects and 
FQHC practice site as a random effect to account for clustering within FQHC practice site/MD.151-153 In the first 
set of models, baseline measurement of the dependent variables (e.g., MA or BP levels) will be included as 
adjustment variable. The test of primary interest is F-test for the treatment x time interaction, which will reflect a 
difference in change between the 2 groups over the study. If a statistically significant treatment x time 

interaction is found, we will obtain odds ratios for SMASH vs SC groups at each of the study time points.  
A mixed effects model (MEM) will be used to compare the primary continuous outcome measures (e.g., 
tray or MPR derived MA scores or BP levels) for the two groups over the study period. Modeling will be carried 
out as described above. We will estimate resting and 24-hr BP changes and MA (MPR) changes for each 
subject over the trial (baseline, 3, 6, 12 &18 months) and the within subject longitudinal trajectories (e.g., 
slopes) and summarize as the mean longitudinal trajectory within each group. ICCs and variance estimates will 
be obtained of efficacy outcomes and covariance structure of the longitudinal scores for determination of 
sample size (and hence adequate power) for a future effectiveness RCT. 
AIM 2 Secondary outcomes of changes in SDT constructs competence & autonomous motivation, % provider 
adherence to JNC8 guidelines (med changes based upon JNC8 guidelines made in EHR & script delivery 
within 24 hrs) & 24-hr BP will be assessed using GLMM with these outcomes as separate dependent variables, 
group as independent variable & primary outcomes (resting BP & MA) & clinical & sociodemographic factors 
included as adjustment variables. Modeling will be carried out as described above.  
AIM 3 Exploratory outcomes of changes in metabolic syndrome /CVD risk factors (TC, LDL, blood 
glucose and HgA1c) in relation to intervention group with type of med (low vs high dose diuretics; old vs new 
selective beta1 blockers, etc.) as covariates will be assessed using MEM as described above in AIM1. 
Cost-effectiveness analyses will be run using established methodology for economic evaluation of electronic 
drug monitoring for MNA.154 Data will be collected on incremental direct and time cost SMASH program adds to 
enhanced SC for facilitating MA and BP control. This includes personnel costs for referral & BP/ MA screening, 
all supplies and equipment used (MedMinders, BP devices, smart phones/ data packages) and costs of 
additional meds beyond SC. Value of project manager’s time will be included in attending to patient assistance 
calls, verification of out of range BPs, etc. Sensitivity analyses will estimate cost changes related to different 
types of personnel time needed to perform her tasks. We will define benefits as difference in cost of health 
services use and lost worked days between SMASH and SC groups. We will compare costs of emergency 
department (ED), outpatient and hospital visits during the 6-month trial and most importantly, the 12 months 
following trial completion. We will use estimates from the Healthcare Cost and Utilization Project145 for ED and 
hospitalization and the Medical Expenditure Panel Survey144 (for outpatient and individual out-of-pocket costs) 
to value healthcare use costs in each group. Thus, healthcare costs will be evaluated at institutional provider, 
third party payer and individual level and all costs adjusted using inflation adjustment from Bureau of Labor 
Statistics.155 We will estimate cost of lost worked days during the 6-mo trial and12-mo follow-up and reported 
baseline income. We will assess differences in means, medians and quartiles based on distribution of the 
variables. As we did in another telehealth project, we will use GLM with appropriate distribution to examine 
association of SMASH with patient level healthcare costs and patient lost income adjusting for patient 
demographics and comorbidities.156 We will conduct sensitivity analyses by estimating different healthcare 
costs and income models while adjusting for clinical outcomes (e.g., % with JNC8 BP control; % with 24-hr BP 
control). We will do the same for healthcare utilization and lost workdays using a count model (Poisson or Neg 
Bin if over dispersion occurs or zero-inflated if many zeros are present). We will perform a comparison of 
SMASH cost with changes in clinical outcomes to provide cost-effectiveness ratios for clinical outcomes. 
Exploratory Moderator Analyses: Our conceptual model will guide moderator analyses of MA and BP control 
using logistic regression with >90% MA or BP control at 6 months as dependent variable and the GLMM/GEE 
model over the entire study (measurement times 3, 6, 12 and 18 months). Modeling will be carried out in a 
sequential fashion. Initial set of models will first be adjusted for sociodemographics (age, gender, education, 
marital status, income), autonomous motivation and biobehavioral factors (e.g., stress, sleep quality, 
depressive symptoms, med side effects, etc.).If needed, models will be further adjusted for new comorbidities 
(e.g., diabetes) and associated additional meds. Effect modifications of covariates (moderators) will be 
examined through inclusion of a covariate-by-group (SMASH vs SC) interaction term in the multivariable 
models.67 We are especially interested in the interaction of treatment by gender, as well as SES and 
autonomous motivation. 
Exploratory MNA Mediation Analyses: Potential mediators will be examined individually and subsequently in 
a multivariable model. Exploratory analyses will follow modifications suggested by MacKinnon, Fairchild and 
Fritz157 of the causal steps approach developed by Baron & Kenny.158 Analyses will be guided by our 
conceptual model framed upon change scores in SDT constructs (competence & autonomous motivation) 
followed by MNA mediators identified in the empirical literature including biobehavioral (e.g. stress, med side 
effects, depression symptoms, sleep quality, perceived disease severity, doctor-patient  relationship, quality of 
life, HTN knowledge/beliefs) and process /uptake features (e.g., opening of motivational/reinforcement 
messages/education info, BP graph uploads via phone, patient SMASH (or SC) usability and satisfaction scale 

scores, mobile app usability scale score). These results will be used in exploratory structural equation 
modeling with outcomes of sustained MA and BP control. Those findings will further guide SMASH refinement 
for a future effectiveness RCT. Dropout rate is an important issue. We will assess reasons for dropout and 
compare groups for missing outcome measures using logistic regression modeling. If >10% of data are 
missing, we will likely add an intermediate evaluation point in a future RCT to provide more data for use in 
endpoint imputation. Frequency distributions of adverse events & serious adverse events will also be obtained. 
Proportions within categories of AEs/SAEs for the SMASH vs. SC will be compared via chi-square analyses. 
D.11. Qualitative & Mixed Methods Analyses: As in our other recent studies,159-163 we will use the constant 
comparative method of qualitative analysis derived from constructivist grounded theory.164,165 This approach 
acknowledges researchers’ prior knowledge and influence in the process, supports and provides guidelines for 
building a conceptual framework to understand interrelations (e.g., what and how) between constructs. NVivo 
11 will be used to identify common themes constructs regarding MA, BP self-monitoring, etc. Iterative coding 
will be conducted by Dr. Chandler to identify thick descriptors of informants’ responses, refine theme 
classifications, and impose a data-derived hierarchy of nodes. Interrelations between individual classifications 
(e.g., gender, age, responder vs partial/non responder) and themes will be examined for relationships. To 
evaluate reliability and validity of the conclusions, Dr. Nemeth will code a random selection of 20% of these 
cases and conduct member checks to ensure validity of the findings. Drs. Chandler and Nemeth will use 
reflection and a process of immersion and crystallization166 to reconcile any differences and reach consensus. 
Once no new themes emerge, thematic saturation will have been reached,167 We will compare and contrast 
themes from participants and providers. The quantitative and qualitative data sources will be analyzed in a 
mixed methods sequential triangulation approach.168 We will refine SMASH content, delivery format and 
feedback mechanisms for initial and sustained use, based on participants’ adherence data, responses to 
feedback, providers’ responses and other variables that might influence optimal use of SMASH.169,170 
D.12. Potential Problems, Pitfalls & Solutions: A potential problem for any RCT is subject recruitment & 
retention. The FQHC network identified 2,619 21-59 yr old AAs with uncontrolled HTN (mean age=45.3 yrs) 
who meet initial prescreening inclusion criteria. Using a 75% participation rate for screening, as experienced in 
the FQHC feasibility trial, we project access to ~1,964 AAs with sole diagnosis of uncontrolled HTN. Our 
SMASH trial which used electronic pill monitoring found 79% had 1 mo adherence score <0.85.22,23 Given our 
91% minimum acceptance into randomization on our feasibility trials involving AAs, a conservative estimate 
would give us ~1411 patients. Multiple tactics will be used to foster high retention including obtaining full 
contact info for subjects’ immediate family members and ≥ 2 friends at enrollment and updating every 
evaluation. Transportation will be provided when needed; project evaluations will be scheduled, whenever 
possible, on subjects’ scheduled clinic visits. Birthday and holiday cards will be sent out and non-study related 
telephone calls made. A second issue may be subject “tech-phobia”. Our research with AA HTNs,20,21 
found little concern regarding use of an electronic tray or automated BP monitor, as they operate similarly to 
instruments they use (e.g., pill trays; digital BP devices).Our SMASH feasibility trials found high acceptability, 
satisfaction and adherence to the MedMinder and BP self-monitoring protocols.22,23,25,26 Patients will be 
provided auto call numbers in their SMASH app should they experience technical problems. A third issue is 
possible post-trial adherence deterioration. We elected not to include a booster program or other post trial 
intervention (e.g., motivational interviewing) as our intent is to determine whether 6 mos of SMASH results in 
persistent improvements in MA and BP control resulting from increased competence and autonomous 
motivation. SDT-based behavioral change programs that are typically 3-6 mos have led to lasting changes 1-2 
yrs later.92,95-97 Tentative support was recently published suggesting sustainability of SMASH program’s impact 
upon MA with a 12-mo post-trial eval of AA kidney transplant patients’ medical records.24 Former SMASH 
patients sustained lower BP levels and better JNC8 designated BP control compared to the SC group. 
Whether such can be achieved with the SMASH program adapted for a more challenging group of patients, 
AAs with sole diagnosis of uncontrolled HTN, requires evaluation. If reductions are observed, the future 
effectiveness RCT will include booster sessions guided by participants’ suggestions. A fourth issue is the 
MedMinder does not detect pill ingestion. Although the gold standard for med intake monitoring is biosensor 
pills (e.g., Proteus), these are not commercially available or financially feasible. Further, a 12-wk trial using the 
Proteus Digital Health ingestible sensor system verified 99-100% accuracy of pills ingested, but 40% of 
patients dropped out during the first month due to side effects (i.e., diarrhea, erythema & rash from the on-body 
sensor patch).171 During weeks 8-12, 61% of the remaining patients required SMS reminders to take their pills. 
In our feasibility trials, increased BP control mirrored increases in MA suggesting AAs with uncontrolled HTN 
do not fake pill intake. The proposed efficacy RCT will determine whether this is replicable and if improvements 
in MA and BP control are sustained over the 6-mo intervention and subsequent 12-mo follow-up. Finally, we 

will have a wealth of data to address important issues not detailed which will guide our future work. For 
example, we will use triangulation of Morisky MA self-report scale, MPR, pharmacy record information and 
MedMinder data to develop an effective algorithm for MA measurement. 
 
PROTECTION OF HUMAN SUBJECTS 
This Human Subjects Research meets the definition of a clinical trial. 
1. Risks to Human Subjects 
a. Human Subjects Involvement, Characteristics, and Design 
This will be a two-arm RCT design that will assess efficacy of the SMASH mHealth program compared to an 
enhanced standard care (SC) program. Participants will be drawn from Fetter Health Care Network (FHCN), 
the sole FQHC center in the 4-county area (Charleston, Dorchester, Colleton and Berkeley counties). The 
Medical University of South Carolina  Family Medicine and Internal Medicine clinics will be available if needed 
for recruitment of participants. Collectively,this offers a unique opportunity to recruit underserved, at risk 
patients without extensive screening protocols. We will recruit 192 AAs with uncontrolled HTN (no other 
comorbidities) and MNA according to the inclusion and exclusion criteria below and the methods described in 
Section D.2. Participants. The Fetter Health Center Information Technology Department will provide a list of 
potentially eligible patients to the SMASH project manager, Dr. Chandler. She will make the initial phone 
contact with potential subjects. She will inform them about the study and that they will have an equal chance of 
being randomized to either the enhanced health education (i.e., enhanced standard care [SC]) or SMASH 
cohort if they are found eligible at the conclusion of the screening period. Following a successful BP screening 
(SBP ≥140 mmHg), a battery of questionnaires are completed and then 24-hour BP monitoring will occur. 
Likelihood of white coat hypertension in these patients is low.30,75,76 We found no case of white coat 
hypertension in the FQHC feasibility trial involving AAs. If the participant’s 24 hour SBP is ≥130mmHg, he/she 
will proceed to the next phase of screening involving use of the Maya MedMinder for one month with reminder 
signals deactivated. If MA score < .85, they will again complete the baseline clinic BP evaluation and 24-hr BP 
monitoring to reconfirm uncontrolled SBP HTN. 
The practice sites will have been randomly assigned to SMASH or SC. The MDs and nurse managers at 
each site will have received an orientation in the SMASH study and refresher on the JNC8 Guidelines for HTN 
management. As in our feasibility trials, the project research technicians responsible for conducting all 
evaluations will remain blinded to the subjects’ status for the entire duration of the study and follow-
up. To help prevent contamination, the SMASH and SC subjects will be reminded by phone the night before 
study evaluations by Dr. Chandler and again in clinic by the nurse manager, not to discuss their involvement in 
the trial with the technicians. Subjects will also be instructed not to discuss their treatment regimen with other 
individuals excepting those in their household. The SMASH project manager, Dr. Chandler, will not be 
directly involved with data collection, as she will be a phone contact for SMASH subjects and will not 
be blinded. This same approach was successful in the 6-month FQHC feasibility trial. 
Primary clinical outcome variables are 1) fraction of subjects reaching JNC8 guidelines for BP control (i.e., 
resting BP <140/90 mmHg), and 2) fraction of subjects with medication adherence score >0.90, as measured 
by electronic medication tray. Secondary clinical outcome measures include provider adherence to JNC8 
guidelines, as measured by timing of medication changes, % reaching 24-hr ambulatory BP control 
(BP<130/80 mmHg) and changes in subjects’ SDT constructs of competence and autonomous motivation. 
Exploratory outcome variables will include cost effectiveness, other MA indices (i.e., pharmacy record based 
medication possession ratio [MPR] and self-report [Morisky scale]) and examination of potential moderators 
(e.g., gender, age, income, etc.) and mediators (e.g., competence, autonomous motivation, perceived disease 
severity, med side effects, depressive symptoms, sleep quality, etc.) on MA and BP control. We will also 
explore impact of SMASH program (i.e., increases in MA) upon changes in physical risk factors of TC, LDL, 
HgA1c and blood glucose. All data will be evaluated on an intent-to-treat basis. 
 
Inclusion Criteria: 
1. 21-59 years old; male or female; African American or Black  
2. Prescribed medication(s) only for HTN; 
3. Medication possession ratio (MPR) <.85 for last 3 months; 
4. uncontrolled HTN (SBP ≥140 mmHg) based upon last clinic visit within previous 12 months, initial 
clinic screening and subsequent recruitment evaluation following one month med intake screening 
with  score of <.85 ;  

5. 24-hour SBP ≥ 130 mmHg on clinic screening and subsequent recruitment evaluation;  
6. Ability to speak, hear and understand English; 
7. Able to take their own BP and self-administer medications; 
8. Owns smart phone with data plan; 
9. Primary care provider’s assent that patient is able to participate 
Exclusion Criteria: 
1. No other known chronic disease (e.g.,chronic kidney disease (GFR<50 mL/1.7 m2/min;diabetes 
(type one or two);renal dialysis ;cancer diagnosis or treatment in past 2 years;prior cv event such as 
heart attack, congestive heart failure, arterial stent, coronary artery bypass graft ; psychiatric illness 
2. Beck Depression Inventory score >13  
3. Ongoing substance abuse (e.g., >21 drinks/week);  
4. Planned pregnancy; 
5. Vulnerable populations such as pregnant or nursing women, prisoners, and institutionalized 
individuals. 
Healthcare Team Focus Groups: The 8 primary providers and their nurse managers whose 4 practice sites 
are randomly selected to deliver SMASH will be eligible to attend a focus group after all patients have 
completed the final follow-up. All participants will provide written informed consent before taking part in the 
focus groups and we anticipate that, as before, all healthcare team members will participate. Due to the nature 
of this sample, a targeted/planned enrollment recruitment table based on gender, race, or ethnicity was not 
developed. 
b. Sources of Materials 
In determining eligibility and subsequent enrollment, participants will have their resting BP measured by a 
research technician during an initial screening visit.If their average of the final 2 SBP readings ≥140 mmHg and 
their 24-hr SBP ≥ 130 mmHg, they will be eligible for the 1-month MA screening using the electronic 
medication tray with its reminder functions disabled. If, at the end of the 1-month MA screening, the adherence 
score is <0.85, they will participate in a baseline study evaluation that will again include measurement of 
resting BP and 24 hour BP. Those who again have uncontrolled HTN (resting SBP ≥140 mmHg and 24-hr SBP 
≥ 130 mmHg) will be eligible for participation in the trial. Participants will have the resting BP and 24-hr BP 
monitoring performed again at months 3, 6, 12, and 18. At each evaluation, participants will complete a battery 
of questionnaires that have been purposely selected as having established psychometric properties for AAs 
and the age range of our cohort (see Appx 1, 7-21 for copies of questionnaires and additional psychometric 
properties than those presented in Table 3). Questionnaires will include measures of self reported MA, 
competence, autonomous motivation, health literacy, HTN knowledge, adverse events, med side effects, 
depression, sleep quality, stress, quality of life, patient satisfaction with provider). They will also complete 
several scales scale that assesses degree of satisfaction with study implementation and study/home 
evaluations, usability of the SMASH protocol ,app and wireless BP device or the enhanced SC group’s  
educational materials, and potential barriers/facilitators of adherence. As part of standard care, all participants 
will have blood drawn at baseline and months 6, 12 and 18 to include TC, LDL, HgA1c and blood glucose 
levels. All subjects will wear an ambulatory BP monitor for 24-hr on several occasions over the course of the 
study. The combination of anthropometric evaluations, resting BP measurements, ambulatory BP 
measurements, and the majority of the questionnaires has been used in prior studies (e.g., HL 05662, HL 
078216, and SMASH feasibility RCTs) and was not considered a burden by the subjects. All study materials 
will be de-identified so that only the subjects ID number will be associated with any collected data.  
On completion of the final follow-up evaluation, a random sample of 32 of the 96 SMASH subjects will 
participate in a focus group (4-5 per group). SMASHers will be stratified by sex, age (<40/>40), practice site 
and MA responder classification. That is, 16 SMASH responders (MA >.90) and 16 non/partial responders (MA 
<.90.) based upon their cumulative adherence score (MedMinder 6 mo MA score and MPR level across follow-
up period).We anticipate 3-4 groups of responders and 3-4 groups of nonresponders. Topic areas will include 
perceptions of the SMASH protocol, the MedMinder electronic medication tray, the home BP monitors, smart 
phone delivery of BP feedback, smart phone-relayed motivational and reinforcement messages. They will 
provide perspectives on the usefulness of SMASH and suggestions for enhancing its acceptability, usability 
and sustainability. Qualitative analyses of the focus groups will identify themes using NVivo 11.0 software to 
analyze audiotape recordings and transcriptions of the group meetings. 
c. Potential Risks 

Potential risks to the participants are minimal. The only invasive procedures are venipunctures, which are 
conducted as part of standard care at baseline, months 6, 12 and 18 for blood labs of which we will focus upon 
TC, LDL, HgA1c and blood glucose. All questionnaires have been purposely selected so that they can be 
completed in the briefest time possible. Those who prefer will have the forms read to them. Participants will be 
given an opportunity to discontinue participation in the study at any time for any reason. There are no aspects 
of the intervention or testing protocol expected to cause physical discomfort with exception of venipunctures. 
The two programs presented (SMASH and enhanced SC) are non-invasive and present no more than minimal 
risks to the participants; the treatment modalities themselves are hygienic and health promoting with no known 
adverse physical side effects. SMASH medication and BP monitoring adherence will be monitored 
automatically via HIPAA compliant transfer of encrypted, deidentifed data to our server. Participants’ data will 
not be stored on the cell phone but will be encrypted and sent to password-protected server storage. The study 
procedures (e.g., resting BP, questionnaires, ambulatory BP) are all non-invasive and present no more than 
minimal risks to the participants. In the unlikely event that adverse event occurs during a study visit, the 
participant will be in the healthcare facility where they normally see their treating physician and where the 
medical team is familiar with their medical history. The situation will be assessed and appropriate treatment will 
be provided, or if necessary, transportation by ambulance to a nearby emergency department will be arranged. 
There are no social or legal risks associated with participation in the study. Confidentiality will be maintained. 
Participant data will be stored in locked files with coded ID numbers.  
2. Adequacy of Protection Against Risks 
a. Recruitment and Informed Consent 
The MUSC IRB has approved the use of SMASH, the various study procedures, and the ICD. The practice site 
MDs and nurse managers maintain CITI certification. Several Fetter Health Care Network (FHCN) MDs are 
quite familiar with SMASH, as they jointly participated in the development of the provider portion of the 
program. They helped design the MD summary report contents and how such a program can best function 
given the way their FHCN center (and other FQHCs) operate. They will receive training from the PI, Dr. 
Treiber, project manager, Dr. Chandler, and Co-I, Dr. Diaz, on the rationale for the SMASH efficacy trial and 
how the programs will operate. The SMASH project manager, Dr. Chandler, will contact potentially eligible 
patients by phone to gauge their interest. If they express an interest in participating, they will be invited to an 
initial screening at the FHCN clinic. She will explain the risks and benefits of study participation at the time of 
their screening visit. Interested participants will have all of their questions answered and will sign a written 
informed consent document. All participants will be reminded that they are free to contact study personnel or 
the PI at any time if any questions or concerns arise. They will be provided a copy of the written consent with 
the SMASH project with contact information for the project manager, the PI, and the MUSC IRB Chair. 
b. Protections Against Risks 
All the material delivered to the SMASH cohort by smart mobile phone and to the SC cohort either by mobile 
phone or hard copy mail are hygienic and health promoting and non-invasive with no known adverse physical 
side effects and present no more than minimal risk to the subject. With exception of standard of care blood 
draws, the study procedures are non-invasive and present no more than minimal risks to the subject. Subject 
data will be stored with coded ID numbers and no identifiers will accompany the data files. Confidentiality will 
be maintained. Dr. Treiber will keep all records in locked storage areas and on encrypted network storage. 
3. Potential Benefits of the Proposed Research to Human Subjects and Others 
Participants in enhanced SC may learn more about how unhealthy lifestyle behaviors (e.g., high salt/fat diet, 
smoking, sedentary lifestyle, alcohol intake) contribute to uncontrolled HTN and CVD events. They may learn 
how to initiate healthy lifestyle changes in such a way that they are likely to be maintained over time. The 
SMASH participants may benefit by learning better self-management skills related to medical regimens, by 
having potential misconceptions clarified (e.g., importance of dosing times, that HTN is a permanent condition), 
by learning the importance of following doctor’s orders (especially as it relates to medicine taking), by attending 
routine clinic evaluations, and by disclosing side effects and the use of any homeopathic/cultural remedies. By 
doing so, they may not only improve their long-term BP control but also reduce their risk of CV events, chronic 
kidney disease, stroke, etc. They will also be better prepared and able to successfully engage in additional 
medication intake regimens that would arise if they develop other comorbidities over time. 

4. Importance of Knowledge Gained.  
Despite tremendous advances in the medical management of HTN, levels of BP control are far from optimal, 
especially among AAs. Two major contributors to uncontrolled HTN are medication non-adherence (MNA) and 
therapeutic inertia. MNA is common among HTNs and contributes to patient morbidity and mortality (e.g., renal 
failure, stroke, diabetes and CV events.) To date, no mHealth RCT has been conducted with AAs that has 
demonstrated high, sustained, MA and improvement in BP control. Medication regimen and BP control 
programs are needed which can be sustained over time by HTNs, especially AAs who have not yet developed 
any other comorbidities. Innovative approaches for improving MNA that are effective, acceptable, feasible, and 
sustainable are urgently needed. Helping patients develop functional health literacy, self-efficacy and intrinsic 
motivation for sustained adherence to their medical regimen with their sole diagnosis of hypertension will help 
curtail the ravages of uncontrolled hypertension upon other biological systems and vasculature leading to 
additional comorbidities and/or CV events. The proposed research will address these issues by evaluating and 
refining a theory-driven mHealth-based med reminder and BP monitoring program that utilizes tailored 
feedback messages to motivate and sustain the subjects’ medical regimen related behaviors. The SMASH 
system will also provide the SMASH primary providers (and their nurse managers) with summaries of subjects’ 
MA and BP alongside JNC8 management guidelines for HTN in an effort to reduce therapeutic inertia and 
allow more rapid and sustained control of HTN. If the efficacy RCT outcomes are positive, we will have 
developed a practical, patient and provider friendly, MA enhancement and BP control program that will be 
ready for a full-scale, multi-site, effectiveness RCT. If sustained control of BP is observed in the full-scale 
effectiveness RCT, we will have made significant strides in our long-term objective to develop practical, 
effective, and sustainable primary and secondary prevention programs for AAs with sole diagnosis of HTN. 
Dissemination of SMASH and other programs as part of best practice models will help curtail the heavy burden 
of uncontrolled HTN and its associated morbidity and mortality.  
5. Data and Safety Monitoring Plan  
The MUSC IRB has reviewed this study and determined that this study presents no more than minimal risk to 
the subjects. Any severe adverse events will be reported to the IRB within 24 hours and all other unanticipated 
and possibly related adverse events will be reported as part of the annual re-approval process per the IRB 
policy. Dr. Treiber will monitor the recruitment of subjects, the conduct of the study, and the integrity of data 
collection. Dr. Treiber and the data manager (Sachin Patel, MS) will continuously monitor adverse events. As 
PI, he will be responsible for ensuring that adverse events are reported to the IRB in compliance with their 
requirements. Given the minimal risk associated with the intervention, we will utilize an internal Data Safety 
Monitoring Board (DSMB) with the addition of two external members. Drs. Diaz and Mueller will comprise the 
internal members. The members external to the project include Dr. Gaynelle Magwood (nurse behavioral 
scientist) and Dr. Robert Adams (neurologist who specializes in management of hypertension and stroke.) 
Both have served on other DSMBs and have significant experience in health-related practice-based 
participatory research programs. The DSMB will meet twice per year to review study progress (e.g., 
recruitment, retention, and adverse events) and Mr. Patel will provide monthly administrative reports that 
describe the study progress including accrual, demographics and subjects’ status. The reports will also 
describe adherence to inclusion/exclusion criteria and study protocol and any adverse events. Drs. Diaz and 
Mueller will review reports on a monthly basis after the intervention has begun. The adequacy of recruitment 
and retention will be addressed at those points. Summary reports, void of personal identifiers, will be provided 
to the NIH annually as part of progress reports. Drs. Adams and Magwood, as well as Drs. Diaz, and Mueller, 
will be alerted if any unexpected serious (e.g., injury requiring medical treatment) adverse event occurs to 
determine whether changes in the study protocol (e.g., additional safety measures, change in exclusion 
criteria) are needed. If, in the unlikely event we encounter any serious adverse events (SAEs), the DSMB will 
convene and determine whether the SAE was likely a result of participation in the trial. If so, and a consensus 
cannot be reached regarding preventing reoccurrence of a similar event, the NIH will be contacted to discuss 
procedures for halting the trial. If any changes to the protocol are needed, Dr. Treiber will notify the IRB and 
the NIH. Summary reports of interim analyses will be provided to NIH as part of annual progress reports. 
Ongoing quality control will include regular data verification and protocol compliance checks to be performed 
by Drs. Treiber, Chandler and Mueller. 
 
  
 

REFERENCES CITED 
 
1. 
Centers for Disease C, Prevention. Vital signs: prevalence, treatment, and control of hypertension--United 
States, 1999-2002 and 2005-2008. MMWR Morbidity and mortality weekly report. 2011;60(4):103-108. 
2. 
Yoon SS, Ostchega Y, Louis T. Recent trends in the prevalence of high blood pressure and its treatment and 
control, 1999-2008. NCHS data brief. 2010(48):1-8. 
3. 
Egan BM, Zhao Y, Axon RN. US trends in prevalence, awareness, treatment, and control of hypertension, 1988-
2008. Jama. 2010;303(20):2043-2050. 
4. 
Olives C, Myerson R, Mokdad AH, Murray CJ, Lim SS. Prevalence, awareness, treatment, and control of 
hypertension in United States counties, 2001-2009. PloS one. 2013;8(4):e60308. PMCID: PMC3618269. 
5. 
Keenan NL, Rosendorf KA, Centers for Disease C, Prevention. Prevalence of hypertension and controlled 
hypertension - United States, 2005-2008. Morbidity and mortality weekly report Surveillance summaries. 
2011;60 Suppl:94-97. 
6. 
Gillespie CD, Hurvitz KA, Control CfD, Prevention. Prevalence of hypertension and controlled hypertension—
United States, 2007–2010. Morbidity and mortality weekly report Surveillance summaries. 2013;62(Suppl 
3):144-148. 
7. 
Krousel-Wood M, Joyce C, Holt E, Muntner P, Webber LS, Morisky DE, Frohlich ED, Re RN. Predictors of decline 
in medication adherence: results from the cohort study of medication adherence among older adults. 
Hypertension. 2011;58(5):804-810. PMCID: PMC3220657. 
8. 
Borzecki AM, Oliveria SA, Berlowitz DR. Barriers to hypertension control. American heart journal. 
2005;149(5):785-794. 
9. 
Dusing R. Overcoming barriers to effective blood pressure control in patients with hypertension. Current medical 
research and opinion. 2006;22(8):1545-1553. 
10. 
Osterberg L, Blaschke T. Adherence to medication. The New England journal of medicine. 2005;353(5):487-497. 
11. 
Agarwal R, Bills JE, Hecht TJ, Light RP. Role of home blood pressure monitoring in overcoming therapeutic inertia 
and improving hypertension control: a systematic review and meta-analysis. Hypertension. 2011;57(1):29-38. 
12. 
Glynn LG, Murphy AW, Smith SM, Schroeder K, Fahey T. Interventions used to improve control of blood pressure 
in patients with hypertension. The Cochrane database of systematic reviews. 2010(3):CD005182. 
13. 
Cappuccio FP, Kerry SM, Forbes L, Donald A. Blood pressure control by home monitoring: meta-analysis of 
randomised trials. Bmj. 2004;329(7458):145. PMCID: PMC478224. 
14. 
Pickering TG, Shimbo D, Haas D. Ambulatory blood-pressure monitoring. N Engl J Med. 2006;354(22):2368-2374. 
15. 
Carter BL, Bergus GR, Dawson JD, Farris KB, Doucette WR, Chrischilles EA, Hartz AJ. A cluster randomized trial to 
evaluate physician/pharmacist collaboration to improve blood pressure control. Journal of clinical hypertension. 
2008;10(4):260-271. PMCID: PMC2453045. 
16. 
Carter BL, Ardery G, Dawson JD, James PA, Bergus GR, Doucette WR, Chrischilles EA, Franciscus CL, Xu Y. 
Physician and pharmacist collaboration to improve blood pressure control. Archives of internal medicine. 
2009;169(21):1996-2002. PMCID: PMC2882170. 
17. 
Mathur R, Hull SA, Badrick E, Robson J. Cardiovascular multimorbidity: the effect of ethnicity on prevalence and 
risk factor management. The British journal of general practice : the journal of the Royal College of General 
Practitioners. 2011;61(586):e262-270. PMCID: PMC3080231. 
18. 
Sarkar C, Dodhia H, Crompton J, Schofield P, White P, Millett C, Ashworth M. Hypertension: a cross-sectional 
study of the role of multimorbidity in blood pressure control. BMC family practice. 2015;16:98. PMCID: 
PMC4528716. 
19. 
Paulsen MS, Andersen M, Thomsen JL, Schroll H, Larsen PV, Lykkegaard J, Jacobsen IA, Larsen ML, Christensen B, 
Sondergaard J. Multimorbidity and blood pressure control in 37 651 hypertensive patients from Danish general 
practice. Journal of the American Heart Association. 2013;2(1):e004531. PMCID: PMC3603256. 
20. 
McGillicuddy JW, Weiland AK, Frenzel RM, Mueller M, Brunner-Jackson BM, Taber DJ, Baliga PK, Treiber FA. 
Patient attitudes toward mobile phone-based health monitoring: questionnaire study among kidney transplant 
recipients. Journal of medical Internet research. 2013;15(1):e6. PMCID: PMC3636312. 
21. 
Jenkins C, Burkett NS, Ovbiagele B, Mueller M, Patel S, Brunner-Jackson B, Saulson R, Treiber F. Stroke patients 
and their attitudes toward mHealth monitoring to support blood pressure control and medication adherence. 
Mhealth. 2016;2. PMCID: PMCPMC4916920. 

22. 
McGillicuddy JW, Gregoski MJ, Weiland AK, Rock RA, Brunner-Jackson BM, Patel SK, Thomas BS, Taber DJ, Chavin 
KD, Baliga PK, Treiber FA. Mobile Health Medication Adherence and Blood Pressure Control in Renal Transplant 
Recipients: A Proof-of-Concept Randomized Controlled Trial. JMIR research protocols. 2013;2(2):e32. PMCID: 
PMC3786124. 
23. 
McGillicuddy JW, Gregoski MJ, Brunner-Jackson BM, Weiland AK, Patel SK, Rock RA, Treiber EM, Davidson LK, 
Treiber FA. Facilitating medication adherence and eliminating therapeutic inertia using wireless technology: 
proof of concept findings with uncontrolled hypertensives and kidney transplant recipients. Journal of The 
Association for Computer Machinery. 2012:1-9. 
24. 
McGillicuddy J, Taber D, Mueller M, Patel S, Baliga P, Chavin K, Sox L, Favela A, Brunner-Jackson B, Treiber F. 
Sustainability of improvements in medication adherence through a mobile health intervention. Progress in 
Transplantation. 2015;25(3):217-223. 
25. 
Davidson TM, McGillicuddy J, Mueller M, Brunner-Jackson B, Favella A, Anderson A, Torres M, Ruggiero KJ, 
Treiber FA. Evaluation of an mHealth Medication Regimen Self-Management Program for African American and 
Hispanic Uncontrolled Hypertensives. J Pers Med. 2015;5(4):389-405. PMCID: PMCPMC4695862. 
26. 
Ovbiagele B, Jenkins C, Patel S, Brunner-Jackson B, Anderson A, Saulson R, Treiber F. Mobile health medication 
adherence and blood pressure control in recent stroke patients. J Neurol Sci. 2015;358(1-2):535-537. 
27. 
James PA, Oparil S, Carter BL, Cushman WC, Dennison-Himmelfarb C, Handler J, Lackland DT, LeFevre ML, 
MacKenzie TD, Ogedegbe O, Smith SC, Jr., Svetkey LP, Taler SJ, Townsend RR, Wright JT, Jr., Narva AS, Ortiz E. 
2014 evidence-based guideline for the management of high blood pressure in adults: report from the panel 
members appointed to the Eighth Joint National Committee (JNC 8). Jama. 2014;311(5):507-520. 
28. 
Holmes L, Jr., Hossain J, Ward D, Opara F. Racial/Ethnic Variability in Hypertension Prevalence and Risk Factors in 
National Health Interview Survey. International Scholarly Research Notices Hypertension [serial on the Internet]. 
2013; 2013: Available from: http://hindawi.com/journals/isrn/2013/257842/. 
29. 
Nwankwo T, Yoon SS, Burt V, Gu Q. Hypertension among adults in the United States: National Health and 
Nutrition Examination Survey, 2011-2012. NCHS data brief. 2013(133):1-8. 
30. 
Bale B. Optimizing hypertension management in underserved rural populations. Journal of the National Medical 
Association. 2010;102(1):10-17. 
31. 
Sowers JR, Epstein M, Frohlich ED. Diabetes, Hypertension, and Cardiovascular Disease: An Update. 
Hypertension. 2001;37(4):1053-1059. 
32. 
Mugo MN, Stump CS, Rao PG, Sowers JR. Chapter 34 - Hypertension and Diabetes Mellitus A2 - Black, Henry R. 
In: Elliott WJ, editor. Hypertension. Philadelphia: W.B. Saunders; 2007. p. 406-417. 
33. 
Gress TW, Nieto FJ, Shahar E, Wofford MR, Brancati FL. Hypertension and antihypertensive therapy as risk 
factors for type 2 diabetes mellitus. New England Journal of Medicine. 2000;342(13):905-912. 
34. 
Cheung BM, Li C. Diabetes and hypertension: is there a common metabolic pathway? Current atherosclerosis 
reports. 2012;14(2):160-166. 
35. 
Kannel WB, Cobb J. Left ventricular hypertrophy and mortality--results from the Framingham Study. Cardiology. 
1992;81(4-5):291-298. 
36. 
Tedla FM, Brar A, Browne R, Brown C. Hypertension in chronic kidney disease: navigating the evidence. 
International journal of hypertension. 2011;2011:132405. PMCID: PMC3124254. 
37. 
Bosworth HB. Medication treatment adherence. In: Bosworth HB, Oddone EZ, Weinberger M, editors. Patient 
treatment adherence: Concepts, interventions, and measurement. Mahwah New Jersey: Lawrence Erlbaum 
Associates; 2006. p. 147-194. 
38. 
Fischer MA, Choudhry NK, Brill G, Avorn J, Schneeweiss S, Hutchins D, Liberman JN, Brennan TA, Shrank WH. 
Trouble getting started: predictors of primary medication nonadherence. The American journal of medicine. 
2011;124(11):1081 e1089-1022. 
39. 
Fischer MA, Stedman MR, Lii J, Vogeli C, Shrank WH, Brookhart MA, Weissman JS. Primary medication non-
adherence: analysis of 195,930 electronic prescriptions. Journal of general internal medicine. 2010;25(4):284-
290. PMCID: PMC2842539. 
40. 
Cramer JA, Benedict A, Muszbek N, Keskinaslan A, Khan ZM. The significance of compliance and persistence in 
the treatment of diabetes, hypertension and dyslipidaemia: a review. International journal of clinical practice. 
2008;62(1):76-87. PMCID: PMC2228386. 
41. 
Romanelli RJ, Schiro TA, Jukes T, Wong KS, Ishisaka DY. Disparities in blood pressure control within a community-
based provider network: an exploratory analysis. The Annals of pharmacotherapy. 2011;45(12):1473-1482. 

42. 
Hirst JA, Farmer AJ, Feakins BG, Aronson JK, Stevens RJ. Quantifying the effects of diuretics and beta-
adrenoceptor blockers on glycaemic control in diabetes mellitus - a systematic review and meta-analysis. Br J 
Clin Pharmacol. 2015;79(5):733-743. PMCID: PMCPMC4415710. 
43. 
Barzilay JI, Davis BR, Cutler JA, Pressel SL, Whelton PK, Basile J, Margolis KL, Ong ST, Sadler LS, Summerson J, 
Group ACR. Fasting glucose levels and incident diabetes mellitus in older nondiabetic adults randomized to 
receive 3 different classes of antihypertensive treatment: a report from the Antihypertensive and Lipid-Lowering 
Treatment to Prevent Heart Attack Trial (ALLHAT). Archives of internal medicine. 2006;166(20):2191-2201. 
44. 
Yang Y, Wei RB, Xing Y, Tang L, Zheng XY, Wang ZC, Gao YW, Li MX, Chen XM. A meta-analysis of the effect of 
angiotensin receptor blockers and calcium channel blockers on blood pressure, glycemia and the HOMA-IR index 
in non-diabetic patients. Metabolism. 2013;62(12):1858-1866. 
45. 
Blackburn DF, Wilson TW. Antihypertensive medications and blood sugar: theories and implications. Can J 
Cardiol. 2006;22(3):229-233. PMCID: PMCPMC2528930. 
46. 
Degli Esposti L, Di Martino M, Saragoni S, Sgreccia A, Capone A, Buda S, Esposti ED. Pharmacoeconomics of 
antihypertensive drug treatment: an analysis of how long patients remain on various antihypertensive therapies. 
Journal of clinical hypertension. 2004;6(2):76-84. 
47. 
Heaton PC, Tundia NL, Luder HR. U.S. emergency departments visits resulting from poor medication adherence: 
2005-07. Journal of the American Pharmacists Association : JAPhA. 2013;53(5):513-519. 
48. 
Chisholm-Burns MA, Spivey CA. The 'cost' of medication nonadherence: consequences we cannot afford to 
accept. Journal of the American Pharmacists Association : JAPhA. 2012;52(6):823-826. 
49. 
Millett C, Gray J, Bottle A, Majeed A. Ethnic disparities in blood pressure management in patients with 
hypertension after the introduction of pay for performance. Annals of family medicine. 2008;6(6):490-496. 
PMCID: PMC2582467. 
50. 
Qvarnstrom M, Wettermark B, Ljungman C, Zarrinkoub R, Hasselstrom J, Manhem K, Sundstrom A, Kahan T. 
Antihypertensive treatment and control in a large primary care population of 21 167 patients. Journal of human 
hypertension. 2011;25(8):484-491. 
51. 
Bautista LE, Vera-Cala LM, Colombo C, Smith P. Symptoms of depression and anxiety and adherence to 
antihypertensive medication. American journal of hypertension. 2012;25(4):505-511. PMCID: PMC3588114. 
52. 
Russell CL, Conn VS, Ashbaugh C, Madsen R, Hayes K, Ross G. Medication adherence patterns in adult renal 
transplant recipients. Research in nursing & health. 2006;29(6):521-532. 
53. 
Vrijens B, Tousset E, Rode R, Bertz R, Mayer S, Urquhart J. Successful projection of the time course of drug 
concentration in plasma during a 1-year period from electronically compiled dosing-time data used as input to 
individually parameterized pharmacokinetic models. Journal of clinical pharmacology. 2005;45(4):461-467. 
54. 
Bangsberg DR, Deeks SG. Spending more to save more: interventions to promote adherence. Annals of internal 
medicine. 2010;152(1):54-56; W-13. PMCID: PMC3606957. 
55. 
Kronish IM, Ye S. Adherence to cardiovascular medications: lessons learned and future directions. Progress in 
cardiovascular diseases. 2013;55(6):590-600. PMCID: PMC3639439. 
56. 
Adherence to long term therapies: evidence for action. World Health Organization; 2003 [updated 2003; cited 
11-19-2014]; Available from: 
http://www.who.int/chp/knowledge/publications/adherence_full_report.pdf?ua=1dd. 
57. 
Jin J, Sklar GE, Min Sen Oh V, Chuen Li S. Factors affecting therapeutic compliance: A review from the patient's 
perspective. Therapeutics and clinical risk management. 2008;4(1):269-286. PMCID: PMC2503662. 
58. 
Julius RJ, Novitsky MA, Jr., Dubin WR. Medication adherence: a review of the literature and implications for 
clinical practice. Journal of psychiatric practice. 2009;15(1):34-44. 
59. 
DiMatteo MR, Haskard KB, Williams SL. Health beliefs, disease severity, and patient adherence: a meta-analysis. 
Med Care. 2007;45(6):521-528. 
60. 
An J, Nichol MB. Multiple medication adherence and its effect on clinical outcomes among patients with 
comorbid type 2 diabetes and hypertension. Med Care. 2013;51(10):879-887. 
61. 
Brown SC, Park DC. Theoretical models of cognitive aging and implications for translational research in medicine. 
The Gerontologist. 2003;43(suppl 1):57-67. 
62. 
Grenard JL, Munjas BA, Adams JL, Suttorp M, Maglione M, McGlynn EA, Gellad WF. Depression and medication 
adherence in the treatment of chronic diseases in the United States: a meta-analysis. Journal of general internal 
medicine. 2011;26(10):1175-1182. PMCID: PMCPMC3181287. 

63. 
Lewis LM, Schoenthaler AM, Ogedegbe G. Patient factors, but not provider and health care system factors, 
predict medication adherence in hypertensive black men. Journal of clinical hypertension. 2012;14(4):250-255. 
64. 
Lewis LM. Factors associated with medication adherence in hypertensive blacks: a review of the literature. J 
Cardiovasc Nurs. 2012;27(3):208-219. 
65. 
Holt EW, Muntner P, Joyce C, Morisky DE, Webber LS, Krousel-Wood M. Life events, coping, and 
antihypertensive medication adherence among older adults: the cohort study of medication adherence among 
older adults. Am J Epidemiol. 2012;176 Suppl 7:S64-71. PMCID: PMCPMC3530357. 
66. 
Ho PM, Bryson CL, Rumsfeld JS. Medication adherence: its importance in cardiovascular outcomes. Circulation. 
2009;119(23):3028-3035. 
67. 
Forsyth J, Schoenthaler A, Chaplin WF, Ogedegbe G, Ravenell J. Perceived discrimination and medication 
adherence in black hypertensive patients: the role of stress and depression. Psychosom Med. 2014;76(3):229-
236. 
68. 
Lewis LM, Ogedegbe C, Ogedegbe G. Enhancing adherence of antihypertensive regimens in hypertensive 
African-Americans: current and future prospects. Expert Rev Cardiovasc Ther. 2012;10(11):1375-1380. PMCID: 
PMCPMC4748723. 
69. 
Redmond N, Baer HJ, Hicks LS. Health behaviors and racial disparity in blood pressure control in the national 
health and nutrition examination survey. Hypertension. 2011;57(3):383-389. PMCID: PMC3048351. 
70. 
Natarajan S, Santa Ana EJ, Liao Y, Lipsitz SR, McGee DL. Effect of treatment and adherence on ethnic differences 
in blood pressure control among adults with hypertension. Annals of epidemiology. 2009;19(3):172-179. 
71. 
Andrade SE, Gurwitz JH, Field TS, Kelleher M, Majumdar SR, Reed G, Black R. Hypertension management: the 
care gap between clinical guidelines and clinical practice. The American journal of managed care. 2004;10(7 Pt 
2):481-486. 
72. 
Okonofua EC, Simpson KN, Jesri A, Rehman SU, Durkalski VL, Egan BM. Therapeutic inertia is an impediment to 
achieving the Healthy People 2010 blood pressure control goals. Hypertension. 2006;47(3):345-351. 
73. 
Carter BL. Blood pressure control-implementing a team approach. US Cardiology. 2011;8(2):108-113. 
74. 
Von Muenster SJ, Carter BL, Weber CA, Ernst ME, Milchak JL, Steffensmeier JJ, Xu Y. Description of pharmacist 
interventions during physician–pharmacist co-management of hypertension. Pharmacy World & Science. 
2008;30(1):128-135. 
75. 
Piper MA, Evans CV, Burda BU, Margolis KL, O'Connor E, Smith N, Webber E, Perdue LA, Bigler KD, Whitlock EP.  
Screening for High Blood Pressure in Adults: A Systematic Evidence Review for the US Preventive Services Task 
Force. Rockville (MD)2014. 
76. 
Kikuya M, Hansen TW, Thijs L, Bjorklund-Bodegard K, Kuznetsova T, Ohkubo T, Richart T, Torp-Pedersen C, Lind 
L, Ibsen H, Imai Y, Staessen JA, International Database on Ambulatory blood pressure monitoring in relation to 
Cardiovascular Outcomes I. Diagnostic thresholds for ambulatory blood pressure monitoring based on 10-year 
cardiovascular risk. Circulation. 2007;115(16):2145-2152. 
77. 
Sieverdes JC, Treiber F, Jenkins C. Improving diabetes management with mobile health technology. The 
American journal of the medical sciences. 2013;345(4):289-295. 
78. 
Militello LK, Kelly SA, Melnyk BM. Systematic review of text-messaging interventions to promote healthy 
behaviors in pediatric and adolescent populations: implications for clinical practice and research. Worldviews on 
evidence-based nursing / Sigma Theta Tau International, Honor Society of Nursing. 2012;9(2):66-77. 
79. 
Free C, Phillips G, Watson L, Galli L, Felix L, Edwards P, Patel V, Haines A. The effectiveness of mobile-health 
technologies to improve health care service delivery processes: a systematic review and meta-analysis. PLoS 
medicine. 2013;10(1):e1001363. PMCID: PMC3566926. 
80. 
de Jongh T, Gurol-Urganci I, Vodopivec-Jamsek V, Car J, Atun R. Mobile phone messaging for facilitating self-
management of long-term illnesses. The Cochrane database of systematic reviews. 2012;12:CD007459. 
81. 
Poushter J. Smartphone Ownership and Internet Usage Continues to Climb in Emerging Economies2016 
8/22/2016]: Available from: http://www.pewglobal.org/2016/02/22/smartphone-ownership-and-internet-
usage-continues-to-climb-in-emerging-economies/. 
82. 
Wu JR, Corley DJ, Lennie TA, Moser DK. Effect of a medication-taking behavior feedback theory-based 
intervention on outcomes in patients with heart failure. Journal of cardiac failure. 2012;18(1):1-9. PMCID: 
PMC3246219. 

83. 
Bonetti D, Johnston M. Perceived control predicting the recovery of individual-specific walking behaviours 
following stroke: testing psychological models and constructs. British journal of health psychology. 2008;13(Pt 
3):463-478. 
84. 
Rosen MI, Dieckhaus K, McMahon TJ, Valdes B, Petry NM, Cramer J, Rounsaville B. Improved adherence with 
contingency management. AIDS patient care and STDs. 2007;21(1):30-40. 
85. 
Rigsby MO, Rosen MI, Beauvais JE, Cramer JA, Rainey PM, O'Malley SS, Dieckhaus KD, Rounsaville BJ. Cue-dose 
training with monetary reinforcement: pilot study of an antiretroviral adherence intervention. Journal of general 
internal medicine. 2000;15(12):841-847. PMCID: PMC1495713. 
86. 
Checchi KD, Huybrechts KF, Avorn J, Kesselheim AS. Electronic medication packaging devices and medication 
adherence: a systematic review. Jama. 2014;312(12):1237-1247. PMCID: PMC4209732. 
87. 
Chow CK, Redfern J, Hillis GS, Thakkar J, Santo K, Hackett ML, Jan S, Graves N, de Keizer L, Barry T, Bompoint S, 
Stepien S, Whittaker R, Rodgers A, Thiagalingam A. Effect of Lifestyle-Focused Text Messaging on Risk Factor 
Modification in Patients With Coronary Heart Disease: A Randomized Clinical Trial. Jama. 2015;314(12):1255-
1263. 
88. 
Kamarck T. Targeted Text Messaging Support for Patients With Coronary Heart Disease. Jama. 
2016;315(10):1056. 
89. 
Free C, Phillips G, Galli L, Watson L, Felix L, Edwards P, Patel V, Haines A. The effectiveness of mobile-health 
technology-based health behaviour change or disease management interventions for health care consumers: a 
systematic review. PLoS medicine. 2013;10(1):e1001362. PMCID: PMCPMC3548655. 
90. 
Bandura A. Self efficacy, The excercise of control. New York: Freeman; 1997. 
91. 
Deci EL, Koestner R, Ryan RM. A meta-analytic review of experiments examining the effects of extrinsic rewards 
on intrinsic motivation. Psychological bulletin. 1999;125(6):627-668; discussion 692-700. 
92. 
Ng J, Ntoumanis N, Thogersen-Ntoumani C, Deci E, Ryan R, Duda J, Williams G. Self-Determination Theory 
Applied to Healthy Contexts: A Meta-Analysis. Perspectives on Psychological Science. 2012;7(4):325-340. 
93. 
Ryan RM, Deci EL. Self-determination theory and the facilitation of intrinsic motivation, social development, and 
well-being. The American psychologist. 2000;55(1):68-78. 
94. 
Ryan RM, Kuhl J, Deci EL. Nature and autonomy: an organizational view of social and neurobiological aspects of 
self-regulation in behavior and development. Development and psychopathology. 1997;9(4):701-728. 
95. 
Ryan RM, Tobin VJ, Rollnick S. Motivational Interviewing and Self-Determination Theory. Journal of Social & 
Clinical Psychology. 2005;24(6):21p. 
96. 
Williams GC, Gagne M, Ryan RM, Deci EL. Facilitating autonomous motivation for smoking cessation. Health 
psychology : official journal of the Division of Health Psychology, American Psychological Association. 
2002;21(1):40-50. 
97. 
Williams GC, Rodin GC, Ryan RM, Grolnick WS, Deci EL. Autonomous regulation and long-term medication 
adherence in adult outpatients. Health psychology : official journal of the Division of Health Psychology, 
American Psychological Association. 1998;17(3):269-276. 
98. 
Nielsen J, Budiu R. Mobile Usability: Pearson Education; 2012. 
99. 
Jaspers MW. A comparison of usability methods for testing interactive health technologies: methodological 
aspects and empirical evidence. International journal of medical informatics. 2009;78(5):340-353. 
100. 
Kaikkonen A, Kekäläinen A, Cankar M, Kallio T, Kankainen A. Usability testing of mobile applications: A 
comparison between laboratory and field testing. Journal of Usability studies. 2005;1(1):4-16. 
101. 
Fernandez S, Chaplin W, Schoenthaler AM, Ogedegbe G. Revision and validation of the medication adherence 
self-efficacy scale (MASES) in hypertensive African Americans. Journal of behavioral medicine. 2008;31(6):453-
462. PMCID: PMC3763496. 
102. 
Resnicow K, Davis R, Zhang N, Tolsma D, Alexander G, Wiese C, Cross WE, Jr., Anderson JP, Calvi J, Strecher V. 
Tailoring a fruit and vegetable intervention on ethnic identity: results of a randomized study. Health psychology : 
official journal of the Division of Health Psychology, American Psychological Association. 2009;28(4):394-403. 
PMCID: PMC3397196. 
103. 
Resnicow K, Davis RE, Zhang G, Konkel J, Strecher VJ, Shaikh AR, Tolsma D, Calvi J, Alexander G, Anderson JP, 
Wiese C. Tailoring a fruit and vegetable intervention on novel motivational constructs: results of a randomized 
study. Annals of behavioral medicine : a publication of the Society of Behavioral Medicine. 2008;35(2):159-169. 

104. 
Resnicow K, Zhou Y, Hawley S, Jimbo M, Ruffin MT, Davis RE, Shires D, Lafata JE. Communication preference 
moderates the effect of a tailored intervention to increase colorectal cancer screening among African 
Americans. Patient education and counseling. 2014;97(3):370-375. 
105. 
Morisky DE, Ang A, Krousel-Wood M, Ward HJ. Predictive validity of a medication adherence measure in an 
outpatient setting. Journal of clinical hypertension. 2008;10(5):348-354. PMCID: PMC2562622. 
106. 
Lukwago SN, Kreuter MW, Bucholtz DC, Holt CL, Clark EM. Development and validation of brief scales to 
measure collectivism, religiosity, racial pride, and time orientation in urban African American women. Family & 
community health. 2001;24(3):63-71. 
107. 
Heidari K. Medical Care Utilization Practices Among African Americans in Low Country Region of South Carolina: 
Bureau of Community Health and Chronic Disease Prevention, South Carolina Department of Health and 
Environmental Control; 2014. 
108. 
Diaz VA, Mainous AG, 3rd, Williamson D, Johnson SP, Knoll ME. Cardiovascular and diabetes risk perception in a 
Hispanic community sample. Ethnicity & disease. 2012;22(1):5-11. 
109. 
Andrews JO, Tingen MS, Jarriel SC, Caleb M, Simmons A, Brunson J, Mueller M, Ahluwalia JS, Newman SD, Cox 
MJ, Magwood G, Hurman C. Application of a CBPR framework to inform a multi-level tobacco cessation 
intervention in public housing neighborhoods. American journal of community psychology. 2012;50(1-2):129-
140. 
110. 
Baguet JP. Out-of-office blood pressure: from measurement to control. Integrated blood pressure control. 
2012;5:27-34. PMCID: PMC3363281. 
111. 
Appel LJ, Champagne CM, Harsha DW, Cooper LS, Obarzanek E, Elmer PJ, Stevens VJ, Vollmer WM, Lin PH, 
Svetkey LP, Stedman SW, Young DR, Writing Group of the PCRG. Effects of comprehensive lifestyle modification 
on blood pressure control: main results of the PREMIER clinical trial. Jama. 2003;289(16):2083-2093. 
112. 
Julius S, Nesbitt SD, Egan BM, Weber MA, Michelson EL, Kaciroti N, Black HR, Grimm RH, Jr., Messerli FH, Oparil 
S, Schork MA, Trial of Preventing Hypertension Study I. Feasibility of treating prehypertension with an 
angiotensin-receptor blocker. N Engl J Med. 2006;354(16):1685-1697. 
113. 
Beck AT, Steer RA, Carbin MG. Psychometric properties of the Beck Depression Inventory: twenty-five years of 
evaluation. Clinical Psychology Review. 1988;8(1):77-100. 
114. 
Beck AT, Steer RA. Beck Depression Inventory Manual. San Antonio, TX: Psychological Corporation, Harcourt, 
Brace; 1993. 
115. 
Rudd MD, Rajab MH. Specificity of the beck depression inventory and the confounding role of comorbid 
disorders in a clinical sample. Cognitive Therapy and Research. 1995;19(1):51-68. 
116. 
Brothwell S, Dutton M, Ferro C, Stringer S, Cockwell P. Optimising the accuracy of blood pressure monitoring in 
chronic kidney disease: the utility of BpTRU. BMC nephrology. 2013;14:218. PMCID: PMC3852944. 
117. 
Groppelli A, Omboni S, Parati G, Mancia G. Evaluation of noninvasive blood pressure monitoring devices 
Spacelabs 90202 and 90207 versus resting and ambulatory 24-hour intra-arterial blood pressure. Hypertension. 
1992;20(2):227-232. 
118. 
Barnes VA, Davis HC, Murzynowski JB, Treiber FA. Impact of meditation on resting and ambulatory blood 
pressure and heart rate in youth. Psychosom Med. 2004;66(6):909-914. 
119. 
Gregoski MJ, Barnes VA, Tingen MS, Dong Y, Zhu H, Treiber FA. Differential Impact of Stress Reduction Programs 
upon Ambulatory Blood Pressure among African American Adolescents: Influences of Endothelin-1 Gene and 
Chronic Stress Exposure. International journal of hypertension. 2012;2012:510291. PMCID: PMC3227499. 
120. 
Wright LB, Gregoski MJ, Tingen MS, Barnes VA, Treiber FA. Impact of Stress Reduction Interventions on Hostility 
and Ambulatory Systolic Blood Pressure in African American Adolescents. The Journal of black psychology. 
2011;37(2):210-233. PMCID: PMC3319013. 
121. 
Russell C, Conn V, Ashbaugh C, Madsen R, Wakefield M, Webb A, Coffey D, Peace L. Taking immunosuppressive 
medications effectively (TIMELink): a pilot randomized controlled trial in adult kidney transplant recipients. Clin 
Transplant. 2010. 
122. 
Rogoza AN, Pavlova TS, Sergeeva MV. Validation of A&D UA-767 device for the self-measurement of blood 
pressure. Blood pressure monitoring. 2000;5(4):227-231. 
123. 
Breaux-Shropshire TL, Brown KC, Pryor ER, Maples EH. Relationship of blood pressure self-monitoring, 
medication adherence, self-efficacy, stage of change, and blood pressure control among municipal workers with 
hypertension. Workplace health & safety. 2012;60(7):303-311. PMCID: PMC3810423. 

124. 
Voils CI, Maciejewski ML, Hoyle RH, Reeve BB, Gallagher P, Bryson CL, Yancy WS, Jr. Initial validation of a self-
report measure of the extent of and reasons for medication nonadherence. Med Care. 2012;50(12):1013-1019. 
PMCID: PMC3494794. 
125. 
Williams GC, Grow VM, Freedman ZR, Ryan RM, Deci EL. Motivational predictors of weight loss and weight-loss 
maintenance. J Pers Soc Psychol. 1996;70(1):115-126. 
126. 
Bailey GR, Barner JC, Weems JK, Leckbee G, Solis R, Montemayor D, Pope ND. Assessing barriers to medication 
adherence in underserved patients with diabetes in Texas. The Diabetes educator. 2012;38(2):271-279. 
127. 
Krousel-Wood M, Islam T, Webber LS, Re RN, Morisky DE, Muntner P. New medication adherence scale versus 
pharmacy fill rates in seniors with hypertension. The American journal of managed care. 2009;15(1):59-66. 
PMCID: PMC2728593. 
128. 
Leslie SR, Gwadry-Sridhar F, Thiebaud P, Patel BV. Calculating medication compliance, adherence and 
persistence in administrative pharmacy claims databases. Pharmaceutical Programming. 2008;1(1):13-19. 
129. 
Sanne S, Muntner P, Kawasaki L, Hyre A, DeSalvo KB. Hypertension knowledge among patients from an urban 
clinic. Ethnicity & disease. 2008;18(1):42-47. 
130. 
Williams MV, Baker DW, Parker RM, Nurss JR. Relationship of functional health literacy to patients' knowledge of 
their chronic disease. A study of patients with hypertension and diabetes. Archives of internal medicine. 
1998;158(2):166-172. 
131. 
Baker DW, Williams MV, Parker RM, Gazmararian JA, Nurss J. Development of a brief test to measure functional 
health literacy. Patient education and counseling. 1999;38(1):33-42. 
132. 
McNaughton CD, Cavanaugh KL, Kripalani S, Rothman RL, Wallston KA. Validation of a Short, 3-Item Version of 
the Subjective Numeracy Scale. Medical decision making : an international journal of the Society for Medical 
Decision Making. 2015;35(8):932-936. PMCID: PMC4592371. 
133. 
Wallston KA, Cawthon C, McNaughton CD, Rothman RL, Osborn CY, Kripalani S. Psychometric properties of the 
brief health literacy screen in clinical practice. Journal of general internal medicine. 2014;29(1):119-126. PMCID: 
PMC3889960. 
134. 
Cunha JP. High Blood Pressure Treatment. 2012 [updated 2012; cited 2012]; Available from: 
http://www.rxlist.com/high_blood_pressure_treatment/article.htm. 
135. 
Ware JE, Kosinski M, Dewey JE, Gandek B. How to Score and Interpret Single-Item Health Status Measures: A 
Manual for Users of the SF-8 Health Survey. Lincoln RI: QualityMetric Incorporated; 2001. 
136. 
Cohen S, Tyrrell DA, Smith AP. Negative life events, perceived stress, negative affect, and susceptibility to the 
common cold. J Pers Soc Psychol. 1993;64(1):131-140. 
137. 
Cohen S, Kamarck T, Mermelstein R. A global measure of perceived stress. J Health Soc Behav. 1983;24(4):385-
396. 
138. 
Buysse DJ, Reynolds CF, 3rd, Monk TH, Berman SR, Kupfer DJ. The Pittsburgh Sleep Quality Index: a new 
instrument for psychiatric practice and research. Psychiatry Res. 1989;28(2):193-213. 
139. 
Knutson KL, Rathouz PJ, Yan LL, Liu K, Lauderdale DS. Stability of the Pittsburgh Sleep Quality Index and the 
Epworth Sleepiness Questionnaires over 1 year in early middle-aged adults: the CARDIA study. Sleep. 
2006;29(11):1503-1506. 
140. 
Moss-Morris R, Weinman J, Petrie KJ, Horne R, Cameron LD, Buick D. The Revised Illness Perception 
Questionnaire (IPQ-R). Psychology and Health. 2002;17:1-16. 
141. 
Bieber C, Muller KG, Nicolai J, Hartmann M, Eich W. How does your doctor talk with you? Preliminary validation 
of a brief patient self-report questionnaire on the quality of physician-patient interaction. Journal of clinical 
psychology in medical settings. 2010;17(2):125-136. 
142. 
Stoyanov SR, Hides L, Kavanagh DJ, Wilson H. Development and Validation of the User Version of the Mobile 
Application Rating Scale (uMARS). JMIR Mhealth Uhealth. 2016;4(2):e72. PMCID: PMCPMC4920963. 
143. 
Stoyanov SR, Hides L, Kavanagh DJ, Zelenko O, Tjondronegoro D, Mani M. Mobile app rating scale: a new tool for 
assessing the quality of health mobile apps. JMIR Mhealth Uhealth. 2015;3(1):e27. PMCID: PMCPMC4376132. 
144. 
Bakken S, Grullon-Figueroa L, Izquierdo R, Lee NJ, Morin P, Palmas W, Teresi J, Weinstock RS, Shea S, Starren J, 
Consortium ID. Development, validation, and use of English and Spanish versions of the telemedicine 
satisfaction and usefulness questionnaire. J Am Med Inform Assoc. 2006;13(6):660-667. PMCID: 
PMCPMC1656962. 
145. 
Demiris G, Speedie S, Finkelstein S. A questionnaire for the assessment of patients' impressions of the risks and 
benefits of home telecare. J Telemed Telecare. 2000;6(5):278-284. 

146. 
Brooke J. SUS-A quick and dirty usability scale. Usability evaluation in industry. 1996;189(194):4-7. 
147. 
Lewis JR, Brown J, Mayes DK. Psychometric Evaluation of the EMO and the SUS in the Context of a Large-Sample 
Unmoderated Usability Study. International Journal of Human-Computer Interaction. 2015;31(8):545-553. 
148. 
Donner A, Klar N. Methods for comparing event rates in intervention studies when the unit of allocation is a 
cluster. Am J Epidemiol. 1994;140(3):279-289; discussion 300-271. 
149. 
Fitzmaurice GM, Laird NM, Ware JH. Applied longitudinal analysis. 2nd ed. Hoboken, NJ: John Wiley & Sons; 
2011. 
150. 
Little RRD. Statistical anlysis with missing data. New York: John Wiley & Sons, Inc.; 1987. 
151. 
Hanley JA, Negassa A, Edwardes MD, Forrester JE. Statistical analysis of correlated data using generalized 
estimating equations: an orientation. Am J Epidemiol. 2003;157(4):364-375. 
152. 
Ballinger GA. Using Generalized Estimating Equations for Longitudinal Data Analysis. Organizational Research 
Methods. 2004;7(2):127-150. 
153. 
Hardin J, Hilbe J. Generalized Estimation Equations. Boca Raton, FL: Chapman & Hall/CRC Press; 2013. 
154. 
Rasu RS, Malewski DF, Banderas JW, Malomo Thomson D, Goggin K. Cost of behavioral interventions utilizing 
electronic drug monitoring for antiretroviral therapy adherence. Journal of acquired immune deficiency 
syndromes. 2013;63(1):e1-8. PMCID: PMC3655520. 
155. 
CPI Inflation Calculator.  Washington, DC: U.S. Bureau of Labor Statistics; 2015 [updated 2015; cited 2-1-2015]; 
Available from: http://www.bls.gov/data/inflation_calculator.htm. 
156. 
Morland LA, Raab M, Mackintosh MA, Rosen CS, Dismuke CE, Greene CJ, Frueh BC. Telemedicine: a cost-
reducing means of delivering psychotherapy to rural combat veterans with PTSD. Telemedicine journal and e-
health : the official journal of the American Telemedicine Association. 2013;19(10):754-759. PMCID: 
PMC3787338. 
157. 
MacKinnon DP, Fairchild AJ, Fritz MS. Mediation analysis. Annu Rev Psychol. 2007;58:593-614. PMCID: 
PMCPMC2819368. 
158. 
Baron RM, Kenny DA. The moderator-mediator variable distinction in social psychological research: conceptual, 
strategic, and statistical considerations. J Pers Soc Psychol. 1986;51(6):1173-1182. 
159. 
Nemeth LS, Nietert PJ, Ornstein SM. High performance in screening for colorectal cancer: a Practice Partner 
Research Network (PPRNet) case study. Journal of the American Board of Family Medicine : JABFM. 
2009;22(2):141-146. PMCID: PMC2696281. 
160. 
Nemeth LS, Feifer C, Stuart GW, Ornstein SM. Implementing change in primary care practices using electronic 
medical records: a conceptual framework. Implementation science : IS. 2008;3:3. PMCID: PMC2254645. 
161. 
Nemeth LS, Ornstein SM, Jenkins RG, Wessell AM, Nietert PJ. Implementing and evaluating electronic standing 
orders in primary care practice: a PPRNet study. Journal of the American Board of Family Medicine : JABFM. 
2012;25(5):594-604. 
162. 
Sieverdes JC, Raynor PA, Armstrong T, Jenkins CH, Sox LR, Treiber FA. Attitudes and perceptions of patients on 
the kidney transplant waiting list toward mobile health-delivered physical activity programs. Prog Transplant. 
2015;25(1):26-34. 
163. 
Sieverdes J, Nemeth L, Magwood G, Baliga P, Chavin K, Ruggiero K, Anderson A, Treiber F. African American 
Kidney Transplant Recipients' Perspectives on Challenges in Living Donation Process. Progress in 
Transplantation. 2015 (In press). 
164. 
Strauss A, Corbin J. Basics of Qualitative Research: Grounded Theory Procedures and Techniques. 2nd ed. San 
Francisco: Sage Publications; 1990. 
165. 
Glaser B, Strauss A. The Discovery of Grounded Theory: Strategies for Qualitative Research. Chicago: Aldine 
Publishing Company; 1967. 
166. 
Borkan J. Immersion/Crystallization. In: Crabtree BF, Miller WL, editors. Doing Qualitative Research. Thousand 
Oaks: Sage Publications, Inc.; 1999. p. 177-194. 
167. 
Patton M. Qualitative Research and Evaluation Methods. San Francisco: Sage Publications; 2001. 
168. 
Creswell J, Plano Clark V. Designing and Conducting Mixed Methods Research. 2nd ed. Thousand Oaks, CA: Sage 
Publications, Inc.; 2011. 
169. 
Riley WT, Rivera DE, Atienza AA, Nilsen W, Allison SM, Mermelstein R. Health behavior models in the age of 
mobile interventions: are our theories up to the task? Transl Behav Med. 2011;1(1):53-71. PMCID: PMC3142960. 
170. 
Resnicow K, Strecher V, Couper M, Chua H, Little R, Nair V, Polk TA, Atienza AA. Methodologic and design issues 
in patient-centered e-health research. Am J Prev Med. 2010;38(1):98-102. 

171. 
Eisenberger U, Wuthrich RP, Bock A, Ambuhl P, Steiger J, Intondi A, Kuranoff S, Maier T, Green D, DiCarlo L, 
Feutren G, De Geest S. Medication adherence assessment: high accuracy of the new Ingestible Sensor System in 
kidney transplants. Transplantation. 2013;96(3):245-250. PMCID: PMC3749815. 
 
 

Autonomous+Motivation+Questionnaire+(TSRQ)((Williams(GC(et(al.(1996)(
(
Description:((The(purpose(of(TSRQ(is(to(assess(the(degree(to(which(one's(motivation(for(a(particular(behavior(
or(set(of(behaviors(is(relatively(autonomous(or(selfRdetermined,(of(if(motivation(is(externally(driven((controlled).(
The(responses(on(the(autonomous(items(are(averaged(to(form(the(reflection(of(autonomous(motivation(for(the(
target(behavior(and(the(responses(on(the(controlled(items(are(averaged(to(form(the(reflection(of(controlled(
motivation(for(the(target(behavior.(In(those(studies(where(amotivation(has(also(been(assessed,(the(amotivated(
responses(are(also(averaged.(These(three(subscale(scores(can(be(used(separately,(or(a(Relative(Autonomy(
Index(can(be(formed(by(subtracting(the(average(for(the(controlled(reasons(with(the(average(for(the(
autonomous(reasons.((Autonomous:(1,3,6,8,11,13m(Controlled:(2,4,7,9,12,14m(No(motivation:(5,10,15)(
(
((
(
1.( Source:((Williams(GC(et(al.((1996)(Motivational(predictors(of(weight(loss(and(weightRloss(maintenance,(
Journal(of(Personality(and(Social(Psychology,(70,(115R126.(
(
Sample(Characteristics:(
94(obese(individuals(who(enrolled(in(a(weight(loss(program.((27%(male(Mean(
age(43.4(Range:(20R77)(
(
Psychometric(Properties:(
Reliability:(
(
TestRretest(coefficient((after(18(months(or(more)(Autonomous(items:(r(=(.47((p(
<(.01),(Controlled(items(.34((p(<.05).(
Validity:(Autonomous(items(correlated(with(Autonomy(orientation(score(of(
General(Causality(Orientations(Scale((r(=.38,(p<(.001)(and(the(Perceived(
Autonomy(Support(of(the(Health(Care(Climate(Questionnaire((r(=.38,(p<.001).(
Predictive(Value:(Autonomous(items(at(start(predicted(attendance((r(=.34,(
p<.001)(and(BMI((r(=(R.11,(p<.05).(
(
2.( Source:(Williams(GC(et(al.((1998)(Autonomous(regulation(and(longRterm(medication(adherence(in(adult(
outpatients,(Health(Psychology,(17,(269R276.(
(
Sample(Characteristics:(
126(Adults(taking(at(least(one(prescription(pill((24.6%(male,(mean(age(56.3(
years,(range:(37R65)(
Psychometric(Properties:(
Reliability:(
Internal(consistency:(Cronbach’s(alpha(score,(Autonomous(items=(.81,(
Controlled(items(=(.84(
(
Validity:(Autonomous(items(correlated(with(the(Perceived(Autonomy(Support(
of(the(Health(Care(Climate(Questionnaire((r(=.24,(p(<.05).(
Predictive(Value:(Autonomous(items(predicted(adherence((r(=.58,(p<.0005).(
(
(

Medication+Adherence+(ASRQ)+
(
The+following+questions+relate+to+the+reasons+why+you+would+either+start+to+take+your+medicine+as+
prescribed+by+your+physician+or+continue+to+do+so.+
+
Different(people(have(different(reasons(for(taking(medicine(as(prescribed,(and(we(want(to(know(how(true(each(
of(the(following(reasons(is(for(you.(Please(indicate(the(extent(to(which(each(reason(is(true(for(you.(
(
All+15+responses+are+to+the+one+question:+
+
The+reason+I+would+take+my+medicine+as+prescribed+by+my+physician+is:+
+
1.+Because+I+feel+that+I+want+to+take+responsibility+for+my+own+health.+
⃝,
⃝,
⃝,
⃝,
⃝,
⃝,
⃝,
1!
Not!at!all!
True!
!
2!
3!
Somewhat!
True!
4!
!
5!
True!
6!
7!
Very!True!
2.+Because+I+would+feel+guilty+or+ashamed+of+myself+if+I+did+not+take+my+medicine+as+prescribed.+
⃝,
⃝,
⃝,
⃝,
⃝,
⃝,
⃝,
1!
Not!at!all!
True!
!
2!
3!
Somewhat!
True!
4!
!
5!
True!
6!
7!
Very!True!
3.+Because+I+personally+believe+it+is+the+best+thing+for+my+health.+
⃝,
⃝,
⃝,
⃝,
⃝,
⃝,
⃝,
1!
Not!at!all!
True!
!
2!
3!
Somewhat!
True!
4!
!
5!
True!
6!
7!
Very!True!
4.+Because+others+would+be+upset+with+me+if+I+did+not.+
⃝,
⃝,
⃝,
⃝,
⃝,
⃝,
⃝,
1!
Not!at!all!
True!
!
2!
3!
Somewhat!
True!
4!
!
5!
True!
6!
7!
Very!True!
5.+I+really+don't+think+about+it.+
⃝,
⃝,
⃝,
⃝,
⃝,
⃝,
⃝,
1!
Not!at!all!
True!
!
2!
3!
Somewhat!
True!
4!
!
5!
True!
6!
7!
Very!True!
6.+Because+I+have+carefully+thought+about+it+and+believe+it+is+very+important+for+many+aspects+of+my+
life.+
⃝,
⃝,
⃝,
⃝,
⃝,
⃝,
⃝,
1!
Not!at!all!
True!
!
!
!
2!
3!
Somewhat!
True!
4!
!
5!
True!
6!
7!
Very!True!

!
7.+Because+I+would+feel+bad+about+myself+if+I+did+not+take+my+medicine+as+prescribed.+
⃝,
⃝,
⃝,
⃝,
⃝,
⃝,
⃝,
1!
Not!at!all!
True!
!
2!
3!
Somewhat!
True!
4!
!
5!
True!
6!
7!
Very!True!
8.+Because+it+is+an+important+choice+I+really+want+to+make.+
⃝,
⃝,
⃝,
⃝,
⃝,
⃝,
⃝,
1!
Not!at!all!
True!
!
2!
3!
Somewhat!
True!
4!
!
5!
True!
6!
7!
Very!True!
9.+Because+I+feel+pressure+from+others+to+do+so.+
⃝,
⃝,
⃝,
⃝,
⃝,
⃝,
⃝,
1!
Not!at!all!
True!
!
2!
3!
Somewhat!
True!
4!
!
5!
True!
6!
7!
Very!True!
10.+Because+it+is+easier+to+do+what+I+am+told+than+think+about+it.+
⃝,
⃝,
⃝,
⃝,
⃝,
⃝,
⃝,
1!
Not!at!all!
True!
!
2!
3!
Somewhat!
True!
4!
!
5!
True!
6!
7!
Very!True!
11.+Because+it+is+consistent+with+my+life+goals.+
⃝,
⃝,
⃝,
⃝,
⃝,
⃝,
⃝,
1!
Not!at!all!
True!
!
2!
3!
Somewhat!
True!
4!
!
5!
True!
6!
7!
Very!True!
12.+Because+I+want+others+to+approve+of+me.+
⃝,
⃝,
⃝,
⃝,
⃝,
⃝,
⃝,
1!
Not!at!all!
True!
!
2!
3!
Somewhat!
True!
4!
!
5!
True!
6!
7!
Very!True!
13.+Because+it+is+very+important+for+being+as+healthy+as+possible.+
⃝,
⃝,
⃝,
⃝,
⃝,
⃝,
⃝,
1!
Not!at!all!
True!
!
2!
3!
Somewhat!
True!
4!
!
5!
True!
6!
7!
Very!True!
14.+Because+I+want+others+to+see+I+can+do+it.+
⃝,
⃝,
⃝,
⃝,
⃝,
⃝,
⃝,
1!
Not!at!all!
True!
!
!
2!
3!
Somewhat!
True!
4!
!
5!
True!
6!
7!
Very!True!

!
15.+I+don't+really+know+why.+
⃝,
⃝,
⃝,
⃝,
⃝,
⃝,
⃝,
1!
Not!at!all!
True!
!
2!
3!
Somewhat!
True!
4!
!
5!
True!
6!
7!
Very!True!
+
+
+

Medication+Adherence+Self]Efficacy+Scale+Revised+(MASES]R)((Fernandez,(et(al.,(2008)(
(
Description:((The(Medication(Adherence(SelfREfficacy(Scale((MASESRR)(consists(of(13(selfRadministered(
questions,(which!measure(situationRspecific(efficacy(beliefs(regarding(adherence(to(prescribed(
antihypertensive(medications.(Responses(are(Not(at(all(sure(=(1,(A(little(sure(=(2,(Fairly(sure(=(3,(Extremely(
sure(=(4.((
(
1.( Fernandez(S,(et(al.((2008)(Revision(and(validation(of(the(medication(adherence(selfRefficacy(scale(
(MASES)(in(hypertensive(African(Americans.(Journal(of(Behavioral(Medicine,(31(6),(453R462(
Sample(Characteristics:(((
168(hypertensive(African(Americans((14%(male)(mean(age(54((±12.4)(
years.(
+
Psychometric(Properties:((
Reliability:(Chronbach’s(alpha(=(.92(
TestRRetest((3(months)(coefficient(=(.51((p<.001).(
Concurrent(Validity:(With(selfRreport(of(adherence,(NonRadherent(Mean(=(
3.51(±(.52,(adherent(Mean(=(3.81(±(.33((p<.001)(
With(electronic(adherence(measure((MEMS)(at(3(months:(r(=(.20,(p(=(.02.(
Predictive(validity:(Baseline(MASESRR(with(MEMS(at(3(months:(r(=(.19,(p(
=(.02.(
2.( Voils(C,(et(al.,((2012)(Initial(Validation(of(a(SelfRReport(Measure(of(the(Extent(of(and(Reasons(for(
Medication(Nonadherence.(Med(Care,(50,(1013R1019.(
Sample(Characteristics:(
202(hypertensive(veterans((86%(male),(mean(age(64.1((±(11)(years,(50%(
Black.(
(
Psychometric(Properties:(
Concurrent(validity:(with(Extent(of(Nonadherence(measure:(r(=(R.42,(
p<.0001.((
+
3.( BreauxRShropshire(T,(et(al.,((2012)!Relationship(of(Blood(Pressure(SelfRMonitoring,(Medication(Adherence,(
SelfREfficacy,(Stage(of(Change,(and(Blood(Pressure(Control(Among(Municipal(Workers(With(Hypertension.(
Workplace(Health(&(Safety,(60(7),(303R311.(
Sample(Characteristics:(
149(hypertensive(municipal(employees((85%(male),(mean(age(47((±(8.4)(
years,(69%(Black.(
(
Psychometric(Properties:(
Concurrent(validity:(with(Morisky(Medication(Adherence(Scale:(r(=(.549,(
p<.001.((
+
+
+

+
MASES]R+
+
Situations(come(up(that(make(it(difficult(for(people(to(take(their(medications(as(prescribed(by(their(doctors.(
Below(is(a(list(of(such(situations.(We(want(to(know(your(feelings(about(taking(your(blood(pressure(
medication(s)(in(each(of(these(situations.(Please(indicate(your(response(by(checking(the(box(that(most(closely(
represents(your(feeling.(There(are(no(right(or(wrong(answers.(
(
For(each(of(the(situations(listed(below,(please(rate(how(sure(you(are(that(you(can(take(your(blood(pressure(
medications(all(of(the(time.(
(
Items+
Not+at+all+
sure+
A+little+
sure+
Fairly+
sure+
Extremely+
sure+
How$confident$are$you$that$you$can$take$your$blood$pressure$medications:+
1.(When(you(are(busy(at(home(
((
((
((
((
2.(When(there(is(no(one(to(remind(you(
((
((
((
((
3.(When(you(worry(about(taking(them(for(the(rest(of(your(
life(
((
((
((
((
4.(When(you(do(not(have(any(symptoms(
((
((
((
((
5.(When(you(are(with(family(members(
((
((
((
((
6.(When(you(are(in(a(public(place(
((
((
((
((
7.(When(the(time(to(take(them(is(between(your(meals(
((
((
((
((
8.(When(you(are(travelling(
((
((
((
((
9.(When(you(take(them(more(than(once(a(day(
((
((
((
((
10.(When(you(have(other(medications(to(take(
((
((
((
((
11.(When(you(feel(well(
((
((
((
((
12.(If(they(make(you(want(to(urinate(while(away(from(
home(
((
((
((
((
Please$rate$how$sure$you$are$that$you$can$carry$out$the$following$task:+
13.(Make(taking(your(medications(part(of(your(routine(
((
((
((
((
(
+
+