A Smartphone Application to Improve Physical Activity in Underactive Older Adults
Phase: NA
Conditions: Sedentary Lifestyle
Sponsor: University of Southern California

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Research Protocol 
IRB Project Title 
A Smartphone Application to Improve Physical Activity in Underactive Older Adults 
Principal Investigator 
Stacey L. Schepens Niemiec, PhD OTR/L 
Assistant Professor of Research  
USC Chan Division of Occupational Science and Occupational Therapy 
1540 Alcazar St., CHP-133 
Los Angeles, CA  90089-9003 
323-442-2069 
Co-Investigators 
Genevieve Dunton, PhD MPH 
Catherine Sarkisian, MD MSPH 
Cheryl Vigen, PhD 
Sarah Barber, PhD 
Collaborators 
Front Porch Center for Innovation and Wellbeing (FPCIW) 
Consultants 
Megan Piper, PhD 
Matthew Niemiec, PT MPT CKTP 
 
 
 

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Table of Contents 
IRB Project Title .................................................................................................................................................................... 1 
Principal Investigator ........................................................................................................................................................... 1 
Co-Investigators ................................................................................................................................................................... 1 
Collaborators ......................................................................................................................................................................... 1 
Consultants ........................................................................................................................................................................... 1 
I. 
Background and Aim ................................................................................................................................................... 3 
II. 
Approach & Methods ................................................................................................................................................... 3 
A. Clinical Trial Design ................................................................................................................................................... 3 
A.1. App Intervention ................................................................................................................................................... 4 
A.2. Clinical Trial Design Details ................................................................................................................................ 4 
B. Participants, Recruitment, and Consent ................................................................................................................. 5 
C. Procedures & Measurement ..................................................................................................................................... 6 
III. Data Management, Analysis, & Statistical Considerations .................................................................................... 7 
IV. Protection of Human Subjects .................................................................................................................................... 8 
A. Risks to Human Subjects ........................................................................................................................................... 8 
A.1. Human Subject Involvement, Characteristics, and Design............................................................................ 8 
A.2. Sources of Materials ............................................................................................................................................ 9 
A.3. Potential Risks ...................................................................................................................................................... 9 
B. Adequacy of Protection against Risks .................................................................................................................... 10 
B.1. Recruitment and Informed Consent ................................................................................................................ 10 
B.2. Protections against Risk .................................................................................................................................... 11 
C. Potential Benefits to Human Subjects and Other ................................................................................................. 12 
D. Importance of Knowledge to be Gained ................................................................................................................ 12 
V. 
References .................................................................................................................................................................. 13 
 
 
 

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I. Background and Aim 
Despite the well-established health benefits of physical activity (PA),[1-7] less than 10% of people aged 
60+ years meet national PA guidelines.[8] Barriers to PA that contribute to this bleak statistic include 
factors such as feeling “too old,”[9] inadequate support,[10-12] and low self-efficacy.[13] Unfortunately, 
after completing home-based, group, or educational interventions, older adults’ PA improvements are 
minimal and short-lived.[7, 14, 15] In light of these challenges, it is important to investigate alternative 
interventions for elders that improve PA.  
 
Attention has recently turned toward using smartphone applications (apps) to improve health behaviors.[16] 
Such technology extends healthcare beyond in-person clinical visits due to its versatility, portability, and 
potential cost-savings. However, few health apps are scientifically evaluated[17-19] and even fewer are 
tailored to the specific needs of older adults. This research gap has prompted the Centers for Disease 
Control to call for studies that link mobile health (mHealth) solutions to healthy aging agendas.[20]  
 
In the proposed study, we will develop, test, and optimize a core app and set of attached specialty features 
that are designed to facilitate older adults’ PA. This package, termed the Moving Up suite, is distinct from 
generic fitness apps because it blends evidence-based behavior change techniques (e.g., self-regulation 
via activity monitoring) in the core app with a set of specialized components that reflect empirically 
supported constructs from social cognitive[21, 22] and stereotype embodiment theory.[23] Specialty 
features include: (a) implicit and explicit messaging to promote positive aging views; (b) sedentary activity 
(SA) monitoring with motivational messaging and peer suggestions; and (c) data-driven, automated remote 
coaching and support. To date, no other app has offered a comparable suite that has been systematically 
optimized to address inactivity in older people, justifying the need to scientifically evaluate this type of tool. 
In the clinical trial phase of the study, we will utilize a highly efficient, innovative methodological approach—
Multiphase Optimization Strategy (MOST)[24, 25]—to provide an experimental context for evaluating each 
of the Moving Up suite’s specialty features. The MOST procedure originated from the field of engineering 
and is explicitly designed to facilitate selection of intervention components by elucidating their individual 
and synergistic effects (a key gap in health app research). 
 
The specific aim of the clinical trial phase of this study is to conduct a pilot test to examine key 
performance characteristics of the PA-tracking core app and its three specialty features. This will 
include the MOST Screening Phase: theory-guided experimentation to identify viable components within a 
multifaceted preliminary intervention plan.[24] Using a factorial design as specified in MOST procedures, 
100 underactive older people (i.e., those accumulating <150 minutes of at least moderate intensity 
activity/week)[8, 26] will be randomly assigned to one of eight conditions which reflect all possible 
combinations of presence vs. absence of the three respective specialty features, given usage of the core 
PA-tracking app. At the end of a four-month intervention period, for the core app as well as for each 
specialty feature we will examine changes from baseline in objective PA, SA time, self-reported PA, and 
functional mobility. We will also test the association between the app component features and theoretically 
postulated mediating constructs (self-efficacy, self-regulation, outcome expectation, social support, aging 
self-perception, and views of aging). In addition, we will document usage rate and satisfaction with the app.  
II. Approach & Methods 
A. Clinical Trial Design 
This two-part study initially involves a two-week field test of the PA-tracking app suite followed by a focus 
group and then a four-month trial of the refined suite. This later segment is the focus of this clinical trial 
protocol description. A description of the app suite and details of the trial design are provided in the 
subsequent sections. 

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A.1. App Intervention 
The PA-tracking app suite was designed using SCT[21, 22] 
and SET[23] as its theoretical framework. SCT posits four 
determinants of health-promoting behavior: self-regulation, 
self-efficacy, social support, and outcome expectation.[21, 
22] SET describes the process and consequences of 
internalizing age stereotypes, such that aging self-
perceptions and general views of aging are associated with 
health and survival.[27, 28] Each construct above has been 
linked empirically to improved PA patterns in elders.[29-32] 
Figure 2 depicts the theoretical framework underlying the 
PA-tracking app suite. For heuristic purposes, arrows 
represent the primary pathways by which we expect the 
suite components to influence the set of mediators and 
thereby PA-related outcomes. It is beyond the scope of this proposal, however, to designate all 
conceivable associations that the app features may have with each theoretical construct.  
 
The PA-tracking core app mainly targets self-regulation and outcome expectation. Its goal-setting function 
submits a default, adjustable daily PA benchmark. By displaying real-time PA, it allows visual tracking of 
goal progress. In addition to the core app, three specialty features are proposed that also address key SCT 
or SET considerations and are tailored to overcome elder PA barriers: (1) Proof Positive, as motivated by 
SET, capitalizes on the beneficial effects that exposure to positive aging messages and stereotypes have 
on health and PA.[29, 33] When activated, users (a) receive texts describing how old age does not equate 
to physical inability, (b) obtain information about the benefits of growing older, and (c) are presented with a 
variety of positive aging stereotype tasks modeled after priming activities commonly used in the field (e.g., 
word scrambles,[34] picture identification,[35], computerized series [33, 36-38]). This last example exposes 
users to blocks of “positive priming words”.[33] Primers are quickly flashed to allow perception without 
awareness[36] while users focus on an image of activity—a step that builds on Levy’s work by 
simultaneously offering explicit cues that promote PA. (2) On Your Feet is designed to reduce SA—a 
health risk factor largely independent of insufficient PA[39]—by using self-regulatory and behavior change 
techniques including goal-setting, progress feedback, and prompting.[40] Accumulated sedentary time is 
displayed alongside self-selected goals; audible, vibratory, or text-based reminders to stand are sent at a 
user-specified frequency; and general tips as well as previously compiled, older adult-identified strategies 
to reduce SA[6] are texted. Additionally, messages about the benefits of reducing SA and overcoming 
barriers (e.g., fatigue) are also sent. (3) Coach Me includes daily messages designed to assist older adults 
in (a) discovering practical ways to integrate brief bouts of PA into their daily routines and (b) overcoming 
common PA barriers.[41, 42] Blending PA with productive activity has been identified as a key facilitator of 
PA engagement in older people.[43, 44] In Coach Me, suggestions on how to intensify common daily 
activities are tailored based on user selections from an activity inventory stored within an individual’s 
Moving Up profile. For example, if a user identifies “laundry” on the inventory, Coach Me may suggest “heel 
raises while holding onto the dryer before placing clothing in a basket.” This app feature is intended to help 
older adults become more active in a minimally intrusive way, while allowing for simultaneous engagement 
in productive and meaningful activities. Coach Me asks users to select obstacles to PA encountered in the 
previous week. Based on those selections, the app sends strategies on how to overcome those barriers in 
the future, thereby targeting self-efficacy.  
 
A.2. Clinical Trial Design Details 
We will utilize the MOST procedure to assess the app suite specialty features’ efficacy and other 
performance aspects. MOST is explicitly designed to disentangle the effects of multiple components that 
make up an intervention26,105—a key project goal given our intent to appraise the merit of novel, previously 
untested app features. Traditionally, multi-component interventions are subjected to efficacy pilot tests 
followed by large RCTs, but in the absence of systematic evaluations of singular components. However, in 
such cases: (a) the intervention may contain inert ingredients that contribute to subpar or cost-inefficient 
results; or (b) difficulties may arise in determining which intervention aspects contribute to efficacy, due to 
the presence of multiple components which have not been individually tested. In contrast, following 

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systematic optimization as facilitated by MOST, subsequent RCTs are expected to produce sharper, more 
interpretable results. 
 
Based on recommendations from the MOST literature, we will employ a 2x2x2 factorial experiment in which 
three between-subject factors, corresponding to the presence vs. absence of each specialty feature, will be 
manipulated in a completely crossed design, given each participant’s utilization of the core app. Following 
random assignment (using a computer algorithm designed for this purpose) to the eight conditions, 
participants will undergo a four-month intervention interval. Experimental outcomes will consist of pre-to-
post change scores on PA-related and mediating variables, and documentation will also be provided for 
parameters such as usage frequency and user satisfaction that are pertinent to subsequent efforts to 
achieve optimization.  
 
Each specialty feature will be provided to half of the participants, leading to respective comparative 
assessments that involve 45 vs. 45 (feature present vs. absent) participants. Accordingly, it is incorrect to 
conceptualize this design as a test of outcome differences between eight separate inadequately powered 
cells; rather, the intent is to collapse information across cells so as to obtain a reasonably large sample 
size when examining each component’s performance.[24] Further, because the specialty features would be 
inexpensive to download if used in large-scale distributions of the app, and because they have been 
carefully designed to reflect empirically supported theory, it is important to avoid premature elimination of 
features on the basis of non-significant experimental effects which in actuality may stem from sample size 
limitations. Consequently, in evaluating intervention components we will downplay the importance of 
(though still include) significance testing of PA outcomes, and instead will incorporate the total array of 
relevant information (e.g., effect sizes, usage rates, satisfaction ratings) in the final component selection 
and fine-tuning process. 
 
B. Participants, Recruitment, and Consent 
For Aim 1, a convenience sample of 15 elders will be recruited from independent-living communities within 
FPCIW’s 2,000-member senior network in Los Angeles (LA) and local senior venues. An estimated 1,300 
FPCIW members use smartphones.[45] Iterative phases of product development require only five to seven 
representative users per prototype iteration,[46] justifying our sample size of 15 (five per app suite specialty 
feature).  
One-hundred community-living older adults who are served by Front Porch Center for Innovation and 
Wellbeing (FPCIW) will be primarily recruited from FPCIW’s 2000-member senior network in Los Angeles. 
FPCIW will facilitate recruitment, referring its eligible members to the study team. Justification for the 
targeted sample size is multifold. First, an adequate number of participants will be available to enable 
meaningful analyses (final N=90) given a four-month attrition rate of 10% (estimate based on averaging 
interval-adjusted study completion rates in five studies of mHealth or web-based PA interventions for adults 
aged >40 years[47-52]. Second, the expected overall (N=90) and per-feature (n=45) sample sizes well 
exceed the number of participants previously described as necessary to determine if a larger trial is 
warranted.[53] Third, the stipulated sample size is easily achievable and represents roughly the maximum 
number of participants attainable given available funding resources.   
Persons will be deemed eligible based on the following criteria. Inclusion criteria: men or women, 65–84 
years old; English speaking; reside in LA or in Pacific Time Zone if participating remotely; score ≥5 on a 6-
item cognitive screener[54]; report <150 minutes of moderate-to-vigorous PA/week as per a single-item 
screener;[55] ambulatory; ability to safely participate in PA as determined by self-report of ability to 
regularly walk safely; smartphone owner for ≥1 month; observed ability to reliably access and operate a 
smartphone during orientation; available by telephone for the duration of either study. Exclusion criteria: 
unwillingness to meet at local community venues and/or via online meetings to comply with study 
procedures for the length of each study. Although not an eligibility criterion per se, access to a computer 
and webcam, and sufficient computer skills to participate in virtual orientation is necessary if in-person 
orientation is not feasible. 

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Prospective participants who have been referred to the study team by FPCIW or who have responded to 
advertisements or presentations will be initially screened for eligibility over the phone or in person by 
authorized research personnel. After initial screening, informed consent materials will be sent or handed to 
prospective participants for pre-review. Authorized research personnel will then perform the consent 
process for qualifying participants at local community venues that are convenient to the participants. If an 
in-person meeting for enrollment (including consenting) is not feasible, we will conduct enrollment activities 
virtually through phone calls or videoconferencing, and will send consent forms electronically to participants 
using DocuSign or a REDCap eConsent form to review and complete. Only key personnel who are HIPAA 
and CITI certified, trained in consenting procedures, and do not have a conflict of interest will conduct the 
consent process. The consenter will explain the study procedures and describe in detail what will be 
expected of participants. Participants will have ample time to ask questions about the study and their role in 
it. If the individual is interested in participating, they will sign the consent form. If participants are not 
comfortable with the study, they may choose not to participate. Following consent, an assessment battery 
would be held next.   
C. Procedures & Measurement 
Participants will complete an orientation, either in-person or online, that includes activation of and training 
to use select app features on their personal phones. They will be encouraged to carry their phones during 
activity, a behavior we will reinforce by providing toting accessories (e.g., waist pouch) and monthly 
telephone check-ins beginning in week one. Participants will be shown how to manually enter PA data that 
cannot be captured automatically (e.g., due to water-based sports). During check-ins, participants will be 
offered technology support, and will be questioned about events that may have altered their phone usage 
or activity patterns (e.g., hospitalization). Additionally, a troubleshooting asynchronous hotline will be made 
available to participants during the intervention. 
 
Study measures (apart from the four-meter walk test and collection of usage data) will be either (1) mailed 
or dropped off/picked up through contactless hand delivery to participants, including paper-based 
instructions or a link to video-based instructions and a pre-addressed/postage pre-paid envelope—
telephone assistance will be made available to complete requested study tasks; (2) emailed with 
instructions for electronic completion—telephone assistance will be made available to complete requested 
study tasks; and/or (3) administered by a condition-blind tester at a FPCIW or other community venue at 
baseline and/or post-intervention. A combination of remote plus in-person assessment session contact may 
be deemed necessary based on participant needs. The most likely scenario for this hybrid contact is if 
participants need in-person support to don their activity monitor appropriately. This will be decided on a 
case-by-case basis and is unlikely to be necessary for more than a few participants. 
 
In-person sessions will typically include 2–8 participants, with the assessment battery lasting approximately 
1.5 hours. Objective PA level (primary targeted outcome) and objective SA time will be assessed during a 
three-day monitoring period pre- and post-intervention the activPAL (Pal Technologies Ltd), a thigh-worn 
monitor that is considered the gold-standard for tracking sedentary behavior in free-living conditions.[56-58] 
Proprietary algorithms available from activPAL software analysis program will be used to aggregate PA- 
and SA-related data. (Although the PA-tracking core app provides useful intervention-facilitating PA 
feedback,[59] app-based PA records will not be used as outcome data because they have not been 
validated for this purpose and do not include useful baseline information.) Auto-calculated times identified 
by activPAL software will be used to identify wear periods and sleep/wake times, with participant reports of 
these periods as manually entered into the device for the purpose of corroboration.   
 
Self-reported PA will be measured via the Physical Activity Scale for the Elderly (PASE).[60] PASE is a ten-
item instrument designed to assess engagement in PAs commonly encountered by older adults, including 
those related to leisure, household, and occupational tasks. The tool is a valid and reliable measure of PA 
engagement in older populations.[60, 61] For assessment sessions conducted in-person, Functional 
mobility will be assessed through a four-meter walk test,[62-65] a commonly used, validated measure of 
physical and functional performance in older adults. 
 

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The potential mediators PA self-efficacy, self-regulation, outcome expectation, and social support will be 
measured using the 78-item PA scale of the Health Beliefs Survey.[66, 67] Subscales demonstrate 
sufficient internal consistencies (Cronbach’s α=0.68–0.90) and are predictive of PA.[32] Aging self-
perceptions will be assessed by the Attitudes Toward Own Aging subscale of the Philadelphia Geriatrics 
Center Morale Scale.[68, 69] This five-question tool captures the subjective aging experience, shows 
moderate internal consistency (Cronbach’s α=0.61–0.64), and predicts mortality risk.[27] Views of aging 
will be measured using the Attitudes to Ageing Questionnaire,[70] a 24-item tool that assesses subjective 
views about age-related psychosocial, physical, and psychological changes; is cross-culturally valid; and is 
psychometrically sound (Cronbach’s α=0.68–0.84).[70] Usage behavior (e.g., frequency of opening the 
app) will be captured via the app platform, and perceived usefulness of assigned features will be measured 
via the the Mobile App Rating Scale – Adapted user version [uMARS], as well as the post-study phone 
interview (included to inform optimization beyond information gleaned from the clinical trial).  
 
Table 1 summarizes the study’s measurement plan for Aims 1 and 2. Each of the aforementioned pre-
existing assessments has been validated for use with community-dwelling older adults.  
Table 1. Overview of Study Variables 
 
Category 
Variable(s) 
Primary Role in Study 
Measurement 
Timing 
Background: 
Demographics/ Health/ 
Smartphone Information 
Age, Sex, Race/Ethnicity, Education,  
Marital Status, Living Status, Income, 
Employment,  Health Conditions, Health 
Tracking Behavior, Mins PA/Wk, Major 
Health Problems (e.g., diabetes), 
Smartphone Ownership Duration, 
Smartphone Platform, Smartphone 
Proficiency (self-rate 1-10), Smartphone 
Carrying Location, Research and Wellness 
Program Participation  
Sample Description  
Potential Covariates 
Demographic/Background Questionnaire 
[~18 items] 
Baseline 
Mediators 
Views of Aging  
Tests of Mediation 
Attitudes to Ageing Questionnaire [24 items] Baseline and post 
Aging Self-Perceptions 
Tests of Mediation 
Attitudes Toward Own Aging subscale of the 
Philadelphia Geriatrics Center Morale Scale; 
[5 items]  
Baseline and post 
PA Self-Regulation, PA Self-Efficacy, PA 
Outcome Expectation, PA Social Support 
Tests of Mediation 
Health Beliefs Survey [78 items] 
Baseline and post 
PA-Related Outcomes 
Objective PA Level 
Primary Dependent Variable 
activPAL 
Baseline and post 
Self-Reported PA Level 
Dependent Variable 
Physical Activity Scale [PASE; 10 items] 
Baseline and post 
Functional Mobility 
Dependent Variable 
4-meter Walk Test 
Baseline and post 
Objective Sedentary Time 
Dependent Variable 
activPAL 
Baseline and post 
Usability 
Satisfaction 
App Refinement 
Mobile App Rating Scale – Adapted User 
Version [uMARS; 5 items] 
Post 
Interview 
4-month phone call 
Objective Usage: Proportion of days 
opening the app 
App Refinement 
App-Stored Usage Data 
full study duration 
 
III. Data Management, Analysis, & Statistical Considerations  
 
Our biostatistician will secure and archive data, and will oversee all data analytic functions. Usage data for 
each participant will be obtained from storage within the app and downloaded manually at in-person 
assessment sessions. Data will be transferred to the biostatistician for analysis and storage on the USC 
secure network. activPAL data will be downloaded and cleaned. Using proprietary algorithms supplied by 
PAL Technologies, waking-hour wear periods will be identified for use in analysis. 
 
Data analysis will be organized around the goal of providing multiple sources of information useful for 
future efforts to optimize the Moving Up app suite. We will calculate descriptive statistics at baseline and/or 
post-intervention for demographic, app usage behavior [proportion of days opening the app ≥1 time], user 
satisfaction [perceived app quality, physical activity-related (objective physical activity [primary outcome; 
daily steps], sedentary activity time [daily sitting time], self-reported physical activity, functional mobility 
[gait speed]), and mediational (i.e., self-efficacy for physical activity, self-regulation for physical activity, 
family social support for physical activity, outcome expectation for physical activity, aging self-perceptions, 
views of aging) outcome variables, both for the overall sample and by on/off status of each of three 
specialty features (i.e., Proof Positive, Coach Me, and On Your Feet).  
 

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Indicator variables will be created to code whether or not the participant had each of the specialty features 
installed on their phone as part of the intervention. Results regarding outcomes and hypothesized 
mediators will be calculated overall and by feature subgroup. The feature subgroups are not mutually 
exclusive since a participant can be randomized to receive 0, 1, 2, or all 3 of the features.  
 
Specialty feature condition effects on the objective physical activity (change in daily steps) primary 
outcome will be analyzed using a mixed effects linear regression model adjusted for confounders (including 
presence/absence of other specialty features, between-feature interactions, select demographic variables 
[age, sex, race/ethnicity, education]), and baseline daily steps. Although significance testing will provide 
merely one source of information in driving app optimization decisions, the anticipated sample size (N=90) 
was chosen to enable 80% power (given α=.10 and a one-tailed test, as consistent with recommendations 
for pilot studies employing MOST) in testing experimentally based pre-post physical activity increases 
associated with a specialty feature (given an effect size of .45, a feasible value based on prior tests of 
technology-based physical activity intervention components). Using change-from-baseline scores for 
objective physical activity, we will derive Cohen’s d effect sizes stratified by presence vs. absence of each 
specialty feature. For secondary physical activity-related outcomes and proposed mediators, we will 
conduct multiple one-tailed t-tests (α=.10) to further explore the potential viability of the specialty features. 
To facilitate later RCT planning, we will also calculate single group pre-post change effect sizes for the full 
sample. Correlation coefficients will be calculated to assess associations between the primary outcome 
(change in daily steps) and proposed mediators. To analyze app usage behavior and user satisfaction, for 
each intervention feature considered separately, we will perform one-tailed t-tests to examine mean 
differences in each variable based on whether or not the participant was assigned to receive that feature.  
 
After participants conclude the clinical trial phase, they will take part in an interview about their experience. 
Interview responses will be audio-recorded, transcribed verbatim, coded, and analyzed using qualitative 
data analysis software. All qualitative data analyses will be performed by the PI, Co-investigators, and/or 
authorized Research Assistants. Initial thematic analysis will incorporate codes suggested from the Health-
ITUEM.[71] Additional codes will be identified as they arise in the data. Rigor will be achieved through peer 
review of themes and by maintaining an audit trail of analytic memos.  
IV. Protection of Human Subjects 
A. Risks to Human Subjects  
A.1. Human Subject Involvement, Characteristics, and Design  
A total of 100 underactive older adults (accounting for 10% attrition) will participate in the clinical trial phase 
to accomplish the aims of the study. Subjects will be between the ages of 65 and 84 years old, and will be 
users of smartphones for ≥1 month. Underactive individuals will be targeted (i.e., those who accumulate 
<150 minutes of at least moderate intensity physical activity per week) due to their high risk for chronic 
disease resultant from lack of physical activity engagement and sedentary behavior. Additional inclusion 
criteria for entrance into the study includes ability to reliably access and operate basic features of a 
smartphone (ascertained by completion of the two-hour orientation and demo session). Exclusion criteria 
are unwillingness to meet at local community venues or comply with study procedures for the length of 
each study. 
A four-month intervention period will take place. On a randomized basis, the research participants (N=100) 
will be assigned to one of eight conditions whereby they will have access to various combinations of the 
app suite features. Intervention dosage is consistent with small pilot studies of physical activity 
interventions for older groups of adults. They will complete an orientation session, either in person or 
online. Check-in phone calls will be made by project staff during months 1, 2, and 3, for purposes of 
troubleshooting and gleaning initial impressions of app usage. A short interview covering usability and 
feasibility will be conducted during the final phone check-in just after completion of the 4-month 
intervention. Pre- and post-intervention, each participant will complete a battery of self-report assessments 
and clinical measures and complete a three-day physical activity monitoring period using a wearable 
accelerometer. These assessments will be either (1) mailed to participants or dropped off/picked up 

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through contactless hand delivery, including paper-based instructions or a link to video-based instructions 
and a pre-addressed/postage pre-paid envelope—telephone assistance will be made available to complete 
requested study tasks; (2) emailed with instructions for electronic completion—telephone assistance will be 
made available to complete requested study tasks; and/or (3) administered by a condition-blind tester at a 
FPCIW or other community venue. A combination of remote plus in-person assessment session contact 
may be deemed necessary based on participant needs. The most likely scenario for this hybrid contact is if 
participants need in-person support to don their activity monitor appropriately. This will be decided on a 
case-by-case basis and is unlikely to be necessary for more than a few participants. If the full assessment 
session is held in-person, each session (excluding the three-day physical activity monitoring component) is 
anticipated to take approximately one hour to complete. Total length of enrollment will be four months and 
approximately two weeks to account for pre- and post-testing. There are no collaborating sites in this 
proposed study.   
A.2. Sources of Materials  
Data will be collected from participants by blinded raters at two assessment sessions (pre- and post-
intervention) or via US mail, contactless hand delivery/pick-up, or secure email for digital completion, two 
three-day activity monitoring periods (pre- and post-intervention), and during a four-month intervention 
period. Data to be gathered at the pre- and post-intervention assessment sessions include demographic 
and background information, health beliefs regarding physical activity, self-reported physical activity, and 
sedentary time. If assessment sessions are held in-person, functional mobility will be assessed during a 
four-meter walk test administered by trained research personnel. Upon completion of assessment 
sessions, data coding forms and materials will be delivered to the study center at USC and kept in locked 
file drawers. During each of the three-day activity monitoring periods, participants will wear a research-
grade accelerometer. Activity patterns and wear patterns tracked through this device will be manually 
downloaded to and stored on a secure database. During the four-month intervention period, participants 
will be utilizing the PA-tracking core app/mechanical pedometer and specified specialty features on their 
smartphones. Data automatically captured through the app such as activity patterns (e.g., minutes 
engaged in moderate intensity activity) and app usage behaviors (e.g., frequency of accessing various app 
features) will be gathered through the in-app tracking software. These data will be downloaded from the 
app database and transferred to a secure USC server in coded format as described above. Participants will 
be educated (verbally and via a written SOP [“Information Collected in App”]) when they install the app, 
about data that will be collected within the app, what will happen to those data at the end of the study.  A 
short interview to collect usability and feasibility data will be conducted during the final phone check-in just 
after completion of the 4-month intervention.  For this study, participant identities will be known to the 
project manager and authorized personnel except for research staff who will complete blinded evaluations 
during the pre- and post-intervention assessment sessions.   
A.3. Potential Risks  
The overall risk to subjects in this study is low.  
Self-report information. It is possible that some participants might feel minor embarrassment when 
reporting aspects of their personal resources, daily activities and behaviors, and health beliefs regarding 
physical activity. It is also possible that some participants will feel uncomfortable with selected aspects of 
the study such as interacting in a small group of peers.   
Functional mobility testing. A low risk stems from participation in the functional mobility test (i.e., the four-
meter walk test) during the pre- and post-intervention assessment sessions. As with any walking task, 
there is always the potential risk of falling. It is unlikely that participants will become fatigued during this 
task given the short distance the test requires to travel.  
Physical activity monitoring using accelerometers. The risks associated with wearing the activPAL 
accelerometer are minor. The devices are small (51 X 34 X 8 mm) and lightweight, about the size of a 

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men’s wristwatch. They are designed for long-term activity monitoring and for use in sleep studies. 
Individuals may report, though unlikely, discomfort from the cloth straps available.   
Physical activity engagement. Engagement in physical activity poses a low risk of physical discomfort to 
participants. As with any intervention that encourages participants to increase physical activity levels, 
participants may experience fatigue or minor muscular discomfort that may accompany increased physical 
activity levels. This discomfort typically resolves in one to two days. There is also a risk for injury related to 
engaging in PA in a non-supervised setting. 
Exposure to explicit and subliminal positive aging stereotype messages. There is a slight risk that exposure 
to positive messages (both explicit and implicit) about aging may have a neutral or negative influence on 
participants’ views about aging and engagement in PA. For instance, a message that is paired with an 
image of an older adult playing tennis may discourage someone who is unable to engage in sports due to 
physical disabilities.  
Confidentiality. There is a slight risk that people who are not connected with this study will learn a 
participant’s identity or personal information. During interviews and focus groups, which are audio recorded 
in a private room, participants will be identified by a false name to protect their identity on the audio 
transcripts. If audible personally identifying information is recorded during the focus group, this information 
will be deleted from the written transcriptions. Audio recordings will be listened to in a private setting and 
stored on a secure server at USC until the transcription process and qualitative data analyses are 
complete. Pseudonyms and real names will only be connected through one password-protected file on the 
Division of OS/OT secure server, in a separate location from the original data and transcribed files. An 
audio recording release form will be required for signature to participate in the focus group.   
There is also a slight risk for a potential security breach of the app that stores participants’ smartphone 
usage patterns and information or the USC server where participant data are finally stored for analysis. To 
mitigate this risk, data auto-collected from the tracking features of the app will be in coded format (i.e., no 
participant personal identifiers will be included with these data) as will be the case for any data collected 
during the assessment session. Additionally, the USC servers are password-protected and include network 
restrictions. Access rights to the servers will be terminated when authorized study personnel leave the 
study.  
Other risks. Participants may choose to use their smartphones in unsafe ways (e.g., accessing an app 
while crossing the street). Though this behavior is not necessarily isolated to our study, to mitigate the risk 
we will distribute a safe handling of phones information sheet following the informed consent process.     
Overall burden. The level of burden for subjects is a concern in any research study, though we feel 
participant burden is relatively low for this study. The most identifiable burden is associated with subjects’ 
time devoted to completing the assessment sessions, interviews, or focus groups, and energy and effort 
involved with utilizing the smartphone app in daily life for four-months. Use of the app is on a voluntary 
basis for the four-month testing period. Participants may use the app and assigned specialty features as 
often or as infrequently as they choose. Participants are also free to withdraw at any time should they 
decide that the burden becomes too great.  
B. Adequacy of Protection against Risks  
B.1. Recruitment and Informed Consent  
We will use a multi-faceted recruitment approach for the proposed research. Participants will be recruited in 
the following ways: (a) telephone contact of potentially eligible participants as identified by our Front Porch 
community partner within their network database; and (b) study opportunity presentations delivered at local 
Front Porch-affiliated community senior centers or outside networks. A Front Porch Project Coordinator will 
be responsible for contacting prospective participants within their community network. If the individual is 
agreeable, contact information will be forwarded to the study team for follow-up and further screening.   

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In all cases, informed consent will be obtained only by authorized, trained study personnel. Each 
prospective subject is given time to read the consent and discuss his or her options with project staff and 
family members. To ensure ample time to peruse the consent information, we routinely mail or e-mail 
copies of a sample document to each interested party. When the prospective participant is ready, a 
dialogue regarding the study will ensue. The study team member is responsible for guiding the discussion, 
and will be instructed to follow a standard format to ensure that all required elements are introduced. 
Explanations will cover all aspects of the intervention, the testing requirements, participants’ rights, and 
other relevant information. Individuals will have an opportunity to ask questions about the study and, if they 
choose to enroll, will sign a printed or electronic consent form. They will be provided with a printed or 
electronic copy of the consent form and the Research Subject’s Bill of Rights.   
B.2. Protections against Risk  
A number of safeguards will be in place to minimize risk. All interactions with participants will be performed 
by qualified study personnel. Prior to performing their duties, all study staff who will interact with 
participants will undergo specific training for their research tasks, with attention being devoted to issues 
surrounding risk to human subjects. Toward this end, all staff members will be required to complete HIPAA 
and IRB certification, and will be informed of potential pitfalls relevant to human subject concerns that 
surround their job duties. Intervention delivery content sent through the automated remote coach will be 
overseen by the PI who is a licensed occupational therapist and Co-I Sarkisian who is a medical doctor. At 
the outset of the study and at subsequent three-month intervals, a project staff meeting will be held in 
which all study personnel will discuss the safety and proper treatment of research participants. These 
meetings will be mandatory for all project personnel who have contact with participants or with data that 
result from the study. Dr. Sarkisian will be present at these meetings, as well as furnish advice regarding 
the medical safety of the intervention and how to deal with any medically relevant problems that arise.   
Self-report information. Subjects may refrain from answering any questions without prejudice. We also 
have subjects complete their surveys in our presence when possible. This serves two purposes: 1) we can 
answer questions that arise regarding individual items, and 2) we can provide immediate assistance if 
necessary. While severe reactions to answering personal questions are rare; we will offer counseling and 
emergency resources available to those in need. Participants who complete mailed or digital assessments 
independently will be provided with a phone number to call with any questions or concerns. 
Functional mobility testing. In order to minimize risks associated with functional mobility testing (i.e., the 4-
meter gait speed test), participants who attend in-person assessment sessions are instructed to walk a 
self-selected normal pace. A study team member will be nearby throughout the testing to offer assistance 
as needed. For those individuals who deem any discomfort or instability too extreme, there is the option of 
discontinuing the testing procedures.  
Physical activity monitoring using accelerometers. We will offer the option of wearing a terry cloth thigh-
band underneath the accelerometer if participants are experiencing discomfort from straps or adhesive. 
The additional layer between the skin and accelerometer eliminates any discomfort associated with the 
device skin contact and does not affect the data collection process. If this option is not acceptable to the 
participant, the subject may be excluded from further participation in the study.  
Physical activity engagement. To mitigate the risk of engaging in increased levels of physical activity, we 
have included self-reported screening question that asks individuals if they believe they are safe to 
regularly walk. Co-I Sarkisian—a medical doctor and geriatrician—has deemed this screening question 
sufficient given the low-risk and non-prescriptive nature of the intervention. If an individual answers “no” to 
this question, then he/she will be excluded from the study. Activity engagement during the intervention 
period is voluntary. We will recommend moderate intensity walking, a low risk physical activity for older 
adults, during the intervention period (i.e., as part of the goal-setting and remote coaching components of 
the app). The medical doctor and physical therapist on our investigative team will provide ongoing 
consultation to ensure safe physical activity engagement. We will ask about adverse events whenever our 

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team has contact with participants to ensure that we capture all events that may affect data outcomes. If 
research personnel who have contact with participants become aware of any clinically significant problems 
related to the health of one of the participants, research personnel will recommend that the participant 
contact his or her primary care facility and will be available to assist him or her with accessing the 
necessary services. For emergency events that occur during assessment visits, we will follow standard 
USC health system protocols.  
Exposure to explicit and subliminal positive aging messages. The implicit messages that contain priming 
words used in the intervention were rated positively in two pilot studies in preparation for a larger study. 
Therefore, the likelihood that the implicit messages will result in negative views about aging is low. The 
explicit messages have all been reviewed by the team’s social psychologist, Dr. Barber, who has expertise 
in older adult stereotype threat. She has confirmed that the messages do not present negative stereotypes 
that could adversely affect older adults’ views on aging. Because the explicit messages may be paired with 
images of older adults, our team has carefully selected images that reflect a wide range of daily activity 
capabilities; images reflecting engagement in extraordinary activities (e.g., skydiving) were avoided. The 
final assessment session, led by a research assistant, will conclude with a careful and detailed debriefing 
conversation about aging stereotypes and their effects on health and wellness in older adults.  
Confidentiality. All information obtained from the participants will be kept confidential among appropriate 
members of the study group. During computerized data analysis, anonymity of all study participants will be 
assured by the appearance of their names next to their study IDs only on a single log, to be maintained and 
stored in a password-protected and HIPAA-compliant REDCap database. Access to the study ID log will 
only be granted to users that need this information to follow-up with the participant. With respect to study 
personnel who will interact with participants, we will maintain strict standards that forbid the leakage of 
information about study participants to unauthorized individuals either within or outside the study team. 
These strategies are likely to succeed in eliminating any possible harm to participants due to leaking of 
personal information. A description of mitigating the risks of being audio recorded during the interviews is 
included in section IV. A.3: Confidentiality. Each of the above safeguards is expected to substantially 
reduce the participants’ study participation risks.  
C. Potential Benefits to Human Subjects and Other  
All individuals who complete the four-month intervention will have access to specialty features of a physical 
activity-based smartphone app not yet commercially available. Because the risks are minimal, and because 
the study promises to generate knowledge about optimizing a smartphone app to encourage physical 
activity in older individuals, the benefits of the study outweigh the risks. For all participants, it is likely that 
the opportunity to participate in a potentially successful mobile health intervention for older adults and the 
knowledge that one is aiding in the quest to develop improved mobile health interventions will benefit the 
participants to a degree that outweighs the risks.  
D. Importance of Knowledge to be Gained  
The knowledge that will result from the study is expected to have important benefits for society. Older 
adults represent the most physically inactive age group, which places them at high risk for chronic, 
disabling conditions. The proposed PA app suite is a unique mobile health tool that shows promise in 
improving older adults’ PA and overall health. A feasibility study of this app shows that older adults are 
willing to utilize a PA-tracking app and find it easy to use and potentially beneficial for health. The proposed 
study will provide valuable information on how to design and develop an acceptable and usable 
smartphone app intervention with maximal potential to improve physical activity and overall health in the 
ever-growing population of older adults. This project will also support future development and testing of the 
PA-tracking app suite compared to alternative mobile health interventions that target elders and thereby 
contribute to national healthy aging agendas. The cumulative value of this knowledge far outweighs the 
risks identified in the previous section.  
 

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