A Smartphone App to Improve Physical Activity

University of Southern California111 enrolled

Overview

The purpose of this study is to develop, test, and optimize a physical activity (PA)-tracking smartphone app and specialty features, which are designed to facilitate older adults' PA by targeting common barriers in this population. For example, one feature sends messages throughout the day about the good things about growing older to combat negative views about aging which has been linked to decreased PA. Participants will include older adult smartphone users who are between the ages of 65 and 84 and are not very physically active. In phase one of the study, three groups of five older adults will be formed to test the PA-tracking app and one of three specialty features for a two-week period, followed by a focus group to learn about the older adults' experiences. In phase two, approximately 100 participants will be randomly assigned to one of eight groups that include various combinations of specialty features with the PA tracker, for the purpose of pilot testing the app for a four-month period. Testing will occur at the beginning and the end of the four-month intervention period, and will measure PA levels, sedentary activity time, self-reported PA, and functional mobility.

In this study, we will optimize a set of tailored specialty app features designed to be paired with a physical activity (PA)-tracking app to boost older adults' PA. This package, termed the MovingUp suite, is distinct from generic fitness apps because it blends a set of specialized components that reflect empirically supported constructs from social cognitive and stereotype embodiment theory with evidence-based behavior change techniques (e.g., self-regulation) foundational to basic activity monitoring. Specialty features include: (a) explicit and implicit messaging to promote positive aging views; (b) sedentary activity monitoring with motivational messaging and peer suggestions; and (c) tailored messaging to increase the intensity level of everyday activities and overcome barriers. We will utilize a highly efficient, innovative methodological approach-Multiphase Optimization Strategy (MOST)-to provide an experimental context for evaluating the viability of each MovingUp specialty feature. Aim 1: Assess the feasibility and acceptability of the three MovingUp specialty features. We will first examine MovingUp's feasibility and acceptability in three groups of five older adults (aged 65-84 years). A basic PA-tracking app plus one of three specialty features will be introduced-a different feature per group-at an orientation session. Groups will then test their assigned specialty feature with the PA tracker for two weeks. This step will involve real-time user data collection, check-ins via phone, and follow-up focus groups. Feasibility and acceptability will be determined by analyzing participants' usage patterns, evaluations of MovingUp features (based on a health technology usability scale and focus group interviews), and self-reported facilitators and barriers to successful app use. Our team will review the data and integrate changes as needed, producing an upgraded prototype to be assessed in Aim 2. Aim 2: Conduct a pilot test to examine performance characteristics and PA-relevant outcomes of MovingUp's specialty features. Aim 2 includes the MOST Screening Phase: theory-guided experimentation to identify viable components within a multifaceted preliminary intervention plan. Using a factorial design as specified in MOST procedures, 100 underactive older adults (i.e., accumulating \<150 minutes of moderate intensity activity per week) 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 a PA tracker app. At the end of a four-month intervention period, for each specialty feature we will examine changes from baseline in PA-related outcomes including: objective PA (primary outcome), sedentary activity time, self-reported PA, and functional mobility. We will also examine the app components' relationships to 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, sustained usage, and perceived usefulness for achieving PA goals for each suite component. Aim 3: Synthesize information from Aim 2 to design an optimized MovingUp suite to be evaluated in a future RCT. Our study team will interpret and synthesize the array of resulting data to derive an optimized MovingUp suite. A set of pre-specified criteria will be used to guide selection of components in the optimized app. Using preliminary efficacy data, the stage will be set for a fully powered RCT of MovingUp's beneficial effects in comparison to alternate technologies such as web-based or mHealth solutions. This project will help establish a methodological foundation for future attempts to enhance PA apps via the addition of theoretically based component features. Moreover, it will provide insights into the theoretical underpinnings of successful PA interventions for older adults, leading to information that transcends any single technology-based solution.

Interventions

Physical Activity (PA) Tracker AppOTHER

This PA tracker app auto-monitors PA and provides a text-based summary of goal progress, thereby targeting self-regulation and outcome expectation.

On Your FeetOTHER

On Your Feet is a specialty app feature designed to be paired with a PA tracker app and reduce sedentary activity-a health risk factor largely independent of insufficient PA. This feature utilizes self-regulatory and behavior change techniques including goal-setting, progress feedback, and prompting. Accumulated sedentary activity time is displayed alongside self-selected goals; reminders to stand are sent at a user-specified frequency; and general tips and previously compiled, older adult-identified strategies to reduce sedentary activity are texted. Additionally, messages about the benefits of reducing sedentary activity and overcoming barriers are sent.

Coach MeOTHER

Coach Me is a specialty app feature designed to be paired with a PA tracker app and includes daily messages that assist older adults in discovering practical ways to integrate PA into their daily routines and overcoming PA barriers. Blending PA with productive activity facilitates PA engagement in older adults. In Coach Me, suggestions on how to intensify daily activities are tailored based on user selections from an activity inventory. This app feature helps older adults become more active in a minimally intrusive way, while allowing for 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, thereby targeting self-efficacy.

Proof PositiveOTHER

Proof Positive is a specialty app feature designed to be paired with a PA tracker app and capitalizes on the beneficial effects that exposure to positive aging messages and stereotypes has on health and PA. 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 weekly positive aging stereotype task modeled after a computerized series. This last function exposes users to blocks of "positive priming words." Primers are quickly flashed to allow perception without awareness while users focus on a simple icon that represents PA. Icons are intended to provide an additional PA cue, maintain user interest, and increase the external validity.

Outcomes

Primary Outcomes

Daily Steps Change From Baseline to Month 4; Main Effect, and 2- and 3-way Interactions

Step counts (objective physical activity) were measured using the activPAL thigh-worn accelerometer during a 72-hour monitoring period. Estimated average change is computed as the change in activPAL-tracked mean daily steps at Month 4 relative to baseline; this outcome is analyzed in a linear regression analysis model. All randomized participants who started the intervention and had valid activity monitor data were utilized in the model (ITT analysis)

Time frame: 72-hour monitoring periods at Month 4 relative to baseline

Secondary Outcomes

Daily Sitting Time (activPAL) Change From Baseline to Month 4

Objective sedentary activity time was measured using the activPAL thigh-worn accelerometer during a 72-hour monitoring period. Expressed as average minutes/day.

Time frame: 72-hour monitoring periods at Month 4 relative to baseline

Self-reported Physical Activity (PASE) Change From Baseline to Month 4

Self-reported physical activity will be measured via the Physical Activity Scale for the Elderly (PASE). PASE is a ten-item instrument designed to assess engagement in physical activities commonly pursued by older adults, including those related to leisure, household, and occupational tasks. The tool is a valid and reliable measure of physical activity engagement in the older adult population. Scores range from 0 to 361. Higher scores indicate a higher level of activity.