Clinical trial NCT03417440: A Smartphone App to Improve Physical Activity
Official title: A Smartphone Application to Improve Physical Activity in Underactive Older Adults
Study type: INTERVENTIONAL
Overall status: COMPLETED
Phase: NA
Conditions: Sedentary Lifestyle
Keywords: smartphone app, physical activity, older adults
Lead sponsor: University of Southern California
Sponsor class: OTHER
Collaborators: name: National Institute on Aging (NIA)
name: University of California, Los Angeles
First posted: 2018-01-31
Enrollment: 111
Sex: ALL
Minimum age (years): 65
Maximum age (years): 84
Standard ages: OLDER_ADULT
Accepts healthy volunteers: yes
Allocation: RANDOMIZED
Intervention model: FACTORIAL
Intervention model description: Multiphase Optimization Strategy (MOST) is a recent methodology for optimizing multi-component interventions prior to performing more comprehensive testing in large RCTs. The Most Framework includes 5 steps: (1) Establish theoretical model; (2) Identify individual intervention components; (3) Conduct experiment to examine individual components; (4) Assemble beta intervention package; and (5) Confirm efficacy of optimized intervention. To our knowledge, only two prior studies have used MOST to refine a complex app with physical activity elements and disentangle the relative efficacy of specific features within a larger suite.
Primary purpose: OTHER

Brief summary: 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.

Detailed description: 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.

Eligibility criteria: Inclusion Criteria:

* 65-84 years old
* English speaking
* reside in Los Angeles
* score ≥5 on a 6-item cognitive screener
* report \<150 minutes of moderate to vigorous PA/week as per a single-item screener
* ambulatory
* able to safely participate in physical activity as determined by the Revised Physical Activity Readiness Questionnaire (rPARQ) or proof of medical clearance from a physician
* smartphone owner for ≥3 months
* observed ability to reliably access and operate a smartphone during orientation.

Exclusion Criteria:

* ≥85 years old, based on limited smartphone ownership and to reduce sample variability

Primary outcomes:
measure: Daily Steps Change From Baseline to Month 4; Main Effect, and 2- and 3-way Interactions
timeFrame: 72-hour monitoring periods at Month 4 relative to baseline
Secondary outcomes:
measure: Daily Sitting Time (activPAL) Change From Baseline to Month 4
timeFrame: 72-hour monitoring periods at Month 4 relative to baseline
measure: Self-reported Physical Activity (PASE) Change From Baseline to Month 4
timeFrame: baseline and 4 months
measure: Gait Speed (4-m Walk Test) Change From Baseline to Month 4
timeFrame: baseline and 4 months
measure: Self-efficacy for Physical Activity (Health Beliefs Survey) Change From Baseline
timeFrame: baseline and 4 months
measure: Self-regulation of Physical Activity (Health Beliefs Survey Physical Activity Portion) Change From Baseline
timeFrame: baseline and 4 months
measure: Family Social Support for Physical Activity (Health Beliefs Survey Physical Activity Portion) Change From Baseline
timeFrame: baseline and 4 months
measure: Outcome Expectation for Physical Activity (Health Beliefs Survey Physical Activity Portion) Change From Baseline
timeFrame: baseline and 4 months
measure: Aging Self-perceptions (Attitudes Toward Own Aging) Change From Baseline
timeFrame: baseline and 4 months
measure: Views of Aging--Psychosocial Loss (Attitudes to Ageing Questionnaire) Change From Baseline
timeFrame: baseline and 4 months
measure: Views of Aging--Physical Change (Attitudes to Ageing Questionnaire) Change From Baseline
timeFrame: baseline and 4 months
measure: Views of Aging--Psychological Growth (Attitudes to Ageing Questionnaire) Change From Baseline
timeFrame: baseline and 4 months
measure: App Usage Behavior
timeFrame: from baseline through Month 4 (daily)
measure: Perceived App Quality (uMARS)
timeFrame: 4 months
Other outcomes:
measure: Correlation of Change in Daily Steps to Change in Hypothesized Mediators
timeFrame: baseline to Month 4 change
Locations:
city: Glendale
country: United States
facility: Front Porch Center for Innovation and Wellbeing
state: California
city: Los Angeles
country: United States
facility: University of Southern California
state: California
Study officials:
References: