Dataset Information

Effect of Adding Telephone-Based Brief Coaching to an mHealth App (Stay Strong) for Promoting Physical Activity Among Veterans: Randomized Controlled Trial.

ABSTRACT: BACKGROUND:Though maintaining physical conditioning and a healthy weight are requirements of active military duty, many US veterans lose conditioning and rapidly gain weight after discharge from active duty service. Mobile health (mHealth) interventions using wearable devices are appealing to users and can be effective especially with personalized coaching support. We developed Stay Strong, a mobile app tailored to US veterans, to promote physical activity using a wrist-worn physical activity tracker, a Bluetooth-enabled scale, and an app-based dashboard. We tested whether adding personalized coaching components (Stay Strong+Coaching) would improve physical activity compared to Stay Strong alone. OBJECTIVE:The goal of this study is to compare 12-month outcomes from Stay Strong alone versus Stay Strong+Coaching. METHODS:Participants (n=357) were recruited from a national random sample of US veterans of recent wars and randomly assigned to the Stay Strong app alone (n=179) or Stay Strong+Coaching (n=178); both programs lasted 12 months. Personalized coaching components for Stay Strong+Coaching comprised of automated in-app motivational messages (3 per week), telephone-based human health coaching (up to 3 calls), and personalized weekly goal setting. All aspects of the enrollment process and program delivery were accomplished virtually for both groups, except for the telephone-based coaching. The primary outcome was change in physical activity at 12 months postbaseline, measured by average weekly Active Minutes, captured by the Fitbit Charge 2 device. Secondary outcomes included changes in step counts, weight, and patient activation. RESULTS:The average age of participants was 39.8 (SD 8.7) years, and 25.2% (90/357) were female. Active Minutes decreased from baseline to 12 months for both groups (P<.001) with no between-group differences at 6 months (P=.82) or 12 months (P=.98). However, at 12 months, many participants in both groups did not record Active Minutes, leading to missing data in 67.0% (120/179) for Stay Strong and 61.8% (110/178) for Stay Strong+Coaching. Average baseline weight for participants in Stay Strong and Stay Strong+Coaching was 214 lbs and 198 lbs, respectively, with no difference at baseline (P=.54) or at 6 months (P=.28) or 12 months (P=.18) postbaseline based on administrative weights, which had lower rates of missing data. Changes in the number of steps recorded and patient activation also did not differ by arm. CONCLUSIONS:Adding personalized health coaching comprised of in-app automated messages, up to 3 coaching calls, plus automated weekly personalized goals, did not improve levels of physical activity compared to using a smartphone app alone. Physical activity in both groups decreased over time. Sustaining long-term adherence and engagement in this mHealth intervention proved difficult; approximately two-thirds of the trial's 357 participants failed to sync their Fitbit device at 12 months and, thus, were lost to follow-up. TRIAL REGISTRATION:ClinicalTrials.gov NCT02360293; https://clinicaltrials.gov/ct2/show/NCT02360293. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID):RR2-10.2196/12526.

SUBMITTER: Damschroder LJ

PROVIDER: S-EPMC7435619 | biostudies-literature | 2020 Aug

REPOSITORIES: biostudies-literature

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Effect of Adding Telephone-Based Brief Coaching to an mHealth App (Stay Strong) for Promoting Physical Activity Among Veterans: Randomized Controlled Trial.

Damschroder Laura J LJ Buis Lorraine R LR McCant Felicia A FA Kim Hyungjin Myra HM Evans Richard R Oddone Eugene Z EZ Bastian Lori A LA Hooks Gwendolyn G Kadri Reema R White-Clark Courtney C Richardson Caroline R CR Gierisch Jennifer M JM

Journal of medical Internet research 20200804 8

<h4>Background</h4>Though maintaining physical conditioning and a healthy weight are requirements of active military duty, many US veterans lose conditioning and rapidly gain weight after discharge from active duty service. Mobile health (mHealth) interventions using wearable devices are appealing to users and can be effective especially with personalized coaching support. We developed Stay Strong, a mobile app tailored to US veterans, to promote physical activity using a wrist-worn physical act ...[more]

PMID: 32687474

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Project description:BACKGROUND:Although maintaining a healthy weight and physical conditioning are requirements of active military duty, many US veterans rapidly gain weight and lose conditioning when they separate from active-duty service. Mobile health (mHealth) interventions that incorporate wearables for activity monitoring have become common, but it is unclear how to optimize engagement over time. Personalized health coaching, either through tailored automated messaging or by individual health coaches, has the potential to increase the efficacy of mHealth programs. In an attempt to preserve conditioning and ward off weight gain, we developed Stay Strong, a mobile app that is tailored to veterans of recent conflicts and tracks physical activity monitored by Fitbit Charge 2 devices and weight measured on a Bluetooth-enabled scale. OBJECTIVE:The goal of this study is to determine the effect of activity monitoring plus health coaching compared with activity monitoring alone. METHODS:In this randomized controlled trial, with Stay Strong, a mobile app designed specifically for veterans, we plan to enroll 350 veterans to engage in an mHealth lifestyle intervention that combines the use of a wearable physical activity tracker and a Bluetooth-enabled weight scale. The Stay Strong app displays physical activity and weight data trends over time. Enrolled participants are randomized to receive the Stay Strong app (active comparator arm) or Stay Strong + Coaching, an enhanced version of the program that adds coaching features (automated tailored messaging with weekly physical activity goals and up to 3 telephone calls with a health coach-intervention arm) for 1 year. Our primary outcome is change in physical activity at 12 months, with weight, pain, patient activation, and depression serving as secondary outcome measures. All processes related to recruitment, eligibility screening, informed consent, Health Insurance Portability and Accountability Act authorization, baseline assessment, randomization, the bulk of intervention delivery, and outcome assessment will be accomplished via the internet or smartphone app. RESULTS:The study recruitment began in September 2017, and data collection is expected to conclude in 2019. A total of 465 participants consented to participate and 357 (357/465, 77%) provided baseline levels of physical activity and were randomized to 1 of the 2 interventions. CONCLUSIONS:This novel randomized controlled trial will provide much-needed findings about whether the addition of telephone-based human coaching and other automated supportive-coaching features will improve physical activity compared with using a smartphone app linked to a wearable device alone. TRIAL REGISTRATION:ClinicalTrials.gov NCT02360293; https://clinicaltrials.gov/ct2/show/NCT02360293 (Archived by WebCite at http://www.webcitation.org/75KQeIFwh). INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID):DERR1-10.2196/12526.

Project description:BackgroundIn the recent decades, the number of apps promoting health behaviors and health-related strategies and interventions has increased alongside the number of smartphone users. Nevertheless, the validity process for measuring and reporting app quality remains unsatisfactory for health professionals and end users and represents a public health concern. The Mobile Application Rating Scale (MARS) is a tool validated and widely used in the scientific literature to evaluate and compare mHealth app functionalities. However, MARS is not adapted to the French culture nor to the language.ObjectiveThis study aims to translate, adapt, and validate the equivalent French version of MARS (ie, MARS-F).MethodsThe original MARS was first translated to French by two independent bilingual scientists, and their common version was blind back-translated twice by two native English speakers, culminating in a final well-established MARS-F. Its comprehensibility was then evaluated by 6 individuals (3 researchers and 3 nonacademics), and the final MARS-F version was created. Two bilingual raters independently completed the evaluation of 63 apps using MARS and MARS-F. Interrater reliability was assessed using intraclass correlation coefficients. In addition, internal consistency and validity of both scales were assessed. Mokken scale analysis was used to investigate the scalability of both MARS and MARS-F.ResultsMARS-F had a good alignment with the original MARS, with properties comparable between the two scales. The correlation coefficients (r) between the corresponding dimensions of MARS and MARS-F ranged from 0.97 to 0.99. The internal consistencies of the MARS-F dimensions engagement (ω=0.79), functionality (ω=0.79), esthetics (ω=0.78), and information quality (ω=0.61) were acceptable and that for the overall MARS score (ω=0.86) was good. Mokken scale analysis revealed a strong scalability for MARS (Loevinger H=0.37) and a good scalability for MARS-F (H=0.35).ConclusionsMARS-F is a valid tool, and it would serve as a crucial aid for researchers, health care professionals, public health authorities, and interested third parties, to assess the quality of mHealth apps in French-speaking countries.

Project description:BACKGROUND:After a mobile health (mHealth) app is created, an important step is to evaluate the usability of the app before it is released to the public. There are multiple ways of conducting a usability study, one of which is collecting target users' feedback with a usability questionnaire. Different groups have used different questionnaires for mHealth app usability evaluation: The commonly used questionnaires are the System Usability Scale (SUS) and Post-Study System Usability Questionnaire (PSSUQ). However, the SUS and PSSUQ were not designed to evaluate the usability of mHealth apps. Self-written questionnaires are also commonly used for evaluation of mHealth app usability but they have not been validated. OBJECTIVE:The goal of this project was to develop and validate a new mHealth app usability questionnaire. METHODS:An mHealth app usability questionnaire (MAUQ) was designed by the research team based on a number of existing questionnaires used in previous mobile app usability studies, especially the well-validated questionnaires. MAUQ, SUS, and PSSUQ were then used to evaluate the usability of two mHealth apps: an interactive mHealth app and a standalone mHealth app. The reliability and validity of the new questionnaire were evaluated. The correlation coefficients among MAUQ, SUS, and PSSUQ were calculated. RESULTS:In this study, 128 study participants provided responses to the questionnaire statements. Psychometric analysis indicated that the MAUQ has three subscales and their internal consistency reliability is high. The relevant subscales correlated well with the subscales of the PSSUQ. The overall scale also strongly correlated with the PSSUQ and SUS. Four versions of the MAUQ were created in relation to the type of app (interactive or standalone) and target user of the app (patient or provider). A website has been created to make it convenient for mHealth app developers to use this new questionnaire in order to assess the usability of their mHealth apps. CONCLUSIONS:The newly created mHealth app usability questionnaire-MAUQ-has the reliability and validity required to assess mHealth app usability.

Project description:BackgroundBehavioral economics has stimulated renewed interest in financial health incentives worldwide. The Carrot Rewards app was developed as part of a public-private partnership to reward Canadians with loyalty points (eg, movies and groceries) for downloading the app, referring friends, and completing an average of 1 to 2 educational health quizzes per week ("micro-learning"), with long-term objectives of increasing health knowledge and encouraging healthy behaviors.ObjectiveThe main objective of this study was to evaluate uptake of a loyalty points-based mHealth app during the exclusive 3-month launch period in British Columbia (BC), Canada. The secondary aims were to describe the health and sociodemographic characteristics of users, as well as participation levels (eg, proportion of quizzes completed and friends referred).MethodsThe app was promoted via loyalty program email campaigns (1.64 million emails). Number of downloads and registrations (users enter age, gender, and valid BC postal code to register) were collected. Additional sociodemographics were inferred by linking postal codes with census data at the local health area (LHA) level. Health risk assessments were also deployed. Participation levels were collected over 3 months and descriptive data were presented.ResultsIn 3 months, 67,464 individuals downloaded the app; in its first week, Carrot Rewards was the most downloaded health app in Canada. Among valid users (n=57,885; at least one quiz completed), the majority were female (62.96%; 36,446/57,885) and aged 18 to 34 years (54.34%; 31,459/57,885). More than half of the users (52.40%; 30,332/57,885) resided in LHAs where the median personal income was below the provincial average (Can $28,765). Furthermore, 64.42% (37,291/57,885) of users lived in metropolitan (ie, urban) LHAs, compared with 56.17% of the general BC population. The most prevalent risk factors were "not" meeting physical activity guidelines (72.70%; 31,765/43,692) and "not" getting the flu shot last year (67.69%; 30,286/44,739). Regarding participation, 60.05% (34,761/57,885) of users were classified as "very high" engagers (>75% quiz completion rate).ConclusionsEarly results suggest that loyalty points may promote mHealth app uptake. The app was downloaded by younger females especially, and BC residents from higher and lower income regions were equally represented. Loyalty points appear to have driven participation throughout the inaugural 3-month period (ie, quiz completion).

Project description:Interventions: The intervention will include (I) providing a wearable tracker; (ii) up to six individual telephone or social media based sessions of health coaching. and (iii) a booklet with physical activity information and motivational tools to support behaviour change. The wearable tracker will be a wrist worn Fitbit Charge 2. Participants will be encouraged to wear the Fitbit during all waking hours, except for showering or swimming. However, it is not mandatory to wear the Fitbit during all waking hours. Participants will choose mode of delivery according to their preferences from a choice of telephone, Skype, zoom, or messenger etc. This is a distance-based intervention. Therefore the wearable tracker will be mailed to participants. Four sessions of health coaching are fixed (at wk 1, 2, 4 and 8) for all participants and will last up to 45 minutes each. However, the intervention includes a patient-centred and stepped-care approach by providing additional health coaching sessions (i.e., at wk 6, and 10) to those who may need them in order to achieve meaningful sustained physical activity change. A Health coach will be employed to deliver the intervention and will be required to have a background in Psychology or allied health discipline (at least to degree level), and previous experience of interviewing or working with patients. There is no specific exercise prescription but participants will be encouraged to meet the physical activity guidelines for cancer survivors, which is at least 150 minutes of moderate-intensity physical activity per week. They will also be informed that 3-5 hours of moderate-intensity physical activity will bring maximum benefits and will be encouraged to reach this goal once achieve the minimum guidelines of 150-minutes per week. The purpose of the health coaching is to motivate and support increased physical activity through supporting self-efficacy, action planning, and coping planning. The first session will cover technical issues and featu Primary outcome(s): The primary outcome is Minutes of Moderate to vigorous physical activity per week assessed using an accelerometer (the Actigraph GT9 X). At each assessment point, participants will be mailed the Actigraph and asked to wear the device on their hip or waist for a period of 7 consecutive days during all waking hours.[week 12 post baseline assessment];Change in minutes of sedentary behaviour per week, also assessed using the Actigraph GT9X . Sedentary behaviour will be defined by accelerometer activity counts of <100 counts per minute, for 20 consecutive minutes or more.[week24 post baseline assessment] Study Design: Purpose: Prevention; Allocation: Randomised controlled trial; Masking: Blinded (masking used);Assignment: Parallel;Type of endpoint: Efficacy

Dataset Information

Effect of Adding Telephone-Based Brief Coaching to an mHealth App (Stay Strong) for Promoting Physical Activity Among Veterans: Randomized Controlled Trial.

Publications

Effect of Adding Telephone-Based Brief Coaching to an mHealth App (Stay Strong) for Promoting Physical Activity Among Veterans: Randomized Controlled Trial.

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