Mobile Health Intervention for Weight Gain Prevention
Recruiting in Palo Alto (17 mi)
Overseen byDeborah F. Tate, PhD
Age: 18 - 65
Sex: Any
Travel: May Be Covered
Time Reimbursement: Varies
Trial Phase: Academic
Recruiting
Sponsor: University of North Carolina, Chapel Hill
Disqualifiers: Pregnancy, Weight loss surgery, Eating disorder, others
No Placebo Group
Trial Summary
What is the purpose of this trial?
Weight gain is disproportionately high among young adults compared to other age groups and of particular concern in the military, which is comprised largely of young adults, as obesity has emerged as a threat to national security. Despite the critical need to address weight gain in young military personnel who can face discharge for failing to meet weight standards, there is currently no evidence-based programs available to them. This study aims to adapt an evidence-based weight gain prevention intervention for delivery in a young adult, active-duty military population using mobile technology to prevent weight gain over 2 years .
Will I have to stop taking my current medications?
The trial information does not specify whether you need to stop taking your current medications.
What data supports the effectiveness of the treatment Fit for Duty-mobile for weight gain prevention?
Research shows that mobile health (mHealth) interventions, like the Fit for Duty-mobile, can help with weight management by using technology such as smartphone apps and wearable devices to track activity and provide personalized coaching. These interventions have been found to support weight loss and maintenance, similar to in-person treatments, and can be effective in promoting healthy behaviors.12345
Is the Mobile Health Intervention for Weight Gain Prevention safe for humans?
How is the Fit for Duty-mobile treatment different from other weight gain prevention treatments?
Eligibility Criteria
This trial is for active-duty Air Force members aged 18-39 stationed at select bases, with a BMI of 21-30. Participants must own a smartphone, expect to be at their base for over a year, and be willing to wear a Fitbit daily. Pregnant individuals or those planning pregnancy soon, people who've had weight loss surgery recently or plan to have it, and anyone with past eating disorders or in another weight loss program cannot join.Inclusion Criteria
You possess a smartphone with an accompanying data and text messaging plan.
Your BMI is between 21 and 30 kg/m^2.
You are an active-duty Air Force personnel stationed at one of the following: Joint Base San Antonio - Lackland, Joint Base San Antonio - Ft
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Exclusion Criteria
I have been diagnosed with or am being treated for an eating disorder.
Currently pregnant, pregnant within the past 6 months, or planning to become pregnant within the next 12 months
Currently participating in a commercial weight loss program
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Trial Timeline
Screening
Participants are screened for eligibility to participate in the trial
2-4 weeks
Treatment
Participants receive a mobile health intervention to prevent weight gain, including a digital fitness tracker, digital scale, smartphone app, and periodic coaching calls
24 months
Remote delivery with periodic virtual coaching calls
Follow-up
Participants are monitored for weight change and other health outcomes after the intervention
4 weeks
Treatment Details
Interventions
- Fit for Duty-mobile (Behavioral Intervention)
- m-Health Control (Behavioral Intervention)
Trial OverviewThe study tests an mHealth intervention called 'Fit for Duty-mobile' designed to prevent weight gain among young adult military personnel using mobile technology over two years. It adapts an evidence-based approach specifically for this population.
Participant Groups
2Treatment groups
Experimental Treatment
Active Control
Group I: Fit for Duty MobileExperimental Treatment1 Intervention
This arm receives a digital fitness tracker; digital scale; smartphone app which delivers a behavioral weight gain prevention intervention; and periodic coaching calls.
Group II: m-Health ControlActive Control1 Intervention
This arm receives a digital fitness tracker, digital scale, and basic information about behavioral approaches for weight gain prevention.
Find a Clinic Near You
Research Locations NearbySelect from list below to view details:
Joint Base San Antonio-LacklandSan Antonio, TX
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Who Is Running the Clinical Trial?
University of North Carolina, Chapel HillLead Sponsor
National Heart, Lung, and Blood Institute (NHLBI)Collaborator
University of VirginiaCollaborator
References
Understanding the Effect of Adding Automated and Human Coaching to a Mobile Health Physical Activity App for Afghanistan and Iraq Veterans: Protocol for a Randomized Controlled Trial of the Stay Strong Intervention. [2020]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.
Formative Evaluation of a Smartphone App for Monitoring Daily Meal Distribution and Food Selection in Adolescents: Acceptability and Usability Study. [2021]Obesity interventions face the problem of weight regain after treatment as a result of low compliance. Mobile health (mHealth) technologies could potentially increase compliance and aid both health care providers and patients.
A Systematic Review of Application and Effectiveness of mHealth Interventions for Obesity and Diabetes Treatment and Self-Management. [2023]The use of mobile and wireless technologies and wearable devices for improving health care processes and outcomes (mHealth) is promising for health promotion among patients with chronic diseases such as obesity and diabetes. This study comprehensively examined published mHealth intervention studies for obesity and diabetes treatment and management to assess their effectiveness and provide recommendations for future research. We systematically searched PubMed for mHealth-related studies on diabetes and obesity treatment and management published during 2000-2016. Relevant information was extracted and analyzed. Twenty-four studies met inclusion criteria and varied in terms of sample size, ethnicity, gender, and age of the participating patients and length of follow-up. The mHealth interventions were categorized into 3 types: mobile phone text messaging, wearable or portable monitoring devices, and applications running on smartphones. Primary outcomes included weight loss (an average loss ranging from -1.97 kg in 16 wk to -7.1 kg in 5 wk) or maintenance and blood glucose reduction (an average decrease of glycated hemoglobin ranging from -0.4% in 10 mo to -1.9% in 12 mo); main secondary outcomes included behavior changes and patient perceptions such as self-efficacy and acceptability of the intervention programs. More than 50% of studies reported positive effects of interventions based on primary outcomes. The duration or length of intervention ranged from 1 wk to 24 mo. However, most studies included small samples and short intervention periods and did not use rigorous data collection or analytic approaches. Although some studies suggest that mHealth interventions are effective and promising, most are pilot studies or have limitations in their study designs. There is an essential need for future studies that use larger study samples, longer intervention (≥ 6 mo) and follow-up periods (≥ 6 mo), and integrative and personalized innovative mobile technologies to provide comprehensive and sustainable support for patients and health service providers.
Smartloss: A Personalized Mobile Health Intervention for Weight Management and Health Promotion. [2023]Synonymous with increased use of mobile phones has been the development of mobile health (mHealth) technology for improving health, including weight management. Behavior change theory (eg, the theory of planned behavior) can be effectively encapsulated into mobile phone-based health improvement programs, which is fostered by the ability of mobile phones and related devices to collect and transmit objective data in near real time and for health care or research professionals and clients to communicate easily.
Adoption and Appropriateness of mHealth for Weight Management in the Real World: A Qualitative Investigation of Patient Perspectives. [2022]Mobile health (mHealth) interventions for weight management can result in weight loss outcomes comparable to in-person treatments. However, there is little information on implementing these treatments in real-world settings.
The Effects of a Mobile Wellness Intervention with Fitbit Use and Goal Setting for Workers. [2020]Background and Introduction: There is strong evidence that worksite wellness programs can significantly improve the health profile of participating workers. To date, little is known about research on the effects of mobile wellness interventions in worksite settings. Furthermore, no studies have been conducted to evaluate mobile wellness interventions with activity trackers and tailoring strategies for physically inactive workers in manufacturing companies. This study aimed to examine the effects of a mobile wellness intervention with Fitbit and goal setting using brief counseling and text messaging among workers. Materials and Methods: A total of 79 (n = 79) workers from large manufacturing companies were allocated into an experimental group (n = 41) and a control group (n = 38). All participants were asked to wear an activity tracker (Fitbit Charger HR) during all waking hours for 5 weekdays. Participants in the experimental group received Fitbit, daily motivational text messaging, and biweekly counseling with a specifically designed workbook for 12 weeks, whereas Fitbit was only provided to the control group. Results: At the 12-week measurement, there were significant differences between the experimental group and control group on wellness (p < 0.001), physical activity behavior (p < 0.001), daily walking steps (p < 0.001), and physical activity self-efficacy (p < 0.001). Discussion and Conclusions: Although Fitbit facilitates an individual's activities by providing information about daily steps, the tracker itself, without additional goal-setting techniques, may be insufficient to encourage behavior change. These findings indicate that the mobile wellness intervention with Fitbit and goal setting using brief counseling and tailored text messaging is more effective for physically inactive workers.
[Mobile health and excess weight: a systematic review]. [2019]To evaluate the impact of using mobile health (mHealth) technologies- the practice of medicine or public health through mobile devices, such as mobile phones-on the prevention of weight gain or treatment of overweight or obesity.
Effect of an accelerometer on body weight and fitness in overweight and obese active duty soldiers. [2019]This study evaluated whether using a web-linked accelerometer, plus mandatory physical training, is associated with various weight- and fitness-related outcomes in overweight/obese active duty soldiers. Soldiers who failed the height/weight standards of the Army Physical Fitness Test (APFT) were randomized to use a Polar FA20 accelerometer device (polar accelerometer group [PA], n = 15) or usual care (UC, n = 13) for 6 months. Both groups received 1.5 hours of lifestyle instruction. We collected data at baseline, 2, 4, and 6 months, and evaluated group differences in temporal changes in study outcomes. At 6 months, 1/28 subjects (UC) passed the APFT height/weight standards. There were no group differences in changes in weight (PA: -0.1 kg vs. UC: +0.3 kg; p = 0.9), body fat (PA: -0.9% vs. UC: -1.1%; p = 0.9), systolic blood pressure (PA: +1.3 mm Hg vs. UC: -2.1 mm Hg; p = 0.2), diastolic blood pressure (PA: +3.8 mm Hg vs. UC: -2.4 mm Hg; p = 0.3), or resting heart rate in beats per minute (bpm) (PA: +7.8 bpm vs. UC: +0.1 bpm; p = 0.2). These results suggest that using an accelerometer with web-based feedback capabilities plus mandatory physical training does not assist in significant weight loss or ability to pass the APFT height/weight standards among overweight/obese soldiers.
Weight Loss Strategies Used by Army Reserve Officer Training Corps Cadets: Implication for Student Health and Wellness Services. [2020]Background: Maintaining a healthy weight is a military requirement for the Reserve Officer Training Corps (ROTC) cadets. Male and female soldiers often have different approaches to maintaining a healthy weight and mobile health (m-health) tools can be harnessed and tailored to the needs of individual cadets. Objectives: This study examined gender differences in technology use, weight loss strategies, information needed to maintain a healthy weight, and willingness to participate in m-health research and programs. Materials and Methods: A self-administered survey was completed by 404 cadets from ROTC programs in Florida in 2017. Results: Most owned smartphones and used them as their primary internet access. Women had significantly lower body mass index than men (p = 0.037). Most used healthy weight loss strategies, including increasing physical activity, reducing sweets, and reducing fried foods. Women were more likely than men to reduce fried foods (p < 0.0003) and sweets (p = 0.020). Most reported a willingness to participate in m-health weight management research and programs, with women more willing to do so (p = 0.038). Most were willing to participate in m-health programs that used text messages, food/activity/sleep apps, smart watches/fitness trackers, and stress management/anxiety apps. Women were more willing to participate in programs that used apps for stress/anxiety management (p = 0.004) and to track food/activity/sleep (p < 0.0001). Most needed information on eating healthy on a budget and eating healthy on-the-run. Conclusions: Opportunities exist for college health and wellness professionals to use a variety of m-health tools and apps to promote general health and wellness and to help cadets achieve and maintain a healthy weight.
Military services fitness database: development of a computerized physical fitness and weight management database for the U.S. Army. [2021]The Department of Defense (DoD) has mandated development of a system to collect and manage data on the weight, percent body fat (%BF), and fitness of all military personnel. This project aimed to (1) develop a computerized weight and fitness database to track individuals and Army units over time allowing cross-sectional and longitudinal evaluations and (2) test the computerized system for feasibility and integrity of data collection over several years of usage. The computer application, the Military Services Fitness Database (MSFD), was designed for (1) storage and tracking of data related to height, weight, %BF for the Army Weight Control Program (AWCP) and Army Physical Fitness Test (APFT) scores and (2) generation of reports using these data. A 2.5-year pilot test of the MSFD indicated that it monitors population and individual trends of changing body weight, %BF, and fitness in a military population.
A mobile health intervention for weight management among young adults: a pilot randomised controlled trial. [2022]Today's generation of young adults are gaining weight faster than their parents; however, there remains insufficient evidence to inform interventions to prevent this weight gain. Mobile phones are a popular means of communication that may provide a convenient, inexpensive means to deliver health intervention programmes. This pilot study aimed to measure the effect of a 12-week mobile health (mHealth) intervention on body weight, body mass index and specific lifestyle behaviours addressed by the programme.