Gamified Weight Loss Program for Obesity
(DASH-Man Trial)
Recruiting in Palo Alto (17 mi)
Age: 18 - 65
Sex: Any
Travel: May Be Covered
Time Reimbursement: Varies
Trial Phase: Academic
Recruiting
Sponsor: Drexel University
Disqualifiers: Cancer, Type I diabetes, Renal failure, others
No Placebo Group
Trial Summary
What is the purpose of this trial?Men in the United States have an exceptionally high prevalence of overweight and obesity, i.e., 71.3%, and 42% of men are currently attempting weight loss. However, men are dramatically underrepresented in weight loss programs. Attempts to modestly adapt standard weight loss programs have seen only minimal success. Mobile applications (mHealth apps) have attractive features, but have low male enrollment and poor efficacy as conventionally delivered. A gamified mHealth program offers the possibility of engaging men and enhancing efficacy given that (1) video gaming is highly appealing to men; (2) gamification features (e.g., digital rewards for attaining "streaks" and milestones, competition) are known enhance enjoyment and motivation and facilitate desired behaviors; and (3) "neurotraining" video games featuring repetitive action mechanics, adaptive difficulty, and feedback can train inhibitory control, a basic brain capacity to inhibit intrinsically-generated approach responses that is strongly linked to body mass and the consumption of high-calorie foods. This project evaluates long-term engagement and outcomes of a professionally-designed, game-based weight loss program. As such, 228 overweight men will be randomized to: (1) a 12-month mHealth weight loss program that includes digital self-monitoring, simplified and self-selected dietary targets, physical activity and a control (sham) non-game neurotraining, or (2) a fully-gamified version of this same program, comprised of a behavior change program featuring team-based competition, digital reinforcers for attainment of streaks and milestones, and an integrated neurotraining video game. Aims include evaluating the efficacy of the gamified program in terms of weight loss, diet and physical activity at 12 months, as well as evaluating hypothesized mediators (inhibitory control and engagement), (enjoyment and compliance) and moderators (baseline frequency of video game play and implicit preferences for Inhibitory Control Training-targeted foods).
Will I have to stop taking my current medications?
The trial does not specify if you need to stop taking your current medications. However, if you have recently started or changed the dosage of a medication that can significantly affect your weight, you may not be eligible to participate.
What data supports the effectiveness of the Gamified Weight Loss Program for Obesity treatment?
Research shows that gamified and digital interventions, like the SIGMA app, which use cognitive behavior therapy (CBT) principles, can help with weight loss by addressing unhealthy eating habits. Additionally, studies indicate that using behavior change techniques and incentives in digital programs can lead to weight loss, suggesting that similar gamified approaches may be effective.
12345Is the gamified weight loss program safe for humans?
The available research on gamified weight loss programs, such as the SIGMA app, primarily focuses on their design and potential effectiveness rather than safety. However, these programs are based on cognitive behavior therapy principles, which are generally considered safe for most people.
12367What makes the Gamified Weight Loss Program for Obesity unique compared to other treatments?
The Gamified Weight Loss Program is unique because it combines cognitive behavior therapy (CBT) principles with a mobile app designed as a game, allowing users to earn points for both in-app activities and real-world physical activities. This approach makes weight loss more engaging and accessible, especially for young adults with maladaptive eating habits, by using a novel scoring system and gamification to encourage behavior change.
12368Eligibility Criteria
This trial is for overweight or obese men (BMI of 25-50 kg/m²) aged 18-65 who enjoy high-calorie foods and can walk two city blocks without stopping. They must be willing to have their doctor contacted about their physical activity level and rapid weight loss if needed. Men with certain medical conditions, recent significant weight loss, or changes in medications affecting weight are excluded.Inclusion Criteria
My BMI is between 25 and 50, indicating I am overweight or obese.
I am between 18 and 65 years old.
Satisfactory completion of all enrollment procedures
+3 more
Exclusion Criteria
I have lost 5% or more of my weight in the last 3 months.
I recently started or changed the dose of a medication that may significantly affect my weight.
I have had weight loss surgery in the past.
+1 more
Trial Timeline
Screening
Participants are screened for eligibility to participate in the trial
2-4 weeks
Treatment
Participants engage in a 12-month mHealth weight loss program with digital self-monitoring, dietary targets, and physical activity, with either a sham or active neurotraining component.
12 months
Follow-up
Participants are monitored for weight loss, diet, and physical activity outcomes, with assessments at months 0, 1, 6, and 12.
12 months
Participant Groups
The study tests a gamified mHealth program against a standard mHealth program for weight loss in men. It includes digital self-monitoring, dietary targets, physical activity, and either a control neurotraining game or an integrated one with team competition and rewards designed to train inhibitory control linked to body mass.
4Treatment groups
Experimental Treatment
Active Control
Placebo Group
Group I: Gamified program with sham ICTExperimental Treatment1 Intervention
One group will receive fully-gamified version of the program with a sham.
Group II: Gamified program with Active ICTExperimental Treatment1 Intervention
One group will receive fully-gamified version of the program with active neurotraining.
Group III: Non-gamified program with Active ICTActive Control1 Intervention
One group will be assigned to a 12-month mobile weight loss program that includes digital self-monitoring, simplified and self-selected dietary targets (to align with neurotraining and promote autonomy , and behavioral strategies with active neurotraining.
Group IV: Non-gamified program with sham ICTPlacebo Group1 Intervention
One group will be assigned to a 12-month mobile weight loss program that includes digital self-monitoring, simplified and self-selected dietary targets (to align with neurotraining and promote autonomy , and behavioral strategies with sham.
Find a Clinic Near You
Research Locations NearbySelect from list below to view details:
Drexel UniversityPhiladelphia, PA
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Who Is Running the Clinical Trial?
Drexel UniversityLead Sponsor
National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK)Collaborator
References
An evidence-based gamified mHealth intervention for overweight young adults with maladaptive eating habits: study protocol for a randomized controlled trial. [2019]Cognitive behavior therapy (CBT) is the first-line of treatment for overweight and obesity patients whose problems originate in maladaptive eating habits (e.g., emotional eating). However, in-person CBT is currently difficult to access by large segments of the population. The proposed SIGMA intervention (i.e., the Self-help, Integrated, and Gamified Mobile-phone Application) is a mHealth intervention based on CBT principles. It specifically targets overweight young adults with underlying maladaptive behaviors and cognitions regarding food. The SIGMA app was designed as a serious game and intended to work as a standalone app for weight maintenance or alongside a calorie-restrictive diet for weight loss. It uses a complex and novel scoring system that allows points earned within the game to be supplemented by points earned during outdoor activities with the help of an embedded pedometer.
Study protocol for Log2Lose: A feasibility randomized controlled trial to evaluate financial incentives for dietary self-monitoring and interim weight loss in adults with obesity. [2019]The obesity epidemic has negative physical, psychological, and financial consequences. Despite the existence of effective behavioral weight loss interventions, many individuals do not achieve adequate weight loss, and most regain lost weight in the year following intervention. We report the rationale and design for a 2×2 factorial study that involves financial incentives for dietary self-monitoring (yes vs. no) and/or interim weight loss (yes vs. no). Outpatients with obesity participate in a 24-week, group-based weight loss intervention. All participants are asked to record their daily dietary and liquid intake on a smartphone application (app) and to weigh themselves daily at home on a study-provided cellular scale. An innovative information technology (IT) solution collates dietary data from the app and weight from the scale. Using these data, an algorithm classifies participants weekly according to whether they met their group's criteria to receive a cash reward ranging from $0 to $30 for dietary self-monitoring and/or interim weight loss. Notice of the reward is provided via text message, and credit is uploaded to a gift card. This pilot study will provide information on the feasibility of using this novel IT solution to provide variable-ratio financial incentives in real time via its effects on recruitment, intervention adherence, retention, and cost. This study will provide the foundation for a comprehensive, adequately-powered, randomized controlled trial to promote short-term weight loss and long-term weight maintenance. If efficacious, this approach could reduce the prevalence, adverse outcomes, and costs of obesity for millions of Americans. Clinicaltrials.gov registration: NCT02691260.
Associations between behaviour change technique clusters and weight loss outcomes of automated digital interventions: a systematic review and meta-regression. [2023]Automated digital interventions for weight loss represent a highly scalable and potentially cost-effective approach to treat obesity. However, current understanding of the active components of automated digital interventions is limited, hindering efforts to improve efficacy. Thus, the current systematic review and meta-analysis (preregistration: PROSPERO 2021-CRD42021238878) examined relationships between utilisation of behaviour change techniques (BCTs) and the efficacy of automated digital interventions for producing weight loss. Electronic database searches (December 2020 to March 2021) were used to identify trials of automated digital interventions reporting weight loss as an outcome. BCT clusters were coded using Michie's 93-item BCT taxonomy. Mixed-effects meta-regression was used to examine moderating effects of BCT clusters and techniques on both within-group and between-group measures of weight change. One hundred and eight conditions across sixty-six trials met inclusion criteria (13,672 participants). Random-effects meta-analysis revealed a small mean post-intervention weight loss of -1.37 kg (95% CI, -1.75 to -1.00) relative to control groups. Interventions utilised a median of five BCT clusters, with goal-setting, feedback and providing instruction on behaviour being most common. Use of Reward and Threat techniques, and specifically social incentive/reward BCTs, was associated with a higher between-group difference in efficacy, although results were not robust to sensitivity analyses.
Using artificial intelligence to optimize delivery of weight loss treatment: Protocol for an efficacy and cost-effectiveness trial. [2023]Gold standard behavioral weight loss (BWL) is limited by the availability of expert clinicians and high cost of delivery. The artificial intelligence (AI) technique of reinforcement learning (RL) is an optimization solution that tracks outcomes associated with specific actions and, over time, learns which actions yield a desired outcome. RL is increasingly utilized to optimize medical treatments (e.g., chemotherapy dosages), and has very recently started to be utilized by behavioral treatments. For example, we previously demonstrated that RL successfully optimized BWL by dynamically choosing between treatments of varying cost/intensity each week for each participant based on automatic monitoring of digital data (e.g., weight change). In that preliminary work, participants randomized to the AI condition required one-third the amount of coaching contact as those randomized to the gold standard condition but had nearly identical weight losses. The current protocol extends our pilot work and will be the first full-scale randomized controlled trial of a RL system for weight control. The primary aim is to evaluate the hypothesis that a RL-based 12-month BWL program will produce non-inferior weight losses to standard BWL treatment, but at lower costs. Secondary aims include testing mechanistic targets (calorie intake, physical activity) and predictors (depression, binge eating). As such, adults with overweight/obesity (N = 336) will be randomized to either a gold standard condition (12 months of weekly BWL groups) or AI-optimized weekly interventions that represent a combination of expert-led group, expert-led call, paraprofessional-led call, and automated message). Participants will be assessed at 0, 1, 6 and 12 months.
BestFIT Sequential Multiple Assignment Randomized Trial Results: A SMART Approach to Developing Individualized Weight Loss Treatment Sequences. [2022]State-of-the-art behavioral weight loss treatment (SBT) can lead to clinically meaningful weight loss, but only 30-60% achieve this goal. Developing adaptive interventions that change based on individual progress could increase the number of people who benefit.
A smartphone-supported weight loss program: design of the ENGAGED randomized controlled trial. [2021]Obesity remains a major public health challenge, demanding cost-effective and scalable weight management programs. Delivering key treatment components via mobile technology offers a potential way to reduce expensive in-person contact, thereby lowering the cost and burden of intensive weight loss programs. The ENGAGED study is a theory-guided, randomized controlled trial designed to examine the feasibility and efficacy of an abbreviated smartphone-supported weight loss program.
Review of innovations in digital health technology to promote weight control. [2021]Advances in technology have contributed to the obesity epidemic and worsened health by reducing opportunities for physical activity and by the proliferation of inexpensive calorie-dense foods. However, much of the same technology can be used to counter these troublesome trends by fostering the development and maintenance of healthy eating and physical activity habits. In contrast to intensive face-to-face treatments, technology-based interventions also have the potential to reach large numbers of individuals at low cost. The purpose of this review is to discuss studies in which digital technology has been used for behavioral weight control, report on advances in consumer technology that are widely adopted but insufficiently tested, and explore potential future directions for both. Web-based, mobile (eg, smartphone), virtual reality, and gaming technologies are the focus of discussion. The best evidence exists to support the use of digital technology for self-monitoring of weight-related behaviors and outcomes. However, studies are underway that will provide additional, important information regarding how best to apply digital technology for behavioral weight control.
Perceived helpfulness of the individual components of a behavioural weight loss program: results from the Hopkins POWER Trial. [2021]Behavioural weight loss programs are effective first-line treatments for obesity and are recommended by the US Preventive Services Task Force. Gaining an understanding of intervention components that are found helpful by different demographic groups can improve tailoring of weight loss programs. This paper examined the perceived helpfulness of different weight loss program components.