Changes in Health-Promoting Behaviors and Their Association with Weight Loss, Retention, and Engagement on a Digital Program: Prospective Study

Behr, Heather; Earl, Sydney; Ho, Annabell Suh; Lee, Jihye; Mitchell, Ellen Siobhan; McCallum, Meaghan; May, Christine N.; Michaelides, Andreas

doi:10.3390/nu14224812

Cited by 8 publications

(4 citation statements)

References 73 publications

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“…This research was limited by the fact that the provision of the scale was not individually randomized but the result of insurance providers’ choice to provide or not provide scales. In addition, although findings from past research show that both self-weighing and retention are associated with weight loss [ 4 , 5 , 7 ], suggesting that the provision of a scale might also be related to weight loss, this question was outside the scope of this analysis. This preliminary study is timely, given the increasing importance of understanding and attenuating the high rates of attrition in digital health [ 8 - 10 ], and might assist insurance providers to weigh the cost of provisioning a scale to the benefits of increased retention in lifestyle behavioral programs.…”

Section: Discussionmentioning

confidence: 98%

The Effects of Providing a Connected Scale in an App-Based Digital Health Program: Cross-sectional Examination

Auster‐Gussman¹,

Rikhy²,

Lockwood³

et al. 2023

JMIR Mhealth Uhealth

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Section: Discussionmentioning

confidence: 98%

The Effects of Providing a Connected Scale in an App-Based Digital Health Program: Cross-sectional Examination

Auster‐Gussman¹,

Rikhy²,

Lockwood³

et al. 2023

JMIR Mhealth Uhealth

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“… 46 The app has several key features of success that we identified, including Cognitive Behavioral Theory grounding. 47 …”

Section: Discussionmentioning

confidence: 99%

Behavioral weight-loss interventions for patients with NAFLD: A systematic scoping review

Balakrishnan

Liu

Schmitt

et al. 2023

Hepatology Communications

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Background: Clinically significant weight loss—which requires sustained dietary and physical activity changes—is central to treating NAFLD. Although behavioral interventions have demonstrated effectiveness in promoting weight loss among primary prevention populations, the data are limited among patients with NAFLD who need weight loss for treatment. We undertook this scoping review to map the existing data on the characteristics, weight-loss outcomes, and determinants of success of interventions evaluated among patients with NAFLD. Methods: We searched Medline, EMBASE, Cochrane, PsycINFO, and Web of Science from inception to January 1, 2023 to identify publications reporting weight loss among adults with NAFLD in behavioral weight-loss interventions. We summarized interventions and classified them as successful if there was an average weight loss of ≥ 5% from baseline across enrolled participants or achieved by ≥ 50% of enrolled participants. Results: We included 28 studies: 10 randomized control trials, ten quasi-experimental, and 8 observational studies. Intervention delivery, duration, and counseling frequency varied; 12 were successful. Retention was highest among telephone interventions and lowest among “real-world” face-to-face interventions. Patients who were women, younger, and/or had multiple metabolic conditions were most likely to dropout. Successful interventions had biweekly counseling, specific physical activity, and calorie targets, behavioral theory grounding, and promoted goal-setting, self-monitoring, and problem-solving. Conclusion: There are limited data on behavioral weight-loss interventions in NAFLD. Research is needed to develop effective interventions generalizable to diverse patient populations and that maximize adherence, particularly among patients who are diabetic, women, and younger.

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“…We speculate that Noom Weight users may have shown significant cost savings compared with non-Noom Weight users because weight management efforts reduced the incidence of chronic conditions and their associated medical costs [42][43][44]. We also speculate that Noom Weight's educational content on healthy behaviors could result in improved medication adherence, especially because a previous study found that Noom Weight users' health responsibility (eg, taking interest in, and responsibility for, their overall physical health) improved over the course of the program [32,45]. However, because this study did not test causal pathways, future research should test and identify potential mechanisms.…”

Section: Comparison With Prior Workmentioning

confidence: 90%

“…At 24 months after the index date, 0.04 fewer inpatient visits, 0.58 fewer outpatient visits, 0.01 fewer surgeries, and 3.13 fewer prescriptions were recorded among Noom Weight users compared with non-Noom Weight users. Noom Weight users had higher use of telehealth services at 12 months after the index date (MD 0.02/user), perhaps because of increased connectivity to digital health services owing to their use of Noom Weight or because of increased health responsibility as a result of the program [32]. There were also a greater number of obesity-specific prescriptions for Noom Weight users compared with non-Noom Weight users at 12 months (MD 0.08/user), which may be related to more health-conscious behavior [32] among newly registered Noom Weight users, potentially leading to higher rates of prescriptions.…”

Section: Principal Findingsmentioning

confidence: 99%

The Impact of a Digital Weight Loss Intervention on Health Care Resource Utilization and Costs Compared Between Users and Nonusers With Overweight and Obesity: Retrospective Analysis Study

Mitchell¹,

Fabry²,

Ho³

et al. 2023

JMIR Mhealth Uhealth

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Background The Noom Weight program is a smartphone-based weight management program that uses cognitive behavioral therapy techniques to motivate users to achieve weight loss through a comprehensive lifestyle intervention. Objective This retrospective database analysis aimed to evaluate the impact of Noom Weight use on health care resource utilization (HRU) and health care costs among individuals with overweight and obesity. Methods Electronic health record data, insurance claims data, and Noom Weight program data were used to conduct the analysis. The study included 43,047 Noom Weight users and 14,555 non–Noom Weight users aged between 18 and 80 years with a BMI of ≥25 kg/m² and residing in the United States. The index date was defined as the first day of a 3-month treatment window during which Noom Weight was used at least once per week on average. Inverse probability treatment weighting was used to balance sociodemographic covariates between the 2 cohorts. HRU and costs for inpatient visits, outpatient visits, telehealth visits, surgeries, and prescriptions were analyzed. Results Within 12 months after the index date, Noom Weight users had less inpatient costs (mean difference [MD] −US $20.10, 95% CI −US $30.08 to −US $10.12), less outpatient costs (MD −US $124.33, 95% CI −US $159.76 to −US $88.89), less overall prescription costs (MD −US $313.82, 95% CI −US $565.42 to −US $62.21), and less overall health care costs (MD −US $450.39, 95% CI −US $706.28 to −US $194.50) per user than non–Noom Weight users. In terms of HRU, Noom Weight users had fewer inpatient visits (MD −0.03, 95% CI −0.04 to −0.03), fewer outpatient visits (MD −0.78, 95% CI −0.93 to −0.62), fewer surgeries (MD −0.01, 95% CI −0.01 to 0.00), and fewer prescriptions (MD −1.39, 95% CI −1.76 to −1.03) per user than non–Noom Weight users. Among a subset of individuals with 24-month follow-up data, Noom Weight users incurred lower overall prescription costs (MD −US $1139.52, 95% CI −US $1972.21 to −US $306.83) and lower overall health care costs (MD −US $1219.06, 95% CI −US $2061.56 to −US $376.55) per user than non–Noom Weight users. The key differences were associated with reduced prescription use. Conclusions Noom Weight use is associated with lower HRU and costs than non–Noom Weight use, with potential cost savings of up to US $1219.06 per user at 24 months after the index date. These findings suggest that Noom Weight could be a cost-effective weight management program for individuals with overweight and obesity. This study provides valuable evidence for health care providers and payers in evaluating the potential benefits of digital weight loss interventions such as Noom Weight.

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Changes in Health-Promoting Behaviors and Their Association with Weight Loss, Retention, and Engagement on a Digital Program: Prospective Study

Cited by 8 publications

References 73 publications

The Effects of Providing a Connected Scale in an App-Based Digital Health Program: Cross-sectional Examination

The Effects of Providing a Connected Scale in an App-Based Digital Health Program: Cross-sectional Examination

Behavioral weight-loss interventions for patients with NAFLD: A systematic scoping review

The Impact of a Digital Weight Loss Intervention on Health Care Resource Utilization and Costs Compared Between Users and Nonusers With Overweight and Obesity: Retrospective Analysis Study

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