Andreas Michaelides

Background: Accessible self-management interventions are required to support people living with breast cancer. Objective: This was an industry-academic partnership study that aimed to collect qualitative user experience data of a prototype app with built-in peer and coach support designed to support the management of health behaviors and weight in women living with breast cancer. Methods: Participants were aged ≥18 years, were diagnosed with breast cancer of any stage within the last 5 years, had completed active treatment, and were prescribed oral hormone therapy. Participants completed demographic surveys and were asked to use the app for 4 weeks. Following this, they took part in in-depth qualitative interviews about their experiences. These were analyzed using thematic analysis. Results: Eight participants (mean age, 45 years; mean time since diagnosis, 32 months) were included. Of the 8 participants, 7 (88%) were white, 6 (75%) had a graduate degree or above, and 6 (75%) had stage I-III breast cancer. Four overarching themes were identified: (1) Support for providing an app earlier in the care pathway; (2) Desire for more weight-focused content tailored to the breast cancer experience; (3) Tracking of health behaviors that are generally popular; and (4) High value of in-app social support. Conclusions: This early user experience work showed that women with breast cancer found an app with integrated social and psychological support appealing to receive support for behavior change and weight management or self-management. However, many features were recommended for further development. This work is the first step in an academic-industry collaboration that would ultimately aim to develop and empirically test a supportive app that could be integrated into the cancer care pathway.

Background: Rising rates of psychological distress (symptoms of depression, anxiety, and stress) among adults in the United States necessitate effective mental wellness interventions. Despite the prevalence of smartphone app–based programs, research on their efficacy is limited, with only 14% showing clinically validated evidence. Our study evaluates Noom Mood, a commercially available smartphone-based app that uses cognitive behavioral therapy and mindfulness-based programming. In this study, we address gaps in the existing literature by examining postintervention outcomes and the broader impact on mental wellness. Objective: Noom Mood is a smartphone-based mental wellness program designed to be used by the general population. This prospective study evaluates the efficacy and postintervention outcomes of Noom Mood. We aim to address the rising psychological distress among adults in the United States. Methods: A 1-arm study design was used, with participants having access to the Noom Mood program for 16 weeks (N=273). Surveys were conducted at baseline, week 4, week 8, week 12, week 16, and week 32 (16 weeks’ postprogram follow-up). This study assessed a range of mental health outcomes, including anxiety symptoms, depressive symptoms, perceived stress, well-being, quality of life, coping, emotion regulation, sleep, and workplace productivity (absenteeism or presenteeism). Results: The mean age of participants was 40.5 (SD 11.7) years. Statistically significant improvements in anxiety symptoms, depressive symptoms, and perceived stress were observed by week 4 and maintained through the 16-week intervention and the 32-week follow-up. The largest changes were observed in the first 4 weeks (29% lower, 25% lower, and 15% lower for anxiety symptoms, depressive symptoms, and perceived stress, respectively), and only small improvements were observed afterward. Reductions in clinically relevant anxiety (7-item generalized anxiety disorder scale) and depression (8-item Patient Health Questionnaire depression scale) criteria were also maintained from program initiation through the 16-week intervention and the 32-week follow-up. Work productivity also showed statistically significant results, with participants gaining 2.57 productive work days from baseline at 16 weeks, and remaining relatively stable (2.23 productive work days gained) at follow-up (32 weeks). Additionally, effects across all coping, sleep disturbance (23% lower at 32 weeks), and emotion dysregulation variables exhibited positive and significant trends at all time points (15% higher, 23% lower, and 25% higher respectively at 32 weeks). Conclusions: This study contributes insights into the promising positive impact of Noom Mood on mental health and well-being outcomes, extending beyond the intervention phase. Though more rigorous studies are necessary to understand the mechanism of action at play, this exploratory study addresses critical gaps in the literature, highlighting the potential of smartphone-based mental wellness programs to lessen barriers to mental health support and improve diverse dimensions of well-being. Future research should explore the scalability, feasibility, and long-term adherence of such interventions across diverse populations.

BACKGROUND Rising rates of psychological distress (symptoms of depression, anxiety, and stress) among adults in the United States necessitate effective mental wellness interventions. Despite the prevalence of smartphone app–based programs, research on their efficacy is limited, with only 14% showing clinically validated evidence. Our study evaluates Noom Mood, a commercially available smartphone-based app that uses cognitive behavioral therapy and mindfulness-based programming. In this study, we address gaps in the existing literature by examining postintervention outcomes and the broader impact on mental wellness. OBJECTIVE Noom Mood is a smartphone-based mental wellness program designed to be used by the general population. This prospective study evaluates the efficacy and postintervention outcomes of Noom Mood. We aim to address the rising psychological distress among adults in the United States. METHODS A 1-arm study design was used, with participants having access to the Noom Mood program for 16 weeks (N=273). Surveys were conducted at baseline, week 4, week 8, week 12, week 16, and week 32 (16 weeks’ postprogram follow-up). This study assessed a range of mental health outcomes, including anxiety symptoms, depressive symptoms, perceived stress, well-being, quality of life, coping, emotion regulation, sleep, and workplace productivity (absenteeism or presenteeism). RESULTS The mean age of participants was 40.5 (SD 11.7) years. Statistically significant improvements in anxiety symptoms, depressive symptoms, and perceived stress were observed by week 4 and maintained through the 16-week intervention and the 32-week follow-up. The largest changes were observed in the first 4 weeks (29% lower, 25% lower, and 15% lower for anxiety symptoms, depressive symptoms, and perceived stress, respectively), and only small improvements were observed afterward. Reductions in clinically relevant anxiety (7-item generalized anxiety disorder scale) and depression (8-item Patient Health Questionnaire depression scale) criteria were also maintained from program initiation through the 16-week intervention and the 32-week follow-up. Work productivity also showed statistically significant results, with participants gaining 2.57 productive work days from baseline at 16 weeks, and remaining relatively stable (2.23 productive work days gained) at follow-up (32 weeks). Additionally, effects across all coping, sleep disturbance (23% lower at 32 weeks), and emotion dysregulation variables exhibited positive and significant trends at all time points (15% higher, 23% lower, and 25% higher respectively at 32 weeks). CONCLUSIONS This study contributes insights into the promising positive impact of Noom Mood on mental health and well-being outcomes, extending beyond the intervention phase. Though more rigorous studies are necessary to understand the mechanism of action at play, this exploratory study addresses critical gaps in the literature, highlighting the potential of smartphone-based mental wellness programs to lessen barriers to mental health support and improve diverse dimensions of well-being. Future research should explore the scalability, feasibility, and long-term adherence of such interventions across diverse populations.

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.

BACKGROUND Accessible self-management interventions are required to support people living with breast cancer. OBJECTIVE This was an industry-academic partnership study that aimed to collect qualitative user experience data of a prototype app with built-in peer and coach support designed to support the management of health behaviors and weight in women living with breast cancer. METHODS Participants were aged ≥18 years, were diagnosed with breast cancer of any stage within the last 5 years, had completed active treatment, and were prescribed oral hormone therapy. Participants completed demographic surveys and were asked to use the app for 4 weeks. Following this, they took part in in-depth qualitative interviews about their experiences. These were analyzed using thematic analysis. RESULTS Eight participants (mean age, 45 years; mean time since diagnosis, 32 months) were included. Of the 8 participants, 7 (88%) were white, 6 (75%) had a graduate degree or above, and 6 (75%) had stage I-III breast cancer. Four overarching themes were identified: (1) Support for providing an app earlier in the care pathway; (2) Desire for more weight-focused content tailored to the breast cancer experience; (3) Tracking of health behaviors that are generally popular; and (4) High value of in-app social support. CONCLUSIONS This early user experience work showed that women with breast cancer found an app with integrated social and psychological support appealing to receive support for behavior change and weight management or self-management. However, many features were recommended for further development. This work is the first step in an academic-industry collaboration that would ultimately aim to develop and empirically test a supportive app that could be integrated into the cancer care pathway.

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.

Health-promoting lifestyle behaviors (e.g., as measured by the HPLP-II) are associated with reductions in lifestyle disease mortality, as well as improved well-being, mental health, and quality of life. However, it is unclear how a weight-management program relates to a broad range of these behaviors (i.e., health responsibility, physical activity, nutrition, spiritual growth, interpersonal relations, and stress management), especially a fully digital program on which individuals have to self-manage their own behaviors in their daily lives (with assistance from a virtual human coach). In the context of a digital setting, this study examined the changes in health-promoting behaviors over 12 months, as well as the associations between health-promoting behaviors and weight loss, retention, and engagement, among participants who self-enrolled in a mobile CBT-based nutritionally focused behavior change weight management program (n = 242). Participants lost a statistically significant amount of weight (M = 6.7 kg; SD = 12.7 kg; t(80) = 9.26, p < 0.001) and reported significantly improved overall health-promoting lifestyle behaviors (i.e., HPLP-II summary scores), as well as, specifically, health responsibility, physical activity, nutrition, spiritual growth, stress management, and interpersonal relations behaviors from baseline to 6 months and from 6 months to 12 months (all ps < 0.008). Health-promoting behaviors at 6 months (i.e., learned health-promoting behaviors) compared to baseline were better predictors of retention and program engagement. A fully digital, mobile weight management intervention can improve HPLP-II scores, which, in turn, has implications for improved retention, program engagement, and better understanding the comprehensive effects of weight management programs, particularly in a digital setting.

Background: Moderate weight loss of 5–10% is considered a realistically achievable weight loss goal and is associated with decreased risk of obesity-related health complications. However, individuals tend to expect that they will lose as much as 20–30% of their body weight when they start a behavioral weight loss program. Current research is limited on how these expectations change over time during weight loss and the consequences of adjusting one’s expectations in a more realistic direction, particularly on a CBT-based program. Method: Therefore, this prospective cohort study evaluated whether individuals adjusted their weight loss expectations over time during real-world use of a mobile CBT-based behavior-change program (Noom Weight) and how this adjustment related to weight loss outcomes, as well as how the amount of adjustment depended on program engagement. Participants had recently signed up for Noom Weight and reported their weight, expectations for weight loss, and psychological well-being at baseline and six months. Engagement was automatically recorded by the program. Results: We found that after using Noom Weight for six months, participants’ expectations became more realistic (i.e., significantly decreased) compared to baseline (−5.77, s.e. = 0.57, p < 0.001), and this downward adjustment was associated with greater weight loss (b = 1.80, 95% CI 1.21–2.38, p < 0.001). Higher program engagement, particularly reading articles focused on CBT-based principles, was associated with greater decreases in expectations over time (b = −0.007, t = −2.22, p = 0.03). Conclusions: The results suggest that CBT-based principles may aid in adjusting weight loss expectations to more realistic levels and that such adjustment is associated with positive weight outcomes. Future research should build on these results by evaluating adjustment in weight loss expectations over time, rather than solely expectations at baseline.

Background: Overweight and obesity are serious public health concerns. As the prevalence of excess weight among individuals continues to increase, there is a parallel need for inexpensive, highly accessible, and evidence-based weight loss programs. Objective: This weight loss trial will aim to examine the efficacy of the Noom weight loss program in comparison to a digital control after a 6-month intervention phase and a 24-month maintenance phase, with assessments continuing for 2 years beyond the intervention (to 30 months—after the baseline). The secondary outcomes include quality of life, psychosocial functioning, sleep quality, physical activity, diet, and health status. This trial will also examine the severity of obesity-related functional impairment, weight loss history, and demographic moderators, along with adherence and self-efficacy as mediators of the outcome. Methods: A total of 600 participants were randomized in a parallel-group, controlled trial to either Noom Healthy Weight Program (intervention) or Noom Healthy Weight Control (control) for a 6-month intervention. Both intervention and control groups include diet and exercise recommendations, educational content, daily logging capabilities, and daily weigh-in entries. The Noom Healthy Weight Program also includes a coach support for weight loss. Remote follow-up assessments of eating, physical activity, psychosocial factors, app use data, and weight will be conducted at 1, 4, 6, 12, 18, 24, and 30 months after baseline. Weight is measured at each follow-up point during a Zoom call using the participants’ scales. Results: Enrollment began in March 2021 and the 6-month intervention phase ended in March 2022. Data collection for the final assessment will be completed in March 2024. Conclusions: This study tests commercially available digital lifestyle interventions for individuals with overweight and obesity seeking weight loss support. Data obtained from the study will evaluate whether the Noom Healthy Weight Control Program can help individuals overcome weight loss, achieve long-term maintenance, adhere to lifestyle changes, and feature use barriers that are present in other traditional weight loss treatments. Trial Registration: ClinicalTrials.gov NCT04797169; https://clinicaltrials.gov/ct2/show/NCT04797169 International Registered Report Identifier (IRRID): DERR1-10.2196/37541

Executive functioning is a key component involved in many of the processes necessary for effective weight management behavior change (e.g., setting goals). Cognitive behavioral therapy (CBT) and third-wave CBT (e.g., mindfulness) are considered first-line treatments for obesity, but it is unknown to what extent they can improve or sustain executive functioning in a generalized weight management intervention. This pilot randomized controlled trial examined if a CBT-based generalized weight management intervention would affect executive functioning and executive function-related brain activity in individuals with obesity or overweight. Participants were randomized to an intervention condition (N = 24) that received the Noom Weight program or to a control group (N = 26) receiving weekly educational newsletters. EEG measurements were taken during Flanker, Stroop, and N-back tasks at baseline and months 1 through 4. After 4 months, the intervention condition evidenced greater accuracy over time on the Flanker and Stroop tasks and, to a lesser extent, neural markers of executive function compared to the control group. The intervention condition also lost more weight than controls (−7.1 pounds vs. +1.0 pounds). Given mixed evidence on whether weight management interventions, particularly CBT-based weight management interventions, are associated with changes in markers of executive function, this pilot study contributes preliminary evidence that a multicomponent CBT-based weight management intervention (i.e., that which provides both support for weight management and is based on CBT) can help individuals sustain executive function over 4 months compared to controls.