Long-Term Efficacy of a Mobile Mental Wellness Program: Prospective Single-Arm Study.

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.

Exploring the benefits and costs of a growth mindset in a digital app weight management program.

We explored the potential benefits and costs of believing one can change their weight (i.e. growth mindset) in the context of a digital weight management program. We investigated mechanisms by which growth mindsets relate to weight loss achievement and body shame. Among participants seeking to lose weight (N = 1626; 74.7% female; 77.9% White; Mage = 45.7), stronger growth mindsets indirectly predicted greater weight loss achievement through positive offset expectations and subsequent increased program engagement. Additionally, stronger growth mindsets predicted less body shame through positive offset expectations but predicted more body shame through increased onset responsibility, replicating the double-edged sword model of growth mindsets. We conclude with applications that leverage growth mindsets for optimal behavior change while mitigating costs such as body shame.

Weight loss maintenance after a digital commercial behavior change program (Noom Weight): Observational cross-sectional survey study.

Background: Behavioral weight loss programs often lead to significant short-term weight loss, but long-term weight maintenance remains a challenge. Most weight maintenance data come from clinical trials, in-person programs, or general population surveys, but there is a need for better understanding of long-term weight maintenance in real-world digital programs. Methods: This observational survey study examined weight maintenance reported by individuals who had used Noom Weight, a digital commercial behavior change program, and identified factors associated with greater weight maintenance. The cross-sectional survey was completed by 840 individuals who had lost at least 10% of their body weight using Noom Weight 6-24 months prior. Results: The study found that 75% of individuals maintained at least 5% weight loss after 1 year, and 49% maintained 10% weight loss. On average, 65% of initial weight loss was maintained after 1 year and 57% after 2 years. Habitual behaviors, such as healthy snacking and exercise, were associated with greater weight maintenance, while demographic factors were not. Conclusion: This study provides real-world data on the long-term weight maintenance achieved using a fully digital behavioral program. The results suggest that Noom Weight is associated with successful weight maintenance in a substantial proportion of users. Future research will use a randomized controlled trial to track weight maintenance after random assignment and at a 2 year follow-up.

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.

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.

Men's Weight Loss Outcomes, Behaviors, and Perceptions in a Self-Directed Commercial Mobile Program: Retrospective Analysis.

BACKGROUND: There is little understanding of men's weight loss outcomes and behaviors in self-directed contexts, such as digital commercial mobile weight management programs. This is an especially pressing question given that men often express disinterest in weight management programs and it is unknown how that manifests in self-directed environments. Aims. Two studies fill this gap by retrospectively observing how men lose weight and engage in weight loss behaviors (Study 1) and their perceptions of improvements and gained knowledge (Study 2) when participating in the full length of a commercial mobile behavior change program called Noom. METHOD: In Study 1, repeated-measures linear mixed modeling was used to examine whether weight loss was statistically significant from baseline to 16 weeks and how engagement behaviors predicted weight in a sample of 7,495 male Noom users. In Study 2, 971 male Noom users completed an exploratory survey on the impact of the behavior change education in the program. RESULTS: In Study 1, men who remained in the full length of the program lost statistically significant weight from baseline to 16 weeks. 63% achieved clinically meaningful (5% or more) weight loss. Engagement in weight loss behaviors on the program predicted the amount of weight lost. In Study 2, men reported learning most about practical application and psychological aspects relating to food and psychology. DISCUSSION AND CONCLUSION: This is the first study to observe men's weight loss outcomes, behaviors, and perceptions of what they learned in a self-directed behavior change program. Our findings have important implications for more effective health promotion for the many men who choose to self-direct their weight loss.

Predictive capacity of COVID-19-related risk beliefs on weight management behaviors on a commercial weight loss program and speed of COVID-19 vaccination uptake: prospective cohort study.

BACKGROUND: Recent work has shown that obesity may be a risk factor for severe COVID-19. However, it is unclear to what extent individuals have heard or believe this risk factor information, and how these beliefs may predict their preventive behaviors (e.g., weight management behaviors or COVID-19 preventive behaviors). Previous work has primarily looked at overall risk likelihood perceptions (i.e., not about obesity as a risk factor) within general populations of varying weight and concentrated on COVID-19-related preventive behaviors. Therefore, this prospective cohort study explored whether beliefs about obesity as a risk factor and overall risk likelihood perceptions predicted weight management and COVID-19 preventive behaviors over the next 16 weeks in individuals with obesity or overweight. METHODS: Participants were 393 individuals in the US who joined a commercial weight management program in January, 2021. We leveraged the mobile program's automatic measurement of real-time engagement in weight management behaviors (e.g., steps taken), while surveys measured risk beliefs at baseline as well as when individuals received COVID-19 vaccination doses (asked monthly) over the next 16 weeks. Mixed effects models predicted engagement and weight loss each week for 16 weeks, while ordinal logistic regression models predicted the month that individuals got vaccinated against COVID-19. RESULTS: We found that belief in obesity as a risk factor at baseline significantly predicted greater engagement (e.g., steps taken, foods logged) in program-measured weight management behaviors over the next 16 weeks in models adjusted for baseline BMI, age, gender, and local vaccination rates (minimally adjusted) and in models additionally adjusted for demographic factors. Belief in obesity as a risk factor at baseline also significantly predicted speed of COVID-19 vaccination uptake in minimally adjusted models but not when demographic factors were taken into account. Exposure to obesity risk factor information at baseline predicted greater engagement over 16 weeks in minimally adjusted models. CONCLUSIONS: The results highlight the potential utility of effective education to increase individuals' belief in obesity risk factor information and ultimately promote engagement or faster vaccination. Future research should investigate to what extent the results generalize to other populations.

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

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.

Executive Function-Related Improvements on a Commercial CBT-Based Weight Management Intervention: Pilot Randomized Controlled Trial.

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.

Feasibility, Acceptability, and Preliminary Outcomes of a Cognitive Behavioral Therapy-Based Mobile Mental Well-being Program (Noom Mood): Single-Arm Prospective Cohort Study.

BACKGROUND: The prevalence of anxiety, depression, and general distress has risen in recent years. Mobile mental health programs have been found to provide support to nonclinical populations and may overcome some of the barriers associated with traditional in-person treatment; however, researchers have voiced concerns that many publicly available mobile mental health programs lack evidence-based theoretical foundations, peer-reviewed research, and sufficient engagement from the public. OBJECTIVE: This study aimed to evaluate the feasibility, acceptability, and preliminary outcomes of Noom Mood, a commercial mobile cognitive behavioral therapy- and mindfulness-based program. METHODS: In this single-arm prospective cohort study, individuals who joined Noom Mood between August and October 2021 completed surveys at baseline and 4-week follow-up. Per-protocol analyses included those who completed both surveys (n=113), and intention-to-treat analyses included all participants (N=185). RESULTS: A majority of the sample reported that the program is easy to use, they felt confident recommending the program to a friend, and they perceived the program to be effective at improving stress and anxiety. There were significant improvements in anxiety symptoms, perceived stress, depressive feelings, emotion regulation, and optimism in both the per-protocol and intention-to-treat analyses (all P<.001). Participants reported benefiting most from learning skills (eg, breathing and cognitive reframing techniques), interacting with the program features, and gaining awareness of their emotions and thought patterns. Participants also made a number of suggestions to improve product functionality and usability. CONCLUSIONS: Results suggest that Noom Mood is feasible and acceptable to participants, with promising preliminary outcomes. Future studies should build on these results to evaluate the effects of Noom Mood using more rigorous designs.

Goal language is associated with attrition and weight loss on a digital program: Observational study.

Behavioral weight loss reduces risk of weight-related health complications. Outcomes of behavioral weight loss programs include attrition and weight loss. There is reason to believe that individuals' written language on a weight management program may be associated with outcomes. Exploring associations between written language and these outcomes could potentially inform future efforts towards real-time automated identification of moments or individuals at high risk of suboptimal outcomes. Thus, in the first study of its kind, we explored whether individuals' written language in actual use of a program (i.e., outside of a controlled trial) is associated with attrition and weight loss. We examined two types of language: goal setting (i.e., language used in setting a goal at the start of the program) and goal striving (i.e., language used in conversations with a coach about the process of striving for goals) and whether they are associated with attrition and weight loss on a mobile weight management program. We used the most established automated text analysis program, Linguistic Inquiry Word Count (LIWC), to retrospectively analyze transcripts extracted from the program database. The strongest effects emerged for goal striving language. In striving for goals, psychologically distanced language was associated with more weight loss and less attrition, while psychologically immediate language was associated with less weight loss and higher attrition. Our results highlight the potential importance of distanced and immediate language in understanding outcomes like attrition and weight loss. These results, generated from real-world language, attrition, and weight loss (i.e., from individuals' natural usage of the program), have important implications for how future work can better understand outcomes, especially in real-world settings.

Body Positivity and Self-Compassion on a Publicly Available Behavior Change Weight Management Program.

According to recent research, body positivity and self-compassion are key outcomes that are tied to better psychological and physical health. To date, it is unclear whether body positivity and self-compassion improve, stay constant, or deteriorate over the course of a weight management program, particularly one that addresses the psychological roots of behavior change. Additionally, beyond controlled settings, there are no studies on body positivity and self-compassion in individuals who choose to join a commercial weight management program. Therefore, this single-arm prospective study examined changes in body positivity and self-compassion from baseline to the 16 week milestone of Noom Weight, a commercial behavior change weight management program informed by acceptance and commitment therapy (ACT), dialectical behavior therapy (DBT), and cognitive behavioral therapy (CBT). We also examined how baseline and over-time changes in body positivity and self-compassion predicted engagement in program-measured relevant behaviors (e.g., exercises logged). Participants were a random subset of individuals who had recently self-enrolled in the program (n = 133). Body positivity and self-compassion were measured via survey at baseline and end of the core program (16 weeks). Self-reported weight and program-recorded engagement were extracted from the program database. Compared to baseline, body appreciation, body image flexibility, self-compassion, and body-focused rumination significantly improved at 16 weeks (all ps < 0.007). Participants lost a statistically significant amount of weight (3.9 kg; t(128)) = 10.64, p < 0.001) by 16 weeks, which was 4.4% body weight. Greater engagement, especially messaging a coach, reading articles, and logging meals, was associated with improvements over time in body appreciation (r = 0.17, p = 0.04), body image flexibility (r = -0.23, p = 0.007), and the brooding component of rumination (r = -0.23, p = 0.007). Greater engagement was also associated with baseline total self-compassion (r = 0.19, p = 0.03) and self-judgment (r = 0.24, p = 0.006). The results suggest that individuals experience improvements in body positivity and self-compassion while learning about ACT, DBT, and CBT through curriculum and coaching in this setting. The results also have important clinical implications, such as the possibility that psychologically-oriented (i.e., ACT, DBT, and CBT-based) weight management could be important to improve body positivity or that baseline self-compassion could be used to target individuals at risk for lower engagement. Future work should investigate these possibilities as well as delineate the causal relationships between body positivity, self-compassion, engagement, and weight loss.

Comparing Outcomes of a Digital Commercial Weight Loss Program in Adult Cancer Survivors and Matched Controls with Overweight or Obesity: Retrospective Analysis.

Maintaining a healthy weight is beneficial for cancer survivors. However, weight loss program effectiveness studies have primarily been in highly controlled settings. This is a retrospective study exploring real-world outcomes (weight loss and program engagement) after use of a digital commercial weight loss program (Noom) in cancer survivors and matched controls. All participants had voluntarily self-enrolled in Noom. Weight and engagement data were extracted from the program. Cancer-related quality of life was secondarily assessed in a one-time cross-sectional survey for survivors. Controls were a sample of Noom users with overweight/obesity who had no history of cancer but 0-1 chronic conditions. Primary outcomes were weight change at 16 weeks and program engagement over 16 weeks. Engagement included frequency of weight, food, and physical activity logging, as well as number of coach messages. Multiple regression controlling for baseline age, gender, engagement, and BMI showed that survivors lost less weight than controls (B = -2.40, s.e. = 0.97, p = 0.01). Survivors also weighed in less (survivors: 5.4 [2.3]; controls: 5.7 [2.1], p = 0.01) and exercised less (survivors: 1.8 [3.2]; controls: 3.2 [4.1], p < 0.001) than controls. However, survivors sent more coach messages (survivors: 2.1 [2.4]; controls: 1.7 [2.0], p < 0.001). Despite controls losing more weight than cancer survivors (-7.0 kg vs. -5.3 kg), survivors lost significant weight in 4 months (M = -6.2%). Cancer survivors can have success on digital commercial programs available outside of a clinical trial. However, they may require additional support to engage in weight management behaviors.

How Do Emotions during Goal Pursuit in Weight Change over Time? Retrospective Computational Text Analysis of Goal Setting and Striving Conversations with a Coach during a Mobile Weight Loss Program.

During behavioral weight management, individuals reflect on their progress and barriers through goal pursuit (goal setting and goal striving). Emotions during goal pursuit are largely unknown, and previous investigations of emotions in weight management have primarily relied on self-report. In this retrospective study, we used a well-validated computational text analysis approach to explore how emotion words changed over time during goal setting and striving conversations with a coach in a mobile weight loss program. Linear mixed models examined changes in emotion words each month from baseline to program end and compared emotion words between individuals who set an overall concrete goal for the program (concrete goal setters) and those who set an overall abstract goal (abstract goal setters). Contrary to findings using self-report, positive emotion words were stable and negative emotion words significantly increased over time. There was a marginal trend towards greater negative emotion word use being associated with greater weight loss. Concrete goal setters used more positive words than abstract goal setters, with no differences in negative emotion words and weight loss. Implications include the possibility that individuals may need increasing support over time for negative emotions expressed during goal setting and striving, and concrete goals could boost positive emotion. Future research should investigate these possibilities.

Self-Reported Nutritional Factors Are Associated with Weight Loss at 18 Months in a Self-Managed Commercial Program with Food Categorization System: Observational Study.

Little is known about nutritional factors during weight loss on digital commercial weight loss programs. We examined how nutritional factors relate to weight loss for individuals after 4 and 18 months on a mobile commercial program with a food categorization system based on energy density (Noom). This is a two-part (retrospective and cross-sectional) cohort study. Two time points were used for analysis: 4 months and 18 months. For 4-month analyses, current Noom users who met inclusion criteria (n = 9880) were split into 5% or more body weight loss and stable weight loss (0 ± 1%) groups. Individuals who fell into one of these groups were analyzed at 4 months (n = 3261). For 18-month analyses, individuals from 4-month analyses who were still on Noom 18 months later were invited to take a one-time survey (n = 803). At 18 months 148 participants were analyzed. Noom has a system categorizing foods as low-, medium-, and high-energy-dense. Measures were self-reported proportions of low-, medium-, and high-energy-dense foods, and self-reported nutritional factors (fruit and vegetable intake, dietary quality, nutrition knowledge, and food choice). Nutritional factors were derived from validated survey measures, and food choice from a novel validated computerized task in which participants chose a food they would want to eat right now. ANOVAs compared participants with 5% or more body weight loss and participants with stable weight (0 ± 1%) at 4 months on energy density proportions. Analyses at 18 months compared nutritional factors across participants with >10% (high weight loss), 5-10% (moderate weight loss), and less than 5% body weight loss (low weight loss), and then assessed associations between nutritional factors and weight loss. Individuals with greater weight loss reported consuming higher proportions of low-energy-dense foods and lower proportions of high-energy-dense foods than individuals with less weight loss at 4 months and 18 months (all ps < 0.02). Individuals with greater weight loss had higher fruit and vegetable intake (p = 0.03), dietary quality (p = 0.02), nutrition knowledge (p < 0.001), and healthier food choice (p = 0.003) at 18 months. Only nutrition knowledge and food choice were associated with weight loss at 18 months (B = -19.44, 95% CI: -33.19 to -5.69, p = 0.006; B = -5.49, 95% CI: -8.87 to -2.11, p = 0.002, respectively). Our results highlight the potential influence of nutrition knowledge and food choice in weight loss on a self-managed commercial program. We also found for the first time that in-the-moment inclination towards food even when just depicted is associated with long-term weight loss.

Cross-National Outcomes of a Digital Weight Loss Intervention in the United States, Canada, United Kingdom and Ireland, and Australia and New Zealand: A Retrospective Analysis.

Mobile health (mHealth) interventions are ubiquitous and effective treatment options for obesity. There is a widespread assumption that the mHealth interventions will be equally effective in other locations. In an initial test of this assumption, this retrospective study assesses weight loss and engagement with an mHealth behavior change weight loss intervention developed in the United States (US) in four English-speaking regions: the US, Australia and New Zealand (AU/NZ), Canada (CA), and the United Kingdom and Ireland (UK/IE). Data for 18,459 participants were extracted from the database of Noom's Healthy Weight Program. Self-reported weight was collected every week until program end (week 16). Engagement was measured using user-logged and automatically recorded actions. Linear mixed models were used to evaluate change in weight over time, and ANOVAs evaluated differences in engagement. In all regions, 27.2-33.2% of participants achieved at least 5% weight loss by week 16, with an average of 3-3.7% weight loss. Linear mixed models revealed similar weight outcomes in each region compared to the US, with a few differences. Engagement, however, significantly differed across regions (P < 0.001 on 5 of 6 factors). Depending on the level of engagement, the rate of weight loss over time differed for AU/NZ and UK/IE compared to the US. Our findings have important implications for the use and understanding of digital weight loss interventions worldwide. Future research should investigate the determinants of cross-country engagement differences and their long-term effects on intervention outcomes.

Psychosocial Characteristics by Weight Loss and Engagement in a Digital Intervention Supporting Self-Management of Weight.

There is substantial variability in weight loss outcomes. Psychosocial characteristics underlying outcomes require better understanding, particularly on self-managed digital programs. This cross-sectional study examines differences in psychosocial characteristics by weight loss and engagement outcome, and which characteristics are most associated with weight loss, on a self-managed digital weight loss program. Some underexplored psychosocial characteristics are included, such as flourishing, or a sense of meaning and purpose in life. A questionnaire was emailed to a random sample of 10,000 current users at week 5 in the program and 10,000 current users at week 17. The questionnaire was completed by 2225 users, and their self-reported weight and recorded program engagement data were extracted from the program's database. Multiple comparison tests indicated that mental health quality of life, depression, anxiety, work-life balance, and flourishing differed by weight loss outcome at program end (week 17; ≥5%, 2-5%, below 2%) and by engagement tertile at program beginning and end (weeks 5 and 17). Only anxiety was associated with weight loss in a backward stepwise regression controlling for engagement and sociodemographic characteristics. Flourishing did not predict weight loss overall but predicted the weight loss outcome group. Our findings have implications for creating more effective interventions for individuals based on psychosocial characteristics and highlight the potential importance of anxiety in underexplored self-managed digital programs.

Psychological, Relational, and Emotional Effects of Self-Disclosure After Conversations With a Chatbot.

Disclosing personal information to another person has beneficial emotional, relational, and psychological outcomes. When disclosers believe they are interacting with a computer instead of another person, such as a chatbot that can simulate human-to-human conversation, outcomes may be undermined, enhanced, or equivalent. Our experiment examined downstream effects after emotional versus factual disclosures in conversations with a supposed chatbot or person. The effects of emotional disclosure were equivalent whether participants thought they were disclosing to a chatbot or to a person. This study advances current understanding of disclosure and whether its impact is altered by technology, providing support for media equivalency as a primary mechanism for the consequences of disclosing to a chatbot.