Retrofit Weight-Loss Outcomes at 6, 12, and 24 Months and Characteristics of 12-Month High Performers: A Retrospective Analysis

Health and Wellness Coaching and Sustained Gains: A Rapid Systematic Review

The Transtheoretical Model of Change identifies key stages in behavior change, including a maintenance stage occurring when a behavior has been upheld for at least 6 months. Health and wellness coaching has demonstrated support for health behavior change, but maintenance of gains has received little attention. Our rapid systematic literature review characterizes both the research exploring sustained gains with health and wellness coaching and what is known about sustained gains after the completion of a health and wellness coaching engagement. Guided by The Cochrane Rapid Reviews Methods Group "Interim Guidance," we drew 231 studies from the 2018 and 2020 Sforzo et al "Compendium of the health and wellness coaching literature," and "Addendum…" appendices. Initial screening and coding for inclusion and exclusion criteria yielded 28 studies for data extraction. We examined studies across outcome categories (physiological, behavioral, psychological, and health risk assessment) to determine whether outcome measures were: not sustained; partially sustained; fully sustained; or improved from immediate post-intervention to a later follow-up period. Twenty-five of the 28 studies reviewed demonstrated partially, or fully, sustained or improved outcomes in one or more variables studied, with sustained gains demonstrated across outcome categories, strengthening confidence in HWC as a facilitator of lasting change.

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.

Dosing of Health and Wellness Coaching for Obesity and Type 2 Diabetes: Research Synthesis to Derive Recommendations

Health and wellness coaching (HWC) is an effective intervention for lifestyle disease such as obesity and type 2 diabetes. The evolving HWC profession needs recommendations to guide clinical practice, particularly the appropriate dose of coaching. The purpose of this paper was to systematically review and synthesize HWC literature to derive HWC programming recommendations. Of 102 papers retrieved, 88 were retained with data extracted determining HWC session number, frequency, duration, program length, and total coaching load. Differential analysis yielded no statistical difference in programming variables for randomized control trials and other designs, nor for studies with significant findings v. those not finding statistical significance, allowing these data to be pooled. The HWC intervention for obesity was slightly more intense (15 sessions over 7-8 mo) than the diabetes programming (12 sessions over 9-10 mo). On average, HWC programming applied in the peer-reviewed literature was 12-15 sessions of 35-40 min duration over 7-9 months. These recommendations for HWC programming variables are put forth as initial practice guidelines and should be examined with comparative effectiveness study for optimization. HWC best practice guidelines for other patient groups (e.g., heart disease, cancer, and chronic pain) should also be studied once an adequate literature data base is available.

Drivers of weight loss in a CDC-recognized digital diabetes prevention program

INTRODUCTION

To investigate the impact of the digital Livongo Diabetes Prevention Program (DPP) on weight at 12 months, understand participants' self-monitoring behaviors associated with greater weight loss, and evaluate the impact of coaching interactions on more frequent self-monitoring behaviors.

RESEARCH DESIGN AND METHODS

A retrospective analysis was performed using data from 2037 participants enrolled in the Livongo DPP who completed lesson 1 and recorded a starting weight during 2016-2017. Self-monitoring behaviors, including weigh-ins, food logging, activity, and coach-participant interactions, were analyzed at 6 and 12 months. Subgroup analysis was conducted based on those who were highly engaged versus those minimally engaged. Multiple regression analysis was performed using demographic, self-monitoring, and lesson attendance data to determine predictors of weight loss at 12 months and coaching impact on self-monitoring.

RESULTS

Participants had a mean age of 50 years (SD ±12), with a starting weight of 94 kg (SD ±21), were college-educated (78%), and were female (74%). Overall, participants lost on average 5.1% of their starting weight. Highly engaged participants lost 6.6% of starting body weight, with 25% losing ≥10% at 12 months. Logistic regression analysis showed each submitted food log was associated with 0.23 kg (p<0.05) weight loss, each lesson completed was associated with 0.14 kg (p<0.05) weight loss, and a week of 150 active minutes was associated with 0.1 kg (p<0.01) weight loss. One additional coach-participant message each week was associated with 1.4 more food logs per week, 1.6% increase in weeks with four or more weigh-ins, and a 2.7% increase in weeks with 150 min of activity.

CONCLUSIONS

Food logging had the largest impact on weight loss, followed by lesson engagement and physical activity. Future studies should examine further opportunities to deliver nutrition-based content to increase and sustain weight loss for DPP.

Persuasive System Design Principles and Behavior Change Techniques to Stimulate Motivation and Adherence in Electronic Health Interventions to Support Weight Loss Maintenance: Scoping Review

BACKGROUND

Maintaining weight after weight loss is a major health challenge, and eHealth (electronic health) solutions may be a way to meet this challenge. Application of behavior change techniques (BCTs) and persuasive system design (PSD) principles in eHealth development may contribute to the design of technologies that positively influence behavior and motivation to support the sustainable health behavior change needed.

OBJECTIVE

This review aimed to identify BCTs and PSD principles applied in eHealth interventions to support weight loss and weight loss maintenance, as well as techniques and principles applied to stimulate motivation and adherence for long-term weight loss maintenance.

METHODS

A systematic literature search was conducted in PsycINFO, Ovid MEDLINE (including PubMed), EMBASE, Scopus, Web of Science, and AMED, from January 1, 2007 to June 30, 2018. Arksey and O'Malley's scoping review methodology was applied. Publications on eHealth interventions were included if focusing on weight loss or weight loss maintenance, in combination with motivation or adherence and behavior change.

RESULTS

The search identified 317 publications, of which 45 met the inclusion criteria. Of the 45 publications, 11 (24%) focused on weight loss maintenance, and 34 (76%) focused on weight loss. Mobile phones were the most frequently used technology (28/45, 62%). Frequently used wearables were activity trackers (14/45, 31%), as well as other monitoring technologies such as wireless or digital scales (8/45, 18%). All included publications were anchored in behavior change theories. Feedback and monitoring and goals and planning were core behavior change technique clusters applied in the majority of included publications. Social support and associations through prompts and cues to support and maintain new habits were more frequently used in weight loss maintenance than weight loss interventions. In both types of interventions, frequently applied persuasive principles were self-monitoring, goal setting, and feedback. Tailoring, reminders, personalization, and rewards were additional principles frequently applied in weight loss maintenance interventions. Results did not reveal an ideal combination of techniques or principles to stimulate motivation, adherence, and weight loss maintenance. However, the most frequently mentioned individual techniques and principles applied to stimulate motivation were, personalization, simulation, praise, and feedback, whereas associations were frequently mentioned to stimulate adherence. eHealth interventions that found significant effects for weight loss maintenance all applied self-monitoring, feedback, goal setting, and shaping knowledge, combined with a human social support component to support healthy behaviors.

CONCLUSIONS

To our knowledge, this is the first review examining key BCTs and PSD principles applied in weight loss maintenance interventions compared with those of weight loss interventions. This review identified several techniques and principles applied to stimulate motivation and adherence. Future research should aim to examine which eHealth design combinations can be the most effective in support of long-term behavior change and weight loss maintenance.

A Remote Intervention to Prevent or Delay Cognitive Impairment in Older Adults: Design, Recruitment, and Baseline Characteristics of the Virtual Cognitive Health (VC Health) Study

Background

A growing body of evidence supports the use of lifestyle interventions for preventing or delaying the onset of Alzheimer disease and other forms of dementia in at-risk individuals. The development of internet-delivered programs would increase the scalability and reach of these interventions, but requires validation to ensure similar effectiveness to brick-and-mortar options.

Objective

We describe the study design, recruitment process, and baseline participant characteristics of the sample in the Virtual Cognitive Health (VC Health) study. Future analyses will assess the impact of the remotely delivered lifestyle intervention on (1) cognitive function, (2) depression and anxiety, and (3) various lifestyle behaviors, including diet, exercise, and sleep, in a cohort of older adults with subjective memory decline. Additional analyses will explore feasibility outcomes, as well as the participants’ engagement patterns with the program.

Methods

Older adults (aged 60-75 years) with subjective memory decline as measured by the Subjective Cognitive Decline 9-item (SCD-9) questionnaire, and who reported feeling worried about their memory decline, were eligible to participate in this single-arm pre-post study. All participants enrolled in the yearlong digital intervention, which consists of health coach-guided lifestyle change for improving diet, exercise, sleep, stress, and cognition. All components of this study were conducted remotely, including the collection of data and the administration of the intervention. We assessed participants at baseline, 12 weeks, 24 weeks, and 52 weeks with online surveys and the Repeatable Battery for the Assessment of Neuropsychological Status (RBANS) test. We will conduct intention-to-treat analysis on all outcomes.

Results

A total of 85 participants enrolled in the intervention and 82 are included in the study sample (3 participants withdrew). The study cohort of 82 participants comprises 61 (74%) female, 72 (88%) white, and 64 (78%) overweight or obese participants, and 55 (67%) have at least a college degree. The average baseline RBANS score was 95.9 (SD 11.1), which is within age-adjusted norms. The average SCD-9 score was 6.0 (SD 2.0), indicating minor subjective cognitive impairment at the beginning of the study. The average baseline Generalized Anxiety Disorder 7-item scale score was 6.2 (SD 4.5), and the average Patient Health Questionnaire 9-item score was 8.5 (SD 4.9), indicating mild levels of anxiety and depression at baseline.

Conclusions

Internet-delivered lifestyle interventions are a scalable solution for the prevention or delay of Alzheimer disease. The results of this study will provide the first evidence for the effectiveness of a fully remote intervention and lay the groundwork for future investigations.

Trial Registration

ClinicalTrials.gov NCT02969460; http://clinicaltrials.gov/ct2/show/NCT02969460 (Archived by WebCite at http://www.webcitation.org/71LkYAkSh)

Registered Report Identifier

RR1-10.2196/11368

A review and critique of published real-world weight management program studies

BACKGROUND

Beyond the essential but somewhat artificial conditions that typify formal clinical studies, real-world evidence (RWE) of weight loss program effectiveness is paramount for an accurate assessment of such programs and refinement of best practices.

OBJECTIVES

To evaluate the current state of RWE studies and publications on weight loss, identify the range of weight loss components being used in RWE programs, and to provide a general overview of the consistency or lack of consistency with regard to measuring and reporting outcomes.

METHODS

A structured search of PubMed was performed to identify relevant English-language publications from 2006 to December 2017 that reported real-world studies of weight loss among adults. Duplicates, non-relevant publications, articles on weight loss surgery, pediatric studies, randomized controlled trials, studies with self-reported weight loss, no objective weight measures, or that failed to include weight loss results were excluded.

RESULTS

This review included 62 RWE publications. Forty-nine studies included dietary intervention, 37 included exercise, 29 included motivational counseling, and 5 contained some patients who had pharmacologic treatment as part of their weight loss regimen. The numbers of participants per study ranged from 10 to more than 3 million. The interventions reported in the publications included diet, exercise, counseling to promote diet and/or exercise, motivational counseling, and pharmacotherapy, and various combinations of these.

CONCLUSIONS

Despite general acceptance that weight loss programs are capable of facilitating successful outcomes, this review revealed substantial inconsistency in the design and reporting of such programs, making it very difficult to draw conclusions about the comparative merits of different real-world weight loss strategies/components. In addition, there was a marked lack of congruence with current weight loss management guidelines, and notably few studies incorporating anti-obesity medications. There clearly is a need for greater rigor and standardization among designing and reporting RWE weight-loss studies.

Impact of the I2AO2 interdisciplinary program led by nursing on psychological comorbidity and quality of life: Randomized controlled clinical trial

OBJECTIVE

Obesity is an entity of highly prevalent multifactorial origin with associated metabolic and psychological comorbidity, causing a negative impact on the quality of life of those who suffer from it. The objective is to evaluate the impact of an interdisciplinary program for nurse-led obesity on quality of life related to health and anxiety.

METHODS

Randomized controlled clinical trial with a sample of 74 subjects diagnosed with obesity (EG: n=37; CG: n=37). The intervention consisted of a 12-month interdisciplinary program (with pre-test, 12month and 24month follow-up) coordinated by nurses.

RESULTS

The anxiety analysis shows that there is no effect of the intervention on S-STAI (F2; 144=0.246; p=0.782), which has increased in both groups. However, there is an effect on T-STAI (F2; 144=8872; p<0.001), which only increases in the control group. The interdisciplinary program has significantly improved health-related quality of life (SF-36), both in physical health parameters as well as in mental health.

CONCLUSION

The interdisciplinary program led by nursing professionals has improved the quality of life related to health and has prevented the increase of anxiety-trait in participants, maintaining the long-term effects.

What Matters in Weight Loss? An In-Depth Analysis of Self-Monitoring

BACKGROUND

Using technology to self-monitor body weight, dietary intake, and physical activity is a common practice used by consumers and health companies to increase awareness of current and desired behaviors in weight loss. Understanding how to best use the information gathered by these relatively new methods needs to be further explored.

OBJECTIVE

The purpose of this study was to analyze the contribution of self-monitoring to weight loss in participants in a 6-month commercial weight-loss intervention administered by Retrofit and to specifically identify the significant contributors to weight loss that are associated with behavior and outcomes.

METHODS

A retrospective analysis was performed using 2113 participants enrolled from 2011 to 2015 in a Retrofit weight-loss program. Participants were males and females aged 18 years or older with a starting body mass index of ≥25 kg/m2, who also provided a weight measurement at the sixth month of the program. Multiple regression analysis was performed using all measures of self-monitoring behaviors involving weight measurements, dietary intake, and physical activity to predict weight loss at 6 months. Each significant predictor was analyzed in depth to reveal the impact on outcome.

RESULTS

Participants in the Retrofit Program lost a mean -5.58% (SE 0.12) of their baseline weight with 51.87% (1096/2113) of participants losing at least 5% of their baseline weight. Multiple regression model (R²=.197, P<0.001) identified the following measures as significant predictors of weight loss at 6 months: number of weigh-ins per week (P<.001), number of steps per day (P=.02), highly active minutes per week (P<.001), number of food log days per week (P<.001), and the percentage of weeks with five or more food logs (P<.001). Weighing in at least three times per week, having a minimum of 60 highly active minutes per week, food logging at least three days per week, and having 64% (16.6/26) or more weeks with at least five food logs were associated with clinically significant weight loss for both male and female participants.

CONCLUSIONS

The self-monitoring behaviors of self-weigh-in, daily steps, high-intensity activity, and persistent food logging were significant predictors of weight loss during a 6-month intervention.

Engagement and outcomes in a digital Diabetes Prevention Program: 3-year update

OBJECTIVE

Translations of the Diabetes Prevention Program (DPP) have proliferated in recent years, with increasing expansion to digital formats. Although these DPP translations have consistently shown favorable clinical outcomes, long-term data for digital formats are limited. This study's objective was to examine clinical outcomes up to 3 years post-baseline and the relationship between program engagement and clinical outcomes in a digital DPP.

RESEARCH DESIGN AND METHODS

In a single-arm, non-randomized trial, 220 patients previously diagnosed with prediabetes were enrolled in the Omada Health Program, a commercially available, 16-week DPP-based weight loss intervention followed by an ongoing weight maintenance intervention. Changes in body weight and A1c were assessed annually. Relationships between program engagement during the first year and clinical outcomes across 3 years were examined.

RESULTS

Participants were socioeconomically diverse (62% women, 50.2% non-Hispanic white, 51.7% college educated or higher). From baseline to 3 years, those participants who completed four or more lessons and nine or more lessons achieved significant sustained weight loss (-3.0% and -2.9%, respectively) and an absolute reduction in A1c (-0.31 and -0.33, respectively) with an average remission from the prediabetes range to the normal glycemic range. Factor analysis of engagement metrics during the first year revealed two underlying dimensions, one comprising lesson completion and health behavior tracking consistency, and the other comprising website logins and group participation. When these two factors were used to predict weight loss, only the logins and group participation factor was a significant predictor of weight loss at 16 weeks and 1 year.

CONCLUSIONS

This study demonstrates significant long-term reductions in body weight and A1c in a digital DPP and identifies patterns of program engagement that predict weight loss.