Efficacy of a Multi-component m-Health Weight-loss Intervention in Overweight and Obese Adults: A Randomised Controlled Trial

An adapted transdiagnostic sleep and circadian intervention for adults with excess weight and suboptimal sleep health: pilot study results

Study Objectives

This single-arm, mixed-methods, pilot study examined the feasibility and preliminary efficacy of an adapted version of the transdiagnostic intervention for sleep and circadian dysfunction (TranS-C) on multidimensional sleep health (MDSH) in a sample of adults with excess weight and suboptimal sleep health.

Methods

Participants received up to eight, weekly, remotely delivered, tailored TranS-C sessions. At pre- and post-intervention, the Pittsburgh Sleep Quality Index, Epworth Sleepiness Scale, and 7 days of Fitbit data were used to evaluate changes in sleep dimensions (regularity, alertness, timing, satisfaction, duration, and efficiency) and the composite MDSH score. Study feasibility examined recruitment, data collection, and intervention engagement (completion of core TranS-C sessions). Acceptability of the intervention was assessed with semi-structured interviews, which were analyzed using thematic analysis.

Results

From 85 referrals, 11 individuals were eligible, and 10 completed the study. All intervention participants completed the measures needed to calculate their composite MDSH score and completed the core intervention sessions. Themes from interviews support the intervention's remote delivery approach, applicability of the information provided, and impact on self-reported health. The intervention resulted in a large improvement in the mean composite MDSH score (Cohen's d = 1.17). Small-to-large effects were also observed for individual sleep health dimensions except for timing.

Conclusions

Adapted TranS-C is acceptable for adults with excess weight and suboptimal sleep health and may be effective at improving short-term MDSH. With changes to recruitment methods, a larger study is feasible. Limitations include the small sample size and the lack of a control condition.

Insomnia, Short Sleep, and Their Treatments: Review of Their Associations with Weight

PURPOSE OF REVIEW

Insomnia and short sleep have been linked with weight gain and obesity. However, these findings have not been consistent across studies. We review recent evidence for the association between insomnia, short sleep, and weight gain, as well as the relationship between behavioral and pharmacological treatments for sleep and weight.

RECENT FINDINGS

The relationship between insomnia and obesity is mixed, with stronger associations between insomnia with short sleep and obesity than other presentations of insomnia. Short sleep is associated with weight gain. Z-drugs and benzodiazapines do not appear to impact weight, but many antidepressants and antipsychotics that are used for insomnia treatment do cause weight gain. The relationships between insomnia and short sleep with weight gain and obesity are inconsistent. More prospective trials are needed to identify mediators and moderators of this relationship to better develop and deliver effective interventions for both sleep and weight problems.

Smartphone applications for nutrition Support: A systematic review of the target outcomes and main functionalities

INTRODUCTION

A proper nutrition is essential for human life. Recently, special attention on this topic has been given in relation to three health statuses: obesity, malnutrition and specific diseases that can be related to food or treated with specific diets. Mobile technology is often used to assist users that wish to regulate their eating habits, and identifying which fields of application have been explored the most by the app developers and which main functionalities have been adopted can be useful in view of future app developments.

METHODS

We selected 322 articles mentioning nutrition support apps through a literature database search, all of which have undergone an initial screening. After the exclusion of papers that were already reviews, not presenting apps or not focused on nutrition, not relevant or not developed for human subjects, 100 papers were selected for subsequent analyses that aimed at identifying the main treated conditions, outcome measures and functionalities implemented in the Apps.

RESULTS

Of the selected studies, 33 focus on specific diseases, 24 on obesity, 2 on malnutrition and 41 on other targets (e.g., weight/diet control). Type 2 diabetes is the most targeted disease, followed by gestational diabetes, hypertension, colorectal cancer and CVDs which all were targeted by more than one app. Most Apps include self-monitoring and coaching functionalities, educational content and artificial intelligence (AI) tools are slightly less common, whereas counseling, gamification and questionnaires are the least implemented. Body weight and calories/nutrients were the most common general outcome measures, while glycated hemoglobin (HbA1c) was the most common clinical outcome. No statistically significant differences in the effectiveness of the different functionalities were found.

CONCLUSION

The use of mobile technology to improve nutrition has been widely explored in the last years, especially for weight control and specific diseases like diabetes; however, other food-related conditions such as Irritable Bowel Diseases appear to be less targeted by newly developed smartphone apps and their related studies. All different kinds of functionalities appear to be equally effective, but further specific studies are needed to confirm the results.

The relationship between sleep quantity, sleep quality and weight loss in adults: A scoping review

Sleep is hypothesized to interact with weight gain and loss; however, modelling this relationship remains elusive. Poor sleep perpetuates a cascade of cardiovascular and metabolic consequences that may not only increase risk of adiposity, but also confound weight loss efforts. We conducted a scoping review to assess the research on sleep and weight loss interventions. We searched six databases for studies of behavioural weight loss interventions that included assessments of sleep in the general, non-clinical adult human population. Our synthesis focused on dimensions of Population, Intervention, Control, and Outcomes (PICO) to identify research and knowledge gaps. We identified 35 studies that fell into one of four categories: (a) sleep at baseline as a predictor of subsequent weight loss during an intervention, (b) sleep assessments after a history of successful weight loss, (c) concomitant changes in sleep associated with weight loss and (d) experimental manipulation of sleep and resulting weight loss. There was some evidence of improvements in sleep in response to weight-loss interventions; however, randomized controlled trials of weight loss interventions tended not to report improvements in sleep when compared to controls. We conclude that baseline sleep characteristics may predict weight loss in studies of dietary interventions and that sleep does not improve because of weight loss alone. Future studies should enrol large and diverse, normal, overweight and obese short sleepers in trials to assess the efficacy of sleep as a behavioural weight loss treatment.

Mobile health (m-health) smartphone interventions for adolescents and adults with overweight or obesity

BACKGROUND

Obesity is considered to be a risk factor for various diseases, and its incidence has tripled worldwide since 1975. In addition to potentially being at risk for adverse health outcomes, people with overweight or obesity are often stigmatised. Behaviour change interventions are increasingly delivered as mobile health (m-health) interventions, using smartphone apps and wearables. They are believed to support healthy behaviours at the individual level in a low-threshold manner.

OBJECTIVES

To assess the effects of integrated smartphone applications for adolescents and adults with overweight or obesity.

SEARCH METHODS

We searched CENTRAL, MEDLINE, PsycINFO, CINAHL, and LILACS, as well as the trials registers ClinicalTrials.gov and World Health Organization International Clinical Trials Registry Platform on 2 October 2023 (date of last search for all databases). We placed no restrictions on the language of publication.

SELECTION CRITERIA

Participants were adolescents and adults with overweight or obesity. Eligible interventions were integrated smartphone apps using at least two behaviour change techniques. The intervention could target physical activity, cardiorespiratory fitness, weight loss, healthy diet, or self-efficacy. Comparators included no or minimal intervention (NMI), a different smartphone app, personal coaching, or usual care. Eligible studies were randomised controlled trials of any duration with a follow-up of at least three months.

DATA COLLECTION AND ANALYSIS

We used standard Cochrane methodology and the RoB 2 tool. Important outcomes were physical activity, body mass index (BMI) and weight, health-related quality of life, self-efficacy, well-being, change in dietary behaviour, and adverse events. We focused on presenting studies with medium- (6 to < 12 months) and long-term (≥ 12 months) outcomes in our summary of findings table, following recommendations in the core outcome set for behavioural weight management interventions.

MAIN RESULTS

We included 18 studies with 2703 participants. Interventions lasted from 2 to 24 months. The mean BMI in adults ranged from 27 to 50, and the median BMI z-score in adolescents ranged from 2.2 to 2.5. Smartphone app versus no or minimal intervention Thirteen studies compared a smartphone app versus NMI in adults; no studies were available for adolescents. The comparator comprised minimal health advice, handouts, food diaries, smartphone apps unrelated to weight loss, and waiting list. Measures of physical activity: at 12 months' follow-up, a smartphone app compared to NMI probably reduces moderate to vigorous physical activity (MVPA) slightly (mean difference (MD) -28.9 min/week (95% confidence interval (CI) -85.9 to 28; 1 study, 650 participants; moderate-certainty evidence)). We are very uncertain about the results of estimated energy expenditure and cardiorespiratory fitness at eight months' follow-up. A smartphone app compared with NMI probably results in little to no difference in changes in total activity time at 12 months' follow-up and leisure time physical activity at 24 months' follow-up. Anthropometric measures: a smartphone app compared with NMI may reduce BMI (MD of BMI change -2.6 kg/m2, 95% CI -6 to 0.8; 2 studies, 146 participants; very low-certainty evidence) at six to eight months' follow-up, but the evidence is very uncertain. At 12 months' follow-up, a smartphone app probably resulted in little to no difference in BMI change (MD -0.1 kg/m2, 95% CI -0.4 to 0.3; 1 study; 650 participants; moderate-certainty evidence). A smartphone app compared with NMI may result in little to no difference in body weight change (MD -2.5 kg, 95% CI -6.8 to 1.7; 3 studies, 1044 participants; low-certainty evidence) at 12 months' follow-up. At 24 months' follow-up, a smartphone app probably resulted in little to no difference in body weight change (MD 0.7 kg, 95% CI -1.2 to 2.6; 1 study, 245 participants; moderate-certainty evidence). A smartphone app compared with NMI may result in little to no difference in self-efficacy for a physical activity score at eight months' follow-up, but the results are very uncertain. A smartphone app probably results in little to no difference in quality of life and well-being at 12 months (moderate-certainty evidence) and in little to no difference in various measures used to inform dietary behaviour at 12 and 24 months' follow-up. We are very uncertain about adverse events, which were only reported narratively in two studies (very low-certainty evidence). Smartphone app versus another smartphone app Two studies compared different versions of the same app in adults, showing no or minimal differences in outcomes. One study in adults compared two different apps (calorie counting versus ketogenic diet) and suggested a slight reduction in body weight at six months in favour of the ketogenic diet app. No studies were available for adolescents. Smartphone app versus personal coaching Only one study compared a smartphone app with personal coaching in adults, presenting data at three months. Two studies compared these interventions in adolescents. A smartphone app resulted in little to no difference in BMI z-score compared to personal coaching at six months' follow-up (MD 0, 95% CI -0.2 to 0.2; 1 study; 107 participants). Smartphone app versus usual care Only one study compared an app with usual care in adults but only reported data at three months on participant satisfaction. No studies were available for adolescents. We identified 34 ongoing studies.

AUTHORS' CONCLUSIONS

The available evidence is limited and does not demonstrate a clear benefit of smartphone applications as interventions for adolescents or adults with overweight or obesity. While the number of studies is growing, the evidence remains incomplete due to the high variability of the apps' features, content and components, which complicates direct comparisons and assessment of their effectiveness. Comparisons with either no or minimal intervention or personal coaching show minor effects, which are mostly not clinically significant. Minimal data for adolescents also warrants further research. Evidence is also scarce for low- and middle-income countries as well as for people with different socio-economic and cultural backgrounds. The 34 ongoing studies suggest sustained interest in the topic, with new evidence expected to emerge within the next two years. In practice, clinicians and healthcare practitioners should carefully consider the potential benefits, limitations, and evolving research when recommending smartphone apps to adolescents and adults with overweight or obesity.

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.

Effectiveness of holistic mobile health interventions on diet, and physical, and mental health outcomes: a systematic review and meta-analysis

Background

Good physical and mental health are essential for healthy ageing. Holistic mobile health (mHealth) interventions-including at least three components: physical activity, diet, and mental health-could support both physical and mental health and be scaled to the population level. This review aims to describe the characteristics of holistic mHealth interventions and their effects on related behavioural and health outcomes among adults from the general population.

Methods

In this systematic review and meta-analysis, we searched MEDLINE, Embase, Cochrane Central Register of Controlled Trials, PsycINFO, Scopus, China National Knowledge Infrastructure, and Google Scholar (first 200 records). The initial search covered January 1, 2011, to April 13, 2022, and an updated search extended from April 13, 2022 to August 30, 2023. Randomised controlled trials (RCTs) and non-randomised studies of interventions (NRSIs) were included if they (i) were delivered via mHealth technologies, (ii) included content on physical activity, diet, and mental health, and (iii) targeted adults (≥18 years old) from the general population or those at risk of non-communicable diseases (NCDs) or mental disorders. Studies were excluded if they targeted pregnant women (due to distinct physiological responses), individuals with pre-existing NCDs or mental disorders (to emphasise prevention), or primarily utilised web, email, or structured phone support (to focus on mobile technologies without exclusive human support). Data (summary data from published reports) extraction and risk-of-bias assessment were completed by two reviewers using a standard template and Cochrane risk-of-bias tools, respectively. Narrative syntheses were conducted for all studies, and random-effects models were used in the meta-analyses to estimate the pooled effect of interventions for outcomes with comparable data in the RCTs. The study was registered in PROSPERO, CRD42022315166.

Findings

After screening 5488 identified records, 34 studies (25 RCTs and 9 pre-post NRSIs) reported in 43 articles with 5691 participants (mean age 39 years, SD 12.5) were included. Most (91.2%, n = 31/34) were conducted in high-income countries. The median intervention duration was 3 months, and only 23.5% (n = 8/34) of studies reported follow-up data. Mobile applications, short-message services, and mobile device-compatible websites were the most common mHealth delivery modes; 47.1% (n = 16/34) studies used multiple mHealth delivery modes. Of 15 studies reporting on weight change, 9 showed significant reductions (6 targeted on individuals with overweight or obesity), and in 10 studies reporting perceived stress levels, 4 found significant reductions (all targeted on general adults). In the meta-analysis, holistic mHealth interventions were associated with significant weight loss (9 RCTs; mean difference -1.70 kg, 95% CI -2.45 to -0.95; I2 = 89.00%) and a significant reduction in perceived stress levels (6 RCTs; standardised mean difference [SMD] -0.32; 95% CI -0.52 to -0.12; I2 = 14.52%). There were no significant intervention effects on self-reported moderate-to-vigorous physical activity (5 RCTs; SMD 0.21; 95%CI -0.25 to 0.67; I2 = 74.28%) or diet quality scores (5 RCTs; SMD 0.21; 95%CI -0.47 to 0.65; I2 = 62.27%). All NRSIs were labelled as having a serious risk of bias overall; 56% (n = 14/25) of RCTs were classified as having some concerns, and the others as having a high risk of bias.

Interpretation

Findings from identified studies suggest that holistic mHealth interventions may aid reductions in weight and in perceived stress levels, with small to medium effect sizes. The observed effects on diet quality scores and self-reported moderate-to-vigorous physical activity were less clear and require more research. High-quality RCTs with longer follow-up durations are needed to provide more robust evidence. To promote population health, future research should focus on vulnerable populations and those in middle- and low-income countries. Optimal combinations of delivery modes and components to improve efficacy and sustain long-term effects should also be explored.

Funding

National Research Foundation, Prime Minister's Office, Singapore, under its Campus for Research Excellence and Technological Enterprise (CREATE) Programme and Physical Activity and Nutrition Determinants in Asia (PANDA) Research Programme.

Weight Management Interventions Provided by a Dietitian for Adults with Overweight or Obesity: An Evidence Analysis Center Systematic Review and Meta-Analysis

BACKGROUND

Obesity is associated with a multitude of comorbidities and considerable health care costs.

OBJECTIVE

The objective of this review was to examine the efficacy of weight management interventions provided by a registered dietitian or international equivalent (referred to as "dietitian").

METHODS

This systematic review and meta-analysis of randomized controlled trials (RCTs) examined the effect of weight management interventions provided by a dietitian, compared with usual care or no intervention, on several cardiometabolic outcomes and quality of life in adults with overweight or obesity. MEDLINE, Embase, PsycINFO, Cochrane CENTRAL, Cochrane Database of Systematic Reviews, and CINAHL databases were searched for eligible RCTs published between January 2008 and January 2021 in the English language. Meta-analyses were conducted using a random-effects model, publication bias was assessed using funnel plots and Egger's statistics, and heterogeneity was assessed by interpreting I2 values. Efficacy of intervention components, such as telehealth or group contacts, were explored in sub-group analyses. Version 2 of the risk-of-bias tool for RCTs was used to assess risk of bias. The Grading of Recommendations Assessment, Development and Evaluation method was used to determine certainty of evidence.

RESULTS

This systematic review included 62 RCTs. Compared with control conditions, weight management interventions provided by a dietitian resulted in improved body mass index (mean difference [MD] -1.5; 95% CI -1.74 to -1.26; moderate evidence certainty); percent weight loss (MD -4.01%; 95% CI -5.26% to -2.75%; high evidence certainty); waist circumference (MD -3.45 cm; 95% CI -4.39 to -2.51 cm; high evidence certainty); blood pressure (MD -3.04 mm Hg; 95% CI -5.10 to -0.98 mm Hg and MD -1.99 mm Hg; 95% CI -3.02 to -0.96 mm Hg for systolic blood pressure and diastolic blood pressure, respectively; moderate and low evidence certainty); and quality of life using the 36-Item Short Form Survey (MD 5.84; 95% CI 2.27 to 9.41 and 2.39; 95% CI 1.55 to 3.23 for physical and mental quality of life, respectively; low and moderate evidence certainty).

CONCLUSIONS

For adults with overweight or obesity, weight management interventions provided by a dietitian are efficacious for improving several examined cardiometabolic outcomes and quality of life.

Effectiveness of interactive technology-assisted interventions on promoting healthy food choices: a scoping review and meta-analysis

Making healthy food choices is crucial for health promotion and disease prevention. While there are an increasing number of technology-assisted interventions to promote healthy food choices, the underlying mechanism by which consumption behaviours and weight status change remains unclear. Our scoping review and meta-analysis of seventeen studies represents 3988 individuals with mean ages ranging from 19·2 to 54·2 years and mean BMI ranging from 24·5 kg/m2 to 35·6 kg/m2. Six main outcomes were identified namely weight, total calories, vegetables, fruits, healthy food, and fats and other food groups including sugar-sweetened beverages, saturated fats, snacks, wholegrains, Na, proteins, fibre, cholesterol, dairy products, carbohydrates, and takeout meals. Technology-assisted interventions were effective for weight loss (g = -0·29; 95 % CI -0·54, -0·04; I2 = 65·7 %, t = -2·83, P = 0·03) but not for promoting healthy food choices. This highlights the complexity in creating effective interactive technology-assisted interventions and understanding its mechanisms of influence and change. We also identified that there needs to be greater application of theory to inform the development of technology-assisted interventions in this area as new and improved interventions are being developed.

Behavioral Sleep Interventions and Cardiovascular Risk Factors: Systematic Review and Meta-analysis of Randomized Controlled Trials

BACKGROUND/OBJECTIVES

Chronic sleep disturbance has been consistently associated with cardiovascular disease. We sought to determine whether behavioral interventions to improve sleep have been associated with improvements in 4 common cardiovascular disease risk factors: hypertension, diabetes mellitus (DM), obesity, and smoking.

METHODS

Randomized controlled trials evaluating the prospective effect of behavioral sleep interventions on (a) blood pressure in participants with hypertension/prehypertension, (b) glycemic control in participants with DM/pre-DM, (c) anthropometrics in participants who were overweight/obese, and (d) smoking status in smokers were eligible. Where feasible, we undertook random-effects meta-analyses of standardized mean differences in cardiovascular disease risk factor change.

RESULTS

Overall, 3 trials met the inclusion criteria for blood pressure, 4 for glycemic control, 9 for overweight/obesity, and 2 for smoking. On meta-analysis, interventions with sleep as the sole behavioral target were associated with a significant reduction in hemoglobin A1c% (-0.84; 95% confidence interval [CI], -1.34 to -0.34), but not a significant reduction in systolic blood pressure (-0.18; 95% CI, -0.55 to 0.20) versus controls. In addition, any interventions with sleep as a behavioral target were associated with significant reductions in hemoglobin A1c% (-0.71; 95% CI, -1.01 to -0.42) and weight (-0.78; 95% CI, -1.11 to -0.45), but not systolic blood pressure (-0.72; 95% CI, -1.82 to 0.37). Trials evaluating smoking status were not amenable to meta-analysis.

CONCLUSION

Behavioral interventions to improve sleep were associated with improved glycemic control in patients with DM. It is also possible that these interventions improve weight in individuals who were overweight/obese. A low number of trials and small sample sizes indicate that further large, well-designed randomized controlled trials of interventions are warranted.

Digital Health Solutions for Weight Loss and Obesity: A Narrative Review

Personal exercise programmes have long been used and prescribed for weight loss and the improvement of quality of life in obese patients. While individualised programmes are usually the preferred option, they can be more costly and challenging to deliver in person. A move to digital programmes with a wider reach has commenced, and demand has increased due to the SARS-CoV-2 pandemic. In this review, we evaluate the current status of digital exercise programme delivery and its evolution over the past decade, with a focus on personalisation. We used specific keywords to search for articles that met our predetermined inclusion and exclusion criteria in order to provide valuable evidence and insights for future research. We identified 55 studies in total in four key areas of focus, from the more recent development of apps and personal digital assistants to web-based programmes and text or phone call interventions. In summary, we observed that apps may be useful for a low-intensity approach and can improve adherence to programmes through self-monitoring, but they are not always developed in an evidence-based manner. Engagement and adherence are important determinants of weight loss and subsequent weight maintenance. Generally, professional support is required to achieve weight loss goals.

The Efficacy of Mobile Applications for Weight Loss

Purpose of Review

A variety of mobile-based applications aimed at weight loss have become popular in recent years. This review describes the features and effectiveness of mobile weight loss apps.

Recent Findings

Overall, mobile apps can help patients lose weight either as well as or better than traditional paper-and-pencil weight loss interventions and often better than minimal intervention control groups. Mobile apps promote multiple strategies, including self-monitoring of diet, exercise, and weight, as well as social support and educational content. Significant variation exists in app types, which makes it difficult to conclude which features drive program effectiveness. Intervention success varies based on patients’ level of engagement with the app. There is a deficit of apps and app-based studies of older, less tech-savvy adults, ethnic/racial minorities, and low-income individuals, as well as longer-term studies.

Summary

Mobile apps can successfully help patients lose weight and represent a cost-effective, accessible alternative to intensive in-person weight loss programs. More research is needed into their long-term potential, especially for hard-to-reach populations.

Medical Nutrition Therapy Interventions Provided by Dietitians for Adult Overweight and Obesity Management: An Academy of Nutrition and Dietetics Evidence-Based Practice Guideline

Overweight and obesity affect most adults living in the United States and are causally linked to several adverse health outcomes. Registered dietitian nutritionists or international equivalents (dietitians) collaborate with each client and other health care professionals to meet client-centered goals, informed by the best available evidence, and translated through a lens of clinical expertise and client circumstances and preferences. Since the last iteration of the Academy of Nutrition and Dietetics guideline on adult weight management in 2014, considerable research has been conducted and circumstances confronting dietitians have evolved. Thus, updated guidance is needed. The objective of this evidence-based practice guideline is to provide recommendations for dietitians who deliver medical nutrition therapy behavioral interventions for adults (18 years and older) with overweight and obesity to improve cardiometabolic outcomes, quality of life, and weight outcomes, when appropriate for and desired by the client. Recommendations in this guideline highlight the importance of considering complex contributors to overweight and obesity and individualizing interventions to client-centered goals based on specific needs and preferences and shared decision making. The described recommendations have the potential to increase access to care and decrease costs through utilization of telehealth and group counseling as effective delivery methods, and to address other barriers to overweight and obesity management interventions. It is essential for dietitians to collaborate with clients and interprofessional health care teams to provide high-quality medical nutrition therapy interventions using the nutrition care process to promote attainment of client-centered outcomes for adults with overweight or obesity.

Efficacy of lifestyle medicine on sleep quality: A meta-analysis of randomized controlled trials

OBJECTIVES

Randomized controlled trials (RCTs) on the efficacy of multicomponent lifestyle medicine (LM) interventions for improving sleep quality have yielded inconsistent findings. This study marks the first meta-analysis to evaluate the efficacy of multicomponent LM interventions in improving sleep quality.

METHODS

We searched six online databases for RCTs that compared multicomponent LM interventions to an active or inactive control group in an adult population and assessed subjective sleep quality as a primary or secondary outcome using validated sleep measures at any post-intervention time-point.

RESULTS

A total of 23 RCTs with 26 comparisons involving 2534 participants were included in the meta-analysis. After excluding outliers, the analysis revealed that multicomponent LM interventions significantly improved sleep quality at immediate post-intervention (d = 0.45) and at short-term follow-up (i.e., <three months) (d = 0.50) relative to an inactive control group. Regarding the comparison with active control, no significant between-group difference was found at any time-point. No meta-analysis was conducted at the medium- and long-term follow-up due to insufficient data. Subgroup analyses supported that multicomponent LM interventions had a more clinically relevant effect on improving sleep quality in participants with clinical levels of sleep disturbance (d = 1.02) relative to an inactive control at immediate post-intervention assessment. There was no evidence of publication bias.

CONCLUSION

Our findings provided preliminary evidence that multicomponent LM interventions were efficacious in improving sleep quality relative to an inactive control at immediate post-intervention and at short-term follow-up. Additional high-quality RCTs targeting individuals with clinically significant sleep disturbance and long-term follow-up are warranted.

Effectiveness of Telemedicine for Reducing Cardiovascular Risk: A Systematic Review and Meta-Analysis

BACKGROUND

Cardiovascular diseases are the leading cause of death globally. There are six cardiovascular risk factors: diabetes, hypertension, hypercholesterolemia, overweight, sedentary lifestyle and smoking. Due to the low attendance of healthy people in the health system, the use of telemedicine can influence the acquisition of a heart-healthy lifestyle.

OBJECTIVE

this systematic review and meta-analysis aimed to determine the effectiveness of telemedicine and e-health in reducing cardiovascular risk.

METHODS

A systematic review and meta-analysis were carried out using the PubMed, Scopus, Cinhal and WOS databases. Randomized controlled studies between 2017 and 2022 in which telemedicine was used to reduce any of the risk factors were included. The methodological quality was assessed using the "PEDro" scale.

RESULTS

In total, 763 studies were obtained; after the review, 28 target articles were selected and finally grouped as follows: 13 studies on diabetes, six on hypertension, seven on obesity and two on physical activity. For all of the risk factors, a small effect of the intervention was seen.

CONCLUSIONS

although the current evidence is heterogeneous regarding the statistically significant effects of telemedicine on various cardiovascular risk factors, its clinical relevance is undeniable; therefore, its use is recommended as long as the necessary infrastructure exists.

Effects of Face-to-Face and eHealth Blended Interventions on Physical Activity, Diet, and Weight-Related Outcomes among Adults: A Systematic Review and Meta-Analysis

An increasing number of studies are blending face-to-face interventions and electronic health (eHealth) interventions to jointly promote physical activity (PA) and diet among people. However, a comprehensive summary of these studies is lacking. This study aimed to synthesize the characteristics of blended interventions and meta-analyze the effectiveness of blended interventions in promoting PA, diet, and weight-related outcomes among adults. Following the PRISMA guidelines, PubMed, SPORTDiscus, PsycINFO, Embase, and Web of Science were systematically searched to identify eligible articles according to a series of inclusion criteria. The search was limited to English language literature and publication dates between January 2002 and July 2022. Effect sizes were calculated as standardized mean difference (SMD) for three intervention outcomes (physical activity, healthy diet, and weight-related). Random effect models were used to calculate the effect sizes. A sensitivity analysis and publication bias tests were conducted. Of the 1561 identified studies, 17 were eligible for the systematic review. Studies varied in participants, intervention characteristics, and outcome measures. A total of 14 studies were included in the meta-analyses. There was evidence of no significant publication bias. The meta-analyses indicated that the blended intervention could lead to a significant increase in walking steps (p < 0.001), total PA level (p = 0.01), and diet quality (p = 0.044), a significant decrease in energy intake (p = 0.004), weight (p < 0.001), BMI (p < 0.001), and waist circumferences (p = 0.008), but had no influence on more moderate-to-vigorous physical activity (MVPA) or fruit and vegetable intake among adults, compared with a control group. The study findings showed that blended interventions achieve preliminary success in promoting PA, diet, and weight-related outcomes among adults. Future studies could improve the blended intervention design to achieve better intervention effectiveness.

The effect of wearable-delivered sleep interventions on sleep outcomes among adults: A systematic review and meta-analysis of randomized controlled trials

The aims of the review were to (i) evaluate the effectiveness of wearable-delivered sleep interventions on sleep outcomes among adults, and (ii) explore the effect of factors affecting total sleep time. Eight databases were searched to identify relevant studies in English from inception until December 23, 2021. The Cochrane Risk of Bias tool version 2.0 and Grading of Recommendations, Assessment, Development, and Evaluations (GRADE) criteria were used to assess the risk of bias and certainty of the evidence, respectively. Twenty randomized controlled trials (RCTs) were included, involving 1608 adults across nine countries. Wearable-delivered sleep interventions elicited significant improvement of 1.96 events/h for the oxygen desaturation index and 3.13 events/h for the respiratory distress index. Meta-analyses found that wearable-delivered sleep interventions significantly decreased sleep disturbance (Hedges' g [g] = -0.37, 95% confidence interval [CI]: -0.59, -0.15) and sleep-related impairment (g = -1.06, 95% CI: -1.99, -0.13) versus the comparators. The wearable-delivered sleep interventions may complement usual care to improve sleep outcomes. More rigorous RCTs with a long-term assessment in a wide range of populations are warranted.

Blended Care Interventions to Promote Physical Activity: A Systematic Review of Randomized Controlled Trials

Background

Blended care interventions combine therapeutic guidance with digital care. Current research results show the promising role of the blended care approach in clinical care. This new way of delivering health care could have the potential to effectively promote physical activity in different public health settings.

Objective

The aim of the systematic review is to investigate the varieties of intervention characteristics of blended care interventions to promote physical activity in terms of structure, behavior change goals, behavior change techniques, and effectiveness of blended care interventions compared to a control group.

Methods

We searched for randomized controlled trials published from 2000 to March 2021 in MEDLINE, CINAHL, Cochrane Central Register of Controlled Trials, SPORTDiscus, PsycINFO, and Web of Science according to the PRISMA guidelines. Risk of bias was assessed using the Cochrane Collaboration tool. Study characteristics, intervention characteristics, and outcome data were extracted. Furthermore, the effect size on the outcome of physical activity was examined or calculated.

Results

In total, the number of reports identified from the database searches was 4828. Of these, 25 studies were included in the review, with a total of 5923 study participants. Results indicated that the characteristics of blended care interventions showed a high heterogeneity. The combinations of therapist-guided interventions and digital interventions allowed the identification of specific subgroups, but they varied in length (range 8–52 weeks, SD 16.6), intensity, and the combination of the components. The most used combination of blended care interventions to promote physical activity was the combination of one-on-one meetings via telephone and Web-based interventions. Motivational models of behavior change were used most frequently as underlying theoretical foundations. Certain behavior change techniques were used consistently across the individual components, e.g., “problem solving” in the therapist-guided component and “feedback on behavior” in the digital component. Considering the effect size of blended care interventions compared with control groups, most studies showed a small effect.

Conclusions

It can be concluded that blended care interventions have potential to promote physical activity. In the future, further high-quality studies should investigate which type of blended care intervention is effective for which target group. Additionally, insights are required on which intervention characteristics are most effective, taking into account new evidence on behavior change.

Registration This systematic literature review was registered in PROSPERO (CRD42020188556).

Supplementary Information

The online version contains supplementary material available at 10.1186/s40798-022-00489-w.

The effect of weight loss interventions for obesity on fertility and pregnancy outcomes: A systematic review and meta-analysis

BACKGROUND

Weight loss could improve fertility, perhaps by reducing insulin resistance.

OBJECTIVES

To assess the effect of weight loss interventions on fertility in women with obesity not recruited because of known infertility.

SEARCH STRATEGY

Three databases during 1966-2020, trial registry.

SELECTION CRITERIA

Randomized controlled trials (RCTs) with a follow-up of 1 year or more, with a mean cohort BMI of 30 kg/m² or above.

DATA COLLECTION AND ANALYSIS

A systematic review and meta-analysis was conducted. The primary outcome was pregnancy. The secondary outcome was weight change.

MAIN RESULTS

A total of 27 RCTs (5938 women) were included. Weight loss interventions showed no statistically significant increase in pregnancies compared to control interventions (24 trials, 97 women with pregnancy; risk ratio [RR] 1.43, 95% confidence interval [CI] 0.91-2.23); weight change (mean difference [MD] -2.36 kg, 21 trials, 95% CI -3.17 to -1.55). Compared with low-fat diets, very-low-carbohydrate diets showed no statistically significant effect on women with pregnancy (three trials, 14 women with pregnancy; RR 1.37, 95% CI 0.49-3.84) or weight change (MD -0.32 kg, 95% CI -3.84 to 3.21).

CONCLUSIONS

Diet-based weight loss interventions for women with obesity not recruited because of infertility were effective at producing long-term weight loss. The effects on fertility were not statistically significant, but few trials provided data. Weight loss trials should routinely collect fertility outcomes.

SYSTEMATIC REVIEW REGISTRATION

PROSPERO CRD42017078819.

Long-Term Effectiveness of a Smartphone App and a Smart Band on Arterial Stiffness and Central Hemodynamic Parameters in a Population with Overweight and Obesity (Evident 3 Study): Randomised Controlled Trial

BACKGROUND

mHealth technologies could help to improve cardiovascular health; however, their effect on arterial stiffness and hemodynamic parameters has not been explored to date.

OBJECTIVE

To evaluate the effect of a mHealth intervention, at 3 and 12 months, on arterial stiffness and central hemodynamic parameters in a sedentary population with overweight and obesity.

METHODS

Randomised controlled clinical trial (Evident 3 study). 253 subjects were included: 127 in the intervention group (IG) and 126 in the control group (CG). The IG subjects were briefed on the use of the Evident 3 app and a smart band (Mi Band 2, Xiaomi) for 3 months to promote healthy lifestyles. All measurements were recorded in the baseline visit and at 3 and 12 months. The carotid-femoral pulse wave velocity (cfPWV) and the central hemodynamic parameters were measured using a SphigmoCor System^® device, whereas the brachial-ankle pulse wave velocity (baPWV) and the Cardio Ankle Vascular Index (CAVI) were measured using a VaSera VS-2000^® device.

RESULTS

Of the 253 subjects who attended the initial visit, 237 (93.7%) completed the visit at 3 months of the intervention, and 217 (85.3%) completed the visit at 12 months of the intervention. At 12 months, IG showed a decrease in peripheral augmentation index (PAIx) (-3.60; 95% CI -7.22 to -0.00) and ejection duration (ED) (-0.82; 95% CI -1.36 to -0.27), and an increase in subendocardial viability ratio (SEVR) (5.31; 95% CI 1.18 to 9.44). In CG, cfPWV decreased at 3 months (-0.28 m/s; 95% CI -0.54 to -0.02) and at 12 months (-0.30 m/s, 95% CI -0.54 to -0.05), central diastolic pressure (cDBP) decreased at 12 months (-1.64 mm/Hg; 95% CI -3.19 to -0.10). When comparing the groups we found no differences between any variables analyzed.

CONCLUSIONS

In sedentary adults with overweight or obesity, the multicomponent intervention (Smartphone app and an activity-tracking band) for 3 months did not modify arterial stiffness or the central hemodynamic parameters, with respect to the control group. However, at 12 months, CG presented a decrease of cfPWV and cDBP, whereas IG showed a decrease of PAIx and ED and an increase of SEVR.

Sustainability of Weight Loss Through Smartphone Apps: Systematic Review and Meta-analysis on Anthropometric, Metabolic, and Dietary Outcomes

Background

Evidence on the long-term effects of weight management smartphone apps on various weight-related outcomes remains scarce.

Objective

In this review, we aimed to examine the effects of smartphone apps on anthropometric, metabolic, and dietary outcomes at various time points.

Methods

Articles published from database inception to March 10, 2022 were searched, from 7 databases (Embase, CINAHL, PubMed, PsycINFO, Cochrane Library, Scopus, and Web of Science) using forward and backward citation tracking. All randomized controlled trials that reported weight change as an outcome in adults with overweight and obesity were included. We performed separate meta-analyses using random effects models for weight, waist circumference, high-density lipoprotein cholesterol, low-density lipoprotein cholesterol, blood glucose level, blood pressure, and total energy intake per day. Methodological quality was assessed using the Cochrane Risk of Bias tool.

Results

Based on our meta-analyses, weight loss was sustained between 3 and 12 months, with a peak of 2.18 kg at 3 months that tapered down to 1.63 kg at 12 months. We did not find significant benefits of weight loss on the secondary outcomes examined, except for a slight improvement in systolic blood pressure at 3 months. Most of the included studies covered app-based interventions that comprised of components beyond food logging, such as real-time diet and exercise self-monitoring, personalized and remote progress tracking, timely feedback provision, smart devices that synchronized activity and weight data to smartphones, and libraries of diet and physical activity ideas.

Conclusions

Smartphone weight loss apps are effective in initiating and sustaining weight loss between 3 and 12 months, but their effects are minimal in their current states. Future studies could consider the various aspects of the socioecological model. Conversational and dialectic components that simulate health coaches could be useful to enhance user engagement and outcome effectiveness.

Trial Registration

International Prospective Register of Systematic Reviews (PROSPERO) CRD42022329197; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=329197

Mental Health Symptom Reduction Using Digital Therapeutics Care Informed by Genomic SNPs and Gut Microbiome Signatures

Neuropsychiatric diseases and obesity are major components of morbidity and health care costs, with genetic, lifestyle, and gut microbiome factors linked to their etiology. Dietary and weight-loss interventions can help improve mental health, but there is conflicting evidence regarding their efficacy; and moreover, there is substantial interindividual heterogeneity that needs to be understood. We aimed to identify genetic and gut microbiome factors that explain interindividual differences in mental health improvement after a dietary and lifestyle intervention for weight loss. We recruited 369 individuals participating in Digbi Health’s personalized digital therapeutics care program and evaluated the association of 23 genetic scores, the abundance of 178 gut microbial genera, and 42 bacterial pathways with mental health. We studied the presence/absence of anxiety or depression, or sleep problems at baseline and improvement on anxiety, depression, and insomnia after losing at least 2% body weight. Participants lost on average 5.4% body weight and >95% reported improving mental health symptom intensity. There were statistically significant correlations between: (a) genetic scores with anxiety or depression at baseline, gut microbial functions with sleep problems at baseline, and (b) genetic scores and gut microbial taxa and functions with anxiety, depression, and insomnia improvement. Our results are concordant with previous findings, including the association between anxiety or depression at baseline with genetic scores for alcohol use disorder and major depressive disorder. As well, our results uncovered new associations in line with previous epidemiological literature. As evident from previous literature, we also observed associations of gut microbial signatures with mental health including short-chain fatty acids and bacterial neurotoxic metabolites specifically with depression. Our results also show that microbiome and genetic factors explain self-reported mental health status and improvement better than demographic variables independently. The genetic and microbiome factors identified in this study provide the basis for designing and personalizing dietary interventions to improve mental health.

The Effectiveness of Combining Nonmobile Interventions With the Use of Smartphone Apps With Various Features for Weight Loss: Systematic Review and Meta-analysis

Background

The effectiveness of smartphone apps for weight loss is limited by the diversity of interventions that accompany such apps. This research extends the scope of previous systematic reviews by including 2 subgroup analyses based on nonmobile interventions that accompanied smartphone use and human-based versus passive behavioral interventions.

Objective

The primary objective of this study is to systematically review and perform a meta-analysis of studies that evaluated the effectiveness of smartphone apps on weight loss in the context of other interventions combined with app use. The secondary objective is to measure the impact of different mobile app features on weight loss and mobile app adherence.

Methods

We conducted a systematic review and meta-analysis of relevant studies after an extensive search of the PubMed, MEDLINE, and EBSCO databases from inception to January 31, 2022. Gray literature, such as abstracts and conference proceedings, was included. Working independently, 2 investigators extracted the data from the articles, resolving disagreements by consensus. All randomized controlled trials that used smartphone apps in at least 1 arm for weight loss were included. The weight loss outcome was the change in weight from baseline to the 3- and 6-month periods for each arm. Net change estimates were pooled across the studies using random-effects models to compare the intervention group with the control group. The risk of bias was assessed independently by 2 authors using the Cochrane Collaboration tool for assessing the risk of bias in randomized trials.

Results

Overall, 34 studies were included that evaluated the use of a smartphone app in at least 1 arm. Compared with controls, the use of a smartphone app–based intervention showed a significant weight loss of –1.99 kg (95% CI –2.19 to –1.79 kg; I²=81%) at 3 months and –2.80 kg (95% CI –3.03 to –2.56 kg; I²=91%) at 6 months. In the subgroup analysis, based on the various intervention components that were added to the mobile app, the combination of the mobile app, tracker, and behavioral interventions showed a statistically significant weight loss of –2.09 kg (95% CI –2.32 to –1.86 kg; I²=91%) and –3.77 kg (95% CI –4.05 to –3.49 kg; I²=90%) at 3 and 6 months, respectively. When a behavioral intervention was present, only the combination of the mobile app with intensive behavior coaching or feedback by a human coach showed a statistically significant weight loss of –2.03 kg (95% CI –2.80 to –1.26 kg; I²=83%) and –2.63 kg (95% CI –2.97 to –2.29 kg; I²=91%) at 3 and 6 months, respectively. Neither the type nor the number of mobile app features was associated with weight loss.

Conclusions

Smartphone apps have a role in weight loss management. Nevertheless, the human-based behavioral component remained key to higher weight loss results.

The role of body mass index, healthy eating-related apps and educational activities on eating motives and behaviours among women during the COVID-19 pandemic: A cross sectional study

The COVID-19 related lockdown made it much more difficult for people to control their eating behaviours and body weight with the methods and means they had used before. This is reflected in reports that show that eating behaviours deteriorated significantly during the COVID-19 pandemic (including in Poland). Therefore, it is important to determine what factors may be conducive to healthy eating behaviours among people with different BMI. As previous studies show, the use of healthy eating related-apps and training programs may be a protective factor against the development of unhealthy eating behaviours. Therefore, it is worth checking whether their action will be a protective factor during COVID-19. The aim of this cross sectional study was to analyse whether the current use of healthy eating-related apps and previous participation in training in this field (educational activities) as well as body mass index may play a role in eating motives and behaviours among women during COVID-19. Our final sample included 1,447 women (age: M = 31.34 ± 11.05). Participants completed: the Eating Motivation Survey, the Emotional Overeating Questionnaire, the Mindful Eating Questionnaire, socio-demographic survey and questions about healthy eating-related apps and training (educational activities). Referring to the selected significant results, our study shows that during COVID-19, the use of healthy eating-related apps alone, as well as the use of apps and prior training participation promote healthy eating motives and behaviours. It suggests that promoting the use of healthy eating applications and the acquisition of knowledge and skills in this field could be one way of shaping resources that can be effectively used to deal with crisis situations.

A pilot randomized trial of simplified versus standard calorie dietary self-monitoring in a mobile weight loss intervention

OBJECTIVE

This study tested the efficacy of a lower-burden, simplified dietary self-monitoring approach compared with a standard calorie monitoring approach for self-monitoring adherence and weight loss in a mobile-delivered behavioral weight loss intervention.

METHODS

Participants (n = 72) with overweight or obesity who had children 2 to 12 years of age living in the home were randomly assigned to a group that used simplified dietary self-monitoring of high-calorie foods (Simplified) or a group that tracked calories (Standard). Both groups received a wireless scale, Fitbit trackers, and a 6-month intervention delivered via a smartphone application with lessons, text messages, and weekly personalized feedback messages.

RESULTS

Percentage weight loss at 6 months was 5.7% (95% CI: -8.3% to -3.2%) in the Standard group and 4.0% (95% CI: -5.7% to -2.3%) in the Simplified group, which was not significantly different. Similar proportions reached 5% weight loss at 6 months (43.2% in Standard and 42.9% in Simplified). There were no differences in number of dietary tracking days or change in average daily caloric intake between groups.

CONCLUSIONS

Two mobile-delivered weight loss interventions produced clinically meaningful levels of weight loss at 6 months, with no differences in dietary tracking adherence or dietary intake. The results suggest that simplified monitoring of high-calorie foods could be a promising alternative to calorie monitoring.

Long-term Effectiveness of a Smartphone App Combined With a Smart Band on Weight Loss, Physical Activity, and Caloric Intake in a Population With Overweight and Obesity (Evident 3 Study): Randomized Controlled Trial

BACKGROUND

Multicomponent mobile health approaches can improve lifestyle intervention results, although little is known about their long-term effectiveness.

OBJECTIVE

This study aims to evaluate the long-term effectiveness (12 months) of a multicomponent mobile health intervention-combining a smartphone app, an activity tracker wristband, and brief counseling, compared with a brief counseling group only-on weight loss and improving body composition, physical activity, and caloric intake in Spanish sedentary adults with overweight or obesity.

METHODS

We conducted a randomized controlled, multicenter clinical trial (Evident 3). A total of 650 participants were recruited from 5 primary care centers, with 318 participants in the intervention group (IG) and 332 in the control group (CG). All participants were briefly counseled about a healthy diet and physical activity at the baseline visit. For the 3-month intervention period, the IG received training to use the app to promote healthy lifestyles and the smart band (Mi Band 2, Xiaomi). All measurements were performed at baseline and at 3 and 12 months. Physical activity was measured using the International Physical Activity Questionnaire-Short Form. Nutritional habits were assessed using the Food Frequency Questionnaire and Adherence to Mediterranean diet questionnaire.

RESULTS

Of the 650 participants included, 563 (86.6%) completed the 3-month visit and 443 (68.2%) completed the 12-month visit. After 12 months, the IG showed net differences in weight (-0.26, 95% CI -1.21 to 0.70 kg; P=.02), BMI (-0.06, 95% CI -0.41 to 0.28 points; P=.01), waist-height ratio (-0.25, 95% CI -0.94 to 0.44; P=.03), body adiposity index (-0.33, 95% CI -0.77 to 0.11; P=.03), waist circumference (-0.48, 95% CI -1.62 to 0.66 cm, P=.04) and hip circumference (-0.69, 95% CI -1.62 to 0.25 cm; P=.03). Both groups lowered daily caloric intake and increased adherence to the Mediterranean diet, with no differences between the groups. The IG increased light physical activity time (32.6, 95% CI -30.3 to 95.04 min/week; P=.02) compared with the CG. Analyses by subgroup showed changes in body composition variables in women, people aged >50 years, and married people.

CONCLUSIONS

The low-intensity intervention of the Evident 3 study showed, in the IG, benefits in weight loss, some body composition variables, and time spent in light physical activity compared with the CG at 3 months, but once the devices were collected, the downward trend was not maintained at the 12-month follow-up. No differences in nutritional outcomes were observed between the groups.

TRIAL REGISTRATION

ClinicalTrials.gov NCT03175614; https://clinicaltrials.gov/ct2/show/NCT03175614.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

RR2-10.1097/MD.0000000000009633.

Implementation of telerehabilitation in Austrian outpatient physiotherapy – A qualitative study / Implementierung von Telerehabilitation in der ambulanten Physiotherapie in Österreich – Eine qualitative Studie

Background

New technologies, for example, telerehabilitation (TR) tools, can support physiotherapists’ work. Even though studies have demonstrated their potential, TR is not yet fully implemented in Austrian outpatient physiotherapy. As a result of the Coronavirus pandemic and the associated lockdowns, physiotherapists in Austria were confronted with the challenge of offering therapies without physical contact. This study aims to investigate opinions and experiences of physiotherapists in Austria regarding TR and its implementation in different clinical fields.

Methods

A qualitative research design with expert interviews and a focus group discussion were conducted. Data were analysed using content analysis. The categories were formed following a deductive-inductive approach.

Results

The interview partners considered opportunities for using synchronous TR in internal medicine as well as orthopaedics and traumatology, especially in later, exercise-dominated stages. In addition, using TR can be supportive for patient education. In the field of neurology, synchronous TR is viewed with some criticism, especially when used for people with severe neuropsychological disorders. Asynchronous TR is considered useful across all disciplines and could support physical therapy from the first therapy session and throughout the treatment. Important questions regarding liability, billing, or data protection still need to be clarified. Interdisciplinary approaches in TR should also be pursued to improve care.

Conclusion

The use of asynchronous TR in addition to regular physiotherapy is seen as promising in all clinical fields. In general, when implementing TR, the needs and requirements of different fields should be considered. Moreover, various framework conditions still need to be clarified for further implementation of TR.

A systematic review of the use of dietary self-monitoring in behavioural weight loss interventions: delivery, intensity and effectiveness

OBJECTIVE

To identify dietary self-monitoring implementation strategies in behavioural weight loss interventions.

DESIGN

We conducted a systematic review of eight databases and examined fifty-nine weight loss intervention studies targeting adults with overweight/obesity that used dietary self-monitoring.

SETTING

NA.

PARTICIPANTS

NA.

RESULTS

We identified self-monitoring implementation characteristics, effectiveness of interventions in supporting weight loss and examined weight loss outcomes among higher and lower intensity dietary self-monitoring protocols. Included studies utilised diverse self-monitoring formats (paper, website, mobile app, phone) and intensity levels (recording all intake or only certain aspects of diet). We found the majority of studies using high- and low-intensity self-monitoring strategies demonstrated statistically significant weight loss in intervention groups compared with control groups.

CONCLUSIONS

Based on our findings, lower and higher intensity dietary self-monitoring may support weight loss, but variability in adherence measures and limited analysis of weight loss relative to self-monitoring usage limits our understanding of how these methods compare with each other.

Efficacy of a Multi-Component m-Health Diet, Physical Activity, and Sleep Intervention on Dietary Intake in Adults with Overweight and Obesity: A Randomised Controlled Trial

This three-arm randomised controlled trial evaluated whether (1) a multi-component weight loss intervention targeting diet, physical activity (PA), and sleep was effective at improving dietary intake over six months and 12 months, compared with a control, and (2) the enhanced diet, PA, and sleep intervention was more effective at improving dietary intake than the traditional diet and PA intervention. A total of 116 adults (70% female, 44.5 years, BMI 31.7 kg/m²) were randomised to either traditional diet and PA intervention; enhanced diet, PA, and sleep intervention; or wait-list control. To examine between-group differences, intervention groups were pooled and compared with the control. Then, the two intervention groups were compared. At six months, the pooled intervention group consumed 1011 fewer kilojoules/day (95% CI −1922, −101), less sodium (−313.2 mg/day; 95% CI −591.3, −35.0), and higher %EI from fruit (+2.1%EI; 95% CI 0.1, 4.1) than the controls. There were no differences in intake between the enhanced and traditional groups at six months. At 12 months, the pooled intervention and control groups reported no significant differences. However, compared to the traditional group, the enhanced reported higher %EI from nutrient-dense foods (+7.4%EI; 95% CI 1.3, 13.5) and protein (+2.4%EI; 95% CI 0.1, 4.6), and reduced %EI from fried/takeaway foods (−3.6%EI; 95% CI −6.5, −0.7), baked sweet products (−2.0%EI; 95% CI −3.6, −0.4), and packaged snacks (−1.1%EI; 95% CI −2.2, −0.3). This weight loss intervention reduced total energy and sodium intakes as well as increased fruit intake in adults at six months. The enhanced intervention group reported improved dietary intake relative to the traditional group at 12 months.

Use of Fitbit Devices in Physical Activity Intervention Studies Across the Life Course: Narrative Review

BACKGROUND

Commercial off-the-shelf activity trackers (eg, Fitbit) allow users to self-monitor their daily physical activity (PA), including the number of steps, type of PA, amount of sleep, and other features. Fitbits have been used as both measurement and intervention tools. However, it is not clear how they are being incorporated into PA intervention studies, and their use in specific age groups across the life course is not well understood.

OBJECTIVE

This narrative review aims to characterize how PA intervention studies across the life course use Fitbit devices by synthesizing and summarizing information on device selection, intended use (intervention vs measurement tool), participant wear instructions, rates of adherence to device wear, strategies used to boost adherence, and the complementary use of other PA measures. This review provides intervention scientists with a synthesis of information that may inform future trials involving Fitbit devices.

METHODS

We conducted a search of the Fitabase Fitbit Research Library, a database of studies published between 2012 and 2018. Of the 682 studies available on the Fitabase research library, 60 interventions met the eligibility criteria and were included in this review. A supplemental search in PubMed resulted in the inclusion of 15 additional articles published between 2019 and 2020. A total of 75 articles were reviewed, which represented interventions conducted in childhood; adolescence; and early, middle, and older adulthood.

RESULTS

There was considerable heterogeneity in the use of Fitbit within and between developmental stages. Interventions for adults typically required longer wear periods, whereas studies on children and adolescents tended to have more limited device wear periods. Most studies used developmentally appropriate behavior change techniques and device wear instructions. Regardless of the developmental stage and intended Fitbit use (ie, measurement vs intervention tool), the most common strategies used to enhance wear time included sending participants reminders through texts or emails and asking participants to log their steps or synchronize their Fitbit data daily. The rates of adherence to the wear time criteria were reported using varying metrics. Most studies supplemented the use of Fitbit with additional objective or self-reported measures for PA.

CONCLUSIONS

Overall, the heterogeneity in Fitbit use across PA intervention studies reflects its relative novelty in the field of research. As the use of monitoring devices continues to expand in PA research, the lack of uniformity in study protocols and metrics of reported measures represents a major issue for comparability purposes. There is a need for increased transparency in the prospective registration of PA intervention studies. Researchers need to provide a clear rationale for the use of several PA measures and specify the source of their main PA outcome and how additional measures will be used in the context of Fitbit-based interventions.

Behavioural mediators of reduced energy intake in a physical activity, diet, and sleep behaviour weight loss intervention in adults

Reduced energy intake is a major driver of weight loss and evidence suggests that physical activity, dietary, and sleep behaviours interact to influence energy intake. Energy restriction can be challenging to sustain. Therefore to improve intervention efficacy, evaluation of how changes in physical activity, diet, and sleep behaviours mediate reduced energy intake in adults with overweight/obesity who participated in a six-month multiple-behaviour-change weight loss intervention was undertaken. This was a secondary analysis of a 3-arm randomised controlled trial. Adults with body mass index (BMI) 25-40 kg/m² were randomised to either: a physical activity and diet intervention; physical activity, diet, and sleep intervention; or wait-list control. Physical activity, dietary intake, and sleep was measured at baseline and six-months using validated measures. The two intervention groups were pooled and compared to the control. Structural equation modelling was used to estimate the mediated effects (AB Coefficient) of the intervention on total energy intake. One hundred and sixteen adults (70% female, 44.5y, BMI 31.7 kg/m²) were enrolled and 70% (n = 81) completed the six-month assessment. The significant intervention effect on energy intake at six-months (-1011 kJ/day, 95% CI -1922, -101) was partially mediated by reduced fat intake (AB = -761.12, 95% CI -1564.25, -53.74) and reduced consumption of energy-dense, nutrient-poor foods (AB = -576.19, 95% CI -1189.23, -97.26). In this study, reducing fat intake and consumption of energy-dense, nutrient-poor foods was an effective strategy for reducing daily energy intake in adults with overweight/obesity at six-months. These strategies should be explicitly targeted in future weight loss interventions.

Effect of a physical activity and sleep m-health intervention on a composite activity-sleep behaviour score and mental health: a mediation analysis of two randomised controlled trials

BACKGROUND

To examine if a composite activity-sleep behaviour index (ASI) mediates the effects of a combined physical activity and sleep intervention on symptoms of depression, anxiety, or stress, quality of life (QOL), energy and fatigue in adults.

METHODS

This analysis used data pooled from two studies: Synergy and Refresh. Synergy: Physically inactive adults (18-65 years) who reported poor sleep quality were recruited for a two-arm Randomised Controlled Trial (RCT) (Physical Activity and Sleep Health (PAS; n = 80), or Wait-list Control (CON; n = 80) groups). Refresh: Physically inactive adults (40-65 years) who reported poor sleep quality were recruited for a three-arm RCT (PAS (n = 110), Sleep Health-Only (SO; n = 110) or CON (n = 55) groups). The SO group was omitted from this study. The PAS groups received a pedometer, and accessed a smartphone/tablet "app" using behaviour change strategies (e.g., self-monitoring, goal setting, action planning), with additional email/SMS support. The ASI score comprised self-reported moderate-to-vigorous-intensity physical activity, resistance training, sitting time, sleep duration, efficiency, quality and timing. Outcomes were assessed using DASS-21 (depression, anxiety, stress), SF-12 (QOL-physical, QOL-mental) and SF-36 (Energy & Fatigue). Assessments were conducted at baseline, 3 months (primary time-point), and 6 months. Mediation effects were examined using Structural Equation Modelling and the product of coefficients approach (AB), with significance set at 0.05.

RESULTS

At 3 months there were no direct intervention effects on mental health, QOL or energy and fatigue (all p > 0.05), and the intervention significantly improved the ASI (all p < 0.05). A more favourable ASI score was associated with improved symptoms of depression, anxiety, stress, QOL-mental and of energy and fatigue (all p < 0.05). The intervention effects on symptoms of depression ([AB; 95%CI] -0.31; - 0.60,-0.11), anxiety (- 0.11; - 0.27,-0.01), stress (- 0.37; - 0.65,-0.174), QOL-mental (0.53; 0.22, 1.01) and ratings of energy and fatigue (0.85; 0.33, 1.63) were mediated by ASI. At 6 months the magnitude of association was larger although the overall pattern of results remained similar.

CONCLUSIONS

Improvements in the overall physical activity and sleep behaviours of adults partially mediated the intervention effects on mental health and quality of life outcomes. This highlights the potential benefit of improving the overall pattern of physical activity and sleep on these outcomes.

TRIAL REGISTRATION

Australian New Zealand Clinical Trial Registry: ACTRN12617000680369 ; ACTRN12617000376347 . Universal Trial number: U1111-1194-2680; U1111-1186-6588. Human Research Ethics Committee Approval: H-2016-0267; H-2016-0181.