A brief behavioural intervention to promote regular self-weighing to prevent weight regain after weight loss: a RCT

Effectiveness of an Artificial Intelligence-Assisted App for Improving Eating Behaviors: Mixed Methods Evaluation

BACKGROUND

A plethora of weight management apps are available, but many individuals, especially those living with overweight and obesity, still struggle to achieve adequate weight loss. An emerging area in weight management is the support for one's self-regulation over momentary eating impulses.

OBJECTIVE

This study aims to examine the feasibility and effectiveness of a novel artificial intelligence-assisted weight management app in improving eating behaviors in a Southeast Asian cohort.

METHODS

A single-group pretest-posttest study was conducted. Participants completed the 1-week run-in period of a 12-week app-based weight management program called the Eating Trigger-Response Inhibition Program (eTRIP). This self-monitoring system was built upon 3 main components, namely, (1) chatbot-based check-ins on eating lapse triggers, (2) food-based computer vision image recognition (system built based on local food items), and (3) automated time-based nudges and meal stopwatch. At every mealtime, participants were prompted to take a picture of their food items, which were identified by a computer vision image recognition technology, thereby triggering a set of chatbot-initiated questions on eating triggers such as who the users were eating with. Paired 2-sided t tests were used to compare the differences in the psychobehavioral constructs before and after the 7-day program, including overeating habits, snacking habits, consideration of future consequences, self-regulation of eating behaviors, anxiety, depression, and physical activity. Qualitative feedback were analyzed by content analysis according to 4 steps, namely, decontextualization, recontextualization, categorization, and compilation.

RESULTS

The mean age, self-reported BMI, and waist circumference of the participants were 31.25 (SD 9.98) years, 28.86 (SD 7.02) kg/m2, and 92.60 (SD 18.24) cm, respectively. There were significant improvements in all the 7 psychobehavioral constructs, except for anxiety. After adjusting for multiple comparisons, statistically significant improvements were found for overeating habits (mean -0.32, SD 1.16; P<.001), snacking habits (mean -0.22, SD 1.12; P<.002), self-regulation of eating behavior (mean 0.08, SD 0.49; P=.007), depression (mean -0.12, SD 0.74; P=.007), and physical activity (mean 1288.60, SD 3055.20 metabolic equivalent task-min/day; P<.001). Forty-one participants reported skipping at least 1 meal (ie, breakfast, lunch, or dinner), summing to 578 (67.1%) of the 862 meals skipped. Of the 230 participants, 80 (34.8%) provided textual feedback that indicated satisfactory user experience with eTRIP. Four themes emerged, namely, (1) becoming more mindful of self-monitoring, (2) personalized reminders with prompts and chatbot, (3) food logging with image recognition, and (4) engaging with a simple, easy, and appealing user interface. The attrition rate was 8.4% (21/251).

CONCLUSIONS

eTRIP is a feasible and effective weight management program to be tested in a larger population for its effectiveness and sustainability as a personalized weight management program for people with overweight and obesity.

TRIAL REGISTRATION

ClinicalTrials.gov NCT04833803; https://classic.clinicaltrials.gov/ct2/show/NCT04833803.

A low-burden, self-weighing intervention to prevent weight gain in adults with obesity who do not enroll in comprehensive treatment

Background

For individuals who are eligible but unlikely to join comprehensive weight loss programs, a low burden self-weighing intervention may be a more acceptable approach to weight management.

Methods

This was a single-arm feasibility trial of a 12-month self-weighing intervention. Participants were healthcare patients with a BMI ≥25 kg/m2 with a weight-related comorbidity or a BMI >30 kg/m2 who reported lack of interest in joining a comprehensive weight loss program, or did not enroll in a comprehensive program after being provided program information. In the self-weighing intervention, participants were asked to weigh themselves daily on a cellular connected scale and were sent text messages every other week with tailored weight change feedback, including messages encouraging use of comprehensive programs if weight gain occurred.

Results

Of 86 eligible patients, 39 enrolled (45.3%) in the self-weighing intervention. Self-weighing occurred on average 4.6 days/week (SD = 1.4). At 12 months, 12 participants (30.8%) lost ≥3% baseline weight, 11 (28.2%) experienced weight stability (±3% baseline), 6 (15.4%) gained ≥3% of baseline weight, and 10 (25.6%) did not have available weight data to evaluate. Three participants reported joining a weight loss program during the intervention (7.7%). Participants reported high intervention satisfaction in quantitative ratings (4.1 of 5), and qualitative interviews identified areas of satisfaction (e.g., timing and content of text messages) and areas for improvement (e.g., increasing personalization of text messages).

Conclusion

A low-burden self-weighing intervention can reach adults with overweight/obesity who would be unlikely to engage in comprehensive weight loss programs; the efficacy of this intervention for preventing weight gain should be further evaluated in a randomized trial.

The Importance of Nutrition in Menopause and Perimenopause-A Review

Menopause is associated with an increased prevalence of obesity, metabolic syndrome, cardiovascular diseases, and osteoporosis. These diseases and unfavorable laboratory values, which are characteristic of this period in women, can be significantly improved by eliminating and reducing dietary risk factors. Changing dietary habits during perimenopause is most effectively achieved through nutrition counseling and intervention. To reduce the risk factors of all these diseases, and in the case of an already existing disease, dietary therapy led by a dietitian should be an integral part of the treatment. The following review summarizes the recommendations for a balanced diet and fluid intake, the dietary prevention of cardiovascular diseases, the role of sleep, and the key preventive nutrients in menopause, such as vitamin D, calcium, vitamin C, B vitamins, and protein intake. In summary, during the period of perimenopause and menopause, many lifestyle factors can reduce the risk of developing all the diseases (cardiovascular disease, insulin resistance, type 2 diabetes mellitus, osteoporosis, and tumors) and symptoms characteristic of this period.

Are there inequalities in the attendance and effectiveness of behavioural weight management interventions for adults in the UK? Protocol for an individual participant data (IPD) meta-analysis

INTRODUCTION

It is important to identify whether behavioural weight management interventions work well across different groups in the population so health inequalities in obesity are not widened. Previous systematic reviews of inequalities in the attendance and effectiveness of behavioural weight management interventions have been limited because few trials report relevant analyses and heterogeneity in the categorisation of inequality characteristics prevents meta-analysis. An individual participant data meta-analysis (IPD-MA) allows us to reanalyse all trials with available data in a uniform way. We aim to conduct an IPD meta-analysis of UK randomised controlled trials to examine whether there are inequalities in the attendance and effectiveness of behavioural weight interventions.

METHODS AND ANALYSIS

In a recently published systematic review, we identified 17 UK-based randomised controlled trials of primary care-relevant behavioural interventions, conducted in adults living with overweight or obesity and reporting weight outcomes at baseline and 1-year follow-up. The corresponding author of each trial will be invited to contribute data to the IPD-MA. The outcomes of interest are weight at 12-months and intervention attendance (number of sessions offered vs number of sessions attended). We will primarily consider whether there is an interaction between intervention group and characteristics where inequalities occur, such as by gender/sex, socioeconomic status or age. The IPD-MA will be conducted in line with the Preferred Reporting Items for Systematic Reviews and Meta-analyses of IPD guidelines.

ETHICS AND DISSEMINATION

No further ethical approval was required as ethical approval for each individual study was obtained by the original trial investigators from appropriate ethics committees. The completed IPD-MA will be disseminated at conferences, in a peer-reviewed journal and contribute to the lead author's PhD thesis. Investigators of each individual study included in the final IPD-MA will be invited to collaborate on any publications that arise from the project.

A systematic review of inequalities in the uptake of, adherence to, and effectiveness of behavioral weight management interventions in adults

The extent to which behavioral weight management interventions affect health inequalities is uncertain, as is whether trials of these interventions directly consider inequalities. We conducted a systematic review, synthesizing evidence on how different aspects of inequality impact uptake, adherence, and effectiveness in trials of behavioral weight management interventions. We included (cluster-) randomized controlled trials of primary care-applicable behavioral weight management interventions in adults with overweight or obesity published prior to March 2020. Data about trial uptake, intervention adherence, attrition, and weight change by PROGRESS-Plus criteria (place of residence, race/ethnicity, occupation, gender, religion, education, socioeconomic status, social capital, plus other discriminating factors) were extracted. Data were synthesized narratively and summarized in harvest plots. We identified 91 behavioral weight loss interventions and 12 behavioral weight loss maintenance interventions. Fifty-six of the 103 trials considered inequalities in relation to at least one of intervention or trial uptake (n = 15), intervention adherence (n = 15), trial attrition (n = 32), or weight outcome (n = 34). Most trials found no inequalities gradient. If a gradient was observed for trial uptake, intervention adherence, and trial attrition, those considered "more advantaged" did best. Alternative methods of data synthesis that enable data to be pooled and increase statistical power may enhance understanding of inequalities in behavioral weight management interventions.

Recruitment, consent and retention of participants in randomised controlled trials: a review of trials published in the National Institute for Health Research (NIHR) Journals Library (1997-2020)

OBJECTIVES

To review the consent, recruitment and retention rates for randomised controlled trials (RCTs) funded by the UK's National Institute for Health Research (NIHR) and published in the online NIHR Journals Library between January 1997 and December 2020.

DESIGN

Comprehensive review.

SETTING

RCTs funded by the NIHR and published in the NIHR Journals Library.

DATA EXTRACTION

Information relating to the trial characteristics, sample size, recruitment and retention.

PRIMARY AND SECONDARY OUTCOME MEASURES

The primary outcome was the recruitment rate (number of participants recruited per centre per month). Secondary outcomes were the target sample size and whether it was achieved; consent rates (percentage of eligible participants who consented and were randomised) and retention rates (percentage of randomised participants retained and assessed with valid primary outcome data).

RESULTS

This review identified 388 individual RCTs from 379 reports in the NIHR Journals Library. The final recruitment target sample size was achieved in 63% (245/388) of the RCTs. The original recruitment target was revised in 30% (118/388) of trials (downwards in 67% (79/118)). The median recruitment rate (participants per centre per month) was found to be 0.95 (IQR: 0.42-2.60); the median consent rate was 72% (IQR: 50%-88%) and the median retention rate was estimated at 88% (IQR: 80%-97%).

CONCLUSIONS

There is considerable variation in the consent, recruitment and retention rates in publicly funded RCTs. Although the majority of (6 out of 10) trials in this review achieved their final target sample; 3 out of 10 trials revised their original target sample size (downwards in 7 out of 10 trials). Investigators should bear this in mind at the planning stage of their study and not be overly optimistic about their recruitment projections.

Association between characteristics of behavioural weight loss programmes and weight change after programme end: systematic review and meta-analysis

OBJECTIVE

To determine if the characteristics of behavioural weight loss programmes influence the rate of change in weight after the end of the programme.

DESIGN

Systematic review and meta-analysis.

DATA SOURCES

Trial registries, 11 electronic databases, and forward citation searching (from database inception; latest search December 2019). Randomised trials of behavioural weight loss programmes in adults with overweight or obesity, reporting outcomes at ≥12 months, including at the end of the programme and after the end of the programme.

REVIEW METHODS

Studies were screened by two independent reviewers with discrepancies resolved by discussion. 5% of the studies identified in the searches met the inclusion criteria. One reviewer extracted the data and a second reviewer checked the data. Risk of bias was assessed with Cochrane's risk of bias tool (version 1). The rate of change in weight was calculated (kg/month; converted to kg/year for interpretability) after the end of the programme in the intervention versus control groups by a mixed model with a random intercept. Associations between the rate of change in weight and prespecified variables were tested.

RESULTS

Data were analysed from 249 trials (n=59 081) with a mean length of follow-up of two years (longest 30 years). 56% of studies (n=140) had an unclear risk of bias, 21% (n=52) a low risk, and 23% (n=57) a high risk of bias. Regain in weight was faster in the intervention versus the no intervention control groups (0.12-0.32 kg/year) but the difference between groups was maintained for at least five years. Each kilogram of weight lost at the end of the programme was associated with faster regain in weight at a rate of 0.13-0.19 kg/year. Financial incentives for weight loss were associated with faster regain in weight at a rate of 1-1.5 kg/year. Compared with programmes with no meal replacements, interventions involving partial meal replacements were associated with faster regain in weight but not after adjustment for weight loss during the programme. Access to the programme outside of the study was associated with slower regain in weight. Programmes where the intensity of the interaction reduced gradually were also associated with slower regain in weight in the multivariable analysis, although the point estimate suggested that the association was small. Other characteristics did not explain the heterogeneity in regain in weight.

CONCLUSION

Faster regain in weight after weight loss was associated with greater initial weight loss, but greater initial weight loss was still associated with reduced weight for at least five years after the end of the programme, after which data were limited. Continued availability of the programme to participants outside of the study predicted a slower regain in weight, and provision of financial incentives predicted faster regain in weight; no other clear associations were found.

STUDY REGISTRATION

PROSPERO CRD42018105744.

The potential of artificial intelligence in enhancing adult weight loss: a scoping review

OBJECTIVE

To present an overview of how artificial intelligence (AI) could be used to regulate eating and dietary behaviours, exercise behaviours and weight loss.

DESIGN

A scoping review of global literature published from inception to 15 December 2020 was conducted according to Arksey and O'Malley's five-step framework. Eight databases (CINAHL, Cochrane-Central, Embase, IEEE Xplore, PsycINFO, PubMed, Scopus and Web of Science) were searched. Included studies were independently screened for eligibility by two reviewers with good interrater reliability (k = 0·96).

RESULTS

Sixty-six out of 5573 potential studies were included, representing more than 2031 participants. Three tenets of self-regulation were identified - self-monitoring (n 66, 100 %), optimisation of goal setting (n 10, 15·2 %) and self-control (n 10, 15·2 %). Articles were also categorised into three AI applications, namely machine perception (n 50), predictive analytics only (n 6) and real-time analytics with personalised micro-interventions (n 10). Machine perception focused on recognising food items, eating behaviours, physical activities and estimating energy balance. Predictive analytics focused on predicting weight loss, intervention adherence, dietary lapses and emotional eating. Studies on the last theme focused on evaluating AI-assisted weight management interventions that instantaneously collected behavioural data, optimised prediction models for behavioural lapse events and enhance behavioural self-control through adaptive and personalised nudges/prompts. Only six studies reported average weight losses (2·4-4·7 %) of which two were statistically significant.

CONCLUSION

The use of AI for weight loss is still undeveloped. Based on the current study findings, we proposed a framework on the applicability of AI for weight loss but cautioned its contingency upon engagement and contextualisation.

Brief interventions for obesity when patients are asked to pay for weight loss treatment: an observational study in primary care with an embedded randomised trial

BACKGROUND

A brief intervention whereby GPs opportunistically facilitate an NHS-funded referral to a weight loss programme is clinically and cost-effective.

AIM

To test the acceptability of a brief intervention and attendance at a weight loss programme when GPs facilitate a referral that requires patients to pay for the service.

DESIGN AND SETTING

An observational study of the effect of a GP encouraging attendance at a weight loss programme requiring self-payment in the West Midlands from 16 October 2018 to 30 November 2018, to compare with a previous trial in England in which the service was NHS-funded.

METHOD

Sixty patients with obesity who consecutively attended primary care appointments received an opportunistic brief intervention by a GP to endorse and offer a referral to a weight loss programme at the patient's own expense. Participants were randomised to GPs who either stated the weekly monetary cost of the programme (basic cost) or who compared the weekly cost to an everyday discretionary item (cost comparison). Participants were subsequently asked to report whether they had attended a weight loss programme.

RESULTS

Overall, 47% of participants (n = 28) accepted the referral; 50% (n = 15) in the basic cost group and 43% (n = 13) in the cost comparison group. This was significantly less than in a previous study when the programme was NHS-funded (77%, n = 722/940; P<0.0001). Most participants reported the intervention to be helpful/very helpful and appropriate/very appropriate (78%, n = 46/59 and 85%, n = 50/59, respectively) but scores were significantly lower than when the programme was NHS-funded (92% n = 851/922 and 88% n = 813/922, respectively; P = 0.004). One person (2%) attended the weight loss programme, which is significantly lower than the 40% of participants who attended when the programme was NHS-funded (P<0.0001).

CONCLUSION

GP referral to a weight loss programme that requires patients to pay rather than offering an NHS-funded programme is acceptable; however, it results in almost no attendance.