Developing evidence-based behavioural strategies to overcome physiological resistance to weight loss in the general population

Physiological and behavioural systems are tolerant of excess energy intake and responsive to energy deficits. Weight loss (WL) changes body structure, physiological function and energy balance (EB) behaviours, which resist further WL and promote subsequent weight regain. Measuring and understanding the response of EB systems to energy deficits is important for developing evidence-based behaviour change interventions for longer-term weight management. Currently, behaviour change approaches for longer-term WL show modest effect sizes. Self-regulation of EB behaviours (e.g. goal setting, action plans, self-monitoring, relapse prevention plans) and aspects of motivation are important for WL maintenance. Stress management, emotion regulation and food hedonics may also be important for relapse prevention, but the evidence is less concrete. Although much is known about the effects of WL on physiological and psychological function, little is known about the way these dynamic changes affect human EB behaviours. Key areas of future importance include (i) improved methods for detailed tracking of energy expenditure, balance and by subtraction intake, using digital technologies, (ii) how WL impacts body structure, function and subsequent EB behaviours, (iii) how behaviour change approaches can overcome physiological resistance to WL and (iv) who is likely to maintain WL or relapse. Modelling physiological and psychological moderators and mediators of EB-related behaviours is central to understanding and improving longer-term weight and health outcomes in the general population.

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Evidence-Based Digital Tools for Weight Loss Maintenance: The NoHoW Project

Obesity Facts ◽

10.1159/000515663 ◽

2021 ◽

pp. 1-14

Author(s):

R. James Stubbs ◽

Cristiana Duarte ◽

António L. Palmeira ◽

Falko F. Sniehotta ◽

Graham Horgan ◽

...

Keyword(s):

Weight Loss ◽

Behaviour Change ◽

Digital Health ◽

Self Regulation ◽

Self Management ◽

Behaviour Change Techniques ◽

Evidence Based ◽

Behavioural Science ◽

Digital Architecture

Background: Effective interventions and commercial programmes for weight loss (WL) are widely available, but most people regain weight. Few effective WL maintenance (WLM) solutions exist. The most promising evidence-based behaviour change techniques for WLM are self-monitoring, goal setting, action planning and control, building self-efficacy, and techniques that promote autonomous motivation (e.g., provide choice). Stress management and emotion regulation techniques show potential for prevention of relapse and weight regain. Digital technologies (including networked-wireless tracking technologies, online tools and smartphone apps, multimedia resources, and internet-based support) offer attractive tools for teaching and supporting long-term behaviour change techniques. However, many digital offerings for weight management tend not to include evidence-based content and the evidence base is still limited. The Project: First, the project examined why, when, and how many European citizens make WL and WLM attempts and how successful they are. Second, the project employed the most up-to-date behavioural science research to develop a digital toolkit for WLM based on 2 key conditions, i.e., self-management (self-regulation and motivation) of behaviour and self-management of emotional responses for WLM. Then, the NoHoW trial tested the efficacy of this digital toolkit in adults who achieved clinically significant (≥5%) WL in the previous 12 months (initial BMI ≥25). The primary outcome was change in weight (kg) at 12 months from baseline. Secondary outcomes included biological, psychological, and behavioural moderators and mediators of long-term energy balance (EB) behaviours, and user experience, acceptability, and cost-effectiveness. Impact: The project will directly feed results from studies on European consumer behaviour, design and evaluation of digital toolkits self-management of EB behaviours into development of new products and services for WLM and digital health. The project has developed a framework and digital architecture for interventions in the context of EB tracking and will generate results that will help inform the next generation of personalised interventions for effective self-management of weight and health.

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The NoHoW protocol: a multicentre 2×2 factorial randomised controlled trial investigating an evidence-based digital toolkit for weight loss maintenance in European adults

BMJ Open ◽

10.1136/bmjopen-2019-029425 ◽

2019 ◽

Vol 9 (9) ◽

pp. e029425 ◽

Cited By ~ 9

Author(s):

Sarah Ellen Scott ◽

Cristiana Duarte ◽

Jorge Encantado ◽

Elizabeth H Evans ◽

Marja Harjumaa ◽

...

Keyword(s):

Weight Loss ◽

Emotion Regulation ◽

Randomised Controlled Trial ◽

Clinical Investigation ◽

Controlled Trial ◽

Self Regulation ◽

Weight Loss Maintenance ◽

Glycated Haemoglobin ◽

Evidence Based ◽

Randomised Controlled

IntroductionObesity and associated diseases place a severe burden on healthcare systems. Behavioural interventions for weight loss (WL) are successful in the short term but often result in weight regain over time. Self-regulation of eating and activity behaviours may significantly enhance weight loss maintenance (WLM) and may be effectively augmented by contextual behavioural approaches to emotion regulation. The NoHoW trial tests the efficacy of a theoretically informed, evidence-based digital toolkit using a mobile-enabled website, activity trackers and Wi-Fi scales for WLM aiming to target (1) self-regulation and motivation, and (2) emotion regulation in adults who achieved clinically significant (≥5%) WL in the previous 12 months (initial body mass index (BMI) ≥25 kg/m2).Methods and analysisThe study is an 18-month, 3-centre, 2×2 factorial single-blind, randomised controlled trial, which recruited 1627 participants achieving ≥5% WL between March 2017 and March 2018. Participants are randomly allocated to one of four arms: (1) self-monitoring only (self-weighing and activity tracker), (2) self-regulation and motivation, (3) emotion regulation or (4) combined self-regulation, motivation and emotion regulation. Participants attend four clinical investigation days at 0, 6, 12 and 18 months and are instructed to use the digital toolkit for 18 weeks during the first 6 months and at their discretion for the remaining 12 months. The primary outcome is change in weight (kg) at 12 months from baseline. Secondary outcomes are body composition (eg, bioimpedance analysis), health biomarkers (glycated haemoglobin, lipids, blood pressure, hair cortisol), dietary intake, physical activity, sleep, motivational, self-regulatory, emotion regulatory moderators/mediators of WLM, engagement, user experience, acceptability and cost-effectiveness of the interventions.Ethics and disseminationEthical approval was granted by Institutional Ethics Committees at the Universities of Leeds (17–0082; 27 February 2017), Lisbon (17/2016; 20 February 2017) and Capital Region of Denmark (H-16030495, 8 March 2017). Results will be published in scientific journals.Trial registration numberISRCTN88405328.

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The H2020 “NoHoW Project”: A Position Statement on Behavioural Approaches to Longer-Term Weight Management

Obesity Facts ◽

10.1159/000513042 ◽

2021 ◽

pp. 1-13

Author(s):

R. James Stubbs ◽

Cristiana Duarte ◽

Ruairi O’Driscoll ◽

Jake Turicchi ◽

Dominika Kwasnicka ◽

...

Keyword(s):

Physical Activity ◽

Weight Loss ◽

Weight Management ◽

Behaviour Change ◽

Weight Regain ◽

Position Statement ◽

Mechanisms Of Action ◽

Evidence Based ◽

Behavioural Interventions ◽

Intervention Content

There is substantial evidence documenting the effects of behavioural interventions on weight loss (WL). However, behavioural approaches to initial WL are followed by some degree of longer-term weight regain, and large trials focusing on evidence-based approaches to weight loss maintenance (WLM) have generally only demonstrated small beneficial effects. The current state-of-the-art in behavioural interventions for WL and WLM raises questions of (i) how we define the relationship between WL and WLM, (ii) how energy balance (EB) systems respond to WL and influence behaviours that primarily drive weight regain, (iii) how intervention content, mode of delivery and intensity should be targeted to keep weight off, (iv) which mechanisms of action in complex interventions may prevent weight regain and (v) how to design studies and interventions to maximise effective longer-term weight management. In considering these issues a writing team within the NoHoW Consortium was convened to elaborate a position statement, and behaviour change and obesity experts were invited to discuss these positions and to refine them. At present the evidence suggests that developing the skills to self-manage EB behaviours leads to more effective WLM. However, the effects of behaviour change interventions for WL and WLM are still relatively modest and our understanding of the factors that disrupt and undermine self-management of eating and physical activity is limited. These factors include physiological resistance to weight loss, gradual compensatory changes in eating and physical activity and reactive processes related to stress, emotions, rewards and desires that meet psychological needs. Better matching of evidence-based intervention content to quantitatively tracked EB behaviours and the specific needs of individuals may improve outcomes. Improving objective longitudinal tracking of energy intake and energy expenditure over time would provide a quantitative framework in which to understand the dynamics of behaviour change, mechanisms of action of behaviour change interventions and user engagement with intervention components to potentially improve weight management intervention design and evaluation.

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Acceptability of Self-regulation Theory based mHealth Behaviorial Intervention for Older Adults with Type 2 Diabetes and Obesity (Preprint)

10.2196/preprints.14224 ◽

2019 ◽

Author(s):

Yaguang Zheng ◽

Katie Weinger ◽

Jordan Greenberg ◽

Lora E. Burke ◽

Susan M. Sereika ◽

...

Keyword(s):

Type 2 Diabetes ◽

Older Adults ◽

Weight Loss ◽

Self Regulation ◽

Self Monitoring ◽

Regulation Theory ◽

Régulation Theory ◽

The Mean ◽

Diabetes And Obesity

BACKGROUND Mobile health (mHealth) is routinely used in younger adults with diabetes for weight loss. However, it is not known if older adult can use mHealth successfully in making lifestyle changes. OBJECTIVE The aim of the study was to examine the acceptability of a self-regulation theory-based mHealth behaviorial intervention for older adults with type 2 diabetes and obesity. METHODS This was a one-group intervention study. Participants received an 8-week self-regulation theory-based intervention consisting of 5 group sessions. They also used the Lose It! App for daily self-monitoring of food intake, a Fitbit, Bluetooth-enabled glucose meters, and weighing scales. At the end of the 8-week intervention, participants were asked to continue use of these devices for daily self-monitoring for 4 more weeks, without additional group sessions. RESULTS The sample (N=9) was White (88.9%) and female (44.4%), with mean 76.4±6.0 years of age (range: 69-89), 15.7±2.0 years of education, 33.3±3.1 kg/m2 for BMI and 7.4%±0.8 for HbA1c. Mild cognitive impairment was observed in 44.4% of sample. Over the 84 days of self-monitoring, the mean % days of using the Lose It!, Fitbit, blood glucose meter, and scale were 82.7±17.6, 85.2±19.7, 65.3±30.1, and 53.0±34.5, respectively. The mean percent weight loss from baseline was 4.92%±0.25. The dose of oral hypoglycemic agents or insulin was reduced in 55.6% of participants. CONCLUSIONS Older adults are able to use mHealth to improve their lifestyle behaviors and clinical outcomes. CLINICALTRIAL NCT03398590

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Development of a theory and evidence-based digital intervention tool for weight loss maintenance: the NoHoW Toolkit (Preprint)

10.2196/preprints.25305 ◽

2020 ◽

Author(s):

Marta Marques ◽

Marcela Matos ◽

Elina Mattila ◽

Jorge Encantado ◽

Cristiana Duarte ◽

...

Keyword(s):

Weight Loss ◽

Emotion Regulation ◽

Weight Management ◽

Behaviour Change ◽

Systematic Approach ◽

Self Regulation ◽

Weight Loss Maintenance ◽

User Testing ◽

Web Based ◽

Logic Models

BACKGROUND Many weight loss programs show short-term effectiveness, but subsequent weight loss maintenance is difficult to achieve. Digital technologies offer promising means to delivering behaviour change approaches at low cost and on a wide scale. The NoHoW project was a European Commission H2020-funded project aimed to develop, test, and evaluate a digital Toolkit designed to promote successful long-term weight management. The Toolkit was tested in an 18-month large-scale international 2 x 2 factorial (motivation and self-regulation versus emotion regulation) randomised controlled trial, conducted in overweight/obese adults who lost ≥5% of their body weight in the preceding twelve months before enrolment into the intervention. OBJECTIVE This paper describes the development of the NoHoW Toolkit focusing on the logic models, content and specifications, and results from user testing. METHODS The Toolkit was developed using a systematic approach including (1) development of the theory-based logic models, (2) selection of behaviour change techniques, (3) translation of these techniques into a digital web-based app (NoHoW Toolkit components), (4) technical development, (5) user evaluation and refinement of the Toolkit. RESULTS The Toolkit included a set of web-based tools and inputs from digital tracking devices (smart scales and activity trackers), with modules targeting weight, physical activity, and dietary behaviours. The final Toolkit was comprised of 34 sessions, distributed through 15 modules, providing active content over a 4-month period. The motivation and self-regulation arm consisted of 8 modules (17 sessions), the emotion regulation arm was presented with 7 modules (17 sessions), and the combined arm received the full Toolkit (15 modules, 34 sessions). The sessions included a range of implementations, such as videos, testimonies, and questionnaires. Further, the Toolkit contained 5 specific data tiles for monitoring weight, steps, healthy eating, mood and sleep. CONCLUSIONS A systematic approach to the development of digital solutions based on theory, evidence, and user testing, may significantly contribute to the advancement of the science of behaviour change and improve current solutions for sustained weight management. Testing the Toolkit using a 2x2 design provided a unique opportunity to examine the effect of motivation and self-regulation and emotion regulation separately, as well as the effect of their interaction in weight loss maintenance. CLINICALTRIAL ISRCTN88405328

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NoHoW Toolkit Development

10.31234/osf.io/n5eyf ◽

2020 ◽

Author(s):

Marta M Marques ◽

Marcela Matos ◽

Elina Mattila ◽

Jorge Encantado ◽

Cristiana Duarte ◽

...

Keyword(s):

Weight Loss ◽

Emotion Regulation ◽

Weight Management ◽

Behaviour Change ◽

Systematic Approach ◽

Self Regulation ◽

Weight Loss Maintenance ◽

Behaviour Change Techniques ◽

Web Based ◽

Logic Models

Background: Many weight loss programs show short-term effectiveness, but subsequent weight loss maintenance is difficult to achieve. Digital technologies offer promising means to delivering behaviour change approaches at low cost and on a wide scale. The NoHoW project was a European Commission H2020-funded project aimed to develop, test, and evaluate a digital Toolkit designed to promote successful long-term weight management. The Toolkit was tested in an 18-month large-scale international 2 x 2 factorial (motivation and self-regulation versus emotion regulation) randomised controlled trial, conducted in overweight/obese adults who lost ≥5% of their body weight in the preceding twelve months before enrolment into the intervention. Objective: This paper describes the development of the NoHoW Toolkit focusing on the logic models, content and specifications, and results from user testing.Methods: The Toolkit was developed using a systematic approach including (1) development of the theory-based logic models, (2) selection of behaviour change techniques, (3) translation of these techniques into a digital web-based app (NoHoW Toolkit components), (4) technical development, (5) user evaluation and refinement of the Toolkit.Results: The Toolkit included a set of web-based tools and inputs from digital tracking devices (smart scales and activity trackers), with modules targeting weight, physical activity, and dietary behaviours. The final Toolkit was comprised of 34 sessions, distributed through 15 modules, providing active content over a 4-month period. The motivation and self-regulation arm consisted of 8 modules (17 sessions), the emotion regulation arm was presented with 7 modules (17 sessions), and the combined arm received the full Toolkit (15 modules, 34 sessions). The sessions included a range of implementations, such as videos, testimonies, and questionnaires. Further, the Toolkit contained 5 specific data tiles for monitoring weight, steps, healthy eating, mood and sleep. Conclusions: A systematic approach to the development of digital solutions based on theory, evidence, and user testing, may significantly contribute to the advancement of the science of behaviour change and improve current solutions for sustained weight management. Testing the Toolkit using a 2x2 design provided a unique opportunity to examine the effect of motivation and self-regulation and emotion regulation separately, as well as the effect of their interaction in weight loss maintenance.

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Development and feasibility study of an app (Ladle) for weight loss and behaviour change

PeerJ ◽

10.7717/peerj.6907 ◽

2019 ◽

Vol 7 ◽

pp. e6907

Author(s):

Jane Ogden ◽

Hazel Maxwell ◽

Adrian Wong

Keyword(s):

Weight Loss ◽

Weight Management ◽

Behaviour Change ◽

Health Care Professionals ◽

Preliminary Analysis ◽

Low Cost ◽

Completion Rate ◽

Evidence Based ◽

Face To Face ◽

Management Interventions

Background Weight management interventions involving behaviour change often utilise face to face interventions which include evidence based behaviour change strategies yet are costly and time intensive. In contrast, digital interventions cost less and have a wider reach yet tend to lack an evidence base and are less effective. Aims The present study therefore aimed to develop an evidence based behaviour change low cost app for weight management and to provide a preliminary analysis of its effectiveness. Methods The Ladle app was developed through evidence review and feedback from health care professionals and patients and consists of a 12 week course focusing on six habits and weight loss facilitated through 36 audio psychological lessons and 12 lessons specifically on the six habits. Each lesson was between 2–5 min (approx. 168 min of lessons). It was evaluated in terms of completion rate, weight loss, adoption of the six habits and participant feedback. Results The results showed a completion rate of 44%, that 52% of Completers showed weight loss of at least 5%, 79% showed weight loss of at least 3%, the median % weight lost was −5% and the median weight loss was −3.8 kg. Further, by the end of 12 weeks the majority (>80%) of participants had adopted four of the six habits for at least 5 days a week and nearly half (45%) had adopted the remaining two habits for at least 4 days out of 7. Feedback comments were mainly positive (n = 80) focusing mostly on the content of the lessons. Some comments were neutral (n = 56) and involved a statement of commitment or a description of a challenge and a minority were negative (n = 23) describing some technical issues which were addressed as the evaluation progressed. Conclusion The new Ladle app offers an evidenced based alternative to more intensive face to face interventions. On preliminary analysis it would seem to have lower completion rates than some more intensive interventions but comparable effectiveness for weight loss. It can also improve habits and is less time-intensive and costly to deliver. Participant feedback was generally positive.

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How users experience and use an eHealth intervention based on self-regulation: a mixed-methods approach (Preprint)

10.2196/preprints.10412 ◽

2018 ◽

Author(s):

Louise Poppe ◽

Celien Van der Mispel ◽

Geert Crombez ◽

Ilse De Bourdeaudhuij ◽

Maïté Verloigne

Keyword(s):

General Population ◽

Behaviour Change ◽

Behavioural Change ◽

Self Regulation ◽

Action Planning ◽

Health Behaviours ◽

Identification Problem ◽

Behaviour Change Techniques ◽

Limited Information ◽

Structured Interviews

BACKGROUND EHealth interventions show stronger effects when informed by solid behaviour change theories. For example, self-regulation models supporting people in translating vague intentions to specific actions have shown to be effective in altering health behaviours. Although these theories inform developers about which behaviour change techniques should be included, they provide limited information about how these techniques can be implemented in online interventions in an engaging way. Taking into account the high levels of attrition in eHealth, investigating users’ experience about the implementation of behaviour change techniques might be a fruitful avenue. OBJECTIVE We investigated how users experienced the implementation of self-regulation techniques in an online intervention targeting physical activity and sedentary behaviour in the general population. METHODS Twenty adults from the general population used the intervention for a period of five weeks. Users’ website data were explored and semi-structured interviews with each of the users were performed. A directed content analysis was performed using NVivo Software. RESULTS The techniques ‘providing feedback on performance’, ‘action planning’ and ‘prompting review of behavioural goals’ were appreciated by the users. However, the implementation of ‘barrier identification/problem solving’ appeared to frustrate users. This was also reflected by the users’ website data: many coping plans were of poor quality. Most users were well-aware of the benefits of adopting a more active way of living and stated not to have learned novel information. However, they appreciated the provided information as it reminded them about the importance of having an active lifestyle. Furthermore, prompting users to self-monitor their behavioural change was not stimulating enough to make users actually monitor their behaviour. CONCLUSIONS Iteratively involving potential end-users offers guidance to optimally adapt the implementation of various behaviour change techniques to the target population. We recommend to create short interventions with a straightforward lay-out that support users in creating and evaluating specific plans for action.

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Self-Regulation and the Writing Process: Enhancing the Performance of Students With Language and Learning Difficulties

Perspectives on Language Learning and Education ◽

10.1044/lle16.1.28 ◽

2009 ◽

Vol 16 (1) ◽

pp. 28-36 ◽

Cited By ~ 1

Author(s):

Gary A. Troia

Keyword(s):

Writing Process ◽

Self Regulation ◽

Learning Difficulties ◽

Evidence Based ◽

Struggling Learners ◽

Evidence Based Practices

Abstract This article first provides an overview of components of self-regulation in writing and specific examples of each component are given. The remainder of the article addresses common reasons why struggling learners experience trouble with revising, followed by evidence-based practices to help students revise their papers more effectively.

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Practicing Academic Independence: Self-Regulation Strategies for Students with Emotional and Behavioral Disorders

Beyond Behavior ◽

10.1177/10742956211020666 ◽

2021 ◽

pp. 107429562110206

Author(s):

Michele L. Moohr ◽

Kinga Balint-Langel ◽

Jonté C. Taylor ◽

Karen L. Rizzo

Keyword(s):

Behavioral Disorders ◽

Cognitive Skills ◽

Emotional And Behavioral Disorders ◽

Self Regulation ◽

Strategy Instruction ◽

Strategy Development ◽

Academic Learning ◽

Self Monitoring ◽

Regulation Strategies ◽

And Behavior

The term self-regulation (SR) refers to a set of specific cognitive skills necessary for students to independently manage, monitor, and assess their own academic learning and behavior. Students with and at risk for emotional and behavioral disorders (EBD) often lack these skills. This article provides educators with step-by-step procedures and information on three research- or evidence-based SR strategies they can implement in their classrooms: self-regulated strategy development, self-monitoring, and strategy instruction.

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