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Health behavior change is central in obesity management. Due to its complexity, there has been a growing body of research on: i) the factors that predict the adoption and maintenance of health behaviors, ii) the development and testing of theories that conceptualize relationships among these factors and with health behaviors, and iii) how these factors can be implemented in effective behavior change interventions, considering characteristics of the content (techniques) and delivery. This short review provides an overview of advances in behavior change science theories and methods, focusing on obesity management, and includes a discussion of the main challenges imposed by this research field.
© 2017 The Author(s)
Published by S. Karger GmbH, Freiburg
Review Article
Obes Facts 2017;10:666–673
Health Behavior Change for Obesity
Pedro J. Teixeira
a Marta M. Marques
a, b
a Interdisciplinary Center for the Study of Human Performance (CIPER), Self-Regulation
Group, Faculty of Human Kinetics, University of Lisbon, Cruz Quebrada/Dafundo , Portugal;
a,b UCL Centre for Behaviour Change University College London, London , UK
Behavior modification · Behavioral interventions · Obesity management · Psychological
Health behavior change is central in obesity management. Due to its complexity, there has
been a growing body of research on: i) the factors that predict the adoption and maintenance
of health behaviors, ii) the development and testing of theories that conceptualize relation-
ships among these factors and with health behaviors, and iii) how these factors can be imple-
mented in effective behavior change interventions, considering characteristics of the content
(techniques) and delivery. This short review provides an overview of advances in behavior
change science theories and methods, focusing on obesity management, and includes a dis-
cussion of the main challenges imposed by this research field.
© 2017 The Author(s)
Published by S. Karger Gmb H, Freiburg
Successfully influencing individual health behaviors has never been as important as it is
today, mainly because of the well-known effects of these behaviors in the prevention and
management of various health conditions, and due to the increased importance placed on
individual autonomy and capacity to self-regulate their own health. Reducing overweight and
obesity are key public health challenges. The World Health Organization (WHO) [1] estimates
that 39% of adults worldwide are overweight and 13% obese, leading to a range of health
complications as well as increased health costs. A recent meta-analysis led by our research
laboratory [2] examining the prevalence of weight control attempts worldwide (72 studies;
Receive d: Januar y 25, 2017
Accepted: Octob er 29, 2017
Published online: Decemb er 14, 2017
Prof. Dr. Pedro J. Teixeira
Interdisciplinary Center for the Study of Human Performan ce (CIPER), Self-
Regulation Group
Faculty of Human Kinetics , University of Lisbon
Estrada da Costa, 1499-0 02 Cruz Quebrada/Dafundo, Portugal
DOI: 10.1159/000484933
This article is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 Interna-
tional License (CC BY-NC-ND) ( Usage and distribu-
tion for commercial purposes as well as any distribution of modified material requires written permission.
Obes Facts 2017;10:666–673
DOI: 10.1159/000484933
Teixeiraa and Marquesa,b: Health Behavior Change for Obesity Management
© 2017 The Author(s). Published by S. Karger GmbH, Freiburg
n = 1,189,942) showed that 42% of adults from general population and 44% from ethnic-
minority populations are trying to lose weight, and 23% reported trying to maintain their
weight at some point. Behavioral interventions targeting changes in diet and physical activity
are the cornerstone of interventions for weight management in overweight and obese popu-
lations [3] and seem to be effective in reducing weight and improving health at least in the
short term (e.g. [4] ).
The emergence and rapid growth of the health behavior change field is one response to
the urgent need to understand the complexity behind individuals’ decisions and engagement
in behaviors that affect their health and well-being, including sustained weight management.
Health behavior change interventions (HBCIs) have the potential to improve the health of
populations if they can be scaled up and appropriately targeted, considering issues like diffi-
culty and motivation for change [5] . Since interventions are meant for the real world, context
sensitivity is paramount. In other words, an intervention is only as successful as its capacity
to adequately respond to a problem in an environment for a certain target population and
focused on certain behavioral outcome(s). Evidence-based practice health behavior change
therefore depends on the adequate development and implementation of interventions [6] ,
making use of standardized methods to report them [7] .
In this short narrative review, we will present some of the most current topics of research
in the field of health behavior change, with a focus on the management of obesity, including
i) the use of formal theories and a correct consideration of their mechanisms of action, ii) the
choice of the behavior change techniques (or ‘active ingredients’) included in HBCIs, and iii)
the use of technology to promote sustained behavior change.
The Role of Theory and Mechanisms of Action
Theories (‘systematic way of understanding events or situations, (…) a set of concepts,
definitions, and propositions that explain or predict these events or situations by illustrating
the relationships between variables’ [8] , p. 4) are useful to understand, explain, and predict
behavior and behavior change, as they conceptualize a set of interrelated constructs oper-
ating as predictors or mechanisms of action underlying behavior change. There are various
levels of constructs that influence health behavior; they are therefore conceptualized in
health behavior change theories. These can be done at the environmental level whether it is
physical, cultural, or social (e.g., advice from a healthcare practitioner, low accessibility, peer
support) or at the individual level including biological factors (e.g., food reward mechanisms)
but also emotions, motivation, and self-regulation skills. Individual factors are considered
fundamental for health behavior change as they are mostly responsible for the process of self-
regulation of health behaviors. For instance, a systematic review looking at psychological
mediators of sustained beneficial effects in lifestyle obesity interventions [9] found that
higher levels of autonomous motivation, self-efficacy/barriers, self-regulation skills, flexible
eating restraint, and positive body image were mediators of medium-/long-term weight
control. High autonomous motivation, self-efficacy, and use of self-regulation skills were
significant mediators of physical activity while for dietary intake no consistent mediators
were identified.
Recently, a broad consensus emerged indicating that HBCIs can be optimized if they are
informed by theory [10] , as it facilitates the understanding of what works to change a certain
behavior and how it works [11] . Theories of behavior change propose the mechanisms of
action (under the broad categories of capacity, opportunity, and motivation) and the moder-
ators of change through causal predictions. While there is an agreement in health behavior
change that the use of theory is useful to promote long-lasting behavior change, there is still
Obes Facts 2017;10:666–673
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limited research on the effectiveness of theory-based (vs. non-theory-based) interventions.
For instance, a recent meta-analysis by Gourlan and colleagues [12] investigated the effects
of 82 theory-based randomized controlled trials targeting physical activity and showed bene-
ficial but small effects of theory-based interventions in changing physical activity (d = 0.31).
Similar results were found in a meta-analysis of digital-based interventions targeting various
health behaviors (85 studies), in which the extensive use of theory (e.g., use theoretical
constructs to develop intervention techniques) was associated with larger intervention
effects [13] . Another meta-analysis examining the influence of theory use in physical activity
and dietary interventions, did not find significant associations (e.g. [14] ). There are several
reasons that may explain these results: i) limited number of theories commonly tested (e.g.,
Social Cognitive Theory, Theory of Planned Behavior), ii) the fact that some theories may not
provide a clear explanation on the process of behavior change maintenance, and iii) when
interventions are explicitly based on theory, they often do not apply it extensively [12, 14] .
Furthermore, research findings suggest that single-theory approaches may be more effective
in influencing behaviors such as physical activity, comparing with those interventions
applying multiple theories [12, 13] . This finding may be related to the fact that some interven-
tions consist of a combination of two or more theories (or key constructs from these theories)
lacking internal coherence and parsimony [15] .
One of the problems faced when intending to use theory in HBCIs is the large number of
theories that currently exist. Recently, a panel of experts has identified and compiled 83
formal theories of behavior and behavior change (including more than 1,700 theoretical
constructs) in a comprehensive compendium [16] . Faced with so many theories from which
to select from, researchers and practitioners need the skills to make decisions regarding the
best candidate theory for a given behavior and context. This can be particularly difficult when
targeting multiple behaviors (e.g., physical activity and diet), which is the case when consid-
ering weight management interventions. To guide this process, efforts have been made to
make frameworks for the development of HBCIs informed by theory. This includes the Inter-
vention Mapping Protocol [17] or the Theoretical Domains Framework [18] . In addition, tools
such as the Theory Coding Scheme allow for an evaluation of the extension of use of theory in
a HBCI [19] . The overarching COM-B model [6] , which contains three broad theory-related
dimensions of behavior change determinants – competence, motivation, and opportunity –,
can also be used to make decisions on the design of HBCIs, especially when this is conducted
without input by health psychologists or behavior change specialists.
While behavioral interventions seem to be effective in promoting weight loss, weight loss
maintenance is a key challenge as most adults that successfully lose weight tend to regain part
of it within 1 year [20] . Currently, there are very few comprehensive treatments available,
and indeed most of the research has focused on the behavioral aspects associated with weight
loss [21, 22] . A recent systematic review on theoretical explanations for behavior change
maintenance [22] identified five interconnected theoretical explanations about how indi-
viduals maintain initial behavior changes over time: i) maintenance motives tendency to
maintain behavior when there are sustained motives (e.g. enjoyment) and congruence
between behavior and identity/values (e.g. self-determination theory [23] ); ii) self-regu-
lation includes self-monitoring and coping strategies (self-regulation theory [24] ); iii)
physical and psychological resources (e.g. self-control theory [25] ), iv) habit habitual
behaviors supported by automatic responses to cues (e.g. habit theory [26] ); and v) environ-
mental and social cues – supportive environment, social support, behavior in line with social
changes (e.g. normalization process theory [27] ). At present, in long-term weight management
there is some support for the effectiveness of HBCIs which are based on self-determination
theory (e.g. [9, 28, 29] ) and self-regulation theories (e.g. [9, 30, 31] ).
Obes Facts 2017;10:666–673
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The Active Ingredients of Interventions: Behavior Change Techniques
A key aspect in the development, implementation and evaluation of HBCIs is the adequate
characterization of its content – the ‘active ingredients’, i.e., the techniques used in interven-
tions to help change another’s or one’s own behavior. These techniques represent the lowest-
level, irreducible, fundamental elements of an intervention aimed to influence on behavior
and are commonly designated behavior change techniques (BCTs) [32] . Some examples of
BCTs are ‘prompt self-monitoring’, ‘provide feedback on progress’, or ‘restructure the envi-
ronment’. Naturally, complex HBCIs typically involve several of such techniques in various
combinations, and detailed taxonomies of BCTs that can be used in HBCIs can be of use in both
research and practice, as they promote a shared language between health behavior change
researchers and practitioners. Interventions can be described in clearer and more consistent
ways and more rigorously tested and compared in research studies, when techniques are
reliably used. In turn, practitioners can more easily and consistently be trained in, and be
evaluated based on, the use of standardized techniques.
The work led by Michie and colleagues [33, 34] is perhaps the most comprehensive and
resulted in BCT taxonomies for a range of behaviors, including physical activity, diet, and
smoking. More recently, these were collapsed into one overarching list – the BCT Taxonomy
v1 – including 93 techniques, organized into 16 higher-level domains [35] . Since the publi-
cation of the first BCT taxonomy [36] , several meta-analyses of randomized controlled trials
have examined the use of BCTs i) looking at the association between the number of BCTs used
and the magnitude of the effects, ii) determining which BCTs effectively target certain theo-
retical constructs, and iii) investigating if certain clusters of theoretically driven BCTs are
associated with better results in several health behaviors (e.g. [37] ) and health conditions
(e.g. [30, 38] ). One of the main reasons for conducting these analyses is that there are typically
considerable levels of heterogeneity in the effects of HBCIs. By examining the techniques used
in these interventions (as well as the theoretical frameworks that support them), we can
select BCTs or clusters of BCTs that can have a higher impact on a certain target behavior
under certain conditions, and exclude others in order to develop more effective HBCIs.
Results from reviews suggest that combined use of BCTs can be associated with greater
effectiveness. Michie and colleagues [37] found that interventions combining self-monitoring
with other BCTs derived from self-regulation theories (e.g. [25] ), such as goal setting, provision
of feedback, planning and goal revisiting, were more effective in promoting changes in
physical activity and healthy eating in the general population than other interventions not
using these techniques. Similar effects were found in other meta-analyses, including weight
loss and maintenance interventions in overweight/obese subjects (e.g. [30] ). In the context
of digital-based interventions for weight management, Hutchesson et al. [39] point to the
potential beneficial effects of self-monitoring and personalized feedback, and Sherrington
and colleagues [40] found that internet-delivered weight loss interventions providing person-
alized feedback resulted in greater weight loss but only in the short term.
While the BCTT V1 was developed without the consideration of the role of theory in
informing the selection and use of BCTs, another common framework for the development of
health behavior change interventions intervention mapping –, clearly states that the
selection of techniques should take into consideration the theoretical parameters for its effec-
tiveness [17] . In this respect, taxonomies can be sought for specific theories, where tech-
niques that target the most important constructs of that framework are described. As an
example, Teixeira and colleagues [41] are currently developing a comprehensive list of tech-
niques used to influence key self-determination theory constructs.
A better linkage between BCTs and health behavior change theories is a potential benefit
since psychological constructs presented in theories are presumably well-targeted by some
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techniques but not (or less so) by others. Techniques are useful in HBCIs to the extent that
they impact on the putative mechanisms of action (e.g. goal setting) to change a given behavior
(e.g. physical activity). Currently, there are efforts begin made in linking clusters of BCTs to
specific mechanisms of action and overarching behavioral theories [42] .
Delivery of Health Behavior Change Interventions: Digital Progress
Another important dimension on the development of effective HBCIs is the delivery of
the intervention, which can have an impact on the effectiveness of interventions (e.g. face to
face vs. printed material; delivered by psychologist vs. nurse) as well as on the operational-
ization of certain theories [43] . While there has been a significant progress in specifying BCTs
and the mechanisms of action and theoretical frameworks involved in health behavior change,
less attention has been given to the elements of delivery. Dombrowski and colleagues [43]
propose that ‘form of delivery’ includes ‘all features through which behavior change inter-
vention content is conveyed including: the provider, format, materials, setting, intensity,
tailoring and style’. Any HBCI can use a combination of forms and modes of delivery (MoDs).
Carey and colleagues [44] , define MoD as the way in which BCTs are delivered. They are
currently developing a hierarchical classification system in order to specify the MoDs applied
in HBCIs, using a similar approach to the development of the BCTT V1. For example, the MoD
‘informational’ includes human, printed material, digital and environmental change; and
‘digital’ includes technology for delivery (e.g. mobile device) and digital content type (e.g
In recent years, there has been a marked increase in the use of digital MoDs in lifestyle
interventions for weight management. These are a viable option as they have the potential
for wide reach at low cost, which is especially relevant if considered in a large scale and if
intended to influence behaviors in the long term (which the case of weight management).
Other advantages of using a digital approach are the potential to adapt content to individual
needs (personalization), the delivery of information in an engaging and interactive form, and
higher degree of fidelity to intervention content [45, 46] .
While digitally based HBCIs are promising, research on their effects is still in an early
stage. In the context of weight management in overweight/obese populations, previous
reviews have reported positive albeit often small effects with considerable between-study
variability [13, 39, 47] . There is therefore the need to identify which intervention components
contribute to the effectiveness of digital-based interventions in promoting sustained weight
management [13, 39, 40] . In a meta-analysis of internet-based interventions for health
behavior change looking at the characteristics of most effective interventions, theory-based
interventions incorporating a larger number of BCTs (vs. interventions with fewer BCTs) and
using a variety of MoDs (e.g. internet, SMS) had larger effects on health-related behaviors
[13] . The only published meta-analysis looking at the interactions between BCTs and MoDs
in digital interventions did not find significant effects [48] . Research focusing on the devel-
opment of strategies for sustained engagement alongside with health behavior change theory
is also a priority for digital interventions [49] .
Research on the effectiveness of using digital MoDs in promoting weight loss mainte-
nance is very limited. There are currently two ongoing projects aiming to fill this gap. The first
is the ‘NoHoW Evidence-Based ICT Tools for Weight Maintenance’ ( ), a
European Commission-funded project (Horizon 2020). Following available guidance for the
development of complex interventions (e.g. [46, 50] ), we developed a toolkit, using evidence-
based intervention techniques derived from promising theoretical frameworks in weight loss
maintenance, such as self-determination theory, self-regulation theory, and emotion regu-
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lation approaches. The toolkit is currently being tested in the context of a full-factorial
randomized controlled trial. It will help us understand if digital-based interventions are an
effective way to apply theory and techniques aiming at promoting weight loss maintenance,
and which content is more effective for each behavior, for whom, under which circumstances
and for which outcomes (Trial Registration: ISRCTN88405328).
The other is the NULevel trial [21] , a self-regulatory intervention using automated remote
weight-monitoring and feedback system using participants’ mobile phones as the main MoD
of theory-based BCTs (e.g., self-monitoring, goal setting, coping plans, and increase moti-
vation), and an initial face-to-face behavioral component. NULevel evaluation is currently
There is a scientifically rigorous body of research aiming to identify and improve our
understanding of how to effectively develop, implement and evaluate HBCIs, namely in the
field of weight management. Researchers have considered effective ways of ‘speaking the
same language’ and to make knowledge accessible for interventionist by developing various
taxonomies and frameworks. While considerable progress is evident in this area, there are
still many questions to be answered and challenges ahead, as shown for example by the vari-
ability of the effects of HBCIs and limited results from meta-analyses examining interactions
between intervention features. The Human Behavior-Change Project led by Michie and
colleagues ( ) is an example of the most recent efforts in the field of
Health behavior change science to promote evidence-based practice [51] . The project consists
of a multidisciplinary team of behavioral scientists, computer scientists, and system archi-
tects, aiming to build an ontology of behavior change interventions that will classify and
organize HBCI features (e.g. BCTs, mechanisms of action, delivery, context) and develop a
‘knowledge system’ that, through artificial intelligence and machine learning, will automati-
cally extract, synthetize, and interpret information from HBCI research reports, therefore
contributing to the design of effective evidence-based interventions [51] . Another landmark
project is the US Science of Behavior Change project ( ), which
also seeks to standardize and synthetize assessment methods and research protocols in the
area of human behavior change. It should be noted that classification systems of features of
health (and other) behaviors are still a work in progress, and there is ongoing debate on its
limitations to capture the complexity of health behavior change [52] .
Disclosure Statement
The authors have no conflicts of interest to declare.
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... La rapidité d'accès à l'information permet une diffusion de masse des interventions. En effet, le développement des technologies au cours des dernières années ont permis de les rendre plus accessibles et abordables, permettant ainsi de pouvoir les diffuser à large échelle (Teixeira & Marques, 2017). De plus, il est estimé qu'environ 50% des personnes ayant commencé un programme d'activité physique classique l'abandonnent dans les six mois (Gao, 2019, p. 61). ...
... Ce type d'intervention permet de personnaliser les contenus (e.g., exercices à réaliser) ou la forme des contenus (e.g., transmission d'informations sous une forme plus attrayante et interactive) aux besoins des utilisateurs (Teixeira & Marques, 2017). Cette adaptation des contenus ou de leur forme peut être paramétrée par l'utilisateur lui-même, ou de manière automatique à l'aide d'algorithmes. ...
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La promotion de l’activité physique est essentielle dans la prise en charge des jeunes femmes atteintes d’obésité sévère, notamment lorsque la prise en charge s’accompagne d’un traitement chirurgical. Dans ce cadre, les technologies de promotion de l’activité physique offrent de nouvelles perspectives d’accompagnement. Ces technologies ont des effets favorables à court terme sur les paramètres physiologiques liés à l’obésité, et sur l’engagement dans l’activité physique. Cependant, leurs effets durables et les mécanismes qui sous-tendent l’efficacité de ces technologies n’ont été que peu étudiés dans la littérature. L’objectif de cette thèse est de contribuer à l’identification de ces mécanismes, en se focalisant principalement sur les mécanismes d’acceptabilité de différents types de technologies de promotion de l’activité physique chez des jeunes femmes en obésité sévère. Une première étude préliminaire a consisté à réaliser une revue systématique des effets et de l’acceptabilité des technologies de promotion de l’activité physique dans le contexte de la chirurgie bariatrique (Etude 1). Une seconde étude préliminaire (Etude 2) a permis de développer et valider un outil psychométrique mesurant l’acceptabilité des technologies de promotion de l’activité physique basé sur le modèle de l’Unified Theory of Acceptance and Use of Technology-2 (UTAUT2). Les études 3 et 4 ont caractérisé le niveau d’acceptabilité de trois types de technologies (i.e., applications mobiles, jeux vidéo actifs, visioconférence), à l’aide de scenarii hypothétiques, et identifié des facteurs motivationnels reliés à l’acceptabilité des technologies. Plus spécifiquement, les orientations générales à la causalité (i.e., orientations concernant l’initiation et la régulation du comportement selon la théorie de l’autodétermination) sont des prédicteurs des profils d’acceptabilité des technologies étudiées. L’étude 5 a ensuite caractérisé le potentiel de changement de comportement de deux technologies de promotion de l’activité physique adaptées au contexte de la chirurgie bariatrique et disponibles sur le marché français : la plateforme MyBody proposée par BePatient, et un programme d’activité physique adaptée réalisé en visioconférence, proposé par Mooven. Au regard des techniques du changement de comportement que ces deux technologies mobilisent, nous pouvons supposer qu’elles auront des effets positifs sur l’activité physique des jeunes femmes en post-chirurgie bariatrique. Afin d’examiner dans quelle mesure l’acceptabilité de ces technologies et les facteurs motivationnels reliés contribuent à l’explication des effets durables de ces technologies, nous avons conçu le protocole d’essai interventionnel randomisé contrôlé OCAPAS (Etude 6). Ce programme de recherche doctoral contribue à l’identification de mécanismes qui sous-tendent l’efficacité des technologies de promotion de l’activité physique en contexte d’obésité. Des différences ont été démontrées entre les technologies en termes : (a) de niveau et de profil d’acceptabilité, (b) d’orientations générales à la causalité prédisant l’acceptabilité de chaque technologie, et (c) de techniques de changement de comportement mobilisées par les technologies. Ces résultats illustrent une extension du modèle théorique de l’UTAUT2. Ils invitent par ailleurs à concevoir un modèle intégratif du changement comportemental par les technologies. Les résultats de l’essai interventionnel, et les perspectives de recherche discutées dans ce travail doctoral, contribueront à enrichir l’étude des conditions d’efficacité des technologies de promotion de l’activité physique, et à préciser les recommandations à destination des professionnels de santé.
... Among them, the most frequently mentioned are interactions between predisposing genetic and metabolic factors and the rapidly changing "obesogenic" environment [2]. Nowadays, obesity is examined as a multidimensional disease, in the therapy of which physical activity, dietary, behavioral, psychological, and pharmacological aspects play crucial roles [3][4][5][6]. ...
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Whether BMI and the competing waist circumference (WC)-based anthropometric indices are associated with obesity-related single-nucleotide polymorphisms (SNPs) is as yet unknown. The current study aimed to evaluate the anthropometric indices (fat mass index, body shape index, visceral adiposity index, relative fat mass, body roundness index, and conicity index) during a weight loss intervention in 36 obese individuals. Blood biochemical parameters (total cholesterol, low-density lipoprotein, high-density lipoprotein, and triglycerides) and three SNPs (FTO rs9939609, TFAP2B rs987237, and PLIN1 rs894160) were assessed in 22 women and 14 men (35.58 ± 9.85 years, BMI 35.04 ± 3.80 kg/m2) who completed a 12-month balanced energy-restricted diet weight loss program. Body composition was assessed via bioelectrical impedance (SECA mBCA515). At the end of the weight loss intervention, all anthropometric indices were significantly reduced (p < 0.05). For the SNP FTO rs9939609, the higher risk allele (A) was characteristic of 88.9% of the study group, in which 10 participants (27.8%) were homozygous. We found a similar distribution of alleles in TFAP2B and PLIN1. Heterozygous genotypes in FTO rs9939609 and TFAP2B rs987237 were predisposed to significant reductions in WC-based novel anthropometric indices during weight loss. The influence of PLIN1 rs894160 polymorphisms on the changes in the analyzed indices during weight loss has not been documented in the present study.
... Thereafter, other options include bariatric surgery [16] and/or medical therapies [17], much of the latter based on our current understanding of the hypothalamic regulation of appetite and metabolism [18]. Ultimately (and regardless of the approach, including surgical and medical options), effective management of obesity must also include a change of behaviour (often termed "lifestyle management") [19]. Indeed, many people managed for obesity only receive behavioural change strategies (including dietary and psychological support). ...
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Background: Resveratrol is a polyphenol chemical that naturally occurs in many plant-based dietary products, most notably, red wine. Discovered in 1939, widespread interest in the potential health benefits of resveratrol emerged in the 1970s in response to epidemiological data on the cardioprotective effects of wine. Objective: To explore the background of resveratrol (including its origins, stability, and metabolism), the metabolic effects of resveratrol and its mechanisms of action, and a potential future role of dietary resveratrol in the lifestyle management of obesity. Data sources: We performed a narrative review, based on relevant articles written in English from a Pubmed search, using the following search terms: “resveratrol”, “obesity”, “Diabetes Mellitus”, and “insulin sensitivity”. Results: Following its ingestion, resveratrol undergoes extensive metabolism. This includes conjugation (with sulfate and glucuronate) within enterocytes, hydrolyzation and reduction within the gut through the action of the microbiota (with the formation of metabolites such as dihydroresveratrol), and enterohepatic circulation via the bile. Ex vivo studies on adipose tissue reveal that resveratrol inhibits adipogenesis and prevents the accumulation of triglycerides through effects on the expression of Peroxisome Proliferator-activated Receptor γ (PPARγ) and sirtuin 1, respectively. Furthermore, resveratrol induces anti-inflammatory effects, supported by data from animal-based studies. Limited data from human-based studies reveal that resveratrol improves insulin sensitivity and fasting glucose levels in patients with Type 2 Diabetes Mellitus and may improve inflammatory status in human obesity. Although numerous mechanisms may underlie the metabolic benefits of resveratrol, evidence supports a role in its interaction with the gut microbiota and modulation of protein targets, including sirtuins and proteins related to nitric oxide, insulin, and nuclear hormone receptors (such as PPARγ). Conclusions: Despite much interest, there remain important unanswered questions regarding its optimal dosage (and how this may differ between and within individuals), and possible benefits within the general population, including the potential for weight-loss and improved metabolic function. Future studies should properly address these important questions before we can advocate the widespread adoption of dietary resveratrol supplementation.
... Although acceptability can only partially explain future use, characterizing it, as well as its antecedents, appears to be a promising avenue and should be incorporated into future effectiveness studies. Furthermore, it has been demonstrated that theoretically based interventions tend to be more effective [40]. A better understanding of physical activity behavior through theoretical models would favor the individualization of the technology-based intervention by tailoring it to the profile of the targeted participants. ...
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The aim of this scoping review is to highlight current trends in the emerging field of technology-based physical activity interventions (TbPAI) in pre- and post-bariatric surgery. Original articles published between 2000 and 2020 on eHealth, bariatric surgery, and physical activity were identified through electronic searches of eight databases. Screening, data extraction, and charting were performed independently by two authors and disagreements were resolved by consensus. Nine full-text articles were included in this review. The studies reported that the physical activity outcomes had improved and the interventions were positively perceived by the target population. We highlight some consistent findings, as well as knowledge gaps, and suggest how future studies could be improved. Graphical abstract
... The prevalence of obesity has reached a global proportion. The most important cause of obesity is excessive food intake, and relative behavioral changes have recently been reported [1]. Adipose tissue accumulation and dysfunction characterize obesity. ...
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A link between obesity and cerebral health is receiving growing recognition. Here, we investigate in the frontal cortex and hippocampus the potential involvement of cholinergic markers in brain alterations previously reported in rats with obesity induced by diet (DIO) after long-term exposure (17 weeks) to a high-fat diet (HFD) in comparison with animals fed with a standard diet (CHOW). The obesity developed after 5 weeks of HFD. Bodyweight, systolic blood pressure, glycemia, and insulin levels were increased in DIO rats compared to the CHOW group. Measurements of malondialdehyde (MDA) provided lipid peroxidation in HFD-fed rats. Western blot and immunohistochemical techniques were performed. Our results showed a higher expression of choline acetyltransferase (ChAT) and vesicular acetylcholine transporter (VAChT) in obese rats but not the VAChT expression in the frontal cortex after 17 weeks of HFD. Furthermore, the acetylcholinesterase (AChE) enzyme was downregulated in HFD both in the frontal cortex and hippocampus. In the brain regions analyzed, it was reported a modulation of certain cholinergic receptors expressed pre- and post-synaptically (alpha7 nicotinic receptor and muscarinic receptor subtype 1). Collectively, these findings point out precise changes of cholinergic markers that can be targeted to prevent cerebral injuries related to obesity.
... This indicates that approaches to strengthen practices although immense, is recommended. The simplest and cost-effective approach as voiced by most students interviewed, is self-change with positive attitude [61]. ...
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Background Overweight and obesity among high school students is a growing distress not only to the individual wellbeing of a person but also to the productivity of communities and economic expense of both developed and developing nations. This study aimed to determine factors contributing to overweight and obesity among high school students in Kiribati through the perception of students. Methods This qualitative study was conducted in four (4) randomly selected senior high schools on South Tarawa, Kiribati from August to November, 2020. A purposive sampling was used to select thirty-two (32) students enrolled into form levels 4–7. A semi-structured open-ended questionnaire was used for data collection using face-to-face in-depth interviews. Data was transcribed and analyzed using thematic analysis method. Results This research revealed that the participants were 21 (65.6%) were females and 11 (34.4%) males from form levels four with 9 (28.1%) participants, five with 9 (28.1%) participants, and form seven with 14 (43.8%) participants. Five themes identified including determinants and prevention of overweight and obesity, education and health system factors, stigma, and being fat comes with high risk. These themes collectively elaborate on the essentials of overweight and obesity that are obtained from perspectives of students. Conclusion A strong cultural belief and practice has caused misperception of overweight and obesity among students with knowledge-behavior gap recognized as the main reason behind the failure in lifestyle changes among adolescents. Strengthen healthy behavioral lifestyle, improve awareness, and support feasible preventative strategies is recommended to all students.
Background To date, few digital behavior change interventions for weight loss maintenance focusing on long-term physical activity promotion have used a sound intervention design grounded on a logic model underpinned by behavior change theories. The current study is a secondary analysis of the weight loss maintenance NoHoW trial and investigated putative mediators of device-measured long-term physical activity levels (six to 12 months) in the context of a digital intervention. Methods A subsample of 766 participants (Age = 46.2 ± 11.4 years; 69.1% female; original NoHoW sample: 1627 participants) completed all questionnaires on motivational and self-regulatory variables and had all device-measured physical activity data available for zero, six and 12 months. We examined the direct and the indirect effects of Virtual Care Climate on post intervention changes in moderate-to-vigorous physical activity and number of steps (six to 12 months) through changes in the theory-driven motivational and self-regulatory mechanisms of action during the intervention period (zero to six months), as conceptualized in the logic model. Results Model 1 tested the mediation processes on Steps and presented a poor fit to the data. Model 2 tested mediation processes on moderate-to-vigorous physical activity and presented poor fit to the data. Simplified models were also tested considering the autonomous motivation and the controlled motivation variables independently. These changes yielded good results and both models presented very good fit to the data for both outcome variable. Percentage of explained variance was negligible for all models. No direct or indirect effects were found from Virtual Care Climate to long term change in outcomes. Indirect effects occurred only between the sequential paths of the theory-driven mediators. Conclusion This is one of the first attempts to test a serial mediation model considering psychological mechanisms of change and device-measured physical activity in a 12-month longitudinal trial. The model explained a small proportion of variance in post intervention changes in physical activity. We found different pathways of influence on theory-driven motivational and self-regulatory mechanisms but limited evidence that these constructs impacted on actual behavior change. New approaches to test these relationships are needed. Challenges and several alternatives are discussed. Trial registration ISRCTN Registry, ISRCTN88405328. Registered 16 December 2016,
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This paper details the development of the Adolescent Intrinsic Motivation AIM2Change intervention to support weight-management in young people previously unable to make changes whilst attending a tier 3 weight management service for children and young people. AIM2Change is an acceptance and commitment therapy (ACT) based intervention that will be delivered one-to-one online over a seven-week period. To develop this intervention, we have triangulated results from a qualitative research study, patient and public involvement groups (PPI) and a COM-B (capability, opportunity, motivation, behaviour) analysis, in a method informed by the person-based approach. The integrated development approach yielded a broad range of perspectives and facilitated the creation of a tailored intervention to meet the needs of the patient group whist remaining pragmatic and deliverable. The next steps for this intervention will be in-depth co-development of the therapy sessions with service users, before implementing a feasibility randomised control trial.
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Although herbal medicines (HMs) are widely used in the prevention and treatment of obesity and obesity-associated disorders, the key constituents exhibiting anti-obesity activity and their molecular mechanisms are poorly understood. Recently, we assessed the inhibitory potentials of several HMs against human pancreatic lipase (hPL, a key therapeutic target for human obesity), among which the root-extract of Rhodiola crenulata (ERC) showed the most potent anti-hPL activity. In this study, we adopted an integrated strategy, involving bioactivity-guided fractionation techniques, chemical profiling, and biochemical assays, to identify the key anti-hPL constituents in the ERC. Nine ERC fractions (retention time=12.5–35 min), obtained using reverse-phase liquid chromatography, showed strong anti-hPL activity, while the major constituents in these bioactive fractions were subsequently identified using liquid chromatography-quadrupole time-of-flight mass spectrometry. Among the identified ERC constituents, 1,2,3,4,6-penta-O-galloyl-β-d-glucopyranose (PGG) and catechin gallate (CG) displayed very potent anti-hPL activity, with pIC50 values of 7.59 ± 0.03 and 7.68 ± 0.23, respectively. Further investigations revealed that PGG and CG potently inhibited hPL in a non-competitive manner, with inhibition constant (Ki) values of 0.012 and 0.082 μM, respectively. Collectively, our integrative analyses enabled us to efficiently identify and characterize the key anti-obesity constituents in the ERC, as well as to elucidate their anti-hPL mechanisms. These findings provide convincing evidence in support of the anti-obesity and lipid-lowering properties of ERC.
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Although web-based interventions are attractive to researchers and users, the evidence about their effectiveness in the promotion of health behaviour change is still limited. Our aim was to review the effectiveness of web-based interventions used in health behavioural change in adolescents regarding physical activity, eating habits, tobacco and alcohol use, sexual behaviour, and quality of sleep. Studies published from 2016 till the search was run (May-to-June 2021) were included if they were experimental or quasi-experimental studies, pre-post-test studies, clinical trials, or randomized controlled trials evaluating the effectiveness of web-based intervention in promoting behaviour change in adolescents regarding those health behaviours. The risk of bias assessment was performed by using the Effective Public Health Practice Project (EPHPP)—Quality Assessment Tool for Quantitative Studies. Fourteen studies were included. Most were in a school setting, non-probabilistic and relatively small samples. All had a short length of follow-up and were theory driven. Thirteen showed significant positive findings to support web-based interventions’ effectiveness in promoting health behaviour change among adolescents but were classified as low evidence quality. Although this review shows that web-based interventions may contribute to health behaviour change among adolescents, these findings rely on low-quality evidence, so it is urgent to test these interventions in larger controlled trials with long-term maintenance.
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Background Behaviour change is key to addressing both the challenges facing human health and wellbeing and to promoting the uptake of research findings in health policy and practice. We need to make better use of the vast amount of accumulating evidence from behaviour change intervention (BCI) evaluations and promote the uptake of that evidence into a wide range of contexts. The scale and complexity of the task of synthesising and interpreting this evidence, and increasing evidence timeliness and accessibility, will require increased computer support. The Human Behaviour-Change Project (HBCP) will use Artificial Intelligence and Machine Learning to (i) develop and evaluate a ‘Knowledge System’ that automatically extracts, synthesises and interprets findings from BCI evaluation reports to generate new insights about behaviour change and improve prediction of intervention effectiveness and (ii) allow users, such as practitioners, policy makers and researchers, to easily and efficiently query the system to get answers to variants of the question ‘What works, compared with what, how well, with what exposure, with what behaviours (for how long), for whom, in what settings and why?’. Methods The HBCP will: a) develop an ontology of BCI evaluations and their reports linking effect sizes for given target behaviours with intervention content and delivery and mechanisms of action, as moderated by exposure, populations and settings; b) develop and train an automated feature extraction system to annotate BCI evaluation reports using this ontology; c) develop and train machine learning and reasoning algorithms to use the annotated BCI evaluation reports to predict effect sizes for particular combinations of behaviours, interventions, populations and settings; d) build user and machine interfaces for interrogating and updating the knowledge base; and e) evaluate all the above in terms of performance and utility. Discussion The HBCP aims to revolutionise our ability to synthesise, interpret and deliver evidence on behaviour change interventions that is up-to-date and tailored to user need and context. This will enhance the usefulness, and support the implementation of, that evidence.
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The purpose of this systematic review and meta-analysis was to estimate the prevalence of personal weight control attempts (weight loss and/or maintenance) worldwide and to identify correlates, personal strategies used and the underlying motives. We included epidemiological/observational studies of adults (≥18 years) reporting prevalence of weight control attempts in the past-year. Seventy-two studies (n = 1,184,942) met eligibility criteria. Results from high quality studies showed that 42% of adults from general populations and 44% of adults from ethnic-minority populations reported trying to lose weight, and 23% of adults from general populations reported trying to maintain weight annually. In general population studies, higher prevalence of weight loss attempts was observed in the decade of 2000–2009 (48.2%), in Europe/Central Asia (61.3%) and in overweight/obese individuals and in women (p < 0.01). Of the 37 strategies (grouped in 10 domains of the Oxford Food and Activity Behaviours Taxonomy) and 12 motives reported for trying to control weight, exercising and dieting (within the energy compensation and restraint domains, respectively) and wellbeing and long-term health were the most prevalent. To our knowledge, this is the first systematic review to investigate weight control attempts worldwide. Key strategies and motives were identified which have implications for future public health initiatives on weight control.
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The purpose of this systematic review and meta-analysis was to estimate the prevalence of personal weight control attempts (weight loss and/or maintenance) worldwide and to identify correlates, personal strategies used and the underlying motives. We included epidemiological/observational studies of adults (≥18 years) reporting prevalence of weight control attempts in the past-year. Seventy-two studies (n = 1,184,942) met eligibility criteria. Results from high quality studies showed that 42% of adults from general populations and 44% of adults from ethnic-minority populations reported trying to lose weight, and 23% of adults from general populations reported trying to maintain weight annually. In general population studies, higher prevalence of weight loss attempts was observed in the decade of 2000–2009 (48.2%), in Europe/Central Asia (61.3%) and in overweight/obese individuals and in women (p < 0.01). Of the 37 strategies (grouped in 10 domains of the Oxford Food and Activity Behaviours Taxonomy) and 12 motives reported for trying to control weight, exercising and dieting (within the energy compensation and restraint domains, respectively) and wellbeing and long-term health were the most prevalent. To our knowledge, this is the first systematic review to investigate weight control attempts worldwide. Key strategies and motives were identified which have implications for future public health initiatives on weight control.
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Background: Understanding links between behaviour change techniques (BCTs) and mechanisms of action (the processes through which they affect behaviour) helps inform the systematic development of behaviour change interventions. Purpose: This research aims to develop and test a methodology for linking BCTs to their mechanisms of action. Methods: Study 1 (published explicit links): Hypothesised links between 93 BCTs (from the 93-item BCT taxonomy, BCTTv1) and mechanisms of action will be identified from published interventions and their frequency, explicitness and precision documented. Study 2 (expert-agreed explicit links): Behaviour change experts will identify links between 61 BCTs and 26 mechanisms of action in a formal consensus study. Study 3 (integrated matrix of explicit links): Agreement between studies 1 and 2 will be evaluated and a new group of experts will discuss discrepancies. An integrated matrix of BCT-mechanism of action links, annotated to indicate strength of evidence, will be generated. Study 4 (published implicit links): To determine whether groups of co-occurring BCTs can be linked to theories, we will identify groups of BCTs that are used together from the study 1 literature. A consensus exercise will be used to rate strength of links between groups of BCT and theories. Conclusions: A formal methodology for linking BCTs to their hypothesised mechanisms of action can contribute to the development and evaluation of behaviour change interventions. This research is a step towards developing a behaviour change 'ontology', specifying relations between BCTs, mechanisms of action, modes of delivery, populations, settings and types of behaviour.
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Background Many online interventions designed to promote health behaviors combine multiple behavior change techniques (BCTs), adopt different modes of delivery (MoD) (eg, text messages), and range in how usable they are. Research is therefore needed to examine the impact of these features on the effectiveness of online interventions. Objective This study applies Classification and Regression Trees (CART) analysis to meta-analytic data, in order to identify synergistic effects of BCTs, MoDs, and usability factors. Methods We analyzed data from Webb et al. This review included effect sizes from 52 online interventions targeting a variety of health behaviors and coded the use of 40 BCTs and 11 MoDs. Our research also developed a taxonomy for coding the usability of interventions. Meta-CART analyses were performed using the BCTs and MoDs as predictors and using treatment success (ie, effect size) as the outcome. ResultsFactors related to usability of the interventions influenced their efficacy. Specifically, subgroup analyses indicated that more efficient interventions (interventions that take little time to understand and use) are more likely to be effective than less efficient interventions. Meta-CART identified one synergistic effect: Interventions that included barrier identification/ problem solving and provided rewards for behavior change reported an average effect size that was smaller (ḡ=0.23, 95% CI 0.08-0.44) than interventions that used other combinations of techniques (ḡ=0.43, 95% CI 0.27-0.59). No synergistic effects were found for MoDs or for MoDs combined with BCTs. Conclusions Interventions that take little time to understand and use were more effective than those that require more time. Few specific combinations of BCTs that contribute to the effectiveness of online interventions were found. Furthermore, no synergistic effects between BCTs and MoDs were found, even though MoDs had strong effects when analyzed univariately in the original study.
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Background: Obesity levels continue to rise annually. Face-to-face weight loss consultations have previously identified mixed effectiveness and face high demand with limited resources. Therefore, alternative interventions, such as internet-delivered interventions, warrant further investigation. The aim was to assess whether internet-delivered weight loss interventions providing personalized feedback were more effective for weight loss in overweight and obese adults in comparison with control groups receiving no personalized feedback. Method: Nine databases were searched, and 12 studies were identified that met all inclusion criteria. Results: Meta-analysis, identified participants receiving personalized feedback via internet-delivered interventions, had 2.13 kg mean difference (SMD) greater weight loss (and BMI change, waist circumference change and 5% weight loss) in comparison with control groups providing no personalized feedback. This was also true for results at 3 and 6-month time points but not for studies where interventions lasted ≥12 months. Conclusion: This suggests that personalized feedback may be an important behaviour change technique (BCT) to incorporate within internet-delivered weight loss interventions. However, meta-analysis results revealed no differences between internet-delivered weight loss interventions with personalized feedback and control interventions ≥12 months. Further investigation into longer term internet-delivered interventions is required to examine how weight loss could be maintained. Future research examining which BCTs are most effective for internet-delivered weight loss interventions is suggested.
Without a complete published description of interventions, clinicians and patients cannot reliably implement interventions that are shown to be useful, and other researchers cannot replicate or build on research findings. The quality of description of interventions in publications, however, is remarkably poor. To improve the completeness of reporting, and ultimately the replicability, of interventions, an international group of experts and stakeholders developed the Template for Intervention Description and Replication (TIDieR) checklist and guide. The process involved a literature review for relevant checklists and research, a Delphi survey of an international panel of experts to guide item selection, and a face-to-face panel meeting. The resultant 12-item TIDieR checklist (brief name, why, what (materials), what (procedure), who intervened, how, where, when and how much, tailoring, modifications, how well (planned), how well (actually carried out)) is an extension of the CONSORT 2010 statement (item 5) and the SPIRIT 2013 statement (item 11). While the emphasis of the checklist is on trials, the guidance is intended to apply across all evaluative study designs. This paper presents the TIDieR checklist and guide, with a detailed explanation of each item, and examples of good reporting. The TIDieR checklist and guide should improve the reporting of interventions and make it easier for authors to structure the accounts of their interventions, reviewers and editors to assess the descriptions, and readers to use the information.
Within any discipline there is always a degree of variability. For medicine it takes the form of Health Professional’s behaviour, for education it’s the style and content of the classroom, and for health psychology, it can be found in patient’s behaviour, the theories used and clinical practice. Over recent years, attempts have been made to reduce this variability through the use of the Behaviour Change Technique Taxonomy, the COM-B and the Behaviour Change Wheel. This paper argues that although the call for better descriptions of what is done is useful for clarity and replication, this systematisation may be neither feasible nor desirable. In particular, it is suggested that the gaps inherent in the translational process from coding a protocol to behaviour will limit the effectiveness of reducing patient variability, that theory variability is necessary for the health and well-being of a discipline and that practice variability is central to the professional status of our practitioners. It is therefore argued that we should celebrate rather than remove this variability in order for our discipline to thrive and for us to remain as professionals rather than as technicians.