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Projeto de investigação
Evidence-based ICT tools for weight loss maintenance
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Testing motivational and self-regulatory mechanisms of action on device-measured physical activity in the context of a weight loss maintenance digital intervention: a secondary analysis of the NoHoW trial
Publication . Encantado, Jorge; Marques, Marta M.; Gouveia, Maria João; Santos, Inês; Sánchez-Oliva, David; O’Driscoll, Ruairi; Turicchi, Jake; Larsen, Sofus C.; Horgan, Graham; Teixeira, Pedro J.; Stubbs, R. James; Heitmann, Berit Lilienthal; Palmeira, António L.
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 under-
pinned 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 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 inde-
pendently. These changes yielded good results and both models presented very good fit to the data for both
outcome variables. 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 was 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.
Users’ experiences with the NoHow web-based toolkit with weight and activity tracking in weight loss maintenance: long-term randomized controlled trial
Publication . Mattila, Elina; Hansen, Susanne; Bundgaard, Lise; Ramsey, Lauren; Dunning, Alice; Silva, Marlene N.; Harjumaa, Marja; Ermes, Miikka; Marques, Marta M.; Matos, Marcela; Larsen, Sofus C.; Encantado, Jorge; Santos, Inês; Horgan, Graham; O'Driscoll, Ruairi; Turicchi, Jake; Duarte, Cristiana; Palmeira, António L.; Stubbs, R James; Heitmann, Berit Lilienthal; Lähteenmäki, Liisa
Background: Digital behavior change interventions (DBCIs) offer a promising channel for providing health promotion services. However, user experience largely determines whether they are used, which is a precondition for effectiveness.
Objective: The primary aim of this study is to evaluate user experiences with the NoHoW Toolkit (TK)-a DBCI that targets weight loss maintenance-over a 12-month period by using a mixed methods approach and to identify the main strengths and weaknesses of the TK and the external factors affecting its adoption. The secondary aim is to objectively describe the measured use of the TK and its association with user experience.
Methods: An 18-month, 2×2 factorial randomized controlled trial was conducted. The trial included 3 intervention arms receiving an 18-week active intervention and a control arm. The user experience of the TK was assessed quantitatively through electronic questionnaires after 1, 3, 6, and 12 months of use. The questionnaires also included open-ended items that were thematically analyzed. Focus group interviews were conducted after 6 months of use and thematically analyzed to gain deeper insight into the user experience. Log files of the TK were used to evaluate the number of visits to the TK, the total duration of time spent in the TK, and information on intervention completion.
Results: The usability level of the TK was rated as satisfactory. User acceptance was rated as modest; this declined during the trial in all the arms, as did the objectively measured use of the TK. The most appreciated features were weekly emails, graphs, goal setting, and interactive exercises. The following 4 themes were identified in the qualitative data: engagement with features, decline in use, external factors affecting user experience, and suggestions for improvements.
Conclusions: The long-term user experience of the TK highlighted the need to optimize the technical functioning, appearance, and content of the DBCI before and during the trial, similar to how a commercial app would be optimized. In a trial setting, the users should be made aware of how to use the intervention and what its requirements are, especially when there is more intensive intervention content.
Hair cortisol concentration, weight loss maintenance and body weight variability: a prospective study based on data from the european NoHoW trial
Publication . Larsen, Sofus C.; Turicchi, Jake; Christensen, Gitte L.; Larsen, Charlotte S.; Jørgensen, Niklas R.; Mikkelsen, Marie-Louise K.; Horgan, Graham; O’Driscoll, Ruairi; Michalowska, Joanna; Duarte, Cristiana; Scott, Sarah E.; Santos, Inês; Encantado, Jorge; Palmeira, António Labisa; Stubbs, R. James; Heitmann, Berit L.
Several cross-sectional studies have shown hair cortisol concentration to be associated with adiposity, but the relationship between hair cortisol concentration and longitudinal changes in measures of adiposity are largely unknown. We included 786 adults from the NoHoW trial, who had achieved a successful weight loss of ≥5% and had a body mass index of ≥25 kg/m2 prior to losing weight. Hair cortisol concentration (pg/mg hair) was measured at baseline and after 12 months. Body weight and body fat percentage were measured at baseline, 6-month, 12-month and 18-month visits. Participants weighed themselves at home ≥2 weekly using a Wi-Fi scale for the 18-month study duration, from which body weight variability was estimated using linear and non-linear approaches. Regression models were conducted to examine log hair cortisol concentration and change in log hair cortisol concentration as predictors of changes in body weight, change in body fat percentage and body weight variability. After adjustment for lifestyle and demographic factors, no associations between baseline log hair cortisol concentration and outcome measures were observed. Similar results were seen when analysing the association between 12-month concurrent development in log hair cortisol concentration and outcomes. However, an initial 12-month increase in log hair cortisol concentration was associated with a higher subsequent body weight variability between month 12 and 18, based on deviations from a nonlinear trend (β: 0.02% per unit increase in log hair cortisol concentration [95% CI: 0.00, 0.04]; P=0.016). Our data suggest that an association between hair cortisol concentration and subsequent change in body weight or body fat percentage is absent or marginal, but that an increase in hair cortisol concentration during a 12-month weight loss maintenance effort may predict a slightly higher subsequent 6-months body weight variability.
Evidence-based digital tools for weight loss maintenance: the NoHoW project
Publication . Stubbs, R. James; Duarte, Cristiana; Palmeira, António Labisa; Sniehotta, Falko F.; Horgan, Graham; Larsen, Sofus C.; Marques, Marta M.; Evans, Elizabeth H.; Ermes, Miikka; Harjumaa, Marja; Turicchi, Jake; O’Driscoll, Ruari; Scott, Sarah E.; Pearson, Beth; Ramsey, Lauren; Mattila, Elina; Matos, Marcela; Sacher, Paul; Woodward, Euan; Mikkelsen, Marie-Louise; Sainsbury, Kirby; Santos, Inês; Encantado, Jorge; Stalker, Carol; Teixeira, Pedro J.; Heitmann, Berit Lilienthal
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.
Consistent sleep onset and maintenance of body weight after weight loss: an analysis of data from the NoHoW trial
Publication . Larsen, Sofus C.; Horgan, Graham; Mikkelsen, Marie-Louise K.; Palmeira, António Labisa; Scott, Sarah; Duarte, Cristiana; Santos, Inês; Encantado, Jorge; O'Driscoll, Ruairi; Turicchi, Jake; Michalowska, Joanna; Stubbs, R. James; Heitmann, Berit L.
Background: Several studies have suggested that reduced sleep duration and quality are associated with an increased risk of obesity and related metabolic disorders, but the role of sleep in long-term weight loss maintenance (WLM) has not been thoroughly explored using prospective data.
Methods and findings: The present study is an ancillary study based on data collected on participants from the Navigating to a Healthy Weight (NoHoW) trial, for which the aim was to test the efficacy of an evidence-based digital toolkit, targeting self-regulation, motivation, and emotion regulation, on WLM among 1,627 British, Danish, and Portuguese adults. Before enrolment, participants had achieved a weight loss of ≥5% and had a BMI of ≥25 kg/m2 prior to losing weight. Participants were enrolled between March 2017 and March 2018 and followed during the subsequent 12-month period for change in weight (primary trial outcome), body composition, metabolic markers, diet, physical activity, sleep, and psychological mediators/moderators of WLM (secondary trial outcomes). For the present study, a total of 967 NoHoW participants were included, of which 69.6% were women, the mean age was 45.8 years (SD 11.5), the mean baseline BMI was 29.5 kg/m2 (SD 5.1), and the mean weight loss prior to baseline assessments was 11.4 kg (SD 6.4). Objectively measured sleep was collected using the Fitbit Charge 2 (FC2), from which sleep duration, sleep duration variability, sleep onset, and sleep onset variability were assessed across 14 days close to baseline examinations. The primary outcomes were 12-month changes in body weight (BW) and body fat percentage (BF%). The secondary outcomes were 12-month changes in obesity-related metabolic markers (blood pressure, low- and high-density lipoproteins [LDL and HDL], triglycerides [TGs], and glycated haemoglobin [HbA1c]). Analysis of covariance and multivariate linear regressions were conducted with sleep-related variables as explanatory and subsequent changes in BW, BF%, and metabolic markers as response variables. We found no evidence that sleep duration, sleep duration variability, or sleep onset were associated with 12-month weight regain or change in BF%. A higher between-day variability in sleep onset, assessed using the standard deviation across all nights recorded, was associated with weight regain (0.55 kg per hour [95% CI 0.10 to 0.99]; P = 0.016) and an increase in BF% (0.41% per hour [95% CI 0.04 to 0.78]; P = 0.031). Analyses of the secondary outcomes showed that a higher between-day variability in sleep duration was associated with an increase in HbA1c (0.02% per hour [95% CI 0.00 to 0.05]; P = 0.045). Participants with a sleep onset between 19:00 and 22:00 had the greatest reduction in diastolic blood pressure (DBP) (P = 0.02) but also the most pronounced increase in TGs (P = 0.03). The main limitation of this study is the observational design. Hence, the observed associations do not necessarily reflect causal effects.
Conclusion: Our results suggest that maintaining a consistent sleep onset is associated with improved WLM and body composition. Sleep onset and variability in sleep duration may be associated with subsequent change in different obesity-related metabolic markers, but due to multiple-testing, the secondary exploratory outcomes should be interpreted cautiously.
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Entidade financiadora
European Commission
Programa de financiamento
H2020
Número da atribuição
643309