Publications by authors named "Bourdeaudhuij I"

Background: Digital health interventions have gained momentum to change health behaviors such as physical activity (PA) and sedentary behavior (SB). Although these interventions show promising results in terms of behavior change, they still suffer from high attrition rates, resulting in a lower potential and accessibility. To reduce attrition rates in the future, there is a need to investigate the reasons why individuals stop using the interventions.

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Background: e- and mHealth interventions using self-regulation techniques like action and coping planning have the potential to tackle the worldwide problem of physical inactivity. However, they often use one-week self-regulation cycles, providing support toward an active lifestyle on a weekly basis. This may be too long to anticipate on certain contextual factors that may fluctuate from day to day and may influence physical activity.

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Background: Some types of sedentary behaviors tend to cluster in individuals or groups of older adults. Insight into how these different types of sedentary behavior cluster is needed, as recent research suggests that not all types of sedentary behavior may have the same negative effects on physical and mental health. Therefore, the aim of this study was to identify sex-specific typologies of older adults' sedentary behavior, and to examine their associations with health-related and socio-demographic factors.

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Background: Although healthy aging can be stimulated by the reduction of sedentary behavior, few interventions are available for older adults. Previous studies suggest that self-monitoring might be a promising behavior change technique to reduce older adults' sedentary behavior. However, little is known about older adults' experiences with a self-monitoring-based intervention aimed at the reduction of sedentary behavior.

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Article Synopsis
  • E- and m-health interventions show potential for modifying health behaviors, focusing on the effectiveness of different behavior change techniques (BCTs) like action planning, coping planning, and self-monitoring.
  • A study involving 473 adults tested these BCTs in various combinations to see their impact on physical activity and sedentary behavior over five weeks using the 'MyPlan2.0' intervention.
  • Results indicated that self-monitoring significantly increased physical activity and reduced sedentary behavior, while combining all three BCTs led to the greatest improvement in physical activity levels.
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Background: Electronic health (eHealth) and mobile health (mHealth) interventions have the potential to tackle the worldwide problem of physical inactivity. However, they often suffer from large attrition rates. Consequently, feasibility and acceptability of interventions have become important matters in the creation of e- and mHealth interventions.

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Background: Wearable trackers for monitoring physical activity (PA) and total sleep time (TST) are increasingly popular. These devices are used not only by consumers to monitor their behavior but also by researchers to track the behavior of large samples and by health professionals to implement interventions aimed at health promotion and to remotely monitor patients. However, high costs and accuracy concerns may be barriers to widespread adoption.

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Creating more physical activity-supportive built environments is recommended by the World Health Organization for controlling noncommunicable diseases. The IPEN (International Physical Activity and Environment Network) Adult Study was undertaken to provide international evidence on associations of built environments with physical activity and weight status in 12 countries on 5 continents ( > 14,000). This article presents reanalyzed data from eight primary papers to identify patterns of findings across studies.

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Background: Ecological momentary assessment (EMA) is a method of collecting real-time data based on repeated measures and observations that take place in participant's daily environment. EMA has many advantages over more traditional, retrospective questionnaires. However, EMA faces some challenges to reach its full potential.

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This study investigated parental influences on preschool children's healthy and unhealthy snacking in relation to child obesity in a large cross-sectional multinational sample. Parents and 3-5 year-old child dyads ( = 5185) in a kindergarten-based study provided extensive sociodemographic, dietary practice and food intake data. Parental feeding practices that were derived from questionnaires were examined for associations with child healthy and unhealthy snacking in adjusted multilevel models, including child estimated energy expenditure, parental education, and nutritional knowledge.

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Background: There is a limited understanding of components that should be included in digital interventions for 24-hour movement behaviors (physical activity [PA], sleep, and sedentary behavior [SB]). For intervention effectiveness, user engagement is important. This can be enhanced by a user-centered design to, for example, explore and integrate user preferences for intervention techniques and features.

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Background: This study aimed to investigate the effect of integrating a video intervention "Movie Models" within the Feel4Diabetes-study on specific parenting practices and related parental self-efficacy regarding children's physical activity, screen-time and eating behaviour in vulnerable families (i.e. families living in low socioeconomic municipalities and at risk for developing type 2 diabetes).

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Background: Leisure-time and transport activity domains are studied most often because they are considered more amenable to intervention, but to date evidence on these domains is limited. The aim of the present study was to examine patterns of socio-demographic correlates of adults' leisure-time and transport physical activity and how these associations varied across 17 cities in 12 countries.

Methods: Participants (N = 13,745) aged 18-66 years in the IPEN Adult study and with complete data on socio-demographic and self-reported physical activity characteristics were included.

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Background And Objectives: Reducing sedentary behavior contributes to healthy aging. In order to develop sedentary behavior interventions, insight is needed into older adults' perceptions of (reducing) sedentary behavior. Therefore, this systematic review aims to synthesize qualitative evidence of older adults' perceptions towards (a) the concept of sedentary behavior, (b) barriers and facilitators of sedentary behavior, and (c) solutions and strategies to reduce sedentary behavior.

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Background: The beneficial effects of physical activity (PA) for older adults are well known. However, few older adults reach the health guideline of 150 min per week of moderate-to-vigorous PA (MVPA). Electronic health (eHealth) interventions are effective in increasing PA levels in older adults in the short term but, rarely, intermediate-term effects after a period without the support of a website or an app have been examined.

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Background: Sedentary behavior occurs largely subconsciously, and thus specific behavior change techniques are needed to increase conscious awareness of sedentary behavior. Chief amongst these behavior change techniques is self-monitoring of sedentary behavior. The aim of this systematic review and meta-analysis was to evaluate the short-term effectiveness of existing interventions using self-monitoring to reduce sedentary behavior in adults.

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Background: Adopting an active lifestyle plays a key role in the prevention and management of chronic diseases such as type 2 diabetes mellitus (T2DM). Web-based interventions are able to alter health behaviors and show stronger effects when they are informed by a behavior change theory. MyPlan 2.

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Background: Sufficient physical activity and a limited amount of sedentary behaviour can prevent a range of chronic diseases. However, most adults do not meet the recommendations for physical activity and sedentary behaviour. Effective and engaging interventions are needed to change people's behaviour.

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Background: Adoption of an active lifestyle plays an important role in the management of type 2 diabetes. Online interventions targeting lifestyle changes in adults with type 2 diabetes have provided mixed results. Previous research highlights the importance of creating theory-based interventions adapted to the population's specific needs.

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Background: This paper investigated the independent and joint associations between aspects of the physical neighbourhood environment and social neighbourhood factors with BMI and overweight status in European adults.

Methods: Data from 5,199 participants in the SPOTLIGHT survey were analysed. Participants reported on their height, weight and perceptions of the neighbourhood.

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Plain English Summary: Society has to cope with a large burden of health issues. There is need to find solutions to prevent diseases and help individuals live healthier lifestyles. Individual needs and circumstances vary greatly and one size fit all solutions do not tend to work well.

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To date, no longitudinal studies examined the change in walking and cycling for transport as distinct outcomes over time and investigated the predictors of those changes. Therefore, this present study examined the change in odds of engagement in walking and cycling for transport as distinct outcomes among Belgian older adults over a three-year follow-up period, and examined factors (i.e.

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This study investigated barriers towards health behaviours (physical activity, limiting sedentary behaviour and healthy dietary habits) experienced by young European families living in vulnerable areas, from multiple perspectives (parents, teachers, local community workers). Focus groups were conducted in six European countries (Belgium, Bulgaria, Finland, Hungary, Greece and Spain). In each country, three focus groups were conducted with parents, one with teachers and one with local community workers.

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Background: Wearables for monitoring physical activity (PA) are increasingly popular. These devices are not only used by consumers to monitor their own levels of PA but also by researchers to track the behavior of large samples. Consequently, it is important to explore how accurately PA can be tracked via these devices.

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