Poster presentation.There still is little empirical evidence on factors that influence GPs’ referral behavior to lifestyle interventions. The aim was to explore 1) GPs´ motivation to refer to lifestyle interventions and to investigate the association between GPs’ own lifestyle-behaviors and their referral behavior, and 2) patient indicators in the decision-making process of the GPs’ referral to lifestyle interventions.
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Abstract Background: Lifestyle interventions for severe mental illness (SMI) are known to have small to modest efect on physical health outcomes. Little attention has been given to patient-reported outcomes (PROs). Aim: To systematically review the use of PROs and their measures, and quantify the efects of lifestyle interventions in patients with SMI on these PROs. Methods: Five electronic databases were searched (PubMed/Medline, Embase, PsycINFO, CINAHL, and Web of Science) from inception until 12 November 2020 (PROSPERO: CRD42020212135). Randomised controlled trials (RCTs) evaluating the efcacy of lifestyle interventions focusing on healthy diet, physical activity, or both for patients with SMI were included. Outcomes of interest were PROs. Results: A total of 11.267 unique records were identifed from the database search, 66 full-text articles were assessed, and 36 RCTs were included, of which 21 were suitable for meta-analyses. In total, 5.907 participants were included across studies. Lifestyle interventions had no signifcant efect on quality of life (g=0.13; 95% CI=−0.02 to 0.27), with high heterogeneity (I2 =68.7%). We found a small efect on depression severity (g=0.30, 95% CI=0.00 to 0.58, I2 =65.2%) and a moderate efect on anxiety severity (g=0.56, 95% CI=0.16 to 0.95, I2 =0%). Discussion: This meta-analysis quantifes the efects of lifestyle interventions on PROs. Lifestyle interventions have no signifcant efect on quality of life, yet they could improve mental health outcomes such as depression and anxiety symptoms. Further use of patient-reported outcome measures in lifestyle research is recommended to fully capture the impact of lifestyle interventions.
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The combination of self-tracking and persuasive eCoaching in healthy lifestyle interventions is a promising approach. The objective of this study is to map the key components of existing healthy lifestyle interventions combining self-tracking and persuasive eCoaching using the scoping review methodology in accordance with the York methodological framework by Arksey and O’Malley. Seven studies were included in this preliminary scoping review. Components related to persuasive eCoaching applied only in effective interventions were reduction of complex behavior into small steps, providing positive motivational feedback by praise and providing reliable information to show expertise. Concerning self-tracking, it did not seem to matter if more action was required by the participant to obtain personal data. The first results of this study indicate the necessity to identify the needs and problems of the specific target group of the interventions, due to differences found between various groups of users. In addition to objective data on lifestyle and health behavior, other factors need to be taken into account, such as the context of use, daily experiences, and feelings of the users.
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Receiving the first “Rijbewijs” is always an exciting moment for any teenager, but, this also comes with considerable risks. In the Netherlands, the fatality rate of young novice drivers is five times higher than that of drivers between the ages of 30 and 59 years. These risks are mainly because of age-related factors and lack of experience which manifests in inadequate higher-order skills required for hazard perception and successful interventions to react to risks on the road. Although risk assessment and driving attitude is included in the drivers’ training and examination process, the accident statistics show that it only has limited influence on the development factors such as attitudes, motivations, lifestyles, self-assessment and risk acceptance that play a significant role in post-licensing driving. This negatively impacts traffic safety. “How could novice drivers receive critical feedback on their driving behaviour and traffic safety? ” is, therefore, an important question. Due to major advancements in domains such as ICT, sensors, big data, and Artificial Intelligence (AI), in-vehicle data is being extensively used for monitoring driver behaviour, driving style identification and driver modelling. However, use of such techniques in pre-license driver training and assessment has not been extensively explored. EIDETIC aims at developing a novel approach by fusing multiple data sources such as in-vehicle sensors/data (to trace the vehicle trajectory), eye-tracking glasses (to monitor viewing behaviour) and cameras (to monitor the surroundings) for providing quantifiable and understandable feedback to novice drivers. Furthermore, this new knowledge could also support driving instructors and examiners in ensuring safe drivers. This project will also generate necessary knowledge that would serve as a foundation for facilitating the transition to the training and assessment for drivers of automated vehicles.
Wheelchair users with a spinal cord injury (SCI) or amputation generally lead an inactive lifestyle, associated with reduced fitness and health. Digital interventions and sport and lifestyle applications (E-platforms) may be helpful in achieving a healthy lifestyle. Despite the potential positive effects of E-platforms in the general population, no studies are known investigating the effects for wheelchair users and existing E-platforms can not be used to the same extent and in the same manner by this population due to differences in physiology, body composition, exercise forms and responses, and risk injury. It is, therefore, our aim to adapt an existing E-platform (Virtuagym) within this project by using existing data collections and new data to be collected within the project. To reach this aim we intend to make several relevant databases from our network available for analysis, combine and reanalyze these existing databases to adapt the existing E-platform enabling wheelchair users to use it, evaluate and improve the use of the adapted E-platform, evaluate changes in healthy active lifestyle parameters, fitness, health and quality of life in users of the E-platform (both wheelchair users and general population) and identify determinants of these changes, identify factors affecting transitions from an inactive lifestyle, through an intermediate level, to an athlete level, comparing wheelchair users with the general population, and comparing Dutch with Brazilian individuals. The analysis of large datasets of exercise and fitness data from various types of individuals with and without disabilities, collected over the last years both in the Netherlands and Brazil, is an innovative and potentially fruitful approach. It is expected that the comparison of e.g. wheelchair users in Amsterdam vs. Sao Paulo or recreative athletes vs. elite athletes provides new insight in the factors determining a healthy and active lifestyle.
Wheelchair users with a spinal cord injury (SCI) or amputation generally lead an inactive lifestyle, associated with reduced fitness and health. Digital interventions and sport and lifestyle applications (E-platforms) may be helpful in achieving a healthy lifestyle. Despite the potential positive effects of E-platforms in the general population, no studies are known investigating the effects for wheelchair users and existing E-platforms can not be used to the same extent and in the same manner by this population due to differences in physiology, body composition, exercise forms and responses, and risk injury. It is, therefore, our aim to adapt an existing E-platform (Virtuagym) within this project by using existing data collections and new data to be collected within the project. To reach this aim we intend to make several relevant databases from our network available for analysis, combine and reanalyze these existing databases to adapt the existing E-platform enabling wheelchair users to use it, evaluate and improve the use of the adapted E-platform, evaluate changes in healthy active lifestyle parameters, fitness, health and quality of life in users of the E-platform (both wheelchair users and general population) and identify determinants of these changes, identify factors affecting transitions from an inactive lifestyle, through an intermediate level, to an athlete level, comparing wheelchair users with the general population, and comparing Dutch with Brazilian individuals. The analysis of large datasets of exercise and fitness data from various types of individuals with and without disabilities, collected over the last years both in the Netherlands and Brazil, is an innovative and potentially fruitful approach. It is expected that the comparison of e.g. wheelchair users in Amsterdam vs. Sao Paulo or recreative athletes vs. elite athletes provides new insight in the factors determining a healthy and active lifestyle.
