Abstract Background: Several interventions have been developed to improve physical health and lifestyle behaviour of people with a severe mental illness (SMI). Recently, we conducted a pragmatic cluster-randomised controlled trial which evaluated the efects of the one-year Severe Mental Illness Lifestyle Evaluation (SMILE) lifestyle intervention compared with usual care in clients with SMI. The SMILE intervention is a 12-month group-based lifestyle intervention with a focus on increased physical activity and healthy food intake. The aim of the current study was to explore the experiences of people with SMI and healthcare professionals (HCPs) regarding implementation feasibility of the SMILE intervention and the fdelity to the SMILE intervention. Methods: A process evaluation was conducted alongside the pragmatic randomized controlled trial. The experiences of clients and HCPs in the lifestyle intervention group were studied. First, descriptive data on the implementation of the intervention were collected. Next, semi-structured interviews with clients (n=15) and HCPs (n=13) were performed. Interviews were audiotaped and transcribed verbatim. A thematic analysis of the interview data was performed using MAXQDA software. In addition, observations of group sessions were performed to determine the fdelity to the SMILE intervention using a standardised form. Results: Ten out of 26 HCPs who conducted the group sessions discontinued their involvement with the intervention, primarily due to changing jobs. 98% of all planned group sessions were performed. Four main themes emerged from the interviews: 1) Positive appraisal of the SMILE intervention, 2) Suggestions for improvement of the SMILE intervention 3) Facilitators of implementation and 4) Barriers of implementation. Both clients and HCPs had positive experiences regarding the SMILE intervention. Clients found the intervention useful and informative. The intervention was found suitable and interesting for all people with SMI, though HCPs sometimes had to tailor the intervention to individual characteristics of patients (e.g., with respect to cognitive functioning). The handbook of the SMILE intervention was perceived as user-friendly and helpful by HCPs. Combining SMILE with daily tasks, no support from other team members, and lack of staf and time were experienced as barriers for the delivery of the intervention Conclusion: The SMILE intervention was feasible and well-perceived by clients and HCPs. However, we also identifed some aspects that may have hindered efective implementation and needs to be considered when implementing the SMILE intervention in daily practice
Abstract Background: Cardiovascular disease is the leading cause of the estimated 11–25 years reduced life expectancy for persons with serious mental illness (SMI). This excess cardiovascular mortality is primarily attributable to obesity, diabetes, hypertension, and dyslipidaemia. Obesity is associated with a sedentary lifestyle, limited physical activity and an unhealthy diet. Lifestyle interventions for persons with SMI seem promising in reducing weight and cardiovascular risk. The aim of this study is to evaluate the effectiveness and cost-effectiveness of a lifestyle intervention among persons with SMI in an outpatient treatment setting. Methods: The Serious Mental Illness Lifestyle Evaluation (SMILE) study is a cluster-randomized controlled trial including an economic evaluation in approximately 18 Flexible Assertive Community Treatment (FACT) teams in the Netherlands. The intervention aims at a healthy diet and increased physical activity. Randomisation takes place at the level of participating FACT-teams. We aim to include 260 outpatients with SMI and a body mass index of 27 or higher who will either receive the lifestyle intervention or usual care. The intervention will last 12 months and consists of weekly 2-h group meetings delivered over the first 6 months. The next 6 months will include monthly group meetings, supplemented with regular individual contacts. Primary outcome is weight loss. Secondary outcomes are metabolic parameters (waist circumference, lipids, blood pressure, glucose), quality of life and health related self-efficacy. Costs will be measured from a societal perspective and include costs of the lifestyle program, health care utilization, medication and lost productivity. Measurements will be performed at baseline and 3, 6 and 12 months. Discussion: The SMILE intervention for persons with SMI will provide important information on the effectiveness, cost-effectiveness, feasibility and delivery of a group-based lifestyle intervention in a Dutch outpatient treatment setting. Trial registration: Dutch Trial Registration NL6660, registration date: 16 November 2017.
Abstract Background Clients with severe mental illness (SMI) have overall poor physical health. SMI reduces life expectancy by 5–17 years, primarily due to physical comorbidity linked to cardiometabolic risks that are mainly driven by unhealthy lifestyle behaviours. To improve physical health in clients with SMI, key elements are systematic somatic screening and lifestyle promotion. The nurse-led GILL eHealth was developed for somatic screening and the imple‑ mentation of lifestyle activities in clients with SMI. Aims of this study are to evaluate the efectiveness of the GILL eHealth intervention in clients with SMI compared to usual care, and to evaluate the implementation process, and the experiences of clients and healthcare providers with GILL eHealth. Methods The GILL study encompasses a cluster-randomised controlled trial in approximately 20 mental health care facilities in the Netherlands. The randomisation takes place at the team level, assigning clients to the eHealth inter‑ vention or the usual care group. The GILL eHealth intervention consists of two complementary modules for somatic screening and lifestyle promotion, resulting in personalised somatic treatment and lifestyle plans. Trained mental health nurses and nurse practitioners will implement the intervention within the multidisciplinary treatment context, and will guide and support the participants in promoting their physical health, including cardiometabolic risk management. Usual care includes treatment as currently delivered, with national guidelines as frame of reference. We aim to include 258 clients with SMI and a BMI of 27 or higher. Primary outcome is the metabolic syndrome severity score. Secondary outcomes are physical health measurements and participants’ reports on physical activity, perceived lifestyle behaviours, quality of life, recovery, psychosocial functioning, and health-related self-efcacy. Measurements will be completed at baseline and at 6 and 12 months. A qualitative process evaluation will be conducted alongside, to evaluate the process of implementation and the experiences of clients and healthcare professionals with GILL eHealth. Discussion The GILL eHealth intervention is expected to be more efective than usual care in improving physical health and lifestyle behaviours among clients with SMI. It will also provide important information on implementation of GILL eHealth in mental health care. If proven efective, GILL eHealth ofers a clinically useful tool to improve physical health and lifestyle behaviours.
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.
