Patients with coronary artery disease (CAD) are more sedentary compared with the general population, but contemporary cardiac rehabilitation (CR) programmes do not specifically target sedentary behaviour (SB). We developed a 12-week, hybrid (centre-based+home-based) Sedentary behaviour IntervenTion as a personaLisEd Secondary prevention Strategy (SIT LESS). The SIT LESS programme is tailored to the needs of patients with CAD, using evidence-based behavioural change methods and an activity tracker connected to an online dashboard to enable self-monitoring and remote coaching. Following the intervention mapping principles, we first identified determinants of SB from literature to adapt theory-based methods and practical applications to target SB and then evaluated the intervention in advisory board meetings with patients and nurse specialists. This resulted in four core components of SIT LESS: (1) patient education, (2) goal setting, (3) motivational interviewing with coping planning, and (4) (tele)monitoring using a pocket-worn activity tracker connected to a smartphone application and providing vibrotactile feedback after prolonged sedentary bouts. We hypothesise that adding SIT LESS to contemporary CR will reduce SB in patients with CAD to a greater extent compared with usual care. Therefore, 212 patients with CAD will be recruited from two Dutch hospitals and randomised to CR (control) or CR+SIT LESS (intervention). Patients will be assessed prior to, immediately after and 3 months after CR. The primary comparison relates to the pre-CR versus post-CR difference in SB (objectively assessed in min/day) between the control and intervention groups. Secondary outcomes include between-group differences in SB characteristics (eg, number of sedentary bouts); change in SB 3 months after CR; changes in light-intensity and moderate-to-vigorous-intensity physical activity; quality of life; and patients’ competencies for self-management. Outcomes of the SIT LESS randomised clinical trial will provide novel insight into the effectiveness of a structured, hybrid and personalised behaviour change intervention to attenuate SB in patients with CAD participating in CR.
MULTIFILE
Much research has been done into the relationship between students’ motivation to learn and their basic psychological needs as defined by the self-determination theory (autonomy, competence, relatedness). However, few studies have explored how these psychological needs relate to different types of maladaptive behavior in the classroom. To prevent or remedy such behavior, more insight into its relationships is required. The present study attempted to determine the relationship between maladaptive behavior of secondary school students (grades 8 and 9) and the degree to which both teachers and peers address their needs for competence, autonomy, and relatedness. Results show significant, negative correlations between maladaptive student behavior in the classroom and the extent to which students’ basic psychological needs are met by teachers and fellow students. Both teachers and fellow students play a role in students’ maladaptive behavior toward school and withdrawn behavior. When it comes to unfriendly behavior, the perceived support of teachers appears to be particularly relevant, while the role of peers is an important factor in delinquent behavior.
ObjectiveThe Plants for Joints (PFJ) intervention significantly improved pain, stiffness, and physical function, and metabolic outcomes, in people with metabolic syndrome-associated osteoarthritis (MSOA). This secondary analysis investigated its effects on body composition.MethodIn the randomized PFJ study, people with MSOA followed a 16-week intervention based on a whole-food plant-based diet, physical activity, and stress management, or usual care. For this secondary analysis, fat mass, muscle mass, and bone mineral density were measured using dual-energy X-ray absorptiometry (DEXA) for all participants. Additionally, in a subgroup (n = 32), hepatocellular lipid (HCL) content and composition of visceral adipose tissue (VAT) were measured using magnetic resonance spectroscopy (MRS). An intention-to-treat analysis with a linear-mixed model adjusted for baseline values was used to analyse between-group differences.ResultsOf 66 people randomized, 64 (97%) completed the study. The PFJ group experienced significant weight loss (−5.2 kg; 95% CI –6.9, −3.6) compared to controls, primarily from fat mass reduction (−3.9 kg; 95% CI –5.3 to −2.5). No significant differences were found in lean mass, muscle strength, or bone mineral density between groups. In the subgroup who underwent MRI scans, the PFJ group had a greater reduction in HCL (−6.5%; 95% CI –9.9, 3.0) compared to controls, with no observed differences in VAT composition.ConclusionThe PFJ multidisciplinary intervention positively impacted clinical and metabolic outcomes, and appears to significantly reduce body fat, including liver fat, while preserving muscle mass and strength.
MULTIFILE
Effectiveness of Supported Education for students with mental health problems, an experimental study.The onset of mental health problems generally occurs between the ages of 16 and 23 – the years in which young people follow postsecondary education, which is a major channel in ourso ciety to prepare for a career and enhance life goals. Several studies have shown that students with mental health problems have a higher chance of early school leaving. Supported Education services have been developed to support students with mental health to remain at school. The current project aims to study the effect of an individually tailored Supported Education intervention on educational and mental health outcomes of students with mental health problems at a university of applied sciences and a community college. To that end, a mixed methods design will be used. This design combines quantitative research (Randomized Controlled Trial) with qualitative research (focus groups, monitoring, interviews). 100 students recruited from the two educational institutes will be randomly allocated to either the intervention or control group.
The consistent demand for improving products working in a real-time environment is increasing, given the rise in system complexity and urge to constantly optimize the system. One such problem faced by the component supplier is to ensure their product viability under various conditions. Suppliers are at times dependent on the client’s hardware to perform full system level testing and verify own product behaviour under real circumstances. This slows down the development cycle due to dependency on client’s hardware, complexity and safety risks involved with real hardware. Moreover, in the expanding market serving multiple clients with different requirements can be challenging. This is also one of the challenges faced by HyMove, who are the manufacturer of Hydrogen fuel cells module (https://www.hymove.nl/). To match this expectation, it starts with understanding the component behaviour. Hardware in the loop (HIL) is a technique used in development and testing of the real-time systems across various engineering domain. It is a virtual simulation testing method, where a virtual simulation environment, that mimics real-world scenarios, around the physical hardware component is created, allowing for a detailed evaluation of the system’s behaviour. These methods play a vital role in assessing the functionality, robustness and reliability of systems before their deployment. Testing in a controlled environment helps understand system’s behaviour, identify potential issues, reduce risk, refine controls and accelerate the development cycle. The goal is to incorporate the fuel cell system in HIL environment to understand it’s potential in various real-time scenarios for hybrid drivelines and suggest secondary power source sizing, to consolidate appropriate hybridization ratio, along with optimizing the driveline controls. As this is a concept with wider application, this proposal is seen as the starting point for more follow-up research. To this end, a student project is already carried out on steering column as HIL