Background and purpose The aim of this study is to investigate changes in movement behaviors, sedentary behavior and physical activity, and to identify potential movement behavior trajectory subgroups within the first two months after discharge from the hospital to the home setting in first-time stroke patients. Methods A total of 140 participants were included. Within three weeks after discharge, participants received an accelerometer, which they wore continuously for five weeks to objectively measure movement behavior outcomes. The movement behavior outcomes of interest were the mean time spent in sedentary behavior (SB), light physical activity (LPA) and moderate to vigorous physical activity (MVPA); the mean time spent in MVPA bouts ≥ 10 minutes; and the weighted median sedentary bout. Generalized estimation equation analyses were performed to investigate overall changes in movement behavior outcomes. Latent class growth analyses were performed to identify patient subgroups of movement behavior outcome trajectories. Results In the first week, the participants spent an average, of 9.22 hours (67.03%) per day in SB, 3.87 hours (27.95%) per day in LPA and 0.70 hours (5.02%) per day in MVPA. Within the entire sample, a small but significant decrease in SB and increase in LPA were found in the first weeks in the home setting. For each movement behavior outcome variable, two or three distinctive subgroup trajectories were found. Although subgroup trajectories for each movement behavior outcome were identified, no relevant changes over time were found. Conclusion Overall, the majority of stroke survivors are highly sedentary and a substantial part is inactive in the period immediately after discharge from hospital care. Movement behavior outcomes remain fairly stable during this period, although distinctive subgroup trajectories were found for each movement behavior outcome. Future research should investigate whether movement behavior outcomes cluster in patterns.
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Purpose (1) To investigate the differences in the course of participation up to one year after stroke between distinct movement behavior patterns identified directly after discharge to the home setting, and (2) to investigate the longitudinal association between the development of movement behavior patterns over time and participation after stroke. Materials and methods 200 individuals with a first-ever stroke were assessed directly after discharge to the home setting, at six months and at one year. The Participation domain of the Stroke Impact Scale 3.0 was used to measure participation. Movement behavior was objectified using accelerometry for 14 days. Participants were categorized into three distinct movement behavior patterns: sedentary exercisers, sedentary movers and sedentary prolongers. Generalized estimating equations (GEE) were performed. Results People who were classified as sedentary prolongers directly after discharge was associated with a worse course of participation up to one year after stroke. The development of sedentary prolongers over time was also associated with worse participation compared to sedentary exercisers. Conclusions The course of participation after stroke differs across distinct movement behavior patterns after discharge to the home setting. Highly sedentary and inactive people with stroke are at risk for restrictions in participation over time. Implications for rehabilitation The course of participation in people with a first-ever stroke up to one year after discharge to the home setting differed based on three distinct movement behavior patterns, i.e., sedentary exercisers, sedentary movers and sedentary prolongers. Early identification of highly sedentary and inactive people with stroke after discharge to the home setting is important, as sedentary prolongers are at risk for restrictions in participation over time. Supporting people with stroke to adapt and maintain a healthy movement behavior after discharge to the home setting could prevent potential long-term restrictions in participation.
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Stroke is the second most common cause of death and the third leading cause of disability worldwide,1,2 with the burden expected to increase during the next 20 years.1 Almost 40% of the people with stroke have a recurrent stroke within 10 years,3 making secondary prevention vital.3,4 High amounts of sedentary time have been found to increase the risk of cardiovascular disease,5–11 particularly when the sedentary time is accumulated in prolonged bouts.12–15 Sedentary behavior, is defined as “any waking behavior characterized by an energy expenditure ≤1.5 Metabolic Equivalent of Task (METs) while in a sitting, reclining or lying posture”.16,17 Studies in healthy people, as well as people with diabetes and obesity, have shown that reducing the total amount of sedentary time and/or breaking up long periods of uninterrupted sedentary time, reduces metabolic risk factors associated with cardiovascular disease.6,9,10,12–15 Recent studies have shown that people living in the community after stroke spend more time each day sedentary, and more time in uninterrupted bouts of sedentary time compared to age-matched healthy peers.18–20 Reducing sedentary time and breaking up long sedentary bouts with short bursts of activity may be a promising intervention to reduce the risk of recurrent stroke and other cardiovascular diseases in people with stroke. To develop effective interventions, it is important to understand the factors associated with sedentary time in people with stroke. Previous studies have found associations between self-reported physical function after stroke and total sedentary time, but inconsistent results with regards to the relationship of age, stroke severity, and walking speed with sedentary time.20,21 These results are from secondary analyses of single-site observational studies, not powered to address associations, and inconsistent in the methods used to determine waking hours; thus making direct comparisons between studies difficult.20,21 Individual participant data pooling, with consistent processing of wake time data, allows novel exploratory analyses of larger datasets with greater power. By pooling all available individual participant data internationally, this study aimed to comprehensively explore the factors associated with sedentary time in community-dwelling people with stroke. Specifically, our research questions were: (1) What factors are associated with total sedentary time during waking hours after stroke? (2) What factors are associated with time spent in prolonged sedentary bouts during waking hours?
Movebite aims to combat the issue of sedentary behavior prevalent among office workers. A recent report of the Nederlandse Sportraad reveal a concerning trend of increased sitting time among Dutch employees, leading to a myriad of musculoskeletal discomforts and significant health costs for employers due to increased sick leave. Recognizing the critical importance of addressing prolonged sitting in the workplace, Movebite has developed an innovative concept leveraging cutting-edge technology to provide a solution. The Movebite app seamlessly integrates into workplace platforms such as Microsoft Teams and Slack, offering a user-friendly interface to incorporate movement into their daily routines. Through scalable AI coaching and real-time movement feedback, Movebite assists individuals in scheduling and implementing active micro-breaks throughout the workday, thereby mitigating the adverse effects of sedentary behavior. In collaboration with the Avans research group Equal Chance on Healthy Choices, Movebite conducts user-centered testing to refine its offerings and ensure maximum efficacy. This includes testing initiatives at sports events, where the diverse crowd provides invaluable feedback to fine-tune the app's features and user experience. The testing process encompasses both quantitative and qualitative approaches based on the Health Belief Model. Through digital questionnaires, Movebite aims to gauge users' perceptions of sitting as a health threat and the potential benefits of using the app to alleviate associated risks. Additionally, semi-structured interviews delve deeper into user experiences, providing qualitative insights into the app's usability, look, and feel. By this, Movebite aims to not only understand the factors influencing adoption but also to tailor its interventions effectively. Ultimately, the goal is to create an environment encouraging individuals to embrace physical activity in small, manageable increments, thereby fostering long-term engagement promoting overall well-being.Through continuous innovation and collaboration with research partners, Movebite remains committed to empowering individuals to lead healthier, more active lifestyles, one micro-break at a time.
Regular physical activity is considered to be an important component of a healthy lifestyle that decreases the risk of coronary heart disease, diabetes mellitus type 2, hypertension, colon and breast cancer, obesity and other debilitating conditions. Physical activity can also improve functional capacity and therefore also the quality of life in older adults. Despite all these favorable aspects, a substantial part of the Dutch older adult population is still underactive or even sedentary. To change this for the better, the Groningen Active Living Model (GALM) was developed.Aim of GALM is to stimulate recreational sports activities in sedentary and underactive older adults in the 55-65 age band. After a door-to-door visit as part of an intensive recruitment phase, a fitness test was conducted followed by the GALM recreational sports program. This program was based on principles from evolutionary-biological play theory and insights fromsocial cognitive theory. The program was versatile in nature (e.g. softball, dance, self-defense, swimming, athletics, etc.) in two main ways: a) to improve compliance with the program different sports were offered, which was reported to be more appealing for older adults; b) by aiming at more components of motor fitness (e.g. strength, flexibility, speed, endurance and coordination). Between 1997 and 2005 more than 552,000 persons were visited door-to-door, over 55,700 were tested, and 41,310 participated in the GALM recreational sports program. The aim of the present thesis is to determine the effects of participation in the GALM recreational sports program on physical activity, health and fitness outcomes.Chapter 2 describes the effectiveness of the GALM recruitment in selecting and recruiting sedentary and underactive older adults. Three municipalities in the Netherlands were selected, and in every municipality four neighborhoods were included. Two of each of the four neighborhoods were randomly assigned as intervention and the others as control neighborhoods. In total, 8,504 persons were mailed and received a home visit. During this home visit the GALM recruitment questionnaire was collected on which the selection between sedentary/underactive and physically active older adults was based. Ultimately we succeeded inincluding 12.3% (315 of the 2,551 qualifying) of the older adults, 79.4% of whom could be indeed considered sedentary or underactive. The cost of successfully recruiting an older adult was estimated at $84.To assess the effects of a physical activity intervention on health and fitness and explain the results, it is necessary to know program characteristics regarding frequency, intensity, time and content of the activities. With respect to the GALM recreational sports activity program, the only unknown characteristic was intensity. Chapter 3 describes the intensity of this program systematically. Using heart rate monitors, data of 97 persons (mean age 60.1 yr) were collected in three municipalities. The mean intensity of all 15 GALM sessions was 73.7% of the predicted maximal heart rate. Six percent of the monitored heart rate time could be classified as light, 33% as moderate and 61% as hard. In summary, the GALM recreational sports program meets the 1998 ACSM recommendations for intensity necessary to improve cardiorespiratory fitness.Chapters 4 and 5 describe the effects of 6 and 12 months of participation in the GALM recreational sports program, and 181 persons were followed over time. Results after 6 months revealed only few significant between-group differences favoring the intervention group (i.e. sleep, diastolic blood pressure, perceived fitness score and grip strength). Changes in energyexpenditure for leisure-time physical activities (EELTPA) showed an increase in both study groups. From 6 to 12 months a decrease in EELTPA occurred in the intervention group and an increase in the control group. The significant positive time effects for the health outcomes (diastolic blood pressure, BMI, percentage of body fat) that were found after 6 months were diminishedfrom 6 to 12 months. However, the energy expenditure for recreational sports activities (EERECSPORT) demonstrated a continuous increase over 12 months. Parallel to this, significant main effects for time were found in performance-based fitness outcomes (i.e. simple reaction time, leg strength, flexibility of hamstrings and lower back, and aerobic endurance). After 12 months only a significant between-group difference for flexibility of the hamstrings andlower back was found, favoring the control group. In conclusion, a short-term increase in EELTPA was found with accompanying improvements in health outcomes that more or less disappeared in 6 to 12 months. In the long term, results showed a continuous increase in EERECSPORT and performance-based fitness. This latter increase is probably a reflection of the significantimprovement over time in EERECSPORT and the fact that recreational sports activities are of a higher intensity.Aerobic endurance is regarded as the most important component of motor fitness that is relevant for older adults to function independently. In Chapter 6, the development in aerobic endurance after 18 months of participation in the GALM recreational sports program was assessed by means of changes in heart rate during fixed submaximal exercise. Since both groups were comparable regarding changes in energy expenditure for physical activity after 6 months and testing confirmed this, both groups were combined and considered as one group. Multilevel analyses were conducted and models for change were developed. A significant decrease in heart rate over time was found at all walking speeds (4, 5, 6 and 7 km/h). The average decrease in heart rate was 5.5, 6.0, 10.0 and 9.0 beats/min for the 4, 5, 6 and 7 km/h walking speeds, respectively. The relative decrease varied from 5.1 to 7.4% relative to average heart rates at baseline. These results illustrate that participation in the GALM recreational sports program has a positive significant effect on aerobic endurance, and that the participants are able to perform at submaximal intensity more easily.Based on the overall results it can be concluded that this study contributes to the field in how to effectively recruit sedentary and underactive older adults and stimulate them to become and stay active in recreational sports activities. As far as we know, this recruitment in combination with the recreational sport program is not only unique but also effective toward increasing performance-based fitness in the long term. Short-term effects were found in other leisure-time activities and health outcomes. To further stimulate other leisure-time and probably health outcomes besides the favorable effects that were already seen, additional interventions that pay more attention to behavioral change in terms of how to integrate other activities besides sports activities are recommended.
