Movement Behavior Patterns in People With First-Ever Stroke

Perceived social support on objective measured sedentary behavior of stroke patients: the mediating role of exercise self-efficacy

Introduction

As stroke patients may have impaired motor function, there may have increased sedentary behavior. Factors associated with sedentary behavior need to be explored to develop targeted interventions. Although studies explore the effects of exercise self-efficacy and perceived social support on sedentary behavior, the relationship is not clear. The aim of this study was to explore the mediating effect of exercise self-efficacy on perceived social support and objective measured sedentary behavior in stroke patients.

Methods

The random sampling method was adopted to select 275 stroke patients from the neurology department of a third-grade hospital of Henan Province from June 2023 to March 2024 in a cross-sectional descriptive study. A general data questionnaire, exercise self-efficacy scale, perceived social support scale, and ActiGraph GT3X accelerometer were used to investigate. The structural equation model was used to analyze the mediating effect of exercise self-efficacy between perceived social support and sedentary behavior.

Results

The mean sedentary behavior time in stroke patients in this study was (479.65 ± 112.65) min, the mean score of perceived social support was (47.53 ± 17.16), and the mean score of exercise self-efficacy was (24.19 ± 6.25). The correlation analysis revealed that, the sedentary behavior of stroke patients was negatively correlated with exercise self-efficacy and perceived social support. The results of the mediation analysis showed that exercise self-efficacy played a partial mediating role between perceived social support and sedentary behavior.

Conclusion

Perceived social support and exercise self-efficacy were influential factors in sedentary behavior. Moreover, the impact of perceived social support on sedentary behavior was partially mediated by exercise self-efficacy. Therefore, to decrease the sedentary behavior, it is crucial to improve the level of perceived social support in stroke patients. Patients with less perceived social support can improve their exercise self-efficacy and thus perceive more social support.

Improving Movement Behavior in People after Stroke with the RISE Intervention: A Randomized Multiple Baseline Study

Objective: High amounts of sedentary behavior increase the risk of cardiovascular disease. This study aimed to determine the preliminary effectiveness and feasibility of the RISE intervention to support community-dwelling people with stroke, who are highly sedentary, to reduce and interrupt sedentary time. Additionally, the added value of including participatory support was determined. Methods: A randomized, multiple-baseline study was conducted including 14 participants. All received the RISE intervention, a 15-week blended behavioral intervention in which a primary care physiotherapist provided personalized coaching in the home setting by using behavior-change techniques and the RISE eCoaching system, including an activity monitor and app to provide real time feedback. Half of the participants (randomly allocated) received participatory support from someone from their social network (e.g., partner or close friend) who joined them in the intervention. Preliminary effectiveness was determined with significant changes in total sedentary time and fragmentation (interruption) of sedentary time using a randomization test. Feasibility was assessed by adherence with the intervention protocol, safety, and satisfaction with the intervention. Results: Participants significantly reduced total sedentary time (p = 0.01) by 1.3 h on average and increased their fragmentation (p < 0.01). Subgroup analyses showed significant improvements in both outcomes only in the group with participatory support. Thirteen (92.9%) participants completed the intervention, no related adverse events occurred, and the reported participant satisfaction was sufficient. Conclusions: The RISE intervention appears promising to support people with stroke who are highly sedentary to reduce and interrupt their sedentary time. Participatory support appears to contribute to greater results. Trial registration: ISRCTN international trial registry, 10694741.

Measurement properties of activity monitoring for a rehabilitation (AMoR) platform in post-stroke individuals in a simulated home environment

AIM

The aim of this study was to evaluate the measurement properties of activity monitoring for a rehabilitation (AMoR) platform for step counting, time spent in sedentary behavior, and postural changes during activities of daily living (ADLs) in a simulated home environment.

METHODS

Twenty-one individuals in the post-stroke chronic phase used the AMoR platform during an ADL protocol and were monitored by a video camera. Spearman's correlation coefficient, mean absolute percent error (MAPE), intraclass correlation coefficient (ICC), and Bland-Altman plot analyses were used to estimate the validity and reliability between the AMoR platform and the video for step counting, time spent sitting/lying, and postural changes from sit-to-stand (SI-ST) and sit-to-stand (ST-SI).

RESULTS

Validity of the platform was observed with very high correlation values for step counting (rs = 0.998) and time spent sitting/lying (rs = 0.992) and high correlation for postural change of SI-ST (rs = 0.850) and ST-SI (rs = 0.851) when compared to the video. An error percentage above 5% was observed only for the SI-ST postural change (7.13%). The ICC values show excellent agreement for step counting (ICC3, k = 0.999) and time spent sitting/lying (ICC3, k = 0.992), and good agreement for SI-ST (ICC3, k = 0.859) and ST-SI (ICC3, k = 0.936) postural change. Values of the differences for step counting, sitting/lying time, and postural change were within the limits of agreement according to the analysis of the Bland-Altman graph.

CONCLUSION

The AMoR platform presented validity and reliability for step counting, time spent sitting/lying, and identification of SI-ST and ST-SI postural changes during tests in a simulated environment in post-stroke individuals.

Accelerometer-Measured Behavior Patterns in Incident Cerebrovascular Disease: Insights for Preventative Monitoring From the UK Biobank

BACKGROUND

The goal was to compare patterns of physical activity (PA) behaviors (sedentary behavior [SB], light PA, moderate-to-vigorous PA [MVPA], and sleep) measured via accelerometers for 7 days between patients with incident cerebrovascular disease (CeVD) (n=2141) and controls (n=73 938).

METHODS AND RESULTS

In multivariate models, cases spent 3.7% less time in MVPA (incidence rate ratio [IRR], 0.963 [95% CI, 0.929-0.998]) and 1.0% more time in SB (IRR, 1.010 [95% CI, 1.001-1.018]). Between 12 and 24 months before diagnosis, cases spent more time in SB (IRR, 1.028 [95% CI, 1.001-1.057]). Within the year before diagnosis, cases spent less time in MVPA (IRR, 0.861 [95% CI, 0.771-0.964]). Although SB time was not associated with CeVD risk, MVPA time, both total min/d (hazard ratio [HR], 0.998 [95% CI, 0.997-0.999]) and guideline threshold adherence (≥150 min/wk) (HR, 0.909 [95% CI, 0.827-0.998]), was associated with decreased CeVD risk. Comorbid burden had a significant partial mediation effect on the relationship between MVPA and CeVD. Cases slept more during 12:00 to 17:59 hours (IRR, 1.091 [95% CI, 1.002-1.191]) but less during 0:00 to 5:59 hours (IRR, 0.984 [95% CI, 0.977-0.992]). No between-group differences were significant at subgroup analysis.

CONCLUSIONS

Daily behavior patterns were significantly different in patients before CeVD. Although SB was not associated with CeVD risk, the association between MVPA and CeVD risk is partially mediated by comorbid burden. This study has implications for understanding observable behavior patterns in cerebrovascular dysfunction and may help in developing remote monitoring strategies to prevent or reduce cerebrovascular decline.

Movement Patterns in Older Adults Recovering From Hip Fracture

The aim of this study was to quantify physical activity and sedentary behavior in older adults recovering from hip fracture and to identify groups based on movement patterns. In this cross-sectional cohort study, older adults (≥70 years) were included 3 months after surgery for proximal femoral fracture. Patients received an accelerometer for 7 days. Demographics and outcomes related to physical function, mobility, cognitive functions, quality of life, and hip fracture were assessed. In total, 43 patients with sufficient accelerometer wear time were included. Across all groups, participants engaged in very low levels of physical activity, spending an average of 11 hr/day in prolonged sedentary behavior. Based on the extracted components from a principal component analysis, three groups with substantial differences in levels of physical activity and sedentary behavior could be distinguished.

Highlighting Unseen Activity Through 48-Hour Continuous Measurement in Subacute Stroke Rehabilitation: Preliminary Cohort Study

BACKGROUND

Motor impairments not only lead to a significant reduction in patient activity levels but also trigger a further deterioration in motor function due to deconditioning, which is an issue that is particularly pronounced during hospitalization. This deconditioning can be countered by sustaining appropriate activity levels. Activities that occur outside of scheduled programs, often overlooked, are critical in this context. Wearable technology, such as smart clothing, provides a means to monitor these activities.

OBJECTIVE

This study aimed to observe activity levels in patients who had strokes during the subacute phase, focusing on both scheduled training sessions and other nontraining times in an inpatient rehabilitation environment. A smart clothing system is used to simultaneously measure heart rate and acceleration, offering insights into both the amount and intensity of the physical activity.

METHODS

In this preliminary cohort study, 11 individuals undergoing subacute stroke rehabilitation were enrolled. The 48-hour continuous measurement system, deployed at admission and reassessed 4 weeks later, monitored accelerometry data for physical activity (quantified with a moving SD of acceleration [MSDA]) and heart rate for intensity (quantified with percent heart rate reserve). The measurements were performed using a wearable activity monitoring system, the hitoe (NTT Corporation and Toray Industries, Inc) system comprising a measuring garment (wear or strap) with integrated electrodes, a data transmitter, and a smartphone. The Functional Independence Measure was used to assess the patients' daily activity levels. This study explored factors such as differences in activity during training and nontraining periods, correlations with activities of daily living (ADLs) and age, and changes observed after 4 weeks.

RESULTS

A significant increase was found in the daily total MSDA after the 4-week program, with the average percent heart rate reserve remaining consistent. Physical activity during training positively correlated with ADL levels both at admission (ρ=0.86, P<.001) and 4 weeks post admission (ρ=0.96, P<.001), whereas the correlation between age and MSDA was not significant during training periods at admission (ρ=-0.41, P=.21) or 4 weeks post admission (ρ=-0.25, P=.45). Conversely, nontraining activity showed a negative correlation with age, with significant negative correlations with age at admission (ρ=-0.82, P=.002) and 4 weeks post admission (ρ=-0.73, P=.01).

CONCLUSIONS

Inpatient rehabilitation activity levels were positively correlated with ADL levels. Further analysis revealed a strong positive correlation between scheduled training activities and ADL levels, whereas nontraining activities showed no such correlation. Instead, a negative correlation between nontraining activities and age was observed. These observations suggest the importance of providing activity opportunities for older patients, while it may also suggest the need for adjusting the activity amount to accommodate the potentially limited fitness levels of this demographic. Future studies with larger patient groups are warranted to validate and further elucidate these findings.

Riding waves to improve functioning: a quantitative evaluation of a Surf Week in individuals with chronic phase brain injury with six months follow-up

PURPOSE

Environmental enrichment seems to enable people in the chronic phase of acquired brain injury (ABI) to experience new functional abilities and motor/coping strategies and consequently to become more adaptable which might prevent/reverse functional decline. This study describes the influence of a five-days Surf Week program on participants on physical function, self-efficacy, functional balance performance and self-perceived recovery.

MATERIALS AND METHODS

A multiple-baseline single-case design was used. Adults participating in the Surf Week in chronic phase of ABI were eligible to participate. Participants completed a battery of tests monitoring physical function, self-efficacy, functional balance performance and self-perceived recovery. This battery was repeated 5 times over a 1-year period, two times pre-Surf Week, three times post-Surf Week. Visual data inspection with two non-overlap methods were used to determine if patients showed sustained improvement in outcomes post-intervention.

RESULTS

A moderate to strong indication for improvements on physical function, functional balance performance and self-perceived recovery exists till six months follow-up. No indication was observed on self-efficacy till six months follow-up.

CONCLUSIONS

A five-days Surf Week is a physically, cognitively and socially intensive stimulating activity that can positively challenge individuals after ABI and seems to improve physical functioning, functional balance performance and self-perceived recovery.

Factors related to high-risk movement behaviour in people with stroke who are highly sedentary and inactive

PURPOSE

To identify Capabilities, Opportunities, and Motivational factors influencing movement behaviour throughout the day in people with stroke who are highly sedentary and inactive to enable intervention development.

METHODS

A qualitative study was conducted using semistructured interviews with people with stroke. The interview guide was based on the Capabilities, Opportunities, and Motivation Behavioural model.

RESULTS

Eleven interviews were conducted. Participants reported a lack of knowledge regarding healthy movement behaviour patterns, a lack of insight into their own movement behaviour, and some physical and cognitive limitations to engage in certain physical activities. Several social and environmental elements affecting movement behaviours were mentioned, their impact on movement behaviour varied among participants. Movement behaviour was mostly driven by habits and daily routine, without conscious regulation.

CONCLUSION

Our findings show that people with stroke are unaware of their own movement behaviour or of the consequences of these behaviours on health. Movement behaviour is, for the most part, based on daily routine and personal habits. This indicates the need for a behaviour change intervention. Such interventions will need to include providing information about healthy movement behaviour, feedback on individual's movement behaviour and individualized support, taking into account the social and environmental context and personal capabilities.

Identifying Unique Subgroups of Individuals With Stroke Using Heart Rate and Steps to Characterize Physical Activity

Background Low physical activity (PA) is associated with poor health outcomes after stroke. Step counts are a common metric of PA; however, other physiologic signals (eg, heart rate) may help to identify subgroups of individuals poststroke at varying levels of risk of poor health outcomes. Here, we aimed to identify clinically relevant subgroups of individuals poststroke based on PA profiles that leverage multiple data sources, including step count and heart rate data, from wearable devices. Methods and Results Seventy individuals poststroke participated. Participants wore a Fitbit Inspire 2 for 1 year and completed clinical assessments. We defined a group-based steps-per-minute threshold and an individual heart rate threshold to categorize each minute of PA into 1 of 4 states: high steps/high heart rate, low steps/low heart rate, high steps/low heart rate, and low steps/high heart rate. We used the proportion of time spent in each state along with steps per day, sedentary time, mean steps among minutes with high steps and high heart rate, and resting heart rate in a k-means clustering algorithm to identify subgroups and compared Activity Measure for Post-Acute Care Mobility T Score, Stroke Impact Scale, and gait speed among subgroups. We identified 3 subgroups, Active (n=8), Sedentary (n=29), and Deconditioned (n=33), which differed significantly on all clustering variables except resting heart rate. We observed significant differences in Activity Measure for Post-Acute Care Mobility T scores between subgroups, with the Deconditioned subgroup exhibiting the lowest score. Conclusions Quantifying PA with heart rate and step count using readily available wearable devices can identify clinically meaningful subgroups of individuals poststroke.

Perspectives of Rehabilitation Professionals on Implementing a Validated Home Telerehabilitation Intervention for Older Adults in Geriatric Rehabilitation: Multisite Focus Group Study

BACKGROUND

Owing to demographic trends and increasing health care costs, quick discharge with geriatric rehabilitation at home is advised and recommended for older adults. Telerehabilitation has been identified as a promising tool to support rehabilitation at home. However, there is insufficient knowledge about how to implement a validated home telerehabilitation system in other contexts. One of the major challenges for rehabilitation professionals is transitioning to a blended work process in which human coaching is supplemented via digital care.

OBJECTIVE

The study aimed to gain an in-depth understanding of the factors that influence the implementation of an evidence-based sensor monitoring intervention (SMI) for older adults by analyzing the perspectives of rehabilitation professionals working in 2 different health ecosystems and mapping SMI barriers and facilitators.

METHODS

We adopted a qualitative study design to conduct 2 focus groups, 1 in person in the Netherlands during winter of 2017 and 1 on the web via Zoom (Zoom Video Communications; owing to the COVID-19 pandemic) in Canada during winter of 2022, to explore rehabilitation providers' perspectives about implementing SMI. Qualitative data obtained were analyzed using thematic analysis. Participants were a group of rehabilitation professionals in the Netherlands who have previously worked with the SMI and a group of rehabilitation professionals in the province of Manitoba (Canada) who have not previously worked with the SMI but who were introduced to the intervention through a 30-minute web-based presentation before the focus group.

RESULTS

The participants expressed different characteristics of the telerehabilitation intervention that contributed to making the intervention successful for at-home rehabilitation: focus on future participation goals, technology support provides the rehabilitation professionals with objective and additional insight into the daily functioning of the older adults at home, SMI can be used as a goal-setting tool, and SMI deepens their contact with older adults. The analysis showed facilitators of and barriers to the implementation of the telerehabilitation intervention. These included personal or client-related, therapist-related, and technology-related aspects.

CONCLUSIONS

Rehabilitation professionals believed that telerehabilitation could be suitable for monitoring and supporting older adults' rehabilitation at home. To better guide the implementation of telerehabilitation in the daily practice of rehabilitation professionals, the following steps are needed: ensuring that technology is feasible for communities with limited digital health literacy and cognitive impairments, developing instruction tools and guidelines, and training and coaching of rehabilitation professionals.

Effects of a multidisciplinary intervention to promote physical activity in patients with stroke undergoing rehabilitation: study protocol for the ActivePAS pilot randomised controlled trial

Introduction

Physical activity after stroke is related to functional recovery and outcomes. To optimise physical activity adapted to a patient's walking ability and characteristics, multidisciplinary support and interventions are required. The Activate Physical Activity for Stroke pilot randomised controlled trial aims to assess the safety and feasibility of a multidisciplinary intervention that promotes physical activity in patients who had a stroke undergoing rehabilitation.

Methods and analysis

This single-centre, randomised controlled trial will enrol 32 patients who had a stroke undergoing rehabilitation. Patients who had a stroke with the ability to walk 50 m with at least hand assistance, regardless of the use of braces or walking aids, and aged≥20 years will be randomly allocated to a multidisciplinary intervention group or control group. Patients in the intervention group will receive instructions for the self-monitoring of hospitalised physical activity and support to promote physical activity by multidisciplinary staff. The primary outcome of the present study is the safety (adverse events) and feasibility (retention and completion rates) of the multidisciplinary intervention. We assess physical activity using a triaxial accelerometer (UW-204NFC, A&D Company) as one of the secondary outcomes.

Ethics and dissemination

The present study has been approved by the Research Ethics Committee of Konan Women's University and the Ethics Committee of Nishi-Kinen Port Island Rehabilitation Hospital. We will disseminate the results of the present study through a peer-reviewed manuscript and presentations at international conferences.

Trial registration number

UMIN000046731.

Beyond steps per day: other measures of real-world walking after stroke related to cardiovascular risk

Background

Significant variability exists in how real-world walking has been measured in prior studies in individuals with stroke and it is unknown which measures are most important for cardiovascular risk. It is also unknown whether real-world monitoring is more informative than laboratory-based measures of walking capacity in the context of cardiovascular risk. The purpose of this study was to determine a subset of real-world walking activity measures most strongly associated with systolic blood pressure (SBP), a measure of cardiovascular risk, in people with stroke and if these measures are associated with SBP after accounting for laboratory-based measures of walking capacity.

Methods

This was a cross-sectional analysis of 276 individuals with chronic (≥ 6 months) stroke. Participants wore an activity monitor for ≥ 3 days. Measures of activity volume, activity frequency, activity intensity, and sedentary behavior were calculated. Best subset selection and lasso regression were used to determine which activity measures were most strongly associated with systolic blood pressure. Sequential linear regression was used to determine if these activity measures were associated with systolic blood pressure after accounting for walking capacity (6-Minute Walk Test).

Results

Average bout cadence (i.e., the average steps/minute across all bouts of walking) and the number of long (≥ 30 min) sedentary bouts were most strongly associated with systolic blood pressure. After accounting for covariates (ΔR² = 0.089, p < 0.001) and walking capacity (ΔR² = 0.002, p = 0.48), these activity measures were significantly associated with systolic blood pressure (ΔR² = 0.027, p = 0.02). Higher systolic blood pressure was associated with older age (β = 0.219, p < 0.001), male gender (β = − 0.121, p = 0.046), black race (β = 0.165, p = 0.008), and a slower average bout cadence (β = − 0.159, p = 0.022).

Conclusions

Measures of activity intensity and sedentary behavior may be superior to commonly used measures, such as steps/day, when the outcome of interest is cardiovascular risk. The relationship between walking activity and cardiovascular risk cannot be inferred through laboratory-based assessments of walking capacity.

The longitudinal association between movement behavior patterns and the course of participation up to one year after stroke

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 rehabilitationThe 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.

Movement behavior patterns composition remains stable, but individuals change their movement behavior pattern over time in people with a first-ever stroke

BACKGROUND

Movement behaviors (i.e., physical activity levels, sedentary behavior) in people with stroke are not self-contained but cluster in patterns. Recent research identified three commonly distinct movement behavior patterns in people with stroke. However, it remains unknown if movement behavior patterns remain stable and if individuals change in movement behavior pattern over time.

OBJECTIVES

1) To investigate the stability of the composition of movement behavior patterns over time, and 2) determine if individuals change their movement behavior resulting in allocation to another movement behavior pattern within the first two years after discharge to home in people with a first-ever stroke.

METHODS

Accelerometer data of 200 people with stroke of the RISE-cohort study were analyzed. Ten movement behavior variables were compressed using Principal Componence Analysis and K-means clustering was used to identify movement behavior patterns at three weeks, six months, one year, and two years after home discharge. The stability of the components within movement behavior patterns was investigated. Frequencies of individuals' movement behavior pattern and changes in movement behavior pattern allocation were objectified.

RESULTS

The composition of the movement behavior patterns at discharge did not change over time. At baseline, there were 22% sedentary exercisers (active/sedentary), 45% sedentary movers (inactive/sedentary) and 33% sedentary prolongers (inactive/highly sedentary). Thirty-five percent of the stroke survivors allocated to another movement behavior pattern within the first two years, of whom 63% deteriorated to a movement behavior pattern with higher health risks. After two years there were, 19% sedentary exercisers, 42% sedentary movers, and 39% sedentary prolongers.

CONCLUSIONS

The composition of movement behavior patterns remains stable over time. However, individuals change their movement behavior. Significantly more people allocated to a movement behavior pattern with higher health risks. The increase of people allocated to sedentary movers and sedentary prolongers is of great concern. It underlines the importance of improving or maintaining healthy movement behavior to prevent future health risks after stroke.

People with Stroke Are Most Sedentary in the Afternoon and Evening

QUESTIONS

What are the daily temporal patterns of movement behaviours (sedentary time, light-intensity physical activity, and moderate-vigorous physical activity) in people with stroke? Do daily temporal patterns of sedentary time differ (a) between subgroups of people with different movement behaviour classifications and (b) over time during the first year after stroke?

DESIGN

This study represents secondary exploratory analyses from an observational, longitudinal cohort study (n = 197).

PARTICIPANTS

This study included people with first-ever stroke recruited from 4 hospitals in the Netherlands.

OUTCOME MEASURES

Movement behaviour was objectively measured using the Activ8 activity monitor within 3 weeks after hospital discharge and again at 6 and 12 months later.

RESULTS

Participants spent the least time sedentary in the morning with proportionally more sedentary time as the day progressed with maximal sedentary time seen in the evening hours. This pattern did not substantially change over time. Sedentary prolongers spent significantly more absolute time sedentary for each hour of the day, but the daily temporal pattern of sedentary time did not differ between this group and either "sedentary movers" or "sedentary exercisers."

CONCLUSION

People living at home after stroke are highly sedentary, particularly in the afternoons and evenings, and this pattern does not change during the first year after stroke. Clinicians should encourage people with stroke to find meaningful tasks to do during the day to reduce their sitting time. Researchers developing interventions to encourage people to sit less should include particular focus on the afternoon and evening time periods.

Physical activity dimensions after stroke: patterns and relation with lower limb motor function

Background

Stroke survivors show deteriorated physical functioning and physical activity levels. Physical activity levels of stroke survivors are generally low. It is increasingly recognized that physical activity is a multidimensional construct that cannot be captured in a single outcome. In-depth insight into multidimensional physical activity patterns may guide the development and timing of targeted rehabilitation interventions. This longitudinal cohort study explored how multidimensional physical activity outcomes develop during recovery in the subacute phase after stroke and if changes in physical activity were correlated to recovery of lower limb motor function.

Methods

Patients were recruited during inpatient rehabilitation. At 3, 12, and 26 weeks post-onset, motor function was measured by the Fugl-Meyer Lower Extremity Assessment (FMA-LE). Physical activity was measured with the Activ8 accelerometer in multiple outcomes: counts per minute during walking (CPM_walking; a measure of Intensity), number of active bouts (Frequency), mean length of active bouts (Distribution) and % of waking time in upright positions (Duration). Generalized estimating equations (GEE) were used to study changes in physical activity over time and the relation with the change in lower limb motor recovery.

Results

Thirty-nine patients (age 56 ± 9, 77% male, 89% ischemic stroke) were included. GEE models showed a significant main effect of time for PA Intensity (+ 13%, p = 0.007) and Duration (+ 64%, p = 0.012) between 3 and 12 weeks. Motor function did not show a significant effect in all PA models across the 3 timepoints (p > 0.020). A significant interaction effect of time × motor function was observed (p < 0.001).

Conclusions

Patterns of PA recovery depend on the PA dimensions: PA Intensity and Duration increased mostly between 3 and 12 weeks post-stroke, whereas Frequency and Distribution did not show substantial changes. Further, no strong associations with motor recovery and high inter-individual variability were documented, which underlies the need to consider factors specific to the disease, the individual patient and the context.

Self-Efficacy Is a Modifiable Factor Associated with Frailty in Those with Minor Stroke: Secondary Analysis of 200 Cohort Respondents

BACKGROUND

Owing to the improvement in acute care, there has been an increase in the number of people surviving stroke and living with its impairments. Frailty is common in people with stroke and has a significant impact on the prognosis after stroke. To reduce frailty progression, potentially modifiable factors should be identified. Increasing levels of self-efficacy influence both behaviour and physical functioning, and therefore it could be a potential target to prevent frailty.

METHODS

This is a prospective cohort study that involved the secondary analysis of the RISE data to examine the relationship between self-efficacy and frailty. The RISE study is a longitudinal study that consists of 200 adults aged 18+ years after their first stroke event. Data were collected from the respondents at 3 weeks, 6 months, 12 months, and 24 months after their discharge from the hospital. Frailty was assessed using the multidimensional frailty index with scores ranging from 0 to 1, and self-efficacy was assessed using the SESx scale, which was dichotomized as low/moderate or high. Frailty trajectories were examined using the repeated linear model. The generalized estimating equation was used to examine the relationship between self-efficacy and frailty at baseline and in the future (6-24 months). The B coefficients were reported at 95% CI before and after adjusting for potential confounders (age, gender, stroke severity, education, and social support).

RESULTS

A total of 200 responses were analysed, and the mean age of the respondents was 67.78 ± 11.53. Females made up 64% of the sample, and the mean frailty score at baseline was 0.17 ± 0.09. After adjusting for confounders, respondents with low self-efficacy had an approximately 5% increase in their frailty scores at baseline and in the 24-month follow-up period compared to those with high self-efficacy.

CONCLUSION

The result from this study showed that self-efficacy was significantly associated with frailty after stroke. Our findings suggest that self-efficacy may play a role in frailty progression among stroke survivors.

Perceptions of recurrence risk and behavioural changes among first-ever and recurrent stroke survivors: A qualitative analysis

Background

Among stroke survivors, the risk of stroke recurrence is high, and stroke survivors' perception of the risk of recurrence is crucial to promote healthy behaviours.

Objectives

This study aimed to explore the perceptions of stroke survivors about their risk of recurrence and healthy behavioural modifications.

Design

A qualitative interview study was carried out.

Results

We interviewed 19 stroke survivors from 3 hospitals. Thematic analysis showed that the perceptions of recurrence risk and healthy behavioural changes differed between first‐ever and recurrent stroke survivors. Three themes were generated from the data of first‐ever stroke survivors: indifference to and unawareness of the risk of stroke recurrence, the need for professional information support and different awareness of the importance of different healthy behaviours. For first‐relapse stroke patients: worry but feel powerlessness towards recurrent event, accurate information is still warranted, regret of unhealthy behaviour patterns. For the survivors suffered two or more times recurrences: perceived severity of recurrences, increased psychological care need, incorrect perceptions of healthy behaviour.

Discussion and Conclusion

Stroke survivors with or without recurrence hold different perceptions towards the risk of recurrence and behavioural changes. The need for information related to warning signs, recurrence risk and risk factors remained consistently unmet. The benefits of healthy behaviours could be a double‐edged sword for the prevention of stroke recurrence if the survivors fail to understand these accurately. It is strongly recommended that a specific recurrence risk communication tool and related health education plan be explored on the basis of the number of times patients have experienced stroke recurrence to inform secondary prevention of stroke in the future.

Patient/Public Contribution

The patients were involved in the formulation of interview questions and conduct of this study. No public was involved in this study.

An Exploration of Sedentary Behavior Patterns in Community-Dwelling People With Stroke: A Cluster-Based Analysis

BACKGROUND AND PURPOSE

Long periods of daily sedentary time, particularly accumulated in long uninterrupted bouts, are a risk factor for cardiovascular disease. People with stroke are at high risk of recurrent events and prolonged sedentary time may increase this risk. We aimed to explore how people with stroke distribute their periods of sedentary behavior, which factors influence this distribution, and whether sedentary behavior clusters can be distinguished?

METHODS

This was a secondary analysis of original accelerometry data from adults with stroke living in the community. We conducted data-driven clustering analyses to identify unique accumulation patterns of sedentary time across participants, followed by multinomial logistical regression to determine the association between the clusters, and the total amount of sedentary time, age, gender, body mass index (BMI), walking speed, and wake time.

RESULTS

Participants in the highest quartile of total sedentary time accumulated a significantly higher proportion of their sedentary time in prolonged bouts (P < 0.001). Six unique accumulation patterns were identified, all of which were characterized by high sedentary time. Total sedentary time, age, gender, BMI, and walking speed were significantly associated with the probability of a person being in a specific accumulation pattern cluster, P < 0.001 - P = 0.002.

DISCUSSION AND CONCLUSIONS

Although unique accumulation patterns were identified, there is not just one accumulation pattern for high sedentary time. This suggests that interventions to reduce sedentary time must be individually tailored.Video Abstract available for more insight from the authors (see the Video Supplemental Digital Content 1, available at: http://links.lww.com/JNPT/A343).

Objectively assessed physical activity and sedentary behavior and global cognitive function in older adults: a systematic review

BACKGROUND

Both physical activity (PA) and sedentary behavior (SB) are important factors for healthy ageing. This systematic review aimed to determine the association of objectively assessed (instrumented) PA and SB with global cognitive function in older adults.

METHODS

PubMed, Embase, the Cochrane Library (via Wiley), CINAHL, PsychINFO, and SPORTDiscus (via EBSCO) were searched from inception to June 21, 2020 for articles that described associations of objectively assessed PA/SB with global cognitive function in older adults aged 60 years and older. Results were synthesized using an effect direction heat map and albatross plots portrayed estimated effect sizes (standardized regression coefficients (βs)), which were summarized in boxplots.

RESULTS

In total, 45 articles were included representing a total of 15,817 older adults (mean/median age ranged from 65 to 88 years; 49.5% female). Longitudinal studies (n = 7) showed that higher moderate-to-vigorous and light PA (MVPA and LPA, respectively) and lower SB were associated with better global cognitive function. Standardized βs of cross-sectional studies (n = 38) showed that lower SB (median [IQR], β = 0.078 [0.004-0.184] and higher LPA (β = 0.096 [0.046-0.188]), activity counts (β = 0.131 [0.049-0.224]), number of steps (β = 0.155 [0.096-0.246]), MVPA (β = 0.163 [0.069-0.285]) and total PA (TPA) (β = 0.174 [0.147-0.255]) were associated with better global cognitive function.

CONCLUSIONS

Higher PA and lower SB are associated with better global cognitive function in older adults. The greatest estimated effect sizes were found for moderate-to-vigorous and TPA, suggesting that greater duration of any PA, and high intensity PA could be most beneficial for global cognitive function.

Arm impairment and walking speed explain real-life activity of the affected arm and leg after stroke

OBJECTIVE

To determine to what extent accelerometer-based arm, leg and trunk activity is associated with sensorimotor impairments, walking capacity and other factors in subacute stroke.

DESIGN

Cross-sectional study.

PATIENTS

Twenty-six individuals with stroke (mean age 55.4 years, severe to mild motor impairment).

METHODS

Data on daytime activity were collected over a period of 4 days from accelerometers placed on the wrists, ankles and trunk. A forward stepwise linear regression was used to determine associations between free-living activity, clinical and demographic variables.

RESULTS

Arm motor impairment (Fugl-Meyer Assessment) and walking speed explained more than 60% of the variance in daytime activity of the more-affected arm, while walking speed alone explained 60% of the more-affected leg activity. Activity of the less-affected arm and leg was associated with arm motor impairment (R2 = 0.40) and independence in walking (R2 = 0.59). Arm activity ratio was associated with arm impairment (R2 = 0.63) and leg activity ratio with leg impairment (R2 = 0.38) and walking speed (R2 = 0.27). Walking-related variables explained approximately 30% of the variance in trunk activity.

CONCLUSION

Accelerometer-based free-living activity is dependent on motor impairment and walking capacity. The most relevant activity data were obtained from more-affected limbs. Motor impairment and walking speed can provide some information about real-life daytime activity levels.

Physical Activity and Diet Quality Modify the Association between Comorbidity and Disability among Stroke Patients

Background: Comorbidity is common and causes poor stroke outcomes. We aimed to examine the modifying impacts of physical activity (PA) and diet quality on the association between comorbidity and disability in stroke patients. Methods: A cross-sectional study was conducted on 951 stable stroke patients in Vietnam from December 2019 to December 2020. The survey questionnaires were administered to assess patients’ characteristics, clinical parameters (e.g., Charlson Comorbidity Index items), health-related behaviors (e.g., PA using the International Physical Activity Questionnaire- short version), health literacy, diet quality (using the Dietary Approaches to Stop Hypertension Quality (DASH-Q) questionnaire), and disability (using the World Health Organization Disability Assessment Schedule II (WHODAS II)). Linear regression models were used to analyze the associations and interactions. Results: The proportion of comorbidity was 49.9% (475/951). The scores of DASH-Q and WHODAS II were 29.2 ± 11.8, 32.3 ± 13.5, respectively. Patients with comorbidity had a higher score of disability (regression coefficient, B, 8.24; 95% confidence interval, 95%CI, 6.66, 9.83; p < 0.001) as compared with those without comorbidity. Patients with comorbidity and higher tertiles of PA (B, −4.65 to −5.48; p < 0.05), and a higher DASH-Q score (B, −0.32; p < 0.001) had a lower disability score, as compared with those without comorbidity and the lowest tertile of PA, and the lowest score of DASH-Q, respectively. Conclusions: Physical activity and diet quality significantly modified the negative impact of comorbidity on disability in stroke patients. Strategic approaches are required to promote physical activity and healthy diet which further improve stroke rehabilitation outcomes.

The course of physical functioning in the first two years after stroke depends on peoples' individual movement behavior patterns

BACKGROUND AND PURPOSE

Deterioration of physical functioning after stroke in the long term is regarded as a major problem. Currently, the relationship between "peoples'" movement behavior patterns (the composition of sedentary behavior and physical activity during waking hours) directly after stroke and the development of physical functioning over time is unknown. Therefore, the objectives of this study were to investigate (1) the course of physical functioning within the first two years after returning home after stroke, and (2) the association between physical functioning and baseline movement behavior patterns.

METHOD

In the longitudinal RISE cohort study, 200 persons with a first-ever stroke discharged to the home-setting were included. Participants' physical functioning was assessed within three weeks, at six months, and one and two years after discharge using the Stroke Impact Scale (SIS) 3.0 subscale physical and the five-meter walk test (5MWT). Three distinct movement behavior patterns were identified in a previous study at baseline and were used in the current study: (1) sedentary exercisers (sufficiently active and 64% of waking hours sedentary), (2) sedentary movers' (inactive and 63% of waking hours sedentary), and (3) sedentary prolongers (inactive and >78% of waking hours sedentary accumulated in long prolonged bouts). The association between movement behavior patterns and the course of physical functioning was determined using longitudinal generalized estimating equations analyses.

RESULTS

Overall participants' physical functioning increased between discharge and six months and declined from six months up to two years. Physical functioning remained stable during the first two years after stroke in sedentary exercisers. Physical functioning improved during the first six months after discharge in sedentary movers and sedentary prolongers and deteriorated in the following six months. Only physical functioning (SIS) of sedentary prolongers further declined from one up to two years. A similar pattern was observed in the 5MWT.

CONCLUSION

Movement behavior patterns identified directly after returning home in people with stroke are associated with and are predictive of the course of physical functioning. Highly sedentary and inactive people with stroke have unfavorable outcomes over time than individuals with higher amounts of physical activity.

Association of Barriers, Fear of Falling and Fatigue with Objectively Measured Physical Activity and Sedentary Behavior in Chronic Stroke

Understanding the fostering factors of physical activity (PA) and sedentary behavior (SB) in post-stroke chronic survivors is critical to address preventive and health interventions. This cross-sectional study aimed to analyze the association of barriers to PA, fear of falling and severity of fatigue encountered by stroke chronic survivors with device-measured PA and SB. Ambulatory community-dwelling post-stroke subjects (≥six months from stroke onset) were evaluated and answered the Barriers to Physical Activity after Stroke Scale (BAPAS), Short Falls Efficacy Scale-International (Short FES-I) and Fatigue Severity Scale (FSS). SB and PA were measured with an Actigraph GT3X+ accelerometer for ≥seven consecutive days. Stepwise multiple linear regression analysis was employed to identify factors associated with PA and SB. Fifty-seven participants (58.2 ± 11.1 years, 37 men) met the accelerometer wear–time criteria (three days, ≥eight h/day). The physical BAPAS score explained 28.7% of the variance of the prolonged sedentary time (β = 0.547; p < 0.001). Additionally, the walking speed (β = 0.452) together with physical BAPAS (β = −0.319) explained 37.9% of the moderate-to-vigorous PA time (p < 0.001). In chronic post-stroke survivors, not only the walking speed but, also, the perceived physical barriers to PA are accounted for the SB and PA. Interventions to reverse SB and to involve subjects post-stroke in higher levels of PA should consider these factors.

Concurrent validity and reliability of an activity monitoring for rehabilitation (AMoR) platform for step counting and sitting/lying time in post-stroke individuals

BACKGROUND

Objective and reliable measurements to investigate daily behavior patterns in people with stroke could help therapeutic interventions after a stroke.

OBJECTIVE

To evaluate whether the Activity Monitoring for Rehabilitation (AMoR) platform has adequate concurrent validity and reliability for step counting and time spent sitting/lying in people post-stroke and to investigate its percentage accuracy for step counting at different walking speeds.

METHODS

Cross-sectional observational study. Fifty chronic post-stroke subjects used the AMoR platform and SAM simultaneously while a Video camera recorded the same activities during clinical trials. Spearman's correlation coefficient, the mean absolute percentage error, the intraclass correlation coefficient and Bland-Altman plot analyses were used to estimate the validity and reliability of the AMoR platform and StepWatch^TM Activity Monitor (SAM). The accuracy percentage was calculated for each device and plotted as a function of the walking speed during the 10-meter walk test (10MWT).

RESULTS

There was a very high correlation for step counting in all tests and a high correlation for time spent sitting/lying. The mean absolute percentage error values remained below 4% for step counting and time sitting/lying. The AMoR platform also showed excellent reliability for step counting and sitting/lying time, with values within the limit of agreement in the Bland-Altman plots. A high percentage of accuracy for step counting in the AMoR platform was observed during the 10MWT.

CONCLUSION

The AMoR platform is valid and reliable for step counting and time spent sitting/lying, with a high percentage of accuracy at different walking speeds in the post-stroke population.

Change in Life's Simple 7 Measure of Cardiovascular Health After Incident Stroke: The REGARDS Study

BACKGROUND AND PURPOSE

Life's Simple 7 (LS7) is a metric for cardiovascular health based on the 7 domains of smoking, diet, physical activity, body mass index, blood pressure, total cholesterol, and fasting glucose. Because they may be targeted for secondary prevention purposes, we hypothesized that stroke survivors would experience improvement in LS7 score over time compared with people who did not experience a stroke. We addressed this hypothesis in the REGARDS study (Reasons for Geographic and Racial Differences in Stroke) cohort of Black and White adults enrolled between 2003 and 2007.

METHODS

Participants who had LS7 data at baseline, were stroke-free at baseline, had a 10-year follow-up visit, and either did not have a stroke or had an ischemic stroke >1 year before follow-up were included (N=7569). Among these participants, 149 (2.0%) had an adjudicated ischemic stroke between the LS7 assessments. LS7 scores were classified as 0 to 2 points for each domain for a maximum score of 14, with higher scores representing better health. Multivariable linear regression was used to test the association of ischemic stroke with change in LS7 score. Covariates included baseline LS7 score, age, race, sex, education, and geographic region.

RESULTS

The 149 stroke survivors had an average of 4.9 years (SD=2.5) of follow-up from the stroke event to the second LS7 assessment. After adjusting for covariates, participants who experienced an ischemic stroke showed 0.28 points more decline in total LS7 score (P=0.03) than those who did not experience a stroke.

CONCLUSIONS

Stroke survivors did not experience improvements in cardiovascular health due to secondary prevention after ischemic stroke. On the contrary, they experienced significantly greater decline, indicating the need for greater efforts in secondary prevention after a stroke.

Active and sedentary bouts in people after stroke and healthy controls: An observational study

BACKGROUND AND PURPOSE

Understanding how both active and sedentary time is accumulated in people after stroke may help to better target interventions to reduce stroke recurrence. This study aimed to determine the difference between stroke and healthy controls in (a) time spent in sedentary and active behaviour, (b) frequency of short and long active and sedentary bouts and (c) time spent in short and long active and sedentary bouts.

METHODS

Analysis of secondary outcomes from a cross-sectional study. Participants were 42 community-dwelling people after stroke and 21 age-matched healthy controls. An activity monitor was used to collect free-living active and sedentary behaviour. Total active (standing and walking) and sedentary (lying, reclining and sitting) time was calculated in minutes per day. Bouts were categorized as short (<5 min, 5-15 min, 15-30 min) or long (>30 min). The frequency of and time spent in each bout were calculated.

RESULTS

Relative to wear time, the stroke group spent 10% (95% confidence interval [CI] 3 to 17) more time in sedentary behaviour and had fewer long active bouts than the healthy controls. The stroke group spent 7% (95% CI 1-13) less time in long active bouts and 11% (95% CI 2-20) more time in long sedentary bouts than the healthy controls.

CONCLUSIONS

Community-dwelling people after stroke spent less time in active behaviour and accumulated more sedentary time in bouts longer than 30 min compared with healthy controls. Increasing active time and breaking up long sedentary time warrants investigation in people after stroke.