Accelerometer and global positioning system measurement of recovery of community ambulation across the first 6 months after stroke: an exploratory prospective study

Objective: To characterize community ambulation and determine if it changes across the first 6 months after discharge from hospital after stroke

Study Protocol: MASK-ED™ (KRS Simulation) - impact on physiotherapy student performance

Purpose: MASK-ED™ (KRS Simulation) involves an educator donning a silicone mask to portray a patient character that has been specifically developed in line with learning outcomes. The effectiveness of MASK-ED™ (KRS Simulation to prepare physiotherapy students prior to commencing work integrated learning has not been investigated.Methodology: This randomised cluster trial will investigate MASK-ED™ (KRS Simulation) in addition to usual teaching in neurological physiotherapy. Physiotherapy students in an intervention group will receive simulated learning via a MASK-ED™ (KRS Simulation) character as well as usual teaching. Students in a control group will receive usual teaching only, including role-play with peers. Consent will be concealed from the investigating team and blinded assessors will assess the primary outcome. Secondary outcomes will be practical and written examination results and a satisfaction survey.Research implications: This will be the first randomised trial investigating MASK-ED™ (KRS Simulation)’s effect on students’ readiness for work integrated learning.Practical implications: The results from this study will inform physiotherapy education and curriculum development by increasing the evidence base for the use of simulation in training physiotherapy students prior to work integrated learning.Originality: MASK-ED™ (KRS Simulation) was developed in nursing education at Central Queensland University, Australia. Although it has been investigated in medical imaging, this is its first practical application within physiotherapy curricula.Limitations: It will be impractical and unfeasible to blind the participants and the investigators to tutorial group allocation and impractical for blind assessing of practical examinations

Identifying factors associated with sedentary time after stroke. Secondary analysis of pooled data from nine primary studies.

<p><b>Background</b>: High levels of sedentary time increases the risk of cardiovascular disease, including recurrent stroke.</p> <p><b>Objective</b>: This study aimed to identify factors associated with high sedentary time in community-dwelling people with stroke.</p> <p><b>Methods</b>: For this data pooling study, authors of published and ongoing trials that collected sedentary time data, using the activPAL monitor, in community-dwelling people with stroke were invited to contribute their raw data. The data was reprocessed, algorithms were created to identify sleep-wake time and determine the percentage of waking hours spent sedentary. We explored demographic and stroke-related factors associated with total sedentary time and time in uninterrupted sedentary bouts using unique, both univariable and multivariable, regression analyses.</p> <p><b>Results</b>: The 274 included participants were from Australia, Canada, and the United Kingdom, and spent, on average, 69% (SD 12.4) of their waking hours sedentary. Of the demographic and stroke-related factors, slower walking speeds were significantly and independently associated with a higher percentage of waking hours spent sedentary (p = 0.001) and uninterrupted sedentary bouts of <i>>30</i> and <i>>60 min</i> (p = 0.001 and p = 0.004, respectively). Regression models explained 11–19% of the variance in total sedentary time and time in prolonged sedentary bouts.</p> <p><b>Conclusion</b>: We found that variability in sedentary time of people with stroke was largely unaccounted for by demographic and stroke-related variables. Behavioral and environmental factors are likely to play an important role in sedentary behavior after stroke. Further work is required to develop and test effective interventions to address sedentary behavior after stroke.</p

Which impairments,activity limitations and personal factors at hospital discharge predict walking activity across the first 6 months poststroke?

Purpose: To determine which impairments, activity limitations and personal factors at hospital discharge poststroke predict volume, frequency, and intensity of walking activity 1, 3, and 6 months later. Materials and Methods: Prospective longitudinal observational study. Thirty-six people with stroke (71 SD 14 years, 69% male) were recruited at hospital discharge and predictors including fatigue, mood, executive function, walking speed, walking endurance, age, prestroke activity, self-efficacy, and perceived stroke recovery and health were collected. At 1, 3, and 6 months follow-up, participants wore an ActivPAL™ accelerometer to collect measures of walking activity. Results: At 1 month, walking endurance predicted all walking activity (R > 0.29, p < 0.01). At 3 months, walking endurance and prestroke activity predicted activity volume and intensity (R = 0.46–0.61, p < 0.001), and prestroke activity predicted activity frequency (R = 0.31, p = 0.004). At 6 months, age-predicted activity volume and frequency (R = 0.34–0.35, p < 0.003), while prestroke activity, discharge walking endurance, and executive function together predicted activity intensity (R = 0.79, p < 0.001). Conclusion: Walking endurance contributes to walking activity outcomes across the first 6 months following hospital discharge poststroke. After 1 month of discharge, factors other than poststroke changes also contribute to activity outcomes, and should be considered when targeting poststroke physical activity.Implications for rehabilitation Walking endurance should be addressed during stroke rehabilitation as higher scores are linked to more walking activity in the first month after discharge. Prestroke factors such as low prestroke activity levels and older age predict reduced walking activity after stroke, so approaches to address barriers these factors may pose are needed in people with stroke. Physical activity interventions should be tailored to the individual, their environment, and context, and take into consideration prestroke factors

Which impairments, activity limitations and personal factors at hospital discharge predict walking activity across the first 6 months poststroke?

Purpose: To determine which impairments, activity limitations and personal factors at hospital discharge poststroke predict volume, frequency, and intensity of walking activity 1, 3, and 6 months later. Materials and Methods: Prospective longitudinal observational study. Thirty-six people with stroke (71 SD 14 years, 69% male) were recruited at hospital discharge and predictors including fatigue, mood, executive function, walking speed, walking endurance, age, prestroke activity, self-efficacy, and perceived stroke recovery and health were collected. At 1, 3, and 6 months follow-up, participants wore an ActivPAL™ accelerometer to collect measures of walking activity. Results: At 1 month, walking endurance predicted all walking activity (R2 > 0.29, p < 0.01). At 3 months, walking endurance and prestroke activity predicted activity volume and intensity (R2 = 0.46–0.61, p < 0.001), and prestroke activity predicted activity frequency (R2 = 0.31, p = 0.004). At 6 months, age-predicted activity volume and frequency (R2 = 0.34–0.35, p < 0.003), while prestroke activity, discharge walking endurance, and executive function together predicted activity intensity (R2 = 0.79, p < 0.001). Conclusion: Walking endurance contributes to walking activity outcomes across the first 6 months following hospital discharge poststroke. After 1 month of discharge, factors other than poststroke changes also contribute to activity outcomes, and should be considered when targeting poststroke physical activity

An Audit of the Use of Simulation in Australian and New Zealand Physiotherapy Curricula

Purpose: The aim of this exploratory research was to investigate the use of simulation in physiotherapy curricula across Australia and New Zealand. The key areas of focus were whether simulation was being used, the forms of simulation used for training and assessment, evidence for educational simulation practices, and the enablers and barriers to implementing simulation into the curricula. Method: All Australian and New Zealand Universities offering a physiotherapy degree were invited to participate in an electronic survey. As no pre-existing tool was available to answer the aims of the study, a custom designed survey was developed. The survey was pilot tested on three physiotherapy academics to limit ambiguity and ensure the questions directly related to the purpose of the study. An introductory invitation was circulated via the Council of Physiotherapy Deans Australia and New Zealand. Open and closed ended questions were analyzed following a sequential explanatory strategy. Results: Fourteen (14) of the possible 22 universities (64%) responded, with all indicating that they use simulation for training or assessment and many using it for both. All core areas of clinical practice were represented, as were low to high-fidelity forms of simulation. Role play (77%), low/medium fidelity manikins (77%), and standardized patients (62%) were the most frequently used for training. Role play (73%), standardized patients (45%), objective structured clinical examinations (45%), and low/medium fidelity manikins (37%) were the most frequently used modalities for assessment. The key enablers appear to be availability of equipment, academic support, growing evidence for its use, safety, and positive student experiences. The key barriers appear to be time, cost, and access to trained staff and equipment. Conclusions: Academics across Australia and New Zealand described simulation practices for both training and assessing physiotherapy students. Academics were able to identify a limited but expanding evidence-base for simulation, more strongly focused on training than simulation-based assessments. Recommendations: Further research may justify increased investment of time, money, resources, and training in different simulation modalities

Are accelerometers and GPS devices valid, reliable and feasible tools for measurement of community ambulation after stroke?

Purpose: To determine validity, reliability and feasibility of accelerometers (ActivPAL, Sensewear Pro(2) Armband) and portable global positioning systems (GPS) (Garmin Forerunner 405CX) for community ambulation measurement after stroke. Methods: Fifteen community-dwelling stroke survivors attended two sessions; completing a 6-minute walk, treadmill walking, and 200-m outdoor circuit. Feasibility was determined by wearing devices over four days. Measures collected included step count, time spent walking, distance, energy expenditure and location. Intra-class correlation coefficients (ICC), Bland-Altman plots and absolute percentage of error (APE) were used to determine validity and reliability. Results: ActivPAL had excellent validity and reliability for most measures (ICC: 0.821-0.999, APE: 0%-11.1%), except for good-excellent findings at speeds < 0.42 m/s (ICC: 0.659-0.894, APE: 1.6%-11.1%). Sensewear had missing values for 23% of recordings and high error for all measures. GPS demonstrated excellent validity and reliability for time spent walking and step count (ICC: 0.805-0.999, APE: 0.9%-10%), and 100% accuracy for location. However, it was not valid or reliable for distance (ICC = -0.139, APE = 23.8%). All devices appeared feasible for community ambulation measurement with assistance for setup and data analysis. Conclusions: ActivPAL and Garmin GPS appear valid, reliable and feasible tools for community ambulation measurement after stroke, except for distance. Sensewear demonstrated poor validity and reliability when worn on the paretic arm