Kara K. Patterson

Adapted dance is a promising intervention to improve physical and psychosocial well-being post-stroke. At-home participation with a live-streamed dance pro

Background: People with stroke often walk with temporal asymmetry; which is related to increased fall risk. The purpose of this study was to determine the relationship between temporal gait asymmetry and mechanical stability among people with sub-acute stroke. Methods: Thirty-one people with sub-acute stroke (<6 months post-stroke) completed six walking trials in a biomechanics laboratory. Three-dimensional motion capture was recorded. Swing symmetry was calculated as a ratio of swing time on the more affected limb divided by swing time on the less affected limb. Mechanical stability was the minimum margin of stability, relative to the medial and lateral borders of the stance limb, during the single support phase of the gait cycle. Multiple linear regression was used to determine the relationship between swing symmetry and mechanical stability, controlling for step width and walking speed. Results: There was a significant negative relationship between swing symmetry and lateral margin of stability on the less affected side (p<0.0001) and medial margin of stability on the more affected side (p=0.023). That is, as swing symmetry increased, the extrapolated centre of mass tended to be closer to the lateral border of the less affected side and farther from the medial border of the more affected side. Conclusion: Gait asymmetry could, in part, result from a strategy to compensate for poor balance control on the more affected side. Alternatively, reduced lateral margin of stability on the less affected side among asymmetric participants indicates instability in this direction and could increase the risk for falling.

People with dementia have worse balance and more falls than older adults with no cognitive impairment. Despite potential benefits, few physical rehabilitation programs exist for people with dementia. This study investigated people who support individuals with dementia's experiences and perspectives with physical rehabilitation. In this qualitative descriptive study, 9 family members, 8 staff, 7 clinicians, and 6 researchers (n = 30) attended interviews or focus groups discussing balance, falls, rehabilitation, exercise, and cognitive impairment. Qualitative data were analyzed using reflexive thematic analysis, through an inductive and semantic approach. Physical rehabilitation for people with dementia may be lacking due to low expectations of abilities; safety concerns driving and limiting rehabilitation; and existing resources being inadequate. Low expectations of people with dementia's abilities to participate in rehabilitation led to exclusion. Safety concerns drove family members to pursue rehabilitation for the person with dementia, whilst risk aversion made staff and professionals hesitant to deliver rehabilitation to this population. Limited rehabilitation prompted family members to seek resources (exercises) provided by staff and professionals, which were viewed as not tailored or challenging enough for the person with dementia. This study highlights the need for increased awareness about physical rehabilitation for people with dementia.

Background: Adapted dance is a promising rehabilitation intervention for physical and psychosocial impairments in people with chronic stroke. However, in-person attendance is hindered by limited community ambulation, transportation, and schedule conflicts. At-home participation with a live-streamed dance program could address these issues, but psychosocial benefits may be diminished because of reduced social interactions. The primary objective of this study was to assess the feasibility and safety of a live-streamed dance program for chronic stroke. Secondary objectives were to characterize participants who choose live-stream vs in-person options and quantify pre-post changes in balance, gait and social connection. Method: People with chronic stroke were given the choice of attending a live-streamed adapted dance program either in-person or at home twice a week for 4 weeks. A priori feasibility criteria were tracked, and participants were characterized with self-report (Center for Epidemiologic Studies Depression Scale; CES-D) and performance-based measures (e.g., Montreal Cognitive Assessment, Chedoke McMaster Assessment) at baseline. Pre-post measures of secondary outcomes included gait speed, Mini Balance Evaluation Systems Test (Mini-BESTest), Activities of Balance Confidence Scale (ABC), and Inclusion of Community in Self scale (ICS). Unpaired median/mean differences in baseline clinical presentation were used to compare in-person and live-stream participants. Paired median/mean differences were used to examine change in secondary outcomes with dance. Results: Interest and enrollment rates for both groups combined were 87% and 38% respectively. Of the 13 people who enrolled, 8 chose in-person and 5 chose live-stream. In-person and live-stream attendance rates were 83% and 89% respectively, and retention rates were 80% and 75% respectively. At baseline, the in-person group had greater depressive symptoms (CES-D score, median [IQR] difference: 11.5 [-21.5, -5]), and faster mean gait speed (-25.8cm/s [-50.98, 0.006]) than the live-stream group. There were no pre-post changes in secondary outcome measures. Conclusions: A live-streamed dance intervention featuring in-class and at-home participation is safe and feasible for people with chronic stroke. These results will inform a future randomized controlled trial to investigate the effects of a live-stream dance program with a longer duration while considering how factors such as gait function and mood may relate to the choice between in-person and at-home attendance.

This pre-post-test study investigated 1) pre-post changes in psychosocial domains with a single virtual salsa class; 2) effect sizes relative to an in-person class, and 3) individual factors, including personality, perceived performance, and enjoyment. An experimental group (n=33) of novice dancers 18-30 years old, participated in a single virtual salsa class. Positive and Negative Affect Scale (PAS, NAS), Perceived Stress Scale (PSS), and the Inclusion in Community and Self-Scale (ICS) were administered before and after class. Participants completed the Big Five Inventory-10 (BFI-10) before, and rated their performance and enjoyment (ordinal scale 1-5) after class. Effect sizes were calculated, and pre-post changes were analyzed with Wilcoxon signed-rank tests. Relationships between pre-post changes and individual factors were analyzed with Spearman’s rank correlations. PAS, NAS, PSS, and ICS significantly improved and effect sizes were larger than those for an in-person salsa class except for ICS. Change in NAS was negatively correlated with neuroticism. These results suggest that a virtual salsa class may improve mood, stress, and social connection similar to in-person classes and change in mood may be influenced by personality traits such as neuroticism. Understanding the psychosocial effects of virtual dance and the influence of individual factors will facilitate implementation of dance as an accessible rehabilitation intervention to improve psychosocial well-being.

BACKGROUND Falls are frequent among long-term care residents. Machine-learning (ML) based fall prediction algorithms may facilitate early intervention; however, we need to understand whether they benefit or hinder clinical decision-making before clinical adoption. OBJECTIVE This study aimed to 1) determine how a ML fall prediction algorithm influences physiotherapists’ prediction of future falls and 2) explore how the ML algorithm influences physiotherapists’ confidence in future fall prediction. METHODS Forty-four registered physiotherapists with experience in geriatrics participated in a virtual observational study. Physiotherapists provided a prediction of the percent likelihood of a long-term care resident (n=5; 3 ratings per resident) falling in the next month, before and after reviewing the output of a fall prediction algorithm and rated their confidence in their prediction. All predictions were compared to the residents’ actual future falls to confirm discriminative ability pre- and post-algorithm. An ROC curve was used to show the performance of the physiotherapist (pre-algorithm) and physiotherapist (post-algorithm) in their ability to discriminate between fallers and non-fallers. Linear mixed models were used to examine factors associated with accuracy pre- and post-algorithm and linear regressions were used to understand changes in physiotherapist confidence pre- and post-algorithm. Finally, content analysis was used to analyze physiotherapist feedback. RESULTS There was an increase in physiotherapists’ ability to discriminate between a resident falling and not falling within the next four weeks after reviewing the results of the algorithm (pre-algorithm area under curve (AUC):0.78; 95% confidence interval (CI):0.49-1; post-algorithm AUC:0.86; 95% CI:0.61-1). Physiotherapist fall predictions moved closer to the algorithm after using it in their decision-making (b=-7.2; p<0.001), even in instances where the algorithm was wrong. There was no effect of age, confidence, and years of clinical experience on physiotherapist (pre-algorithm) accuracy, however, there was an effect of confidence and age on physiotherapist (post-algorithm) accuracy. Most (33/44) physiotherapists reported that they would use a fall prediction algorithm to complement their assessments, but many had concerns about algorithmic accuracy and transparency. CONCLUSIONS ML-based prediction models may improve a physiotherapist’s fall risk assessment but they do not improve their decisional confidence and there is a risk of automation bias. Future research is needed into how to best incorporate information from these algorithms into clinical decision-making around fall risk and address issues of safety and accountability.

The Canadian Stroke Best Practice Recommendations 7 ^th edition update of the Rehabilitation, Recovery and Community Participation module is presented in three parts. This publication, Part One of the series, reflects the growing and changing body of research evidence available to guide planning, ongoing screening and assessment, management, education, and support of individuals with stroke, their families, and caregivers. This module provides guidance for the planning and delivery of coordinated and seamless systems of care from acute stroke onset to return to community settings by an interdisciplinary team of healthcare providers with expertise in stroke. These recommendations were developed with active involvement of people with lived experience of stroke at all phases. These recommendations are intended to support the progress achieved during the initial recovery stages and enable individuals with stroke to resume life roles and leisure activities as best as possible, to achieve optimal recovery goals. Evidence for effective rehabilitation therapies and support for individuals with stroke and their families continues to emerge and gaps in knowledge should drive future research.

The 7th edition update of the Rehabilitation, Recovery and Community Participation module is presented in three parts. Part Three of the series reflects the current research evidence focused on person-centered care, optimizing an individual’s return to their community and engaging in active and meaningful participation. Emphasis is placed on regular healthcare follow-up, maximizing secondary prevention strategies, assessment, diagnosis, and management of mood disorders and cognitive status, sleep health, and post-stroke fatigue. Personal issues that are important and meaningful to individuals with stroke are addressed, including returning to driving, vocational roles, relationships, sexuality, life roles, leisure, social participation, advance care planning, and palliative care. This module highlights the need for coordinated and seamless systems of care that extend beyond the first few months after stroke, building on progress achieved during the initial recovery, to support seamless longer-term recovery. The main goal of these recommendations is to help individuals with stroke achieve as much independence as possible in meaningful life roles and leisure activities. Successful planning across transitions requires integrated and coordinated people-centered efforts by all stroke team members and the broader community. Active engagement of the individual and family at all stages of planning and goal setting is essential.