Feasibility of a Self-directed Upper Extremity Training Program to Promote Actual Arm Use for Individuals Living in the Community With Chronic Stroke.

Objective: To determine the feasibility of a self-directed training protocol to promote actual arm use in everyday life. The secondary aim was to explore the initial efficacy on upper extremity (UE) outcome measures. Design: Feasibility study using multiple methods. Setting: Home and outpatient research lab. Participants: Fifteen adults (6 women, 9 men, mean age=53.08 years) with chronic stroke living in the community. There was wide range of UE functional levels, ranging from dependent stabilizer (limited function) to functional assist (high function). Intervention: Use My Arm-Remote protocol. Phase 1 consisted of clinician training on motivational interviewing (MI). Phase 2 consisted of MI sessions with participants to determine participant generated goals, training activities, and training schedules. Phase 3 consisted of UE task-oriented training (60 minutes/day, 5 days/week, for 4 weeks). Participants received daily surveys through an app to monitor arm training behavior and weekly virtual check-ins with clinicians to problem-solve challenges and adjust treatment plans. Outcome Measures: Primary outcome measures were feasibility domains after intervention, measured by quantitative study data and qualitative semi-structured interviews. Secondary outcomes included the Canadian Occupational Performance Measure (COPM), Motor Activity Log (MAL), Fugl-Meyer Assessment (FMA), and accelerometry-based duration of use metric measured at baseline, discharge, and 4-week follow-up. Results: The UMA-R was feasible in the following domains: recruitment rate, retention rate, intervention acceptance, intervention delivery, adherence frequency, and safety. Adherence to duration of daily practice did not meet our criteria. Improvements in UE outcomes were achieved at discharge and maintained at follow-up as measured by COPM-Performance subscale (F[1.42, 19.83]=17.72, P<.001) and COPM-Satisfaction subscale (F[2, 28]=14.73, P<.001), MAL (F[1.31, 18.30]=12.05, P<.01) and the FMA (F[2, 28]=16.62, P<.001). Conclusion: The UMA-R was feasible and safe to implement for individuals living in the community with chronic stroke. Adherence duration was identified as area of refinement. Participants demonstrated improvements in standardized UE outcomes to support initial efficacy of the UMA-R. Shared decision-making and behavior change frameworks can support the implementation of UE self-directed rehabilitation. Our results warrant the refinement and further testing of the UMA-R.

Differential Impact of the COVID-19 Pandemic on Health Care Utilization Disruption for Community-Dwelling Individuals With and Without Acquired Brain Injury.

OBJECTIVE: To delineate health care disruption for individuals with acquired brain injury (ABI) during the peak of the pandemic and to understand the impact of health care disruption on health-related quality of life (HRQoL). DESIGN: Cross-sectional survey. SETTING: General community. PARTICIPANTS: Volunteer sample of adults with traumatic brain injury (TBI; n=33), adults with stroke (n=66), and adults without TBI or stroke (n=108) with access to the internet and personal technology (N=207). INTERVENTIONS: Not applicable. MAIN OUTCOME MEASURES: Not applicable. RESULTS: Participants with TBI and stroke reported high rates of disruption in care specific to their diagnosis (53%-54.5%), while participants across all groups reported disruption for major medical care (range, 68.2%-80%), general health care (range, 60.3%-72.4%), and mental health care (range, 31.8%-83.3%). During the pandemic, participants with TBI and stroke used telehealth for care specific to their diagnosis (40.9%-42.4%), whereas all participants used telehealth for major medical care (range, 50%-86.7%), general health care (range, 31.2%-53.3%), and mental health care (range, 53.8%-72.7%). Disruption in TBI or stroke care and type of ABI explained 27.1% of the variance in HRQoL scores (F2,95=16.82, P<.001, R 2=0.262), and disruption in mental health care explained 14.8% of the variance (F1,51=8.86, P=.004, R 2=0.148). CONCLUSIONS: Individuals with and without ABI experienced pronounced disruption in health care utilization overall. However, individuals who experienced a disruption in care specific to TBI or mental health care were most vulnerable to decreased HRQoL. Telehealth was a viable alternative to in-person visits for individuals with and without ABI, but limitations included difficulty with technology, difficulty with comprehensive examination, and decreased rapport with providers.