Background: Following stroke, patients/clients suffer from significant impairments. However, weakness is the predominant common denominator. Historically, strengthening or high-intensity resistance training has been excluded from neurorehabilitation programs because of the concern that high-exertion activity, including strengthening, would increase spasticity. Contemporary research studies challenge this premise. Method: This evidence-based review was conducted to determine whether high-intensity resistance training counteracts weakness without increasing spasticity in persons poststroke and whether resistance training is effective in improving functional outcome compared to traditional rehabilitation intervention programs. The studies selected were graded as to the strength of the recommendations and the levels of evidence. The treatment effects including control event rate (CER), experimental event rate (EER), absolute risk reduction (ARR), number needed to treat (NNT), relative benefit increase (RBI), absolute benefit increase (ABI), and relative risk (RR) were calculated when sufficient data were present. Results: A total of 11 studies met the criteria. The levels of evidence ranged from fair to strong (3B to 1B). Conclusions: Despite limited long-term follow-up data, there is evidence that resistance training produces increased strength, gait speed, and functional outcomes and improved quality of life without exacerbation of spasticity.

Objective: The objective was to evaluate implementation of telehealth physical therapy in response to COVID-19 and identify implementation strategies to maintain and scale up telehealth physical therapy within a large urban academic medical center. Methods: The Reach Effectiveness Adoption Implementation Maintenance (RE-AIM) framework was used to evaluate telehealth physical therapy implementation. Patient-level data were extracted from electronic medical records between March 16, 2020, and May 16, 2020 (implementation phase). Reach was defined as the proportion of physical therapy sessions completed via telehealth. Effectiveness was assessed using a patient-reported satisfaction survey with a 5-point Likert scale. Adoption was defined as the proportion of physical therapists who used telehealth. Implementation was assessed through qualitative analysis of patient and clinician perspectives to identify emergent themes, retrospectively classify strategies used during the implementation phase, and prospectively identify evidence-based strategies to increase telehealth maintenance and scale-up. Maintenance of telehealth was defined as the proportion of patients who indicated they would attend another telehealth session. Results: There were 4548 physical therapy sessions provided by 40 therapists from March 22, 2020, to May 16, 2020, of which 3883 (85%) were telehealth. Ninety-four percent of patients were satisfied. All physical therapists (100%) used telehealth technology at least once. Retrospectively classified and prospectively identified evidence-based strategies were organized into 5 qualitative themes that supported implementation: organizational factors (policies, preexisting partnerships), engaging external stakeholders (satisfaction survey), champions (clinician leaders), clinician education (dynamic, ongoing training), and process (promote adaptability, small tests of change). Ninety-two percent of patients reported they would attend another telehealth session. Conclusion: Findings from this study suggest that implementation of telehealth physical therapy during the COVID-19 pandemic was feasible and acceptable in this setting. Impact: These results can be used to guide future health policy, quality improvement, and implementation science initiatives to expand the use and study of telehealth for physical therapy.

Background: Chronic shoulder pain (CSP) is a common condition with various etiologies, including rotator cuff disorders, adhesive capsulitis, shoulder instability, and shoulder arthritis. It is associated with substantial disability and psychological distress, resulting in poor productivity and quality of life. Physical therapy constitutes the mainstay treatment for CSP, but several barriers exist in accessing care. In recent years, telerehabilitation has gained momentum as a potential solution to overcome such barriers. It has shown numerous benefits, including improving access and convenience, promoting patient adherence, and reducing costs. However, to date, no previous randomized controlled trial has compared fully remote digital physical therapy to in-person rehabilitation for nonoperative CSP. Objective: The aim of this study is to compare clinical outcomes between digital physical therapy and conventional in-person physical therapy in patients with CSP. Methods: We conducted a single-center, parallel-group, randomized controlled trial involving 82 patients with CSP referred for outpatient physical therapy. Participants were randomized into digital or conventional physical therapy (8-week interventions). The digital intervention consisted of home exercise, education, and cognitive behavioral therapy (CBT), using a device with movement digitalization for biofeedback and asynchronous physical therapist monitoring through a cloud-based portal. The conventional group received in-person physical therapy, including exercises, manual therapy, education, and CBT. The primary outcome was the change (baseline to 8 weeks) in function and symptoms using the short-form of Disabilities of the Arm, Shoulder, and Hand questionnaire. Secondary outcome measures included self-reported pain, surgery intent, analgesic intake, mental health, engagement, and satisfaction. All questionnaires were delivered electronically. Results: A total of 90 participants were randomized into digital or conventional physical therapy, with 82 receiving the allocated intervention. Both groups experienced significant improvements in function measured by the short-form of the Disabilities of the Arm, Shoulder, and Hand questionnaire, with no differences between groups (–1.8, 95% CI –13.5 to 9.8; P=.75). For secondary outcomes, no differences were observed in surgery intent, analgesic intake, and mental health or worst pain. Higher reductions were observed in average and least pain in the conventional group, which, given the small effect sizes (least pain 0.15 and average pain 0.16), are unlikely to be clinically meaningful. High adherence and satisfaction were observed in both groups, with no adverse events. Conclusions: This study shows that fully remote digital programs can be viable care delivery models for CSP given their scalability and effectiveness, assessed through comparison with high-dosage in-person rehabilitation. Trial Registration: ClinicalTrials.gov (NCT04636528); https://clinicaltrials.gov/study/NCT04636528

Background: Although evidence-based guidelines for physical therapy for patients with chronic low back pain (cLBP) are available, selecting patient-reported outcome measures to capture complexity of health status and quality of life remains a challenge. PROMIS-10 Global Health (GH) may be used to screen for impactful health risks and enable patient-centered care. The purpose of this study was to investigate the interrelationships between PROMIS-10 GH scores and patient demographics, health status, and healthcare utilization in patients with cLBP who received physical therapy. Methods: A retrospective review of de-identified electronic health records of patients with cLBP was performed. Data were collected for 328 patients seen from 2017 to 2020 in three physical therapy clinics. Patients were grouped into HIGH and LOW initial assessment scores on the PROMIS-10 Global Physical Health (PH) and Global Mental Health (MH) measures. Outcomes of interest were patient demographics, health status, and healthcare utilization. Mann–Whitney U and chi-square tests were used to determine differences between groups, and binary logistic regression was used to calculate odds ratios (OR) to determine predictors of PH-LOW and MH-LOW group assignments. Results: The PH-LOW and MH-LOW groups contained larger proportions of patients who were African American, non-Hispanic, and non-commercially insured compared to PH-HIGH and MH-HIGH groups (p < .05). The PH-LOW and MH-LOW groups also had a higher Charlson comorbidity index (CCI), higher rates of diabetes and depression, and more appointment cancellations or no-shows (p < .05). African American race (OR 2.54), other race (2.01), having Medi-Cal insurance (OR 3.37), and higher CCI scores (OR 1.55) increased the likelihood of being in the PH-LOW group. African American race (OR 3.54), having Medi-Cal insurance (OR 2.19), depression (OR 3.15), kidney disease (OR 2.66), and chronic obstructive pulmonary disease (OR 1.92) all increased the likeihood of being in the MH-LOW group. Conclusions: Our study identified groups of patients with cLBP who are more likely to have lower PH and MH scores. PROMIS-10 GH provides an opportunity to capture and identify quality of life and global health risks in patients with cLBP. Using PROMIS-10 in physical therapy practice could help identify psychosocial factors and quality of life in the population with cLBP.

Objective: The purpose of this study was to examine telehealth physical therapy utilization 1 year into the COVID-19 pandemic and identify factors that influence physical therapists’ delivery of telehealth in an urban academic medical center. Methods: Electronic medical record data were extracted within the dates of interest (March 22, 2021 to May 15, 2021), the proportion of physical therapy sessions delivered via telehealth were identified, and patient characteristics were compared by telehealth volume (0 vs ≥1 session, 1 vs >1 session). Qualitative data also were collected from physical therapists via semi-structured interviews, and a directed content analysis was conducted, informed by the Capability, Opportunity, Motivation, and Behavior model, to identify factors influencing telehealth delivery. Results: Telehealth was used for 3793 of 8038 (47.2%) physical therapist sessions, and 1028 unique patients had at least 2 physical therapist sessions (without telehealth: 6.6% [n = 68], telehealth once: 39.1% [n = 402], telehealth more than once: 54.3% [n = 558]). Patients without telehealth were older, non-English speaking, had non-commercial insurance, and had at least 1 chronic health condition. Patients with telehealth more than once had a neurologic diagnosis and lived farther from the treating clinic. Capabilities that influenced telehealth delivery were physical therapist clinical skills and knowledge, technical proficiency, telehealth-specific interpersonal skills, and cognitive flexibility. Factors external to physical therapists—including the environment, patient equipment and technology proficiency, physical therapist equipment, clinic factors, and patient and referring provider perspectives—also influenced telehealth delivery. Finally, patient needs and telehealth as a beneficial tool guided physical therapist intention to use telehealth. Conclusion: Sustained telehealth utilization outcomes 1 year into the COVID-19 pandemic and an interaction among physical therapist, patient, and environmental factors support the long-term potential of telehealth physical therapy in an urban academic medical center. Impact: These findings support the long-term potential of telehealth approaches and can be used to inform telehealth physical therapist training programs and clinical implementation, future research, and health policy.

Background: Despite efforts to view electronic health records (EHR) data through an equity lens, crucial contextual information regarding patients’ social environments remains limited. Integrating EHR data and Geographic Information Systems (GIS) technology can give deeper insights into the relationships between patients’ social environments, health outcomes, and geographic factors. This study aims to identify regions with the fastest and slowest access to outpatient physical therapy services using bivariate choropleth maps to provide contextual insights that may contribute to health disparity in access. Methods: This was a retrospective cohort study of patients’ access timelines for the first visit to outpatient physical therapy services (n = 10,363). The three timelines evaluated were (1) referral-to-scheduled appointment time, (2) scheduled appointment to first visit time, and (3) referral to first visit time. Hot and coldspot analyses (CI 95%) determined the fastest and slowest access times with patient-level characteristics and bivariate choropleth maps that were developed to visualize associations between access patterns and disadvantaged areas using Area Deprivation Index scores. Data were collected between January 1, 2016 and January 1, 2020. EHR data were geocoded via GIS technology to calculate geospatial statistics (G_i^∗ statistic from ArcGIS Pro) in an urban area. Results: Statistically significant differences were found for all three access timelines between coldspot (i.e., fast access group) and hotspot (i.e., slow access group) comparisons (p < .05). The hotspot regions had higher deprivation scores; higher proportions of residents who were older, privately insured, female, lived further from clinics; and a higher proportion of Black patients with orthopaedic diagnoses compared to the coldspot regions. Conclusions: Our study identified and described local areas with higher densities of patients that experienced longer access times to outpatient physical therapy services. Integration of EHR and GIS data is a more robust method to identify health disparities in access to care. With this approach, we can better understand the intricate interplay between social, economic, and environmental factors contributing to health disparities in access to care.