BACKGROUND: Physical inactivity in people with chronic stroke profoundly affects daily function and increases recurrent stroke risk and mortality, making physical activity improvements an important target of intervention. We compared the effects of a high-intensity walking intervention (FAST), a step activity monitoring behavioral intervention (SAM), or a combined intervention (FAST+SAM) on physical activity (ie, steps/day). We hypothesized the combined intervention would yield the greatest increase in steps/day. METHODS: This assessor-blinded multisite randomized controlled trial was conducted at 4 university/hospital-based laboratories. Participants were 21 to 85 years old, walking without physical assistance following a single, unilateral noncerebellar stroke of ≥6 months duration, and randomly assigned to FAST, SAM, or FAST+SAM for 12 weeks (2–3 sessions/week). FAST training consisted of walking-related activities at 70% to 80% heart rate reserve, while SAM received daily feedback and goal setting of walking activity (steps/day). Assessors and study statistician were masked to group assignment. The a priori–determined primary outcome and end point was a comparison of the change in steps/day between the 3 intervention groups from pre- to post-intervention. Adverse events were tracked after randomization. All randomized participants were included in the intent-to-treat analysis. RESULTS: Participants were enrolled from July 18, 2016, to November 16, 2021. Of 2385 participants initially screened, 250 participants were randomized (mean [SE] age, 63 [0.80] years; 116 females/134 males), with 89 assigned to FAST, 81 to SAM, and 80 to FAST+SAM. Steps/day significantly increased in both the SAM (mean [SE], 1542 [267; 95% CI, 1014–2069] P <0.001) and FAST+SAM group (1307 [280; 95% CI, 752–1861] P <0.001) but not in the FAST group (406 [238; 95% CI, −63 to 876] P =0.09). There were no deaths or serious study-related adverse events. CONCLUSIONS: Only individuals with chronic stroke who completed a step activity monitoring behavioral intervention with skilled coaching and goal progression demonstrated improvements in physical activity (steps/day). REGISTRATION: URL: https://www.clinicaltrials.gov ; Unique identifier: NCT02835313.

Walking behavior in the chronic stroke population is multi-factorial. Previous work focused on the role of physical and biopsychosocial factors in understanding daily stepping post stroke. However,...

Background: Social and physical environmental factors affect real-world walking activity in individuals with stroke. However, environmental factors are often non-modifiable, presenting a challenge for clinicians working with individuals with stroke whose real-world walking is limited due to environmental barriers. Objective: The purpose of this work was to test a model hypothesizing the relationships among environmental factors (specifically, living situation and area deprivation), modifiable factors, and real-world walking activity to understand opportunities for intervention. We hypothesized that balance self-efficacy would mediate the relationship between the environment and real-world walking and that physical capacity would moderate this mediation. Methods: This was a cross-sectional study of 282 individuals with chronic (≥6 months) stroke. We tested the indirect effect to determine if mediation was present. Multiple group structural equation modeling was used to test if physical capacity moderated this mediation. A χ² difference test was used to compare the moderation model against the null (no moderation) model. Results: Balance self-efficacy mediated the relationship between area deprivation and real-world walking (indirect effect: β = −0.04, P = .04). Both the moderation and null models fit the data equally well statistically (χ²(5) = 6.9, P = .23). We therefore accepted the simpler (null) model and concluded that the mediation was not moderated. Conclusions: Targeting balance self-efficacy may be an effective approach to improving real-world walking in persons with stroke who experience barriers within the physical environment. A stroke survivor’s physical capacity may not impact this approach. Future work should consider utilizing more specific measures of the social and physical environment to better understand their influences on real-world walking activity in individuals with stroke. However, the results of this work provide excellent targets for future longitudinal studies targeting real-world walking activity in stroke.

It was previously found that balance self-efficacy mediated the relationship between physical capacity and participation after stroke. The effect of other factors that influence participation, such as depression, on this relationship has not been explored. This study examined the effect of symptoms of depression on the mediated relationship between physical capacity and participation by balance self-efficacy in individuals after stroke. In this cross-sectional study, 282 persons with chronic stroke (>6 months) were classified as having either low or high Geriatric Depression Scale scores. This study used a multiple group structural equation model to test moderated mediation by comparing a constrained model (indicating no effect of depression on the mediation) and an unconstrained model (indicating an effect of depression on the mediation). The models were compared using a chi-squared difference test. The chi-squared difference test suggested that the unconstrained model was a better fit, indicating that depressive symptoms moderated the mediated relationship between physical capacity and participation (χ²_{(3, N = 282)} = 9.0). In the Low Depression group, a significant indirect effect indicated that balance self-efficacy did mediate the relationship between physical capacity and participation. There was no significant indirect effect in the High Depression group. The results suggest the relationship between physical capacity and participation appears to be mediated by balance self-efficacy in individuals after stroke with low reports of depressive symptoms, but in those with high reports of depressive symptoms, physical capacity and balance self-efficacy are unrelated to participation. Targeting balance self-efficacy to improve post-stroke participation may be beneficial only for individuals with low reports of depression. In individuals after stroke with high reports of depression, treatment should include and emphasize the treatment of those depressive symptoms. Additional work further examining these complex relationships is warranted.

Background: While many factors are associated with stepping activity after stroke, there is significant variability across studies. One potential reason to explain this variability is that there are certain characteristics that are necessary to achieve greater stepping activity that differ from others that may need to be targeted to improve stepping activity. Objective: Using two step thresholds (2500 steps/day, corresponding to home vs. community ambulation and 5500 steps/day, corresponding to achieving physical activity guidelines through walking), we applied 3 different algorithms to determine which predictors are most important to achieve these thresholds. Methods: We analyzed data from 268 participants with stroke that included 25 demographic, performance-based and self-report variables. Step 1 of our analysis involved dimensionality reduction using lasso regularization. Step 2 applied drop column feature importance to compute the mean importance of each variable. We then assessed which predictors were important to all 3 mathematically unique algorithms. Results: The number of relevant predictors was reduced from 25 to 7 for home vs. community and from 25 to 16 for aerobic thresholds. Drop column feature importance revealed that 6 Minute Walk Test and speed modulation were the only variables found to be important to all 3 algorithms (primary characteristics) for each respective threshold. Other variables related to readiness to change activity behavior and physical health, among others, were found to be important to one or two algorithms (ancillary characteristics). Conclusions: Addressing physical capacity is necessary but not sufficient to achieve important step thresholds, as ancillary characteristics, such as readiness to change activity behavior and physical health may also need to be targeted. This delineation may explain heterogeneity across studies examining predictors of stepping activity in stroke.

Introduction: Rehabilitation is facing a critical practice gap: Patients seek out rehabilitation services to improve their activity in daily life, yet recent work demonstrates that rehabilitation may be having a limited impact on improving this outcome due to lack of objective data on patients’ activity in daily life. Remote monitoring using wearable sensor technology is a promising solution to this address this gap. The purpose of this study was to understand patient and clinician awareness of the practice gap and preferences for integrating wearable sensor technology into rehabilitation care.Methods: This study used a mixed-methods approach consisting of surveys and 1:1 interviews with clinicians (physical and occupational therapists or assistants) employed at an outpatient rehabilitation clinic within an academic medical center and patients seeking care at this clinic. Data were analyzed using descriptive statistics and thematic analysis.Results: Data saturation was reached from nineteen clinicians and ten patients. Both clinicians and patients recognized the importance of measuring activity outside the clinic and viewed wearable sensor technology as an objective measurement tool. Most clinicians (63%) preferred continuous (vs. intermittent) monitoring within a care episode and most patients (60%) were willing to sync their sensor data as often as instructed by their provider. To maximize integration into clinical workflows, clinicians voiced a preference for availability of sensor data in the electronic health record.Conclusions: Clinicians and patients value the use of wearable sensor technology to improve measurement of activity outside the clinic environment and expressed preferences for how this technology could best be integrated into routine rehabilitation care.