Lisa A. Simpson

The Health and Life Priorities of Individuals with Spinal Cord Injury: A Systematic Review

Determining the priorities of individuals with spinal cord injury (SCI) can assist in choosing research priorities that will ultimately improve their quality of life. This systematic review examined studies that directly surveyed people with SCI to ascertain their health priorities and life domains of importance. Twenty-four studies (a combined sample of 5262 subjects) that met the inclusion criteria were identified using electronic databases (Medline, EMBASE, CINAHL, and PsycINFO). The questionnaire methods and domains of importance were reviewed and described. While the questionnaires varied across studies, a consistent set of priorities emerged. Functional recovery priorities were identified for the following areas: motor function (including arm/hand function for individuals with tetraplegia, and mobility for individuals with paraplegia), bowel, bladder, and sexual function. In addition, health, as well as relationships, emerged as important life domains. The information from this study, which identified the priorities and domains of importance for individuals with SCI, may be useful for informing health care and research agenda-setting activities.

Effect of Stroke on Fall Rate, Location and Predictors: A Prospective Comparison of Older Adults with and without Stroke

Background The literature suggests that stroke is a major risk factor for falls, but there is a lack of prospective, controlled studies which quantify fall-risk after stroke. The purpose of this study was to compare the rates, location and predictors among individuals recently discharged home from stroke rehabilitation to age and sex matched controls. Methodology/Principal Findings A sample of 80 people with stroke and 90 controls received baseline assessments of balance, mobility and balance confidence. Falls were recorded prospectively over 13 months for both groups. Group differences in fall rates and contribution of clinical measures to falls were determined using negative binomial regression. Fall location was compared between groups using χ2 statistics. The rate of falls for individuals with stroke was 1.77 times the rate for the control group. People with stroke were more likely to fall at home. Poorer balance (Berg Balance Scale) was associated with greater falls for both stroke and control groups (incidence rate ratio [IRR]: 0.908 and IRR: 0.877 respectively). A faster Timed Up and Go Test was associated with greater falls for the stroke group (IRR: 0.955) while better walking endurance (Six Minute Walk Test) was associated with greater falls for the controls (IRR: 1.004). Balance confidence was not an independent predictor in either group. Conclusions Individuals recently discharged home are at greater risk of falling than individuals without stroke. Attention to home environment is warranted. Balance function can predict falls for both people with stroke and age and sex matched controls. Increased mobility may increase exposure to fall opportunities.

Capturing step counts at slow walking speeds in older adults: comparison of ankle and waist placement of measuring device.

OBJECTIVE It is important for older adults to be physically active, but many older adults walk slowly. This study examined the accuracy of a commercially available step-count device (Fitbit One) at slow speeds and compared the accuracy of the device when worn at the ankle and waist in older adults. METHODS The Fitbit One was placed at the ankle and waist of participants (n=42; mean age 73 years) while they performed walking trials at 7 different speeds (0.3-0.9 m/s). Step counts obtained from video recordings were used as the gold standard comparison to determine the accuracy of the device. RESULTS The ankle-worn device had significantly less error than the waist-worn device at all speeds. The percentage error of the ankle-worn device was less than 10% at speeds of 0.4-0.9 m/s and did not record zero steps at any speed. The percentage error of the waist-worn device was below 10% at only the 2 fastest speeds (0.8 and 0.9 m/s) and recorded zero steps for numerous participants at speeds of 0.3-0.5 m/s. CONCLUSION The Fitbit One can accurately capture steps at slow speeds when placed at the ankle and thus may be appropriate for capturing physical activity in slow-walking older adults.

“Stepping Up” Activity Poststroke: Ankle-Positioned Accelerometer Can Accurately Record Steps During Slow Walking

Background As physical activity in people poststroke is low, devices that monitor and provide feedback of walking activity provide motivation to engage in exercise and may assist rehabilitation professionals in auditing walking activity. However, most feedback devices are not accurate at slow walking speeds. Objective This study assessed the accuracy of one accelerometer to measure walking steps of community-dwelling individuals poststroke. Design This was a cross-sectional study. Methods Two accelerometers were positioned on the nonparetic waist and ankle of participants (N=43), and walking steps from these devices were recorded at 7 speeds (0.3–0.9 m/s) and compared with video recordings (gold standard). Results When positioned at the waist, the accelerometer had more than 10% error at all speeds, except 0.8 and 0.9 m/s, and numerous participants recorded zero steps at 0.3 to 0.5 m/s. The device had 10% or less error when positioned at the ankle for all speeds between 0.4 and 0.9 m/s. Limitations Some participants were unable to complete the faster walking speeds due to their walking impairments and inability to maintain the requested walking speed. Conclusions Although not recommended by the manufacturer, positioning the accelerometer at the ankle (compared with the waist) may fill a long-standing need for a readily available device that provides accurate feedback for the altered and slow walking patterns that occur with stroke.

Functional Recovery Following Stroke: Capturing Changes in Upper-Extremity Function

Background and purpose. Augmenting changes in recovery is core to the rehabilitation process following a stroke. Hence it is essential that outcome measures are able to detect change as it occurs, a property known as responsiveness. This article critically reviewed the responsiveness of functional outcome measures following stroke, specifically examining tools that captured upper-extremity (UE) functional recovery. Methods. A systematic search of the literature was undertaken to identify articles providing responsiveness data for 3 types of change (observed, detectable, and important). Results. Data from 68 articles for 14 UE functional outcome measures were retrieved. Larger percentage changes were required to be considered important when obtained through anchor-based methods (eg, based on patient opinion or comparative measure) compared with distribution methods (eg, statistical estimates). Larger percentage changes were required to surpass the measurement error for patient-perceived functional measures (eg, Motor Activity Log) compared with laboratory-based performance measures (eg, Action Research Arm Test). The majority of rehabilitation interventions have similar effect sizes on patient-perceived UE function and laboratory-based UE function. Conclusions. The magnitude of important change or change that surpasses measurement error can vary substantially depending on the method of calculation. Rehabilitation treatments can affect patient perceptions of functional change as effectively as laboratory-based functional measures; however, larger sample sizes may be required to account for the larger measurement error associated with patient-perceived functional measures.

Rating of Everyday Arm-Use in the Community and Home (REACH) Scale for Capturing Affected Arm-Use after Stroke: Development, Reliability, and Validity

Objective To develop a brief, valid and reliable tool [the Rating of Everyday Arm-use in the Community and Home (REACH) scale] to classify affected upper limb use after stroke outside the clinical setting. Methods Focus groups with clinicians, patients and caregivers (n = 33) and a literature review were employed to develop the REACH scale. A sample of community-dwelling individuals with stroke was used to assess the validity (n = 96) and inter-rater reliability (n = 73) of the new scale. Results The REACH consists of separate scales for dominant and non-dominant affected upper limbs, and takes five minutes to administer. Each scale consists of six categories that capture ‘no use’ to ‘full use’. The intraclass correlation coefficient and weighted kappa for inter-rater reliability were 0.97 (95% confidence interval: 0.95–0.98) and 0.91 (0.89–0.93) respectively. REACH scores correlated with external measures of upper extremity use, function and impairment (rho = 0.64–0.94). Conclusions The REACH scale is a reliable, quick-to-administer tool that has strong relationships to other measures of upper limb use, function and impairment. By providing a rich description of how the affected upper limb is used outside of the clinical setting, the REACH scale fills an important gap among current measures of upper limb use and is useful for understanding the long term effects of stroke rehabilitation.

Force Myography for Monitoring Grasping in Individuals with Stroke with Mild to Moderate Upper-Extremity Impairments: A Preliminary Investigation in a Controlled Environment

There is increasing research interest in technologies that can detect grasping, to encourage functional use of the hand as part of daily living, and thus promote upper-extremity motor recovery in individuals with stroke. Force myography (FMG) has been shown to be effective for providing biofeedback to improve fine motor function in structured rehabilitation settings, involving isolated repetitions of a single grasp type, elicited at a predictable time, without upper-extremity movements. The use of FMG, with machine learning techniques, to detect and distinguish between grasping and no grasping, continues to be an active area of research, in healthy individuals. The feasibility of classifying FMG for grasp detection in populations with upper-extremity impairments, in the presence of upper-extremity movements, as would be expected in daily living, has yet to be established. We explore the feasibility of FMG for this application by establishing and comparing (1) FMG-based grasp detection accuracy and (2) the amount of training data necessary for accurate grasp classification, in individuals with stroke and healthy individuals. FMG data were collected using a flexible forearm band, embedded with six force-sensitive resistors (FSRs). Eight participants with stroke, with mild to moderate upper-extremity impairments, and eight healthy participants performed 20 repetitions of three tasks that involved reaching, grasping, and moving an object in different planes of movement. A validation sensor was placed on the object to label data as corresponding to a grasp or no grasp. Grasp detection performance was evaluated using linear and non-linear classifiers. The effect of training set size on classification accuracy was also determined. FMG-based grasp detection demonstrated high accuracy of 92.2% (σ = 3.5%) for participants with stroke and 96.0% (σ = 1.6%) for healthy volunteers using a support vector machine (SVM). The use of a training set that was 50% the size of the testing set resulted in 91.7% (σ = 3.9%) accuracy for participants with stroke and 95.6% (σ = 1.6%) for healthy participants. These promising results indicate that FMG may be feasible for monitoring grasping, in the presence of upper-extremity movements, in individuals with stroke with mild to moderate upper-extremity impairments.

H-GRASP: the feasibility of an upper limb home exercise program monitored by phone for individuals post stroke

Abstract Purpose: To investigate the feasibility of a phone-monitored home exercise program for the upper limb following stroke. Methods: A pre-post double baseline repeated measures design was used. Participants completed an 8-week home exercise program that included behavioural strategies to promote greater use of the affected upper limb. Participants were monitored weekly by therapists over the phone. The following feasibility outcomes were collected: Process (e.g. recruitment rate); Resources (e.g. exercise adherence rate); Management (e.g. therapist monitoring) and Scientific (e.g. safety, effect sizes). Clinical outcomes included: The Chedoke Arm and Hand Inventory, Motor Activity Log, grip strength and the Canadian Occupational Performance Measure. Results: Eight individuals with stroke were recruited and six participants completed the exercise program. All but one of the six participants met the exercise target of 60 minutes/day, 6 days/week. Participants were stable across the baseline period. The following post-treatment effect sizes were observed: CAHAI (0.944, p = 0.046); MALQ (0.789, p = 0.03) grip strength (0.947, p = 0.046); COPM (0.789, p = 0.03). Improvements were maintained at three and six month follow ups. Conclusions: Community dwelling individuals with stroke may benefit from a phone-monitored upper limb home exercise program that includes behavioural strategies that promote transfer of exercise gains into daily upper limb use. Implications for Rehabilitation A repetitive, task-oriented home exercise program that utilizes telephone supervision may be an effective method for the treatment of the upper limb following stroke This program is best suited for individuals with mild to moderate level impairment and experience a sufficient level of challenge from the exercises An exercise program that includes behavioural strategies may promote transfer of exercise gains into greater use of the affected upper limb during daily activities

Support service utilization and out-of-pocket payments for health services in a population-based sample of adults with neurological conditions

Background Social support can help to deal with the consequences of neurological conditions and promote functional independence and quality of life. Our aim was to evaluate the impact of neurological conditions on the use of support and health-care services in a population-based sample of community-dwelling adults with neurological conditions. Methods Data were from the Survey of Living with Neurological Conditions in Canada, which was derived from a representative sample of household residents. Formal and informal support received and out-of-pocket payments were assessed by personal interviews. Logistic regression was used to explore the association between support service utilization and six common neurological conditions (Stroke, Parkinsons disease, Alzheimers disease/dementias, traumatic brain injury, spinal cord injury and multiple sclerosis) with stroke as the reference category. Results The sample contained 2,410 respondents and equate to an estimated 459,770 when sample weights were used. A larger proportion of people within each of the neurological conditions received informal support than formal support (at least twice as much). Samples with the non-stroke conditions were more likely to receive formal assistance for personal (odds ratios 2.7 to 5.6; P < 0.05) and medical (odds ratios 2.4 to 4.4; P < 0.05) care compared to the stroke group. Also, the non-stroke conditions were more likely to receive informal assistance (odds ratios 2.7 to 17.9; P < 0.05) and less likely to make out-of-pocket payments for rehabilitation therapy (odds ratios 0.2 to 0.3; P < 0.05) than the stroke group. The Alzheimer’s disease/dementia group had the highest proportion who received formal and informal support services. Conclusions Our findings suggest that Canadians with neurological conditions receive more informal assistance than formal assistance. Furthermore, it appears that stroke survivors receive less support services, while those with Alzheimer’s disease/dementia receive the most compared to other adult neurological conditions. Such data can help inform the development of support services in the community.