Corrigendum: Referent data for investigations of upper limb accelerometry: harmonized data from three cohorts of typically-developing children.

[This corrects the article DOI: 10.3389/fped.2024.1361757.].

Quantifying the effects of sleep on sensor-derived variables from upper limb accelerometry in people with and without upper limb impairment.

BACKGROUND: Despite the promise of wearable sensors for both rehabilitation research and clinical care, these technologies pose significant burden on data collectors and analysts. Investigations of factors that may influence the wearable sensor data processing pipeline are needed to support continued use of these technologies in rehabilitation research and integration into clinical care settings. The purpose of this study was to investigate the effect of one such factor, sleep, on sensor-derived variables from upper limb accelerometry in people with and without upper limb impairment and across a two-day wearing period. METHODS: This was a secondary analysis of data collected during a prospective, longitudinal cohort study (n = 127 individuals, 62 with upper limb impairment and 65 without). Participants wore a wearable sensor on each wrist for 48 h. Five upper limb sensor variables were calculated over the full wear period (sleep included) and with sleep time removed (sleep excluded): preferred time, non-preferred time, use ratio, non-preferred magnitude and its standard deviation. Linear mixed effects regression was used to quantify the effect of sleep on each sensor variable and determine if the effect differed between people with and without upper limb impairment and across a two-day wearing period. RESULTS: There were significant differences between sleep included and excluded for the variables preferred time (p < 0.001), non-preferred time (p < 0.001), and non-preferred magnitude standard deviation (p = 0.001). The effect of sleep was significantly different between people with and without upper limb impairment for one variable, non-preferred magnitude (p = 0.02). The effect of sleep was not substantially different across wearing days for any of the variables. CONCLUSIONS: Overall, the effects of sleep on sensor-derived variables of upper limb accelerometry are small, similar between people with and without upper limb impairment and across a two-day wearing period, and can likely be ignored in most contexts. Ignoring the effect of sleep would simplify the data processing pipeline, facilitating the use of wearable sensors in both research and clinical practice.

Knowledge Translation Task Force for core measures clinical practice guideline: a short report on the process and utilization.

BACKGROUND: As part of the 2018 Clinical Practice Guideline (CPG): A Core Set of Outcome Measures for Adults with Neurologic Conditions Undergoing Rehabilitation, a Knowledge Translation (KT) Task Force was convened. The purpose of this short report was to (1) demonstrate the potential impact of a CPG KT Task Force through a practical example of efforts to implement a CPG into neurologic physical therapy practice and (2) describe the process to convene a KT Task Force and develop products (KT Toolkit) to facilitate implementation of the CPG. METHODS: To describe the process used by the KT Task Force to develop and review a KT Toolkit for implementation of the CPG. RESULTS: Utilizing the Knowledge-To-Action Cycle framework, eight tools were developed as part of the KT Toolkit and are available with open access to the public. Findings indicate that the Core Outcome Measures Homepage, which houses the KT Toolkit, has had greater than 70,000 views since its publication. CONCLUSIONS: This short report serves as an example of the efforts made to implement a CPG into physical therapy practice. The processes to facilitate KT and the tools developed can inform future implementation efforts and underscore the importance of having a KT Task Force to implement a CPG. Moving forward, KT Task Forces should be convened to implement new or revised guidelines. TRIAL REGISTRATION: N/A.

Referent data for investigations of upper limb accelerometry: harmonized data from three cohorts of typically-developing children.

Aim: The rise of wearable sensing technology shows promise for addressing the challenges of measuring motor behavior in pediatric populations. The current pediatric wearable sensing literature is highly variable with respect to the number of sensors used, sensor placement, wearing time, and how data extracted from the sensors are analyzed. Many studies derive conceptually similar variables via different calculation methods, making it hard to compare across studies and clinical populations. In hopes of moving the field forward, this report provides referent upper limb wearable sensor data from accelerometers on 25 variables in typically-developing children, ages 3-17 years. Methods: This is a secondary analysis of data from three pediatric cohorts of children 3-17 years of age. Participants (n = 222) in the cohorts wore bilateral wrist accelerometers for 2-4 days for a total of 622 recording days. Accelerometer data were reprocessed to compute 25 variables that quantified upper limb movement duration, intensity, symmetry, and complexity. Analyses examined the influence of hand dominance, age, gender, reliability, day-to-day stability, and the relationships between variables. Results: The majority of variables were similar on the dominant and non-dominant sides, declined slightly with age, and were not different between boys and girls. ICC values were moderate to excellent. Variation within individuals across days generally ranged from 3% to 32%. A web-based R shiny object is available for data viewing. Interpretation: With the use of wearable movement sensors increasing rapidly, these data provide key, referent information for researchers as they design studies, and analyze and interpret data from neurodevelopmental and other pediatric clinical populations. These data may be of particularly high value for pediatric rare diseases.

ICF classification of therapeutic goals for outpatient episodes of neurorehabilitation in post-stroke and Parkinson disease.

PURPOSE: To understand therapeutic priorities, a secondary data analysis on a retrospective cohort was conducted to classify rehabilitation goals according to the International Classification of Functioning, Disability, and Health (ICF). MATERIALS AND METHODS: Therapeutic goals from an initial outpatient physical or occupational therapy evaluation for patients post-stroke or with Parkinson disease, were classified into Level 1 of the ICF. Goals in the Activity and Participation component were further sub-classified as activity capacity or activity performance (self-report or direct) in daily life. RESULTS: 776 goals across 104 participants were classified into Level 1 of the ICF. The majority, 73% (563/776) were classified as Activity and Participation, 20% (155/776) as Body Function and 2% (17/776) as Environmental Factors. Fifty-two percent (400/776) of all goals were classified as activity capacity and 21% (163/776) as activity performance in daily life, with 21% (160/776) of goals measuring self-report activity performance in daily life and less than 1% (3/776) of goals measuring direct activity performance in daily life. CONCLUSIONS: While the majority of therapeutic goals were classified into the Activity and Participation component, less than 1% of goals measured direct activity performance in daily life. If people seek outpatient rehabilitation to improve functioning in their real-world environment, therapeutic goal setting should reflect this.

The majority of therapeutic goals for an episode of outpatient neurorehabilitation were classified into the Activity and Participation component of the International Classification of Functioning, Disability, and Health.However, less than 1% of therapeutic goals measured direct activity performance in daily life.If people with neurological diagnoses seek out outpatient rehabilitation to improve functioning in their real-world environment, than therapeutic goal setting should reflect this.

Comprehensive Assessment of the Activity Level of the ICF Using Both Capacity and Performance Measures: A Case Report.

Individuals with neurologic conditions seek physical therapy services to improve mobility in their daily lives. While clinicians commonly track activity capacity, measurement of activity performance in daily life is an emerging yet unstandardized practice within routine clinical physical therapy. The purpose of this case report is to (1) provide an example of the structure, clinical reasoning, and implementation of both activity capacity and activity performance level assessments across an episode of outpatient physical therapy and (2) to describe how objective activity performance in daily life tracking supported the physical therapy intervention and education plan. A 42-year-old woman presented to outpatient neurologic physical therapy with a rare autoimmune-mediated disorder with primary goals of independently caring for her youngest child and grandchild, walking without limitations in the home and community, participating in exercise, and returning to work due to deconditioning and dizziness. The patient participated in 12 visits across a span of 4.5 months targeting performance in daily life (steps per day), aerobic conditioning, and vestibular habituation. Activity capacity measurement served as a standardized assessment of what the patient was able to do in the clinic, and activity performance in daily life tracking via a Samsung wrist worn consumer-grade device provided a quantitative assessment of real-world daily stepping activity. Tracking of activity performance in daily life was an essential component of physical therapy management that provided an objective quantification of daily stepping activity to identify barriers and facilitators to increasing daily performance in an individual with a medical diagnosis of Susac syndrome.

Predicting later categories of upper limb activity from earlier clinical assessments following stroke: an exploratory analysis.

BACKGROUND: Accelerometers allow for direct measurement of upper limb (UL) activity. Recently, multi-dimensional categories of UL performance have been formed to provide a more complete measure of UL use in daily life. Prediction of motor outcomes after stroke have tremendous clinical utility and a next step is to explore what factors might predict someone's subsequent UL performance category. PURPOSE: To explore how different machine learning techniques can be used to understand how clinical measures and participant demographics captured early after stroke are associated with the subsequent UL performance categories. METHODS: This study analyzed data from two time points from a previous cohort (n = 54). Data used was participant characteristics and clinical measures from early after stroke and a previously established category of UL performance at a later post stroke time point. Different machine learning techniques (a single decision tree, bagged trees, and random forests) were used to build predictive models with different input variables. Model performance was quantified with the explanatory power (in-sample accuracy), predictive power (out-of-bag estimate of error), and variable importance. RESULTS: A total of seven models were built, including one single decision tree, three bagged trees, and three random forests. Measures of UL impairment and capacity were the most important predictors of the subsequent UL performance category, regardless of the machine learning algorithm used. Other non-motor clinical measures emerged as key predictors, while participant demographics predictors (with the exception of age) were generally less important across the models. Models built with the bagging algorithms outperformed the single decision tree for in-sample accuracy (26-30% better classification) but had only modest cross-validation accuracy (48-55% out of bag classification). CONCLUSIONS: UL clinical measures were the most important predictors of the subsequent UL performance category in this exploratory analysis regardless of the machine learning algorithm used. Interestingly, cognitive and affective measures emerged as important predictors when the number of input variables was expanded. These results reinforce that UL performance, in vivo, is not a simple product of body functions nor the capacity for movement, instead being a complex phenomenon dependent on many physiological and psychological factors. Utilizing machine learning, this exploratory analysis is a productive step toward the prediction of UL performance. Trial registration NA.

Accuracy of an Algorithm in Predicting Upper Limb Functional Capacity in a United States Population.

OBJECTIVE: To determine the accuracy of an algorithm, using clinical measures only, on a sample of persons with first-ever stroke in the United States (US). It was hypothesized that algorithm accuracy would fall in a range of 70%-80%. DESIGN: Secondary analysis of prospective, observational, longitudinal cohort; 2 assessments were done: (1) within 48 hours to 1 week poststroke and (2) at 12 weeks poststroke. SETTING: Recruited from a large acute care hospital and followed over the first 6 months after stroke. PARTICIPANTS: Adults with first-ever stroke (N=49) with paresis of the upper limb (UL) at ≤48 hours who could follow 2-step commands and were expected to return to independent living at 6 months. INTERVENTION: Not applicable. MAIN OUTCOME MEASURES: The overall accuracy of the algorithm with clinical measures was quantified by comparing predicted (expected) and actual (observed) categories using a correct classification rate. RESULTS: The overall accuracy (61%) and weighted κ (62%) were significant. Sensitivity was high for the Excellent (95%) and Poor (81%) algorithm categories. Specificity was high for the Good (82%), Limited (98%), and Poor (95%) categories. Positive predictive value (PPV) was high for Poor (82%) and negative predictive value (NPV) was high for all categories. No differences in participant characteristics were found between those with accurate or inaccurate predictions. CONCLUSIONS: The results of the present study found that use of an algorithm with clinical measures only is better than chance alone (chance=25% for each of the 4 categories) at predicting a category of UL capacity at 3 months post troke. The moderate to high values of sensitivity, specificity, PPV, and NPV demonstrates some clinical utility of the algorithm within health care settings in the US.

Upper Limb Performance in Daily Life Approaches Plateau Around Three to Six Weeks Post-stroke.

Background. Wearable sensors allow for direct measurement of upper limb (UL) performance in daily life. Objective. To map the trajectory of UL performance and its relationships to other factors post-stroke. Methods. Participants (n = 67) with first stroke and UL paresis were assessed at 2, 4, 6, 8, 12, 16, 20, and 24 weeks after stroke. Assessments captured UL impairment (Fugl-Meyer), capacity for activity (Action Research Arm Test), and performance of activity in daily life (accelerometer variables of use ratio and hours of paretic limb activity), along with other potential modifying factors. We modeled individual trajectories of change for each measurement level and the moderating effects on UL performance trajectories. Results. Individual trajectories were best fit with a 3-parameter logistic model, capturing the rapid growth early after stroke within the longer data collection period. Plateaus (90% of asymptote) in impairment (bootstrap mean ± SE: 32 ± 4 days post-stroke) preceded those in capacity (41 ± 4 days). Plateau in performance, as measured by the use ratio (24 ± 5 days), tended to precede plateaus in impairment and capacity. Plateau in performance, as measured by hours of paretic activity (41 ± 6 days), occurred at a similar time to that of capacity and slightly lagged impairment. Modifiers of performance trajectories were capacity, concordance, UL rehabilitation, depressive symptomatology, and cognition. Conclusions. Upper limb performance in daily life approached plateau 3 to 6 weeks post-stroke. Individuals with stroke started to achieve a stable pattern of UL use in daily life early, often before neurological impairments and functional capacity started to stabilize.

Executive Function Moderates Functional Outcomes of Engagement Strategies During Rehabilitation in Older Adults.

OBJECTIVE: This study examined cognitive, affective, and medical impairments and their impact on rehabilitation approaches for improving functional outcome after hospitalization in older adults. DESIGN: A secondary analysis of a randomized clinical trial in 229 adults 65 yrs or older admitted to two skilled nursing facilities undergoing rehabilitation services was conducted. Patients were randomized to receive physical and occupational therapy by therapists trained in systematic approaches to engage patients, called Enhanced Medical Rehabilitation, or standard of care. The outcome of interest was functional improvement, defined as Barthel Index at discharge (controlling for Barthel Index upon admission). This study analyzed the relationship of measures of cognition, depression, and medical comorbidities as predictors of functional outcome and as moderators interacting with treatment group. RESULTS: Clock drawing score moderated treatment effect size; the functional improvement of Enhanced Medical Rehabilitation over standard of care therapy reduced with increasing executive impairment. In contrast, general cognitive abilities, depression, medical comorbidities, and readiness for rehabilitation were neither predictors nor moderators of functional improvement. CONCLUSIONS: For older adults undergoing rehabilitation, greater functional improvement with the motivational techniques of Enhanced Medical Rehabilitation was contingent on patients having intact executive function. Given that executive function impairments are common in rehabilitation populations, new strategies are needed to improve treatment outcomes in physical/occupational therapy. TO CLAIM CME CREDITS: Complete the self-assessment activity and evaluation online at http://www.physiatry.org/JournalCME. CME OBJECTIVES: Upon completion of this article, the reader should be able to (1) Discuss the role of baseline affective, cognitive, and medical impairments in impacting functional outcomes of older adults undergoing rehabilitation; (2) Describe the behavioral change and motivational approaches that are core features of the novel intervention known as Enhanced Medical Rehabilitation (E-MR); and (3) Determine the role of baseline executive function in moderating the effect of rehabilitation intervention on functional outcomes in older adults. LEVEL: Advanced. ACCREDITATION: The Association of Academic Physiatrists is accredited by the Accreditation Council for Continuing Medical Education to provide continuing medical education for physicians.The Association of Academic Physiatrists designates this Journal-based CME activity for a maximum of 1.0 AMA PRA Category 1 Credit(s)™. Physicians should only claim credit commensurate with the extent of their participation in the activity.

Activity Level and Intensity of Older Adults in Skilled Nursing Rehabilitation Measured via Actigraphy.

BACKGROUND AND PURPOSE: Increasing activity has been shown to improve outcomes in patients receiving post-acute rehabilitation, but little is known about the activity duration and intensity that are actually occurring throughout the rehabilitative stay for older adults in skilled nursing facilities. The purpose of this study was to quantify duration and intensity of movement in older adults receiving rehabilitation in a skilled nursing facility, using 4-limb actigraphy. METHODS: Observational study of 92 older adults admitted for rehabilitation services at 2 skilled nursing facilities. All participants wore actigraph accelerometers (wGT3X+) on bilateral wrists and ankles for 24 hours, inclusive of 1 session each of physical and occupational therapy. Using actigraphy data, we calculated (a) movement duration (time the dominant or noninvolved upper or lower limb was active) and (b) movement intensity (sum of activity counts per minute for the dominant or noninvolved upper or lower limb). RESULTS: Over the 24-hour period, the lower limb moved a total median [interquartile range] of 01:10 (hours:minutes) [01:01] and the upper limb moved a total average (SD) of 04:45 (02:00). When participants did move, it was at low intensities with 61 [87] and 610 [623] activity counts per minute for lower limb out-of-therapy time and during physical therapy, respectively. For the upper limb, activity counts per minute were 689 (388) for out-of-therapy movement and 1359 (695) during physical therapy. However, neither the lower or upper limb reached a moderate-intensity level (2690-6166 counts per minute). DISCUSSION: Older adults receiving rehabilitation in 2 skilled nursing facilities had low movement duration and movement intensity both in and out of therapy. CONCLUSION: Rehabilitation interventions for older adults should target and increase movement duration and intensity, during and after skilled nursing facility care.

Implementation of Wearable Sensing Technology for Movement: Pushing Forward into the Routine Physical Rehabilitation Care Field.

While the promise of wearable sensor technology to transform physical rehabilitation has been around for a number of years, the reality is that wearable sensor technology for the measurement of human movement has remained largely confined to rehabilitation research labs with limited ventures into clinical practice. The purposes of this paper are to: (1) discuss the major barriers in clinical practice and available wearable sensing technology; (2) propose benchmarks for wearable device systems that would make it feasible to implement them in clinical practice across the world and (3) evaluate a current wearable device system against the benchmarks as an example. If we can overcome the barriers and achieve the benchmarks collectively, the field of rehabilitation will move forward towards better movement interventions that produce improved function not just in the clinic or lab, but out in peoples' homes and communities.

Day-to-Day Variability of Walking Performance Measures in Individuals Poststroke and Individuals With Parkinson Disease.

BACKGROUND AND PURPOSE: Improvement of walking performance is a primary goal for individuals poststroke or with Parkinson disease (PD) who receive physical therapy. More data about day-to-day variability of walking performance are critical for determining if changes in performance have occurred. METHODS: Baseline assessments were utilized from an ongoing, observational, prospective cohort study including 84 individuals poststroke (n = 37) or with PD (n = 47) receiving outpatient physical therapy services to improve mobility. Participants wore step activity monitors for up to 7 days to measure walking performance (steps per day, walking duration, maximum 30-minute output, and peak activity index) in daily life. Correlation analyses evaluated relationships between both capacity and performance measures as well as the relationships between mean performance variables and day-to-day variability. Regression analyses explored factors that contribute to variability in day-to-day performance variables. RESULTS: Mean steps per day for participants poststroke (5376 ± 2804) and with PD (8149 ± 4490) were consistent with previously reported cohorts. Greater amounts of walking were related to more day-to-day variability, with moderate correlations found between the mean and day-to-day variability of each performance measure, regardless of medical diagnosis or walking speed. Day-to-day variability is large (upwards of 50% of the mean), with the amount of walking performance serving as the primary predictor of day-to-day variability in walking performance. DISCUSSION AND CONCLUSIONS: The results of this study elucidate the factors that are related to and predict day-to-day variability of performance. Walking performance metrics should be evaluated over multiple days and greater variability should be anticipated with greater amounts of performance.Video Abstract available for more insights from the authors (see the Video, Supplemental Digital Content 1, available at: http://links.lww.com/JNPT/A319).

Effects of remote limb ischemic conditioning on muscle strength in healthy young adults: A randomized controlled trial.

Remote limb ischemic conditioning (RLIC) is a clinically feasible method in which brief, sub-lethal bouts of ischemia protects remote organs or tissues from subsequent ischemic injury. A single session of RLIC can improve exercise performance and increase muscle activation. The purpose of this study, therefore, was to assess the effects of a brief, two-week protocol of repeated RLIC combined with strength training on strength gain and neural adaptation in healthy young adults. Participants age 18-40 years were randomized to receive either RLIC plus strength training (n = 15) or sham conditioning plus strength training (n = 15). Participants received RLIC or sham conditioning over 8 visits using a blood pressure cuff on the dominant arm with 5 cycles of 5 minutes each alternating inflation and deflation. Visits 3-8 paired conditioning with wrist extensors strength training on the non-dominant (non-conditioned) arm using standard guidelines. Changes in one repetition maximum (1 RM) and electromyography (EMG) amplitude were compared between groups. Both groups were trained at a similar workload. While both groups gained strength over time (P = 0.001), the RLIC group had greater strength gains (9.38 ± 1.01 lbs) than the sham group (6.3 ± 1.08 lbs, P = 0.035). There was not a significant group x time interaction in EMG amplitude (P = 0.231). The RLIC group had larger percent changes in 1 RM (43.8% vs. 26.1%, P = 0.003) and EMG amplitudes (31.0% vs. 8.6%, P = 0.023) compared to sham conditioning. RLIC holds promise for enhancing muscle strength in healthy young and older adults, as well as clinical populations that could benefit from strength training.

Dose of remote limb ischemic conditioning for enhancing learning in healthy young adults.

Remote limb ischemic conditioning (RLIC) is a technique in which tissues distant from the target organ are exposed to brief, sub-lethal bouts of ischemia. The effects of remotely applied ischemic conditioning are systemically transferred to the target organ, and typically manifested as protection from subsequent ischemic injury. Previous studies in our lab have found and confirmed that RLIC enhances learning and retention during motor training on a balance task. The current study tested the effect of RLIC dose (number of cycles) on learning enhancement in young, healthy adults. Forty healthy participants age 18-40 years were randomized to receive 5 cycles of sham conditioning (n = 9), 3 cycles of RLIC (n = 11), 4 cycles of RLIC (n = 10), or 5 cycles of RLIC (n = 10) using a blood pressure cuff around the upper arm once a day for 7 consecutive weekdays (Days 1-7). Participants concurrently trained on a balance task, bimanual cup stacking task, and a discrete sequence production task on Days 3-7. Change in performance on each of the three tasks was compared across groups. Participants in all four groups improved their performance on each of the three tasks over time. However, RLIC at any dose did not enhance learning on any of the three tasks. While RLIC is safe, inexpensive, and clinically feasible, reproducibility may be challenged by unidentified factors, raising critical challenges to the straightforward translation of RLIC for improving rehabilitation outcomes in individuals recovering from neurological injury.

Remote Limb Ischemic Conditioning and Motor Learning: Evaluation of Factors Influencing Response in Older Adults.

Remote limb ischemic conditioning (RLIC) is a clinically feasible method of promoting tissue protection against subsequent ischemic insult. Recent findings from our lab demonstrated that RLIC robustly enhances motor learning in young, healthy humans. The next step is to determine which individuals would receive maximum benefit from RLIC before applying these findings to clinical rehabilitation populations such as stroke. Numerous factors, such as age, sex, body mass index (BMI), and cardiovascular comorbidities may influence the response. Sixty-nine participants aged 40-80 were randomized to receive either RLIC (n = 33) or sham (n = 36) conditioning. Participants underwent seven consecutive sessions consisting of RLIC or sham conditioning with a blood pressure cuff on the upper extremity and motor training on a stability platform balance task, with two follow-up sessions. Balance change (post-test-pre-test) was compared across participants, groups, and the factors of age, sex, BMI, and comorbidities. Participants in both groups improved their performance on the balance task from pre- to post-test. Overall balance change was independently associated with age and BMI. There was no difference in balance change between RLIC and Sham groups. However, RLIC significantly enhanced balance performance in participants with no comorbidities. Compared with our previous study in young adults, middle-aged and older adults demonstrated smaller improvements on the balance task. RLIC enhanced learning in middle-aged and older adults only in the absence of pre-defined comorbidities. RLIC may be a promising tool for enhancing motor recovery, but the accumulation of comorbidity with age may decrease its effectiveness.

A Method for Quantifying Upper Limb Performance in Daily Life Using Accelerometers.

A key reason for referral to rehabilitation services after stroke and other neurological conditions is to improve one's ability to function in daily life. It has become important to measure a person's activities in daily life, and not just measure their capacity for activity in the structured environment of a clinic or laboratory. A wearable sensor that is now enabling measurement of daily movement is the accelerometer. Accelerometers are commercially-available devices resembling large wrist watches that can be worn throughout the day. Data from accelerometers can quantify how the limbs are engaged to perform activities in peoples' homes and communities. This report describes a methodology to collect accelerometry data and turn it into clinically-relevant information. First, data are collected by having the participant wear two accelerometers (one on each wrist) for 24 h or longer. The accelerometry data are then downloaded and processed to produce four different variables that describe key aspects of upper limb activity in daily life: hours of use, use ratio, magnitude ratio, and the bilateral magnitude. Density plots can be constructed that visually represent the data from the 24 h wearing period. The variables and their resultant density plots are highly consistent in neurologically-intact, community-dwelling adults. This striking consistency makes them a useful tool for determining if upper limb daily performance is different from normal. This methodology is appropriate for research studies investigating upper limb dysfunction and interventions designed to improve upper limb performance in daily life in people with stroke and other patient populations. Because of its relative simplicity, it may not be long before it is also incorporated in clinical neurorehabilitation practice.

Enhanced Medical Rehabilitation: Effectiveness of a clinical training model.

BACKGROUND: Patient engagement in medical rehabilitation can be greatly influenced by their provider during therapy sessions. We developed Enhanced Medical Rehabilitation (EMR), a set of provider skills grounded in theories of behavior change. EMR utilizes 18 motivational techniques focused on providing frequent feedback to patients on their effort and progress and linking these to patient goals. OBJECTIVE: To examine the effectiveness of a clinical training protocol for clinicians to do EMR, as measured by clinician adherence. METHODS: A physical therapist, physical therapist assistant, occupational therapist, and certified occupational therapist assistant were trained in EMR. Training consisted of five formal training sessions and individual and group coaching. Adherence to EMR techniques was measured during two phases: Pre-Training and Maintenance, with an a priori target of 90% adherence by clinicians to each EMR technique. RESULTS: With training and coaching, clinician adherence per therapeutic activity significantly improved in 13 out of 18 items (p < 0.05). The target of 90% adherence was not achieved for many items. CONCLUSIONS: Our training and coaching program successfully trained clinicians to promote patient engagement during therapeutic service delivery, although not typically to 90% or greater adherence. Ongoing coaching efforts were necessary to increase adherence.