Identification of a know-do gap: An observational study of the assessment and treatment of dysphagia during inpatient stroke rehabilitation in primary healthcare in Norway.

PURPOSE: Oropharyngeal dysphagia is a common swallowing impairment post-stroke managed by speech language pathologists (SLP). This article aims to demonstrate a local know-do gap assessment for usual dysphagia care for patients undergoing inpatient stroke rehabilitation in primary healthcare in Norway, which included an assessment of the functional level of the patients and characteristics and outcomes of treatment. MATERIALS AND METHODS: In this observational study, we assessed the outcomes and interventions of patients admitted to inpatient rehabilitation following stroke. The patients received usual care from SLPs while the research team administered a dysphagia assessment protocol that included assessment of several swallowing domains including oral intake, swallowing, patient self-reported functional health status and health-related quality of life, and oral health. The treating SLPs documented the treatments provided in a treatment diary. RESULTS: Of 91 patients who consented, 27 were referred for SLP and 14 received treatment. During the median treatment period of 31.5 days (IQR = 8.8-57.0), patients received 7.0 treatment sessions (IQR = 3.8-13.5) of 60 minutes (IQR = 55-60). The patients who received SLP treatment demonstrated no/minor disorders (n = 7) and moderate/severe disorders (n = 7). Dysphagia treatments primarily included oromotor training and advice on bolus modification and were provided without association to dysphagia severity. Patients with moderate/severe swallowing impairments received slightly more SLP sessions over a longer time. CONCLUSIONS: This study identified gaps between current and best practices and opportunities to improve assessment, decision-making, and implement evidence-based practices.

A large, curated, open-source stroke neuroimaging dataset to improve lesion segmentation algorithms.

Accurate lesion segmentation is critical in stroke rehabilitation research for the quantification of lesion burden and accurate image processing. Current automated lesion segmentation methods for T1-weighted (T1w) MRIs, commonly used in stroke research, lack accuracy and reliability. Manual segmentation remains the gold standard, but it is time-consuming, subjective, and requires neuroanatomical expertise. We previously released an open-source dataset of stroke T1w MRIs and manually-segmented lesion masks (ATLAS v1.2, N = 304) to encourage the development of better algorithms. However, many methods developed with ATLAS v1.2 report low accuracy, are not publicly accessible or are improperly validated, limiting their utility to the field. Here we present ATLAS v2.0 (N = 1271), a larger dataset of T1w MRIs and manually segmented lesion masks that includes training (n = 655), test (hidden masks, n = 300), and generalizability (hidden MRIs and masks, n = 316) datasets. Algorithm development using this larger sample should lead to more robust solutions; the hidden datasets allow for unbiased performance evaluation via segmentation challenges. We anticipate that ATLAS v2.0 will lead to improved algorithms, facilitating large-scale stroke research.

No add-on effect of tDCS on fatigue and depression in chronic stroke patients: A randomized sham-controlled trial combining tDCS with computerized cognitive training.

BACKGROUND: Fatigue and emotional distress rank high among self-reported unmet needs in life after stroke. Transcranial direct current stimulation (tDCS) may have the potential to alleviate these symptoms for some patients, but the acceptability and effects for chronic stroke survivors need to be explored in randomized controlled trials. METHODS: Using a randomized sham-controlled parallel design, we evaluated whether six sessions of 1 mA tDCS (anodal over F3, cathodal over O2) combined with computerized cognitive training reduced self-reported symptoms of fatigue and depression. Among the 74 chronic stroke patients enrolled at baseline, 54 patients completed the intervention. Measures of fatigue and depression were collected at five time points spanning a 2 months period. RESULTS: While symptoms of fatigue and depression were reduced during the course of the intervention, Bayesian analyses provided evidence for no added beneficial effect of tDCS. Less severe baseline symptoms were associated with higher performance improvement in select cognitive tasks, and study withdrawal was higher in patients with more fatigue and younger age. Time-resolved symptom analyses by a network approach suggested higher centrality of fatigue items (except item 1 and 2) than depression items. CONCLUSION: The results reveal no add-on effect of tDCS on fatigue or depression but support the notion of fatigue as a relevant clinical symptom with possible implications for treatment adherence and response.

Cardiometabolic risk factors associated with brain age and accelerate brain ageing.

The structure and integrity of the ageing brain is interchangeably linked to physical health, and cardiometabolic risk factors (CMRs) are associated with dementia and other brain disorders. In this mixed cross-sectional and longitudinal study (interval mean = 19.7 months), including 790 healthy individuals (mean age = 46.7 years, 53% women), we investigated CMRs and health indicators including anthropometric measures, lifestyle factors, and blood biomarkers in relation to brain structure using MRI-based morphometry and diffusion tensor imaging (DTI). We performed tissue specific brain age prediction using machine learning and performed Bayesian multilevel modeling to assess changes in each CMR over time, their respective association with brain age gap (BAG), and their interaction effects with time and age on the tissue-specific BAGs. The results showed credible associations between DTI-based BAG and blood levels of phosphate and mean cell volume (MCV), and between T1-based BAG and systolic blood pressure, smoking, pulse, and C-reactive protein (CRP), indicating older-appearing brains in people with higher cardiometabolic risk (smoking, higher blood pressure and pulse, low-grade inflammation). Longitudinal evidence supported interactions between both BAGs and waist-to-hip ratio (WHR), and between DTI-based BAG and systolic blood pressure and smoking, indicating accelerated ageing in people with higher cardiometabolic risk (smoking, higher blood pressure, and WHR). The results demonstrate that cardiometabolic risk factors are associated with brain ageing. While randomized controlled trials are needed to establish causality, our results indicate that public health initiatives and treatment strategies targeting modifiable cardiometabolic risk factors may also improve risk trajectories and delay brain ageing.

A qualitative study exploring contributors to the success of a community of practice in rehabilitation.

BACKGROUND: Communities of Practice (CoPs) focus on learning, knowledge sharing, and creation, and research indicates they can improve healthcare performance. This article describes the development of a CoP that focused on synthesizing and adapting evidence in Physical Medicine and Rehabilitation (PM&R). This study aimed to investigate the CoP members' experiences and perceived barriers and enablers of CoP success in the early phase of a CoP. METHODS: Physical therapists and a physician (n = 10) volunteered for a CoP that synthesized literature of PM&R evidence. CoP members participated in education and training on critical appraisal and knowledge synthesis, practiced critical appraisal skills, and summarized literature. Three months after CoP initiation, semi-structured interviews were conducted to understand the CoP members' experiences and reflections. Members also completed an online survey that included the Evidence-Based Practice Confidence scale (EPIC), questions related to CoP activities, and demographics before CoP initiation. We utilized the Capability, Opportunity, and Motivation Model of Behaviour (COM-B) to explore how these experiences related to the behavioral adaptation and participation. RESULTS: Ten themes related to the potential contributors to CoP success and failure were identified. These included project management, technological solutions, efficacy, organizational support, interaction, the bigger picture, self-development, time, and motivation. CONCLUSIONS: Contributors to CoP success may include clearly articulated project goals and participant expectations, education and training, reliable technology solutions, organizational support, face-to-face communication, and good project management. Importantly, CoP members need time to participate in activities.

Structural brain disconnectivity mapping of post-stroke fatigue.

Stroke patients commonly suffer from post stroke fatigue (PSF). Despite a general consensus that brain perturbations constitute a precipitating event in the multifactorial etiology of PSF, the specific predictive value of conventional lesion characteristics such as size and localization remains unclear. The current study represents a novel approach to assess the neural correlates of PSF in chronic stroke patients. While previous research has focused primarily on lesion location or size, with mixed or inconclusive results, we targeted the extended structural network implicated by the lesion, and evaluated the added explanatory value of a structural disconnectivity approach with regards to the brain correlates of PSF. To this end, we estimated individual structural brain disconnectome maps in 84 S survivors in the chronic phase (≥3 months post stroke) using information about lesion location and normative white matter pathways obtained from 170 healthy individuals. PSF was measured by the Fatigue Severity Scale (FSS). Voxel wise analyses using non-parametric permutation-based inference were conducted on disconnectome maps to estimate regional effects of disconnectivity. Associations between PSF and global disconnectivity and clinical lesion characteristics were tested by linear models, and we estimated Bayes factor to quantify the evidence for the null and alternative hypotheses, respectively. The results revealed no significant associations between PSF and disconnectome measures or lesion characteristics, with moderate evidence in favor of the null hypothesis. These results suggest that symptoms of post-stroke fatigue among chronic stroke patients are not simply explained by lesion characteristics or the extent and distribution of structural brain disconnectome, and are discussed in light of methodological considerations.

White matter microstructure across the adult lifespan: A mixed longitudinal and cross-sectional study using advanced diffusion models and brain-age prediction.

The macro- and microstructural architecture of human brain white matter undergoes substantial alterations throughout development and ageing. Most of our understanding of the spatial and temporal characteristics of these lifespan adaptations come from magnetic resonance imaging (MRI), including diffusion MRI (dMRI), which enables visualisation and quantification of brain white matter with unprecedented sensitivity and detail. However, with some notable exceptions, previous studies have relied on cross-sectional designs, limited age ranges, and diffusion tensor imaging (DTI) based on conventional single-shell dMRI. In this mixed cross-sectional and longitudinal study (mean interval: 15.2 months) including 702 multi-shell dMRI datasets, we combined complementary dMRI models to investigate age trajectories in healthy individuals aged 18 to 94 years (57.12% women). Using linear mixed effect models and machine learning based brain age prediction, we assessed the age-dependence of diffusion metrics, and compared the age prediction accuracy of six different diffusion models, including diffusion tensor (DTI) and kurtosis imaging (DKI), neurite orientation dispersion and density imaging (NODDI), restriction spectrum imaging (RSI), spherical mean technique multi-compartment (SMT-mc), and white matter tract integrity (WMTI). The results showed that the age slopes for conventional DTI metrics (fractional anisotropy [FA], mean diffusivity [MD], axial diffusivity [AD], radial diffusivity [RD]) were largely consistent with previous research, and that the highest performing advanced dMRI models showed comparable age prediction accuracy to conventional DTI. Linear mixed effects models and Wilk's theorem analysis showed that the 'FA fine' metric of the RSI model and 'orientation dispersion' (OD) metric of the NODDI model showed the highest sensitivity to age. The results indicate that advanced diffusion models (DKI, NODDI, RSI, SMT mc, WMTI) provide sensitive measures of age-related microstructural changes of white matter in the brain that complement and extend the contribution of conventional DTI.

Genetic control of variability in subcortical and intracranial volumes.

Sensitivity to external demands is essential for adaptation to dynamic environments, but comes at the cost of increased risk of adverse outcomes when facing poor environmental conditions. Here, we apply a novel methodology to perform genome-wide association analysis of mean and variance in ten key brain features (accumbens, amygdala, caudate, hippocampus, pallidum, putamen, thalamus, intracranial volume, cortical surface area, and cortical thickness), integrating genetic and neuroanatomical data from a large lifespan sample (n = 25,575 individuals; 8-89 years, mean age 51.9 years). We identify genetic loci associated with phenotypic variability in thalamus volume and cortical thickness. The variance-controlling loci involved genes with a documented role in brain and mental health and were not associated with the mean anatomical volumes. This proof-of-principle of the hypothesis of a genetic regulation of brain volume variability contributes to establishing the genetic basis of phenotypic variance (i.e., heritability), allows identifying different degrees of brain robustness across individuals, and opens new research avenues in the search for mechanisms controlling brain and mental health.

Reliability, sensitivity, and predictive value of fMRI during multiple object tracking as a marker of cognitive training gain in combination with tDCS in stroke survivors.

Computerized cognitive training (CCT) combined with transcranial direct current stimulation (tDCS) has showed some promise in alleviating cognitive impairments in patients with brain disorders, but the robustness and possible mechanisms are unclear. In this prospective double-blind randomized clinical trial, we investigated the feasibility and effectiveness of combining CCT and tDCS, and tested the predictive value of and training-related changes in fMRI-based brain activation during attentive performance (multiple object tracking) obtained at inclusion, before initiating training, and after the three-weeks intervention in chronic stroke patients (>6 months since hospital admission). Patients were randomized to one of two groups, receiving CCT and either (a) tDCS targeting left dorsolateral prefrontal cortex (1 mA), or (b) sham tDCS, with 40s active stimulation (1 mA) before fade out of the current. Of note, 77 patients were enrolled in the study, 54 completed the cognitive training, and 48 completed all training and MRI sessions. We found significant improvement in performance across all trained tasks, but no additional gain of tDCS. fMRI-based brain activation showed high reliability, and higher cognitive performance was associated with increased tracking-related activation in the dorsal attention network and default mode network as well as anterior cingulate after compared to before the intervention. We found no significant associations between cognitive gain and brain activation measured before training or in the difference in activation after intervention. Combined, these results show significant training effects on trained cognitive tasks in stroke survivors, with no clear evidence of additional gain of concurrent tDCS.

TVA-based modeling of short-term memory capacity, speed of processing and perceptual threshold in chronic stroke patients undergoing cognitive training: case-control differences, reliability, and associations with cognitive performance.

Attentional deficits following stroke are common and pervasive, and are important predictors for functional recovery. Attentional functions comprise a set of specific cognitive processes allowing to attend, filter and select among a continuous stream of stimuli. These mechanisms are fundamental for more complex cognitive functions such as learning, planning and cognitive control, all crucial for daily functioning. The distributed functional neuroanatomy of these processes is a likely explanation for the high prevalence of attentional impairments following stroke, and underscores the importance of a clinical implementation of computational approaches allowing for sensitive and specific modeling of attentional sub-processes. The Theory of Visual Attention (TVA) offers a theoretical, computational, neuronal and practical framework to assess the efficiency of visual selection performance and parallel processing of multiple objects. Here, in order to assess the sensitivity and reliability of TVA parameters reflecting short-term memory capacity (K), processing speed (C) and perceptual threshold (t 0), we used a whole-report paradigm in a cross-sectional case-control comparison and across six repeated assessments over the course of a three-week computerized cognitive training (CCT) intervention in chronic stroke patients (> 6 months since hospital admission, NIHSS ≤ 7 at hospital discharge). Cross-sectional group comparisons documented lower short-term memory capacity, lower processing speed and higher perceptual threshold in patients (n = 70) compared to age-matched healthy controls (n = 140). Further, longitudinal analyses in stroke patients during the course of CCT (n = 54) revealed high reliability of the TVA parameters, and higher processing speed at baseline was associated with larger cognitive improvement after the intervention. The results support the feasibility, reliability and sensitivity of TVA-based assessment of attentional functions in chronic stroke patients.

Dissecting the cognitive phenotype of post-stroke fatigue using computerized assessment and computational modeling of sustained attention.

Post-stroke fatigue (PSF) is prevalent among stroke patients, but its mechanisms are poorly understood. Many patients with PSF experience cognitive difficulties, but studies aiming to identify cognitive correlates of PSF have been largely inconclusive. With the aim of characterizing the relationship between subjective fatigue and attentional function, we collected behavioral data using the attention network test (ANT) and self-reported fatigue scores using the fatigue severity scale (FSS) from 53 stroke patients. In order to evaluate the utility and added value of computational modeling for delineating specific underpinnings of response time (RT) distributions, we fitted a hierarchical drift diffusion model (hDDM) to the ANT data. Results revealed a relationship between fatigue and RT distributions. Specifically, there was a positive interaction between FSS score and elapsed time on RT. Group analyses suggested that patients without PSF increased speed during the course of the session, while patients with PSF did not. In line with the conventional analyses based on observed RT, the best fitting hDD model identified an interaction between elapsed time and fatigue on non-decision time, suggesting an increase in time needed for stimulus encoding and response execution rather than cognitive information processing and evidence accumulation. These novel results demonstrate the significance of considering the sustained nature of effort when defining the cognitive phenotype of PSF, intuitively indicating that the cognitive phenotype of fatigue entails an increased vulnerability to sustained effort, and suggest that the use of computational approaches offers a further characterization of specific processes underlying behavioral differences.

Brain scans from 21,297 individuals reveal the genetic architecture of hippocampal subfield volumes.

The hippocampus is a heterogeneous structure, comprising histologically distinguishable subfields. These subfields are differentially involved in memory consolidation, spatial navigation and pattern separation, complex functions often impaired in individuals with brain disorders characterized by reduced hippocampal volume, including Alzheimer's disease (AD) and schizophrenia. Given the structural and functional heterogeneity of the hippocampal formation, we sought to characterize the subfields' genetic architecture. T1-weighted brain scans (n = 21,297, 16 cohorts) were processed with the hippocampal subfields algorithm in FreeSurfer v6.0. We ran a genome-wide association analysis on each subfield, co-varying for whole hippocampal volume. We further calculated the single-nucleotide polymorphism (SNP)-based heritability of 12 subfields, as well as their genetic correlation with each other, with other structural brain features and with AD and schizophrenia. All outcome measures were corrected for age, sex and intracranial volume. We found 15 unique genome-wide significant loci across six subfields, of which eight had not been previously linked to the hippocampus. Top SNPs were mapped to genes associated with neuronal differentiation, locomotor behaviour, schizophrenia and AD. The volumes of all the subfields were estimated to be heritable (h2 from 0.14 to 0.27, all p < 1 × 10-16) and clustered together based on their genetic correlations compared with other structural brain features. There was also evidence of genetic overlap of subicular subfield volumes with schizophrenia. We conclude that hippocampal subfields have partly distinct genetic determinants associated with specific biological processes and traits. Taking into account this specificity may increase our understanding of hippocampal neurobiology and associated pathologies.

Implementation of High-Intensity Stepping Training During Inpatient Stroke Rehabilitation Improves Functional Outcomes.

Background and Purpose- Therapeutic strategies that capitalize on the intrinsic capacity for neurological recovery early poststroke to improve locomotion are uncertain. Emerging data suggest that task-specific stepping practice provided at higher cardiovascular intensities may be critical dosage parameters that could maximize locomotor recovery. The purpose of this investigation was to determine the comparative effectiveness of providing high-intensity training on locomotor capacity early poststroke as compared with usual care. Methods- A quasi-experimental design was used to compare changes in stepping activity (StepWatch), walking, and balance outcomes during usual care (n=56) versus high-intensity stepping intervention (n=54) in inpatient stroke patients. Primary outcomes assessed weekly included self-selected and fastest gait speed, 6-minute walk test, and the Berg Balance Scale, with secondary outcomes of Swedish Postural Assessment Scale for Stroke-Norwegian version, Functional Ambulation Category, 30-s sit-to-stand, strength (average manual muscle testing), and Barthel Index. Regression analyses identified relationships between demographics, baseline function, and training activities (steps per day; duration achieved, 70%-85% maximum heart rates) and primary outcomes at discharge. Results- Following implementation of high-intensity stepping, average steps per day (5777±2784) were significantly greater than during usual care (3917±2656; P<0.001). Statistically different and clinically meaningful changes in self-selected speed (0.39±0.28 versus 0.16±0.26 m/s) and fastest gait speed (0.47±0.41 versus 0.17±0.38 m/s; both P<0.001) were observed following high-intensity interventions versus usual care and at every assessment throughout the length of stay. Changes in Berg Balance Scale and 6-minute walk test were also statistically and clinically different between groups, while secondary measures of Functional Ambulation Category and strength were also different at discharge. Primary predictors of improved walking capacity were steps per day, baseline impairments, and age. Conclusions- Provision of high-intensity stepping training applied during inpatient rehabilitation resulted in significantly greater walking and balance outcomes. This training paradigm should be further tested in other contexts to determine the generalizability to real-world and community settings.

Cross-Sectional and Longitudinal MRI Brain Scans Reveal Accelerated Brain Aging in Multiple Sclerosis.

Multiple sclerosis (MS) is an inflammatory disorder of the central nervous system. By combining longitudinal MRI-based brain morphometry and brain age estimation using machine learning, we tested the hypothesis that MS patients have higher brain age relative to chronological age than healthy controls (HC) and that longitudinal rate of brain aging in MS patients is associated with clinical course and severity. Seventy-six MS patients [71% females, mean age 34.8 years (range 21-49) at inclusion] were examined with brain MRI at three time points with a mean total follow up period of 4.4 years (±0.4 years). We used additional cross-sectional MRI data from 235 HC for case-control comparison. We applied a machine learning model trained on an independent set of 3,208 HC to estimate individual brain age and to calculate the difference between estimated and chronological age, termed brain age gap (BAG). We also assessed the longitudinal change rate in BAG in individuals with MS. MS patients showed significantly higher BAG (4.4 ± 6.6 years) compared to HC (Cohen's D = 0.69, p = 4.0 × 10-6). Longitudinal estimates of BAG in MS patients showed high reliability and suggested an accelerated rate of brain aging corresponding to an annual increase of 0.41 (SE = 0.15) years compared to chronological aging (p = 0.008). Multiple regression analyses revealed higher rate of brain aging in patients with more brain atrophy (Cohen's D = 0.86, p = 4.3 × 10-15) and increased white matter lesion load (WMLL) (Cohen's D = 0.55, p = 0.015). On average, patients with MS had significantly higher BAG compared to HC. Progressive brain aging in patients with MS was related to brain atrophy and increased WMLL. No significant clinical associations were found in our sample, future studies are warranted on this matter. Brain age estimation is a promising method for evaluation of subtle brain changes in MS, which is important for predicting clinical outcome and guide choice of intervention.

Unilateral neglect post stroke: Eye movement frequencies indicate directional hypokinesia while fixation distributions suggest compensational mechanism.

INTRODUCTION: Eye movements and spatial attention are closely related, and eye-tracking can provide valuable information in research on visual attention. We investigated the pathology of overt attention in right hemisphere (RH) stroke patients differing in their severity of neglect symptoms by using eye-tracking during a dynamic attention task. METHODS: Eye movements were recorded in 26 RH stroke patients (13 with and 13 without unilateral spatial neglect, and a matched group of 26 healthy controls during a Multiple Object Tracking task. We assessed the frequency and spatial distributions of fixations, as well as frequencies of eye movements to the left and to the right side of visual space so as to investigate individuals' efficiency of visual processing, distribution of attentional processing resources, and oculomotoric orienting mechanisms. RESULTS: Both patient groups showed increased fixation frequencies compared to controls. A spatial bias was found in neglect patients' fixation distribution, depending on neglect severity (indexed by scores on the Behavioral Inattention Test). Patients with more severe neglect had more fixations within the right field, while patients with less severe neglect had more fixations within their left field. Eye movement frequencies were dependent on direction in the neglect patient group, as they made more eye movements toward the right than toward the left. CONCLUSION: The patient groups' higher fixation rates suggest that patients are generally less efficient in visual processing. The spatial bias in fixation distribution, dependent on neglect severity, suggested that patients with less severe neglect were able to use compensational mechanisms in their contralesional space. The observed relation between eye movement rates and directions observed in neglect patients provides a measure of the degree of difficulty these patients may encounter during dynamic situations in daily life and supports the idea that directional oculomotor hypokinesia may be a relevant component in this syndrome.

Key Brain Network Nodes Show Differential Cognitive Relevance and Developmental Trajectories during Childhood and Adolescence.

Human adolescence is a period of rapid changes in cognition and goal-directed behavior, and it constitutes a major transitional phase towards adulthood. One of the mechanisms suggested to underlie the protracted maturation of functional brain networks, is the increased network integration and segregation enhancing neural efficiency. Importantly, the increasing coordinated network interplay throughout development is mediated through functional hubs, which are highly connected brain areas suggested to be pivotal nodes for the regulation of neural activity. To elucidate brain hub development during childhood and adolescence, we estimated voxel-wise eigenvector centrality (EC) using functional magnetic resonance imaging (fMRI) data from two different psychological contexts (resting state and a working memory task), in a large cross-sectional sample (n = 754) spanning the age from 8 to 22 years, and decomposed the maps using independent component analysis (ICA). Our results reveal significant age-related centrality differences in cingulo-opercular, visual, and sensorimotor network nodes during both rest and task performance, suggesting that common neurodevelopmental processes manifest across different mental states. Supporting the functional significance of these developmental patterns, the centrality of the cingulo-opercular node was positively associated with task performance. These findings provide evidence for protracted maturation of hub properties in specific nodes of the brain connectome during the course of childhood and adolescence and suggest that cingulo-opercular centrality is a key factor supporting neurocognitive development.

Mental health assessment in rehabilitation: a descriptive study through an international internet survey.

This cross-sectional study assessed international rehabilitation practitioners' views of mental health assessment (MHA), related specifically to assessment tools and needs in the field. We delivered an anonymous web-based survey capturing rehabilitation practioners' perspectives on MHA practices, assessment tools, and needs through the American Congress of Rehabilitation Medicine in the USA and through national rehabilitation networks in Finland and Norway. Altogether, 355 rehabilitation professionals answered the survey. Unmet MHA needs, most often attributed to insufficient time (112/269 responders), were recognized among rehabilitation professionals irrespective of the country of practice. When professional experience was weighed against barriers to conducting MHA, cost was statistically significantly linked to professional experience, with those with less experience viewing cost more as a barrier (P=0.019). Rehabilitation professionals from different professions, in different countries, and working with a variety of clinical populations recognize defined barriers to MHA in rehabilitation.

Reported use of evidence in clinical practice: a survey of rehabilitation practices in Norway.

BACKGROUND: The South Eastern Health Region in Norway serves approximately 2.8 million people, which is more than half of Norway's population. Physical medicine and rehabilitation services are provided by 9 public hospital trusts and 30 private rehabilitation facilities. The purposes of this study were to conduct a psychometric analysis of the EBP Implementation Scale (EBPIS) and describe rehabilitation clinicians' self-reported 1) use of evidence-based practices (EBPs), 2) use of EBPs across hospitals, and 3) determine factors associated with use of EBPs in the South Eastern Health Region in Norway. METHODS: A cross-sectional study using an online survey was conducted with public hospitals and private rehabilitation centers. The survey, which was distributed throughout the region, included the EBPIS, 8 questions related to EBP in the health region, and demographics. Response frequencies were calculated and described. Internal consistency and factor structure of the EBPIS and its subscales were determined. Associations and differences in groups with similar demographics, EBPIS scores, and use of EBPs were identified. RESULTS: A total of 316 individuals completed the survey, including allied health clinicians, nurses, psychologists, social workers, and physicians. The EBPIS mean score was 30/72. A factor analysis identified that the EBPIS can be divided into 3 subscales: literature search and critical appraisal (α = .80), knowledge sharing (α = .83), and practice evaluation (α = .74). EBP activities reported were primarily related to literature searches, critical appraisal, and discussing evidence. Approximately 65 and 75% of respondents agreed that the same OMs and evidence based interventions were used within the local clinic respectively. Fewer agreed that the same OMs (13%) and evidence-based interventions (39%) are used regionally. CONCLUSION: The EBPIS and its subscales demonstrated excellent internal consistency. Practice variability exists in rehabilitation throughout Southeastern Norway. An increased emphasis on use of EBP throughout the region is needed.

Clinical Utility of Mindfulness Training in the Treatment of Fatigue After Stroke, Traumatic Brain Injury and Multiple Sclerosis: A Systematic Literature Review and Meta-analysis.

BACKGROUND: Fatigue is a common symptom following neurological illnesses and injuries, and is rated as one of the most debilitating sequela in conditions such as stroke, traumatic brain injury (TBI), and multiple sclerosis (MS). Yet effective treatments are lacking, suggesting a pressing need for a better understanding of its etiology and mechanisms that may alleviate the symptoms. Recently mindfulness-based interventions have demonstrated promising results for fatigue symptom relief. OBJECTIVE: Investigate the efficacy of mindfulness-based interventions for fatigue across neurological conditions and acquired brain injuries. MATERIALS AND METHODS: Systematic literature searches were conducted in PubMed, Medline, Web of Science, and PsycINFO. We included randomized controlled trials applying mindfulness-based interventions in patients with neurological conditions or acquired brain injuries. Four studies (N = 257) were retained for meta-analysis. The studies included patients diagnosed with MS, TBI, and stroke. RESULTS: The estimated effect size for the total sample was -0.37 (95% CI: -0.58, -0.17). CONCLUSION: The results indicate that mindfulness-based interventions may relieve fatigue in neurological conditions such as stroke, TBI, and MS. However, the effect size is moderate, and further research is needed in order to determine the effect and improve our understanding of how mindfulness-based interventions affect fatigue symptom perception in patients with neurological conditions.

Bridging the gap between clinical neuroscience and cognitive rehabilitation: the role of cognitive training, models of neuroplasticity and advanced neuroimaging in future brain injury rehabilitation.

BACKGROUND: Magnetic resonance imaging (MRI) has brought about advances in the fields of brain plasticity and lifespan brain change, that might be of special interest for cognitive rehabilitation research and, eventually, in clinical practice. Parallel, intensive cognitive training studies show promising results for the prospect of retraining some of the impaired functioning following acquired brain injury. OBJECTIVES: However, cognitive training research is largely performed without concurrent assessments of brain structural change and reorganization, which could have addressed possible mechanisms of training-related neuroplasticity. METHODS: Criticism of cognitive training studies is often focused on lack of ecologically valid, daily-living assessments of treatment effect, and on whether the applied cognitive measures overlap too much with the training exercises. Yet, the present paper takes another point of view, where the relevance of recent MRI research of brain plasticity to the field of cognitive rehabilitation is examined. RESULTS: Arguably, treatment ought to be measured at the same level of the International Classification of Functioning, Disability and Health model, as it is targeting. In the case of cognitive training that will be the "body structure" and "body function" levels. CONCLUSIONS: MRI has shown promise to detect macro- and microstructural activity-related changes in the brain following intensive training.