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OBJECTIVES: Children diagnosed with auditory processing disorders (APD) experience difficulties in auditory functioning and with memory, attention, language, and reading tasks. However, it is not clear whether the behavioral characteristics of these children are distinctive from the behavioral characteristics of children diagnosed with a different developmental disorder, such as specific language impairment (SLI), dyslexia, attention-deficit hyperactivity disorder (ADHD), learning disorder (LD), or autism spectrum disorder. This study describes the performance of children diagnosed with APD, SLI, dyslexia, ADHD, and LD to different outcome measurements. The aim of this study was to determine (1) which characteristics of APD overlap with the characteristics of children with SLI, dyslexia, ADHD, LD, or autism spectrum disorder; and (2) if there are characteristics that distinguish children diagnosed with APD from children diagnosed with other developmental disorders.DESIGN: A systematic review. Six electronic databases (Pubmed, CINAHL, Eric, PsychINFO, Communication & Mass Media Complete, and EMBASE) were searched to find peer-reviewed studies from 1954 to May 2015. The authors included studies reporting behaviors and performance of children with (suspected) APD and children diagnosed with a different developmental disorder (SLI, Dyslexia, ADHD, and LD). Two researchers identified and screened the studies independently. Methodological quality of the included studies was assessed with the American Speech-Language-Hearing Association's levels-of-evidence scheme.RESULTS: In total, 13 studies of which the methodological quality was moderate were included in this systematic review. In five studies, the performance of children diagnosed with APD was compared with the performance of children diagnosed with SLI: in two with children diagnosed with dyslexia, one with children diagnosed with ADHD, and in another one with children diagnosed with LD. Ten of the studies included children who met the criteria for more than one diagnosis. In four studies, there was a comparison made between the performances of children with comorbid disorders. There were no studies found in which the performance of children diagnosed with APD was compared with the performance of children diagnosed with autism spectrum disorder. Children diagnosed with APD broadly share the same characteristics as children diagnosed with other developmental disorders, with only minor differences between them. Differences were determined with the auditory and visual Duration Pattern Test, the Children's Auditory Processing Performance Scale questionnaire, and the subtests of the Listening in Spatialized Noise-Sentences test, in which noise is spatially separated from target sentences. However, these differences are not consistent between studies and are not found in comparison to all groups of children with other developmental disorders.CONCLUSIONS: Children diagnosed with APD perform equally to children diagnosed with SLI, dyslexia, ADHD, and LD on tests of intelligence, memory or attention, and language tests. Only small differences between groups were found for sensory and perceptual functioning tasks (auditory and visual). In addition, children diagnosed with dyslexia performed poorer in reading tasks compared with children diagnosed with APD. The result is possibly confounded by poor quality of the research studies and the low quality of the used outcome measures. More research with higher scientific rigor is required to better understand the differences and similarities in children with various neurodevelopmental disorders.
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Movement is an essential part of our lives. Throughout our lifetime, we acquire many different motor skills that are necessary to take care of ourselves (e.g., eating, dressing), to work (e.g., typing, using tools, care for others) and to pursue our hobbies (e.g., running, dancing, painting). However, as a consequence of aging, trauma or chronic disease, motor skills may deteriorate or become “lost”. Learning, relearning, and improving motor skills may then be essential to maintain or regain independence. There are many different ways in which the process of learning a motor skill can be shaped in practice. The conceptual basis for this thesis was the broad distinction between implicit and explicit forms of motor learning. Physiotherapists and occupational therapists are specialized to provide therapy that is tailored to facilitate the process of motor learning of patients with a wide range of pathologies. In addition to motor impairments, patients suffering from neurological disorders often also experience problems with cognition and communication. These problems may hinder the process of learning at a didactic level, and make motor learning especially challenging for those with neurological disorders. This thesis focused on the theory and application of motor learning during rehabilitation of patients with neurological disorders. The overall aim of this thesis was to provide therapists in neurological rehabilitation with knowledge and tools to support the justified and tailored use of motor learning in daily clinical practice. The thesis is divided into two parts. The aim of the first part (Chapters 2‐5) was to develop a theoretical basis to apply motor learning in clinical practice, using the implicit‐explicit distinction as a conceptual basis. Results of this first part were used to develop a framework for the application of motor learning within neurological rehabilitation (Chapter 6). Afterwards, in the second part, strategies identified in first part were tested for feasibility and potential effects in people with stroke (Chapters 7 and 8). Chapters 5-8 are non-final versions of an article published in final form in: Chapter 5: Kleynen M, Moser A, Haarsma FA, Beurskens AJ, Braun SM. Physiotherapists use a great variety of motor learning options in neurological rehabilitation, from which they choose through an iterative process: a retrospective think-aloud study. Disabil Rehabil. 2017 Aug;39(17):1729-1737. doi: 10.1080/09638288.2016.1207111. Chapter 6: Kleynen M, Beurskens A, Olijve H, Kamphuis J, Braun S. Application of motor learning in neurorehabilitation: a framework for health-care professionals. Physiother Theory Pract. 2018 Jun 19:1-20. doi: 10.1080/09593985.2018.1483987 Chapter 7: Kleynen M, Wilson MR, Jie LJ, te Lintel Hekkert F, Goodwin VA, Braun SM. Exploring the utility of analogies in motor learning after stroke: a feasibility study. Int J Rehabil Res. 2014 Sep;37(3):277-80. doi: 10.1097/MRR.0000000000000058. Chapter 8: Kleynen M, Jie LJ, Theunissen K, Rasquin SM, Masters RS, Meijer K, Beurskens AJ, Braun SM. The immediate influence of implicit motor learning strategies on spatiotemporal gait parameters in stroke patients: a randomized within-subjects design. Clin Rehabil. 2019 Apr;33(4):619-630. doi: 10.1177/0269215518816359.
Although learning analytics benefit learning, its uptake by higher educational institutions remains low. Adopting learning analytics is a complex undertaking, and higher educational institutions lack insight into how to build organizational capabilities to successfully adopt learning analytics at scale. This paper describes the ex-post evaluation of a capability model for learning analytics via a mixed-method approach. The model intends to help practitioners such as program managers, policymakers, and senior management by providing them a comprehensive overview of necessary capabilities and their operationalization. Qualitative data were collected during pluralistic walk-throughs with 26 participants at five educational institutions and a group discussion with seven learning analytics experts. Quantitative data about the model’s perceived usefulness and ease-of-use was collected via a survey (n = 23). The study’s outcomes show that the model helps practitioners to plan learning analytics adoption at their higher educational institutions. The study also shows the applicability of pluralistic walk-throughs as a method for ex-post evaluation of Design Science Research artefacts.
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Huntington’s disease (HD) and various spinocerebellar ataxias (SCA) are autosomal dominantly inherited neurodegenerative disorders caused by a CAG repeat expansion in the disease-related gene1. The impact of HD and SCA on families and individuals is enormous and far reaching, as patients typically display first symptoms during midlife. HD is characterized by unwanted choreatic movements, behavioral and psychiatric disturbances and dementia. SCAs are mainly characterized by ataxia but also other symptoms including cognitive deficits, similarly affecting quality of life and leading to disability. These problems worsen as the disease progresses and affected individuals are no longer able to work, drive, or care for themselves. It places an enormous burden on their family and caregivers, and patients will require intensive nursing home care when disease progresses, and lifespan is reduced. Although the clinical and pathological phenotypes are distinct for each CAG repeat expansion disorder, it is thought that similar molecular mechanisms underlie the effect of expanded CAG repeats in different genes. The predicted Age of Onset (AO) for both HD, SCA1 and SCA3 (and 5 other CAG-repeat diseases) is based on the polyQ expansion, but the CAG/polyQ determines the AO only for 50% (see figure below). A large variety on AO is observed, especially for the most common range between 40 and 50 repeats11,12. Large differences in onset, especially in the range 40-50 CAGs not only imply that current individual predictions for AO are imprecise (affecting important life decisions that patients need to make and also hampering assessment of potential onset-delaying intervention) but also do offer optimism that (patient-related) factors exist that can delay the onset of disease.To address both items, we need to generate a better model, based on patient-derived cells that generates parameters that not only mirror the CAG-repeat length dependency of these diseases, but that also better predicts inter-patient variations in disease susceptibility and effectiveness of interventions. Hereto, we will use a staggered project design as explained in 5.1, in which we first will determine which cellular and molecular determinants (referred to as landscapes) in isogenic iPSC models are associated with increased CAG repeat lengths using deep-learning algorithms (DLA) (WP1). Hereto, we will use a well characterized control cell line in which we modify the CAG repeat length in the endogenous ataxin-1, Ataxin-3 and Huntingtin gene from wildtype Q repeats to intermediate to adult onset and juvenile polyQ repeats. We will next expand the model with cells from the 3 (SCA1, SCA3, and HD) existing and new cohorts of early-onset, adult-onset and late-onset/intermediate repeat patients for which, besides accurate AO information, also clinical parameters (MRI scans, liquor markers etc) will be (made) available. This will be used for validation and to fine-tune the molecular landscapes (again using DLA) towards the best prediction of individual patient related clinical markers and AO (WP3). The same models and (most relevant) landscapes will also be used for evaluations of novel mutant protein lowering strategies as will emerge from WP4.This overall development process of landscape prediction is an iterative process that involves (a) data processing (WP5) (b) unsupervised data exploration and dimensionality reduction to find patterns in data and create “labels” for similarity and (c) development of data supervised Deep Learning (DL) models for landscape prediction based on the labels from previous step. Each iteration starts with data that is generated and deployed according to FAIR principles, and the developed deep learning system will be instrumental to connect these WPs. Insights in algorithm sensitivity from the predictive models will form the basis for discussion with field experts on the distinction and phenotypic consequences. While full development of accurate diagnostics might go beyond the timespan of the 5 year project, ideally our final landscapes can be used for new genetic counselling: when somebody is positive for the gene, can we use his/her cells, feed it into the generated cell-based model and better predict the AO and severity? While this will answer questions from clinicians and patient communities, it will also generate new ones, which is why we will study the ethical implications of such improved diagnostics in advance (WP6).