Literature DB >> 26882364

How Does Severity of Aphasia Influence Individual Responsiveness to Rehabilitation? Using Big Data to Understand Theories of Aphasia Rehabilitation.

Swathi Kiran1.   

Abstract

Our ability to make great progress in delivering, optimizing, and predicting rehabilitation outcomes for individuals with aphasia is challenged by factors that influence rehabilitation outcomes. These include patient demographic factors such as age, education, and neurologic factors such as time poststroke, the site and size of the lesion, and the resulting severity of language impairment. Also variable across individuals is the type of treatment and its duration and intensity. This article examines the utility of big data analysis for understanding one of these factors, severity of impairment, and how individual responsiveness to rehabilitation is influenced by a patient's severity of language and cognitive impairment(s). Using examples from two studies and a larger data set, we show that when rehabilitation is tailored to an individual's specific level of impairment, severe and mild patients both show improvements in accuracy and latency. Furthermore, more severe patients tend to show substantial gains on targeted rehabilitation tasks as well as on standardized tests. These results provide support for recent reviews of aphasia rehabilitation studies in concluding that systematic aphasia rehabilitation is indeed effective, and importantly, severity is not a negative prognostic indicator for successful outcomes. Thieme Medical Publishers 333 Seventh Avenue, New York, NY 10001, USA.

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Year:  2016        PMID: 26882364     DOI: 10.1055/s-0036-1571358

Source DB:  PubMed          Journal:  Semin Speech Lang        ISSN: 0734-0478            Impact factor:   1.761


  4 in total

1.  Comparison of Therapy Practice at Home and in the Clinic: A Retrospective Analysis of the Constant Therapy Platform Data Set.

Authors:  Jason Godlove; Veera Anantha; Mahendra Advani; Carrie Des Roches; Swathi Kiran
Journal:  Front Neurol       Date:  2019-02-25       Impact factor: 4.003

2.  The Application of Lexical Retrieval Training in Tablet-Based Speech-Language Intervention.

Authors:  Jeanne Gallée; Rachel Pittmann; Suzanne Pennington; Sofia Vallila-Rohter
Journal:  Front Neurol       Date:  2020-11-16       Impact factor: 4.003

3.  Closing the Digital Divide in Speech, Language, and Cognitive Therapy: Cohort Study of the Factors Associated With Technology Usage for Rehabilitation.

Authors:  Michael Munsell; Emily De Oliveira; Sadhvi Saxena; Jason Godlove; Swathi Kiran
Journal:  J Med Internet Res       Date:  2020-02-07       Impact factor: 5.428

Review 4.  Mobile Apps for Speech-Language Therapy in Adults With Communication Disorders: Review of Content and Quality.

Authors:  Atiyeh Vaezipour; Jessica Campbell; Deborah Theodoros; Trevor Russell
Journal:  JMIR Mhealth Uhealth       Date:  2020-10-29       Impact factor: 4.773

  4 in total

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