Login / Signup

Cue responsiveness as a measure of emerging language ability in aphasia.

Megan E SchliepVictoria E Tilton-BolowskySofia Vallila-Rohter
Published in: Topics in stroke rehabilitation (2021)
Background: Prior research suggests that initial aphasia severity, lesion size, and lesion location are the most salient factors in predicting recovery outcomes. While these factors provide important prognostic information, information that is individualized and readily available to clinicians is limited. Deficits in naming are common to all aphasia types and are routinely targeted in aphasia assessment and treatment, with cues provided to facilitate lexical retrieval.Objectives: In this study, we examine aphasia recovery factors that are readily available to clinicians, examining whether a person's ability to improve naming with cues, indicating "stimulability," will be predictive of future word retrieval.Methods: Ten participants with aphasia following a left-hemisphere stroke participated in initial assessment, seven of whom met criteria for longitudinal assessment. Stroke and early clinical recovery data were collected for all participants. At four timepoints over one year we evaluated longitudinal participants' naming ability and measured the proportion of successful lexical retrieval with the presentation of phonemic, feature, and sentence cues.Results: For all participants, multiple descriptive factors regarding recovery, including lesion information, information from the acute inpatient timeframe, and communication opportunities, were examined. For individuals followed longitudinally, naming stimulability did not consistently predict naming accuracy at the subsequent assessment timepoint. Individuals' attempts at naming emerged as a metric related to future naming performance warranting further evaluation.Conclusions: Multiple factors related to recovery must be considered when providing prognostic information. Naming stimulability and attempts at naming provide some information regarding future performance, but are not consistently reliable across timepoints.
Keyphrases
  • health information
  • atrial fibrillation
  • current status
  • healthcare
  • mental health
  • machine learning
  • type diabetes
  • intensive care unit
  • tyrosine kinase
  • insulin resistance
  • smoking cessation
  • combination therapy