Screening for Dyslexia in University Students: a Standardized Procedure Based on Conditional Inference Trees.

OBJECTIVE: The focus of this study is on providing tools to enable researchers and practitioners to screen for dyslexia in adults entering university. The first aim is to validate and provide diagnostic properties for a set of seven tests including a 1-min word reading test, a 2-min pseudoword reading test, a phonemic awareness test, a spelling test, the Alouette reading fluency test, a connected-text reading fluency test, and the self-report Adult Reading History Questionnaire (ARHQ). The second, more general, aim of this study was to devise a standardized and confirmatory procedure for dyslexia screening from a subset of the initial seven tests. We used conditional inference tree analysis, a supervised machine learning approach to identify the most relevant tests, cut-off scores, and optimal order of test administration. METHOD: A combined sample of 60 university students with dyslexia (clinical validation group) and 65 university students without dyslexia (normative group) provided data to determine the diagnostic properties of these tests including sensitivity, specificity, and cut-off scores. RESULTS: Results showed that combinations of four tests (ARHQ, text reading fluency, phonemic awareness, pseudoword reading) and their relative conditional cut-off scores optimize powerful discriminatory screening procedures for dyslexia, with an overall classification accuracy of approximately 90%. CONCLUSIONS: The novel use of the conditional inference tree methodology explored in the present study offered a way of moving toward a more efficient screening battery using only a subset of the seven tests examined. Both clinical and theoretical implications of these findings are discussed.

Text Reading Fluency and Text Reading Comprehension Do Not Rely on the Same Abilities in University Students With and Without Dyslexia.

Developmental dyslexia is a specific learning condition characterized by severe and persistent difficulties in written word recognition, decoding and spelling that may impair both text reading fluency and text reading comprehension. Despite this, some adults with dyslexia successfully complete their university studies even though graduating from university involves intensive exposure to long and complex texts. This study examined the cognitive skills underlying both text reading comprehension and text reading fluency (TRF) in a sample of 54 university students with dyslexia and 63 university students without dyslexia, based on a set of tests adapted for an adult population, including listening comprehension, word reading, pseudoword reading (i.e., decoding), phonemic awareness, spelling, visual span, reading span, vocabulary, non-verbal reasoning, and general knowledge. The contribution of these skills to text reading fluency and text reading comprehension was examined using stepwise multiplicative linear regression analyses. As far as TRF is concerned, a regression model including word reading, pseudoword reading and spelling best fits the data, while a regression model including listening comprehension, general knowledge and vocabulary best fits the data obtained for text reading comprehension. Overall, these results are discussed in the light of the current literature on adults with dyslexia and both text reading fluency and text reading comprehension.

E-book reading hinders aspects of long-text comprehension for adults with dyslexia.

Developmental dyslexia is a long-lasting reading deficit that persists into adulthood. In spite of many difficulties, some adults with dyslexia reach levels of reading comprehension similar to those of unimpaired readers and successfully study at university. While digital technologies offer many potential tools to facilitate reading, there are differences between printed books and e-books, particularly regarding the interaction between the reader and the text (paratextual cues). This study used long-text reading to investigate (1) different aspects of reading comprehension skills (literal and inferential processes, location of events within a story, and reconstruction of the plot) among university students with dyslexia and (2) the impact of e-book reading on reading comprehension in this population. Thirty adults with dyslexia and 30 matched skilled readers read the same text presented from a printed book and an e-book (Amazon Kindle). Questions were open-ended and both questions and answers used oral format. Results showed that with the printed book, dyslexic adults performed similarly to skilled readers in both literal and inferential reading comprehension tasks. Moreover, they performed at the same level or higher than skilled readers in tasks assessing spatiotemporal aspects of reading (localization of events and plot reconstruction). Conversely, with the e-book reader, the dyslexic adults were outperformed by skilled readers both in literal and spatiotemporal comprehension tasks. These results suggest that reading from an e-book hinders some aspects of reading comprehension for adults with dyslexia. However, when reading a printed book without time pressure, university students with dyslexia performed as well as, or better than, non-impaired readers on some measures of reading comprehension. Therefore, digital reading devices might not always be advantageous to them.