The Jyväskylä Longitudinal Study of Dyslexia (JLD)
H. Lyytinen, T. Ahonen, P. Lyytinen, A-M. Poikkeus, P. Leppänen, T. Guttorm, M. Torppa, J. Hämäläinen, A. Puolakanaho, P. Salmi, R. Ketonen and K. Eklund.
U.Goswami (Cambridge University), K. Pugh (Haskins Laboratories), D. Brandeis (University of Zürich and Central Institute of Mental Health, Mannheim), E. Grigorenko (Moscow State University / Yale University), F. Hoeft (Stanford University), J. Kere (Karolinska Institutet), T. Kujala (Helsingin Yliopisto), G. Schulte-Körne (Ludwig-Maximillians-Universität München), D. Molfese (University of Nebraska-Lincoln), G. Georgiou (University of Alberta).
This prospective study of dyslexia aims to identify early precursors and thus the roots of dyslexia by following the early development of children born at risk for dyslexia. The sample of subjects has been screened from more than 8000 families expecting a baby between the years 1993-96 in the Central Finland area to find families with a dyslexic parent who also had a close dyslexic relative. The research consists of a comprehensive developmental follow-up of 100 children of these families and a matched control group of equal size. A description of screening procedure and data collection phases is presented here, and a detailed list of tests and measures .
1. Early auditory-phonic and linguistic skills
3. Cognitive and neurocognitive skills, especially language skills and phonological processing
4. Interactional and home environmental factors
6. Predictions of dyslexia
7. Diagnosing dyslexia and identification of children with risk
8. Follow-up of literacy development
9. Adulthood dyslexia
Summary of key findings
The most recent review on the key findings are reported in Lyytinen, H., et al. (2008). Early identification and prevention of dyslexia: Results from a prospective follow-up study of children at familial risk for dyslexia. In G. Reid, A. Fawcett, F. Manis, & L. Siegel (Eds.), The SAGE Handbook of Dyslexia (pp. 121-146). Sage Publishers. We include here a short description of some of the key findings. Please find the relevant referencecs for the key results from the list of publications below.
1. Familial risk for dyslexia is a strong predictor of difficulties in reading and spelling development. The incidence of dyslexia among children born at risk for dyslexia was 4-fold in comparison to the control group at the end of 2nd grade, 38 vs. 9 children, respectively. In addition, group comparisons at earlier age showed that the at-risk group had (a) differences in brain event-related potentials (ERPs) to speech and tone contrasts already at birth and 6 months of age (Leppänen et al., 1999; 2002; Guttorm et al., 2001), (b) differences in categorizing phonemic length at 6 months of age (Richardson et al., 2003), and (c) poorer skills than control group children in various cognitive skills that are known to predict reading and spelling (e.g. vocabulary, inflectional morphology, phonological processing, letter knowledge, and rapid automatized naming) starting from language measures already at the age 2 of years (e.g. Lyytinen, P. & Lyytinen, H., 2004, Lyytinen, P. et al., 2005).
2. In addition to familial risk, there are also other strong predictors of reading and spelling development and dyslexia. The best cognitive predictors of decoding accuracy and speed were phonological awareness, rapid automatized naming, and letter knowledge, starting from the 3.5 years of age (Puolakanaho et al., 2007; Torppa et al., 2010). Spelling was best predicted by phonological awareness (Torppa et al., in press) and reading comprehension difficulties by vocabulary (Torppa et al. 2007). Very early predictors of pre-reading and reading and spelling skills were ERPs to tones and speech sounds measured at birth (Guttorm et al., 2010; Leppänen et al., 2010).
3. Environmental are also linked with language and literacy development. Children’s language development has been found to be linked to maternal supportive behaviour in play situations (Lyytinen et al., 2003b), maternal activating strategy (Laakso et al., 1999a), and to the amount of parent-child shared book reading (Torppa et al., 2007). Teaching the names of letters at home was shown to be a significant predictor of children’s later letter knowledge (Torppa et al., 2006). In addition, school classroom membership was found to explain about 10 % of the variance in children’s reading development at early grades (Torppa et al., 2007). It should be noted, however, that children’s interest in reading does play a significant role and reading interest is likely as much a prerequisite as a consequence of shared reading (e.g. Lyytinen et al., 1998; Torppa et al., 2007).
List of publications from the Jyväskylä Longitudinal Study of Dyslexia & Developmental Neuropsychology and Learning Disorders
So far, altogether 13 doctoral dissertations have been completed on the data collected in the Jyväskylä Longitudinal Study of Dyslexia.
Current status of data collection
A description of screening procedure and data collection phases is presented here. At present, the data for the last cohort JLD children and their classmates has been gathered from the 9th grade in March 2012. In addition to the 200 JLD children followed from birth data will also be collected from round 2000 classmates, in similar fahion that was done also at the 1st – 3rd, and 7th grades. Besides, all children will attend assessments including containing reading measures planned and used by the OECD Programme for International Student Assessment (PISA), which will allow us to compare the reading outcomes of JLD children to large national and international samples.
- The Academy of Finland, Center of Excellence, Learning and Motivation Research, 2006-2011
- The Academy of Finland, Center of Excellence, Human Development and Its Risk Factors, 1997-2005
- The Academy of Finland 1992-1994, 1995-1997
- The Academy of Finland 1998-
- University of Jyväskylä 1994
- RAY 1995-1999 (Support functions for the families)