Large Scale Studies of Dyslexia in Florida Richard K. Wagner and Yusra Ahmed Florida State University and FCRR NIH Multidisciplinary Learning Disabilities Center (P50 HD052120)
Alternative Approaches • 1. Typical research study. • 2. Meta-analysis. • 3. Large-scale study.
Large-Scale Study of Incidence of Specific Reading Comprehension Disability
Personal Interest in Reading Comprehension Problems • Comprehension errors run in my family.
If admitted to this country, would you advocate overthrow of the government of the United States by force or violence? Question on a Form
If admitted to this country, would you advocate overthrow of the government of the United States by force or violence? violence Question on a Form
Reported Incidence of Reading Comprehension Disability • 10 percent of 7-11 year-olds are poor at reading comprehension despite being accurate and fluent at decoding (Nation, 2004).
Many Possible Causes • “There is room for lots of things to go wrong when comprehension fails” (Perfetti, 1994, p. 885, cited by Nation, 2005).
Possible Causes (Science of Reading: A Handbook) • 1. Decoding difficulties. • 2. Difficulties with meaning (vocabulary). • 3. Difficulty with syntax. • 4. Limitations in working memory. • 5. Poor inference making. • 6. Inadequate comprehension monitoring. • 7. Limited prior domain knowledge. • 8. Insensitivity to text structure.
Reading Comprehension Task • When the next slide appears, read the text as quickly as you can and summarize the passage in a brief sentence. • Ready?
Answer a Simple Question • Is necrobiosis a conceivable source of orogeny or of a pomiferous pompelmous?
Simple Question • Is necrobiosis conceivably related to orogeny or to the development of a pomiferous pompelmous? • Obviously the normal death of cells (necrobiosis) is not related to mountain building (orogeny), but is part of the process of the development of fruit bearing (pomiferous) trees (pompelmous).
Ordering Causes by Severity of Consequences for Comprehension • Primary • Decoding difficulties. • Secondary • Difficulties with meaning (vocabulary). • Tertiary • Difficulty with syntax; limitations in working memory; poor inference making; inadequate comprehension monitoring; limited prior domain knowledge; insensitivity to text structure.
Present Studies • Question Addressed: • What is the incidence of reading comprehension disability not attributable to primary or secondary causes? • Design feature: • Attempted to address issue of small samples sizes of typical studies by using the PMRN (progress monitoring and reporting network) database.
Study Design • 1. Identify individuals who are poor at reading comprehension. • Score at or below 5th percentile on Stanford Achievement Test (SAT-10) Reading Comprehension.
Study Design • 2. Determine how many individuals are poor at comprehension yet adequate at decoding. • SAT 10 at or below 5th percentile; • DIBELS Nonsense Word Fluency (NWF) greater than or equal to 25th percentile.
Study Design • 2. Determine how many individuals are poor at comprehension yet adequate at decoding and vocabulary. • SAT 10 at or below 5th percentile; • DIBELS Nonsense Word Fluency (NWF) greater than or equal to 25th percentile. • Peabody Picture Vocabulary Test (PPVT) greater than or equal to 25th percentile.
How Many Were Poor at… • Reading comprehension (SAT 10 < 5th%) • 1,669 (4.73%) out of 35,314
How Many Were Poor at… • Reading comprehension (SAT 10 < 5th %) • 1,669 (4.73%) out of 35,314 • yet adequate at decoding (nonword fluency >= 25th %)?
How Many Were Poor at… • Reading comprehension (SAT 10 < 5th %) • 1,669 (4.73%) out of 35,314 • yet adequate at decoding (nonword fluency >= 25th %)? • only 85 (0.24%) out of 35,314!
How Many Were Poor at… • Reading comprehension (SAT 10 < 5th %) • 1,669 (4.73%) out of 35,314 • yet adequate at decoding (nonword fluency >= 25th %)? • only 85 (0.24%) out of 35,314! • and in vocabulary (PPVT >= 25th %)?
How Many Were Poor at… • Reading comprehension (SAT 10 < 5th %) • 1,669 (4.73%) out of 35,314 • yet adequate at decoding (nonword fluency >= 25th %)? • only 85 (0.24%) out of 35,314! • and in vocabulary (PPVT >= 25th %)? • only 23 (0.07%) out of 35,314!
Surprising Result: Virtually All Had Problems in Decoding • Sample size was 35,314. • But it was a single study. Results need to be replicated.
First Grade Results • Of 150,000 6-year-olds, only .2 to .5 percent were poor at comprehension yet adequate at decoding. • May be nature of reading comprehension at age 6—decoding explains about everything.
Comparing Second-Grade Results to First-Grade Results • Second-grade results differ a little: • Percentage of children who are poor at reading comprehension yet adequate at decoding is about 2 percent, compared to .5 percent in first grade. • But identical when adequate vocabulary is also imposed: • Less than .2 percent for both.
What about Third Grade? • We could not do identical study because we don’t have nonsense word fluency (NWF) as decoding measure for third grade. • But we do have Gates-McGinnite reading vocabulary as a combined measure of decoding and vocabulary.
What About Less Severe Reading Comprehension Problems • Select if SAT 10 =< 20th %ile. • Require decoding and vocabulary 1 standard deviation higher (56th %ile) or just somewhat higher (40th %ile). • Representative second-grade results for most lenient (40th %ile) criterion.
What These Results Say • Specific reading comprehension not associated with presence of primary (decoding) or secondary (vocabulary) causes is exceedingly rare: • Less than 0.1 % of first-graders. • Less than 0.2 % of second-graders. • Less than 0.3 % of third-graders.
What These Results Don’t Say • Results don’t imply that individuals poor at reading comprehension don’t also show deficits in various tertiary factors.
What These Results Don’t Say • Results don’t imply that individuals poor at reading comprehension don’t also show deficits in various tertiary factors. • decoding gains from intervention rarely translate into equivalent gains in comprehension.
Conclusions • Individuals with tertiary causes (e.g., metacognitive deficiency) in absence of primary (decoding) and secondary (vocabulary) causes are rare.
Conclusions • For screening purposes, a combination of decoding and vocabulary should be remarkably effective.
Conclusions • Its worse not to know the words (primary problem in decoding or secondary problem in decoding vocabulary) than to not know whether you know the words (tertiary problem in metacognition).
Gender Differences in Reading Disability: Reasons to Care • 1. An active and controversial issue. • 2. Gender bias in identification and provision of services may be pervasive. • 3. Implications for theories of etiology. • 4. New approaches to identification being considered potentially could mitigate referral bias if it exists. • Ex. Universal screening as front end of RTI.
Current Controversy: Two Views • 1. Male vulnerability is a myth. • observed ratios of 2:1 or 3:1 in clinics and classrooms reflect referral bias. • true ratio is 1:1 or boys favored only minimally.
Key Study: Shaywitz et al. (1990) • Obtained both school-identified ratio and objective ratio for same sample. • Statistically significant ratio of 2.2:1 found for school identified ratio. • Non-significant ratio of 1.4:1 found for objective criteria. • Sample size modest however (18 boys versus 13 girls with RD). • A 2:1 ratio would not even be significant.
Current Controversy: Two Views • 2. Male vulnerability is real. • males roughly twice as likely to be affected.
Key Supporting Studies • Liederman et al., 2005, review of the literature. • Ratios ranged from 1.2:1 to 6.8:1. • Concluded that true ratio was between 1.7:1 and 2:1.
Key Questions • 1. What is the magnitude of male vulnerability for reading disability if it exists? • Answered by examining gender ratios for research-based operational definitions applied universally.
Key Questions • 2. How accurately does school-identification predict research-based identification? • Answered by classification analyses that use school-identification to predict research-based identification.
Key Questions • 3. What is the magnitude of referral bias if it exists? Answered by three empirical analyses: • A. Magnitude of difference in gender ratios for school-identified versus research identified samples. • B. Less overlap between school- and research-identification for boys than for girls. • C. Lower mean performance for girls compared to boys for school-identified samples.
Key Questions • 4. Do gender ratios vary as a function of: • A. Level of severity of reading problem? • Studies differ on level used. • B. Whether operational definition is based on low-achievement or IQ-achievement discrepancy? • Some suggestion that gender differences occur for IQ-discrepancy but not low-achievement definitions. • C. The kind of reading measure examined?