Preventing Reading Disabilities by Assessing and Remediating Phonemic Skills

Berninger, Virginia W.; Thalberg, Stanton P.; DeBruyn, Irma; Smith, Roderick W.

doi:10.1080/02796015.1987.12085316

Cited by 65 publications

(15 citation statements)

References 21 publications

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“…Phonological awareness. Syllable and phoneme segmenting and blending skills were assessed using the three subtests of the English Modified Rosner Test (EMRT; Berninger, Thalberg, DeBruyn, & Smith, 1987). In these three subtests the children are asked to remove (1) syllables, (2) singleton phonemes, and (3) phonemes in blends from familiar words.…”

Section: Early Reading Skillsmentioning

confidence: 99%

Bilingual children show advantages in nonverbal auditory executive function task

Foy

Mann²

2013

International Journal of Bilingualism

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Previous studies have shown that bilinguals have greater control over attentional resources than monolinguals in nonverbal tasks, perhaps reflecting domain-general enhancements of executive functioning (EF). Most studies of this bilingual advantage have used tasks with visual stimuli whereas fewer studies have examined attentional control in bilinguals in auditory tasks. We studied components of EF in two Go/No-Go auditory tasks with (1) nonverbal auditory stimuli and (2) verbal auditory stimuli in 5-year-old Spanish–English bilingual ( n = 30) and English-speaking monolingual ( n = 30) children matched on age, gender, short-term memory (digits forward subtest), and early reading skills (phoneme awareness and letter naming). The Go/No-Go tasks were modeled after a continuous performance task (CPT) (Mahone, Pillion, & Hiemenz, 2001) and included additional blocks of trials to measure the effects of switching targets. The bilingual children made fewer errors and had shorter reaction times (RTs) in the second block of the nonverbal auditory tasks than the monolinguals, but there were no differences on the verbal auditory task. Our results suggest that early bilingualism may confer advantages in young children for responding to nonverbal auditory stimuli under conditions that require cognitive flexibility.

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Section: Early Reading Skillsmentioning

confidence: 99%

Bilingual children show advantages in nonverbal auditory executive function task

Foy

Mann²

2013

International Journal of Bilingualism

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“…Pairs of items for this task were created based on the first 25 words on the WRMT-R Word Identification test (Woodcock, 1987). Children's phonological skills were assessed with the Modified Rosner Test (Berninger, Thalberg, DeBruyn, & Smith, 1987), which assesses both syllable deletion and phoneme deletion. RAN was assessed with Wolf's rapid automatized naming of letters (Wolf, Bally, & Morris, 1986).…”

Section: Predictor Measuresmentioning

confidence: 99%

“…Moreover, the students with double and triple deficits in reading-related language skills Note. N = 128. β = standardized regression coefficient; R 2 = total variance accounted for by paired variables; WI = Woodcock Reading Mastery Test-Revised (WRMT-R; Woodcock, 1987) Word Identification subtest, slope over pre-mid-posttest; WA = WRMT-R Word Attack subtest, slope over pre-mid-posttest; VIQ = Wechsler Intelligence Scale for Children, 3rd edition (Wechsler, 1991) Verbal IQ standard score; Phon = phonological skills, composite z score of the Modified Rosner Test (Berninger, Thalberg, DeBruyn, & Smith, 1987) Syllable Deletion and Phoneme Deletion subtests; Orth = orthographic skills, composite z score of the alphabet task (Berninger, 1999) and the orthographic choice task (Olson, Forsberg, & Wise, 1994); RAN = rapid automatized naming of letters (Wolf, Bally, & Morris, 1986) time for naming continuous rows of letters; Attn = tutors' Likert ratings (1 = very poor, 5 = very good ) of student's selective, sustained, and switching attention during tutorial sessions. *p < .05.…”

Section: Do Verbal Iq Other Reading-related Language Abilities and Attention Predict Growth In Word Reading In Response To Early Reading mentioning

confidence: 99%

“…Different subscripts indicate significant differences, p < .05, using Fisher's protected least significant difference t test. WI = Woodcock Reading Mastery Test-Revised (WRMT-R; Woodcock, 1987) Word Identification subtest; WA = WRMT-R Word Attack subtest; RAN = rapid automatized naming of letters (Wolf, Bally, & Morris, 1986); Phon = phonological skills, composite of modified Rosner Syllable Deletion and Phoneme Deletion subtests (Berninger, Thalberg, DeBruyn, & Smith, 1987); Orth = orthographic skills, composite of alphabet task (Berninger, 1999) and orthographic choice task (Olson, Foresberg, & Wise, 1994).…”

Section: Do Verbal Iq Other Reading-related Language Abilities and Attention Predict Growth In Word Reading In Response To Early Reading mentioning

confidence: 99%

“…N = 128. WA = Woodcock Reading Mastery Test-Revised (WRMT-R;Woodcock, 1987) Word Attack subtest, slope over pre-mid-posttest; WI = WRMT-R Word Identification subtest, slope over pre-midposttest; VIQ = Wechsler Intelligence Scale for Children, 3rd edition(Wechsler, 1991) Verbal IQ standard score; Phon = phonological skills, composite z score of the Modified Rosner Test(Berninger, Thalberg, DeBruyn, & Smith, 1987) Syllable Deletion and Phoneme Deletion subtests; Orth = orthographic skills, composite z score of the alphabet task…”

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confidence: 99%

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Predicting Response to Early Reading Intervention From Verbal IQ, Reading-Related Language Abilities, Attention Ratings, and Verbal IQ—Word Reading Discrepancy

et al. 2003

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Additional analyses of a previously published study addressed three questions about growth in word reading during early reading intervention: (1) How well do Verbal IQ, reading-related language abilities (phonological, rapid naming, and orthographic), and attention ratings predict reading growth? (2) How well do language deficits predict reading growth? and (3) How well does Verbal IQ-word reading discrepancy predict reading growth? Univariate analyses showed that Verbal IQ, phonological skills, orthographic skills, rapid automatized naming (RAN), and attention ratings predicted the response to early intervention, but multivariate analyses based on a combination of predictors for real-word reading and pseudoword reading showed that Verbal IQ was not the best unique predictor. Students with double or triple deficits in language skills (RAN, phonological, and orthographic processing) responded more slowly to early intervention than students without language deficits. Verbal IQ-word reading discrepancy did not predict the response to early intervention in reading. Overall results supported the use of reading-related language and attention measures rather than IQ-achievement discrepancy in identifying candidates for early reading intervention.

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Familial aggregation of dyslexia phenotypes. II: Paired correlated measures

Hsu¹,

Wijsman²,

Berninger³

et al. 2002

Am. J. Med. Genet.

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Dyslexia is a common and complex behavioral disorder characterized by unexpected difficulty in learning to read. Psychometric measures used to assess dyslexia often evaluate overlapping processes or abilities. To identify subphenotypes amenable to model-based linkage analyses, we have used careful language phenotyping, familial aggregation analyses of single phenotype measures, and segregation analyses. In the current study, to identify covariates to use in future segregation analyses we examined six pairs of related measures selected from among the most promising candidates in the initial aggregation analyses whose aggregation patterns were most consistent with a genetic basis. For these reciprocal aggregation analyses each measure is evaluated with the paired measure as the covariate to obtain information about the interdependence of the paired measures on shared genetic factors. Six pairs of measures were evaluated: 1) accuracy and efficiency of phonological decoding; 2) phonological nonword memory and written spelling; 3) phonological decoding accuracy and written spelling; 4) inattention ratings and rapid automatized naming for switching letters and numerals (RAS); 5) inattention ratings and oral reading rate; and 6) RAS and oral reading rate. Results of these analyses provide evidence that there may be a genetic contribution to efficiency of phonological decoding in addition to the genetic contribution it shares with accuracy of phonological decoding, a genetic contribution to phonological nonword memory in addition to the genetic contribution it shares with written spelling, a genetic contribution to written spelling in addition to the genetic contribution it shares with accuracy of phonological decoding, and a genetic contribution to inattention ratings in addition to the genetic contribution it shares with either RAS or oral reading rate.

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Preventing Reading Disabilities by Assessing and Remediating Phonemic Skills

Cited by 65 publications

References 21 publications

Bilingual children show advantages in nonverbal auditory executive function task

Bilingual children show advantages in nonverbal auditory executive function task

Predicting Response to Early Reading Intervention From Verbal IQ, Reading-Related Language Abilities, Attention Ratings, and Verbal IQ—Word Reading Discrepancy

Familial aggregation of dyslexia phenotypes. II: Paired correlated measures

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