African American Preschoolers' Performance on Norm-Referenced Language Assessments: Examining the Effect of Dialect Density and the Use of Scoring Modifications.

PURPOSE: We investigated and compared the outcomes from two standardized, norm-referenced screening assessments of language (i.e., Clinical Evaluation of Language Fundamentals Preschool-Second Edition [CELFP-2], Diagnostic Evaluation of Language Variation-Screening Test [DELV-ST]) with African American preschoolers whose spoken dialect differed from that of General American English (GAE). We (a) described preschoolers' performance on the CELFP-2 Core Language Index (CLI) and its subtests with consideration of degree of dialect variation (DVAR) observed, (b) investigated how the application of dialect-sensitive scoring modifications to the expressive morphology and syntax Word Structure (WS) subtest affected CELFP-2 CLI scores, and (c) evaluated the screening classification agreement rates between the DELV-ST and the CELFP-2 CLI. METHOD: African American preschoolers (N = 284) completed the CELFP-2 CLI subtests (i.e., Sentence Structure, WS, Expressive Vocabulary) and the DELV-ST. Density of spoken dialect use was estimated with the DELV-ST Part I Language Variation Status, and percentage of DVAR was calculated. The CELFP-2 WS subtest was scored with and without dialect-sensitive scoring modifications. RESULTS: Planned comparisons of CELFP-2 CLI performance indicated statistically significant differences in performance based on DELV-ST-determined degree of language variation groupings. Scoring modifications applied to the WS subtest increased subtest scaled scores and CLI composite standard scores. However, preschoolers who demonstrated strong variation from GAE continued to demonstrate significantly lower performance than preschoolers who demonstrated little to no language variation. Affected-status agreement rates between assessments (modified and unmodified CELFP-2 CLI scores and DELV-ST Part II Diagnostic Risk Status) were extremely low. CONCLUSIONS: The application of dialect-specific scoring modifications to standardized, norm-referenced assessments of language must be simultaneously viewed through the lenses of equity, practicality, and psychometry. The results of our multistage study reiterate the need for reliable methods of identifying risk for developmental language disorder within children who speak American English dialects other than GAE. SUPPLEMENTAL MATERIAL: https://doi.org/10.23641/asha.26017978.

Modeling Item-Level Spelling Variance in Adults: Providing Further Insights into Lexical Quality.

Purpose: The lexical quality (LQ) hypothesis predicts that a skilled reader's lexicon will be inhabited by a range of low- to high-quality items, and the probability of representing a word with high quality varies as a function of person-level, word-level, and item-specific variables. These predictions were tested with spelling accuracy as a gauge of LQ. Method: Item-response based crossed random effects models explored simultaneous contributions of person-level (e.g., participant's decoding skill), word-level (e.g., word's transparency rating), item-specific (e.g., participant's familiarity with specific word), and person-by-word interaction predictors (e.g., decoding by transparency rating interaction) to the spelling of 25 commonly misspelled irregular English words in 61 undergraduate university students (M = 19.4 years, 70.49% female, 39.34% Hispanic, 81.97% White). Results: Substantial variance among individuals in item-level spelling accuracy was accounted for by person-level decoding skill; item-specific familiarity, proportion of schwas correctly represented, and correctly identifying the word from its mispronunciation; and an interaction of transparency rating by general decoding skill. Conclusions: Consistent with the LQ hypothesis, results suggest that one's ability to form a high-quality lexical representation of a given word depends on a complex combination of person-level abilities, word-level characteristics, item-specific experiences, and an interaction between person- and word-level influences.

Spelling-to-pronunciation transparency ratings for the 20,000 most frequently written English words.

Given English orthography's quasi-regular nature, applying common decoding rules to a word does not always result in a correct pronunciation matching the stored phonological form (e.g., the word tongue). To arrive at a correct pronunciation, developing readers must make the match between a decoded pronunciation and a word's correct pronunciation stored in memory. Developmentally, this matching process varies as a function of child skill (e.g., decoding, vocabulary) and word characteristics (e.g., spelling-to-pronunciation transparency, concreteness), with each being continuously distributed. Spelling-to-pronunciation transparency ratings represent a global measure of the ease of arriving at a word's correct pronunciation from its decoded pronunciation and in experimental studies has been shown to be a critical dimension in assessing the difficulty of a word for developing readers (e.g., Steacy et al., 2022a, 2022b). This study aimed to create a database of spelling-to-pronunciation transparency ratings for the 23,282 most frequently written English words, made available in the supplemental materials for future analyses. We asked adults to rate words' spelling-to-pronunciation transparency on a scale of 1-6 (1 = very easy to match, 6 = very difficult). Results of multiple regression analyses revealed variance in ratings to be unaccounted for by other word features, demonstrating the uniqueness of these ratings. Furthermore, words that are considered irregular, classified previously as strange, or contained at least one schwa received higher ratings, demonstrating strong associations between transparency and regularity. Lastly, these ratings significantly predicted both adult word naming time and child word reading accuracy above and beyond other word features known to predict reading.

Set for Variability as a Critical Predictor of Word Reading: Potential Implications for Early Identification and Treatment of Dyslexia.

Quasiregular orthographies such as English contain substantial ambiguities between orthography and phonology that force developing readers to acquire flexibility during decoding of unfamiliar words, a skill referred to as a "set for variability" (SfV). The ease with which a child can disambiguate the mismatch between the decoded form of a word and its actual lexical phonological form has been operationalized using the SfV mispronunciation task (e.g., the word wasp is pronounced to rhyme with clasp [i.e., /wæsp/] and the child must recognize the actual pronunciation of the word to be /wɒsp/). SfV has been shown to be a significant predictor of word reading variance. However, little is known about the relative strength of SfV as a predictor of word reading compared to other well-established predictors or the strength of this relationship in children with dyslexia. To address these questions, we administered the SfV task to a sample of grade 2-5 children (N=489) along with other reading related measures. SfV accounted for 15% unique variance in word reading above and beyond other predictors, whereas phonological awareness (PA) accounted for only 1%. Dominance analysis indicated SfV is the most powerful predictor, demonstrating complete statistical dominance over other variables including PA. Quantile regression revealed SfV is a stronger predictor at lower levels of reading skill, indicating it may be an important predictor in students with dyslexia. Results suggest that SfV is a powerful and potentially highly sensitive predictor of early reading difficulties and, therefore, may be important for early identification and treatment of dyslexia.

Screening screeners: calculating classification indices using correlations and cut-points.

Given the recent push for universal screening, it is important to take into account how well a screener identifies children at risk for reading problems as well as how screener and sample information contribute to this classification. Picking the best cut-point for a particular sample and screening goal can be challenging given that test manuals often report classification information for a specific cut-point and sample base rate which may not generalize to other samples. By assuming a bivariate normal distribution, it is possible to calculate all of the classification information for a screener based on the correlation between the screener and outcome, the cut-point on the outcome (i.e., the base rate in the sample), and the cut-point on the screener. We provide an example with empirical data to validate these estimation procedures. This information is the basis for a free online tool that provides classification information for a given correlation between screener and outcome and cut-points on each. Results show that the correlation between screener and outcome needs to be greater than .9 (higher than observed in practice) to obtain good classification. These findings are important for researchers, administrators, and practitioners because current screeners do not meet these requirements. Since a correlation is dependent on the reliability of the measures involved, we need screeners with better reliability and/or multiple measures to increase reliability. Additionally, we demonstrate the impact of base rate on positive predictive power and discuss how gated screening can be useful in samples with low base rates.

Unpacking the Unique Relationship Between Set for Variability and Word Reading Development: Examining Word- and Child-Level Predictors of Performance.

Set for variability (SfV) is an oral language task which requires an individual to disambiguate the mismatch between the decoded form of an irregular word and its actual lexical pronunciation. For example, in the task, the word wasp is pronounced to rhyme with clasp (i.e., /wæsp/) and the individual must recognize the actual pronunciation of the word to be /wɒsp/. SfV has been shown to be a significant predictor of both item-specific and general word reading variance above and beyond that associated with phonemic awareness skill, letter-sound knowledge, and vocabulary skill. However, very little is known about the child characteristics and word features that affect SfV item performance. In this study we explored whether word features and child characteristics that involve phonology only are adequate to explain item-level variance in SfV performance or whether including predictors that involve the connection between phonology and orthography explain additional variance. To accomplish this we administered the SfV task (N=75 items) to a sample of grade 2-5 children (N=489) along with a battery of reading, reading related, and language measures. Results suggest that variance in SfV performance is uniquely accounted for by measures tapping phonological skill along with those capturing knowledge of phonology to orthography associations, but more so in children with better decoding skill. Additionally, word reading skill was found to moderate the influence of other predictors suggesting that how the task is approached may be impacted by word reading and decoding ability.

Modeling Complex Word Reading: Examining Influences at the Level of the Word and Child on Mono- and Polymorphemic Word Reading.

Purpose: The probability of a child reading a word correctly is influenced by both child skills and properties of the word. The purpose of this study was to investigate child-level skills (set for variability and vocabulary), word-level properties (concreteness), word structure (mono- vs. polymorphemic), and interactions between these properties and word structure within a comprehensive item-level model of complex word reading. This study is unique in that it purposely sampled both mono- and polymorphemic polysyllabic words. Method: A sample of African American (n = 69) and Hispanic (n =6) students in grades 2-5 (n =75) read a set of mono- and polymorphemic polysyllabic words (J=54). Item-level responses were modeled using cross-classified generalized random-effects models allowing variance to be partitioned between child and word while controlling for other important child factors and word features. Results: Set for variability and the interaction between concreteness and word structure (i.e., mono- vs. polymorphemic) were significant predictors. Higher probabilities of reading poly- over monomorphemic words were identified at lower levels of concreteness with the opposite at higher levels of concreteness. Conclusions: Results indicate important predictors at both the child- and word-level and support the importance of morphological structure for reading abstract polysyllabic words.

A Simulation Study on the Performance of Different Reliability Estimation Methods.

The accuracy of certain internal consistency estimators have been questioned in recent years. The present study tests the accuracy of six reliability estimators (Cronbach's alpha, omega, omega hierarchical, Revelle's omega, and greatest lower bound) in 140 simulated conditions of unidimensional continuous data with uncorrelated errors with varying sample sizes, number of items, population reliabilities, and factor loadings. Estimators that have been proposed to replace alpha were compared with the performance of alpha as well as to each other. Estimates of reliability were shown to be affected by sample size, degree of violation of tau equivalence, population reliability, and number of items in a scale. Under the conditions simulated here, estimates quantified by alpha and omega yielded the most accurate reflection of population reliability values. A follow-up regression comparing alpha and omega revealed alpha to be more sensitive to degree of violation of tau equivalence, whereas omega was affected greater by sample size and number of items, especially when population reliability was low.

Modeling and Visualizing the Codevelopment of Word and Nonword Reading in Children From First Through Fourth Grade: Informing Developmental Trajectories of Children With Dyslexia.

Developmental studies examining relations between word reading (WR) and decoding in typical and dyslexic populations routinely cut the reading distribution to form distinct groups. However, dichotomizing continuous variables to study development is problematic for multiple reasons. Instead, we modeled and visualized the parallel growth of WR and nonword reading (NWR) factor scores longitudinally in a Grade 1-4 developmental sample (N = 588). The results indicate that while WR and NWR growth factors are highly related (r = .71), the relation between WR and NWR trajectories change as a function of initial WR. Results are interpreted within computational models of dyslexia in which children with dyslexia overfit orthography â†’ phonology relations at the level of the word, limiting the development of sublexical representations needed to read nonwords.

Correction to: Predicting Arabic word reading: A cross-classified generalized random-effects analysis showing the critical role of morphology.

The original version of this article unfortunately contained the following errors.

Sight word acquisition in first grade students at risk for reading disabilities: an item-level exploration of the number of exposures required for mastery.

The purpose of this study was to examine word learning efficiency in at-risk first grade students (N = 93) participating in a yearlong study evaluating a multicomponent intervention targeting word reading and decoding skills. As part of each intervention lesson, students participated in a 1 to 3-min sight word reading activity in which high-frequency words were read from a list until mastered, at which point the word dropped off the list. This study explored factors predicting the number of exposures required for item reading mastery (N = 145 words). Specifically, we explored how the number of word exposures required to reach mastery varied as a function of linguistic features of the words and cognitive characteristics of the students. Using item-level crossed-random effects models, we found students required an average of 5.65 exposures for mastery, with word features representing word length, vocabulary grade, and imageability being significant predictors of learning efficiency. We also found a significant interaction between pretest word reading skill and imageability of a word, with this semantic feature being especially important for the poorest readers. Results indicate that in the absence of typical word recognition skills, poor readers tend to rely on other sources of information to learn words, which tend to be related to the semantic features of words.

The Prevalence of Dyslexia: A New Approach to Its Estimation.

How prevalent is dyslexia? A definitive answer to this question has been elusive because of the continuous distribution of reading performance and predictors of dyslexia and because of the heterogeneous nature of samples of poor readers. Samples of poor readers are a mixture of individuals whose reading is consistent with or expected based on their performance in other academic areas and in language, and individuals with dyslexia whose reading is not consistent with or expected based on their other performances. In the present article, we replicate and extend a new approach for determining the prevalence of dyslexia. Using model-based meta-analysis and simulation, three main results were found. First, the prevalence of dyslexia is better represented as a distribution that varies as a function of severity as opposed to any single-point estimate. Second, samples of poor readers will contain more expected poor readers than unexpected or dyslexic readers. Third, individuals with dyslexia can be found across the reading spectrum as opposed to only at the lower tail of reading performance. These results have implications for screening and identification, and for recruiting participants for scientific studies of dyslexia.

Predicting Arabic word reading: A cross-classified generalized random-effects analysis showing the critical role of morphology.

The distinctive features of the Arabic language and orthography offer opportunities to investigate multiple word characteristics at the item level. The aim of this paper was to model differences in word reading at the item level among 3rd grade native Arabic-speaking children (n = 303) using cross-classified generalized random-effects (CCGRE) analysis. The participants read 80 vowelized words that varied in multiple elements that may contribute to their decodability: number of letters, number of syllables, number of morphemes, ligaturing (connectivity), semantics (concrete vs. abstract), orthographic frequency, root type frequency, and part of speech. Morphological awareness (MA) was included as a person-level predictor. Results of individual models showed that MA, number of letters, number of syllables, number of morphemes, number of ligatures, orthographic frequency, and part of speech were significantly related to the probability of a correct response. However, when all predictors were entered simultaneously, only MA and number of morphemes remained significant. These results underscore the important role of morphology in the lexical structure of Arabic words and in Arabic word reading. Discussion focuses on the role of morphology in Arabic reading and the implications for intervention to improve word recognition in children learning to read Arabic.

Combining Old and New for Better Understanding and Predicting Dyslexia.

Despite decades of research, it has been difficult to achieve consensus on a definition of common learning disabilities such as dyslexia. This lack of consensus represents a fundamental problem for the field. Our approach to addressing this issue is to use model-based meta-analyses and Bayesian models with informative priors to combine the results of a large number of studies for the purpose of yielding a more stable and well-supported conceptualization of reading disability. A prerequisite to implementing these models is establishing informative priors for dyslexia. We illustrate a new approach for doing so based on the known distribution of the difference between correlated variables, and use this distribution to determine the proportion of poor readers whose poor reading is unexpected (i.e., likely to be due to dyslexia) as opposed to expected.

Evaluating Health Advice in a Web 2.0 Environment: The Impact of Multiple User-Generated Factors on HIV Advice Perceptions.

Unlike traditional media, social media systems often present information of different types from different kinds of contributors within a single message pane, a juxtaposition of potential influences that challenges traditional health communication processing. One type of social media system, question-and-answer advice systems, provides peers' answers to health-related questions, which yet other peers read and rate. Responses may appear good or bad, responders may claim expertise, and others' aggregated evaluations of an answer's usefulness may affect readers' judgments. An experiment explored how answer feasibility, expertise claims, and user-generated ratings affected readers' assessments of advice about anonymous HIV testing. Results extend the heuristic-systematic model of persuasion (Chaiken, 1980) and warranting theory (Walther & Parks, 2002). Information that is generally associated with both systematic and heuristic processes influenced readers' evaluations. Moreover, content-level cues affected judgments about message sources unexpectedly. When conflicting cues were present, cues with greater warranting value (consensus user-generated ratings) had greater influence on outcomes than less warranted cues (self-promoted expertise). Findings present a challenge to health professionals' concerns about the reliability of online health information systems.