Research in Developmental Disabilities 34 (2013) 1090–1099

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Research in Developmental Disabilities

Contributions of phonological awareness, phonological short-termmemory, and rapid automated naming, toward decoding ability instudents with mild intellectual disability

Amanallah Soltani *, Samsilah Roslan

Department of Foundations of Education, Faculty of Educational Studies, University Putra Malaysia, Serdang, Selangor, Malaysia

A R T I C L E I N F O

Article history:

Received 30 July 2012

Received in revised form 7 December 2012

Accepted 12 December 2012

Available online 9 January 2013

Keywords:

Decoding ability

Phonological awareness

Phonological short-term memory

Rapid automated naming

Intellectual disability

A B S T R A C T

Reading decoding ability is a fundamental skill to acquire word-specific orthographic

information necessary for skilled reading. Decoding ability and its underlying

phonological processing skills have been heavily investigated typically among developing

students. However, the issue has rarely been noticed among students with intellectual

disability who commonly suffer from reading decoding problems. This study is aimed at

determining the contributions of phonological awareness, phonological short-term

memory, and rapid automated naming, as three well known phonological processing

skills, to decoding ability among 60 participants with mild intellectual disability of

unspecified origin ranging from 15 to 23 years old. The results of the correlation analysis

revealed that all three aspects of phonological processing are significantly correlated with

decoding ability. Furthermore, a series of hierarchical regression analysis indicated that

after controlling the effect of IQ, phonological awareness, and rapid automated naming are

two distinct sources of decoding ability, but phonological short-term memory significantly

contributes to decoding ability under the realm of phonological awareness.

� 2012 Elsevier Ltd. All rights reserved.

1. Introduction

Decoding ability refers to the conversion of printed letters into equivalent speech sounds. It is a fundamental skill toacquire word-specific orthographic information necessary for skilled reading (Kirby, Desrochers, Roth, & Lai, 2008). Worddecoding requires attending to the graphemes details of a word, identifying phonemes represented in the word, blending astring of the phonemes, and finally reading the word. Typical beginner readers usually move through the stages successfullywhen they step forward in their academic skills (Barker, 2010). However, compared to their non disabled peers, studentswith intellectual disability may have considerable difficulties in passing decoding steps effectively and their decodingabilities often lag behind their chronological and mental age (Cawley & Parmar, 1995; Conners, Atwell, Rosenquist, & Sligh,2001; Gronna, Jenkins, & Chin-Chance, 1998). Decoding deficiencies in students with intellectual disability may impede theirword-specific orthographic information and consequently interfere with their reading accuracy. Hence, understandingphonological processing aspects underlying decoding abilities in these students may have profound implications for theirremedial intervention programs.

Phonological awareness, phonological short-term memory, and rapid automated naming are three well known aspects ofphonological processing closely related to decoding ability (Wagner & Torgesen, 1987; Wagner et al., 1997). Phonologicalawareness refers to the ability to manipulate individual sounds or phoneme of a given language and make judgment about

* Corresponding author. Tel.: +98 9136159952.

E-mail address: soltanimani@yahoo.com (A. Soltani).

0891-4222/$ – see front matter � 2012 Elsevier Ltd. All rights reserved.

http://dx.doi.org/10.1016/j.ridd.2012.12.005

A. Soltani, S. Roslan / Research in Developmental Disabilities 34 (2013) 1090–1099 1091

them (Schuele & Boudreau, 2008). Phonological short-term memory involves storing distinct phonological features for ashort period of time. Finally, rapid automated naming refers to rapid efficient retrieval of a series of names of colors, objects,digits, and letters presented in random orders (Denckla & Rudel, 1974).

A large number of studies have consistently established that the three aspects of phonological processing stronglycontribute to reading abilities typically in developing participants, although there are some controversies as to whether theyhave independent unique contributions or share some common variances (e.g., Elbro, 1996; Goswami & Bryant, 1990; Share,1995; Wagner & Torgesen, 1987). However, a small number of researchers are concerned with the issue within participantswith intellectual disability, especially those of unspecified origin (Conners, Atwell, Rosenquist, & Sligh, 2001; Wise, Sevcik,Romski, & Morris, 2010; Saunders & DeFulio, 2007). In some ways, this may be because it is assumed that low IQs in studentswith intellectual disability explains their poor reading performance and there is no need to look for any specific dysfunction.Nevertheless, as mentioned by Conners et al. (2001), intelligence is neither the only nor the most important predictor ofreading performance. Controlling the effect of IQ, there are some unique variances in reading performance accounted forother cognitive functions.

The goal of the present study is to investigate the contributions of phonological awareness, phonological short-termmemory, and rapid automatic naming to decoding ability in students with intellectual disability of unspecified origin aftercontrolling the effect of IQ. In the following sections, an overview of the three phonological processing skills and theircontributions to decoding ability are reviewed.

1.1. Phonological awareness and decoding ability

As mentioned earlier, phonological awareness refers to the ability of manipulating individual sounds or phoneme of agiven language and making judgment about them (Schuele & Boudreau, 2008). Phonological awareness is an umbrella termused to describe a variety of tasks such as blending and segmenting phonemes or syllables in a word, rhyme detection tasks,initial and final phoneme or syllables detection tasks, and finally initial and final phoneme or syllables deletion tasks.

It has been argued that phonological awareness is the prerequisite to the ability to decode words (Wagner & Torgesen,1987). The point of this argument is that awareness of phonemes is essential to segment letter strings into phoneme basedunits and subsequently blending the resulting phonemes into words which are fundamental to develop a decoding ability.Concerning typically developing participants, numerous correlation studies have confirmed that phonological awareness isdirectly linked to decoding ability (e.g., Hester & Hodson, 2004; Plaza & Cohen, 2003; Roman, Kirby, Parrila, Wade-Woolley, &Deacon, 2009; Strattman & Hodson, 2005; Tengestal & Tqnnessen, 2011). When measuring prior to or at the onset of readinginstruction, empirical studies have demonstrated that phonological awareness successfully predicts decoding ability andreading performance in later years (e.g., Catts, Fey, Zhang, & Tomblin, 2001; de Jong & van der Leij, 1999, 2002; Georgiou,Parrila, & Papadopoulos, 2008; Hogan, Catts, & Little, 2005; Pokorni, Worthington, & Jamison, 2004; Torgesen et al., 1999;Wagner et al., 1997). Furthermore, training studies have shown that explicit instruction in phonological awareness leads togain not only in decoding ability skill but also in general reading ability (e.g., Ball & Blachman, 1991; Durguno-lu & Ouml,2002; Gillon & Dodd, 1995; Gillon, 2000; Pokorni et al., 2004; Torgesen, Wagner, Rashotte, Herron, & Lindamood, 2010;Torgesen et al., 1999)

Concerning subjects with intellectual disability, most studies addressed the question of whether phonological awarenessskills are correlated with reading decoding ability, have involved participants with Down syndrome. Taken together, theirfindings approved the significant link between different measures of phonological awareness and reading decoding abilities(for a review see Lemons & Fuchs, 2010; Nass, Melby-Lervag, Hulme, & Lyster, 2012). Similar results were also reported byWise et al. (2010) in a sample of 80 elementary school age students with mild intellectual disability of heterogeneousetiology (mostly Down syndrome, fragile � syndrome, and unspecified origin). The researchers found that, after controllingfor chronological age and vocabulary knowledge, phonological awareness tasks accounted for a large and significant amountof unique variance of both word and non word decoding skills. Additional supports were provided by Saunders and DeFulio(2007) who found strong relationships between certain measures of phonological awareness (sound categorization tasks)and decoding abilities after controlling for IQ in thirty (21–58 years old) adults with mild intellectual disability of unspecifiedorigin. Furthermore, in another study, Conners et al. (2001) compared 21 stronger decoders with 44 weaker decoders, all ofwhom had intellectual disability of heterogeneous etiology. The participants were between 8 and 12 years of age, with anIQ < 70. Their initial group comparisons revealed that the stronger decoders were significantly better than weaker decodersin phonological awareness tasks (t = 2.49, SE = 4.07).

1.2. Phonological short-term memory and decoding ability

Phonological short-term memory capacity, as measured by non word repetition tasks, has been consistently related toword and non word decoding ability (Gathercole & Baddeley, 1993; Gathercole, Willis, & Baddeley, 1991; Wagner et al.,1997). Simultaneously, the nature of this relationship remains debatable. Some researchers have found that phonologicalshort-term memory does not uniquely contribute to decoding ability, when the effects of phonological awareness or otheraspects of phonological processing are controlled (Muter & Snowling, 1998; Ramus et al., 2003; Wagner et al., 1997). Theresearchers suggested that verbal item information is stored in the short-term memory directly via temporary activation ofthe language network; in that case, processing and storage of verbal item information directly depends upon the availability

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and richness of underlying phonological and semantic representation. This led the researchers to accept that the corecognitive skill required for decoding ability is the linguistic awareness of the phonological structures of the spoken language.

Other researchers have reported that verbal short-term memory makes a unique contribution to decoding ability beyondthat of phonological awareness (Gathercole et al., 1991; Hansen & Bowey, 1994; Tractenberg, 2002). They suggested thateffect of phonological short-term memory should enable the reader to apply maximum resources to the tasks of blendingtogether isolated phonemes to make words (Wagner & Torgesen, 1987). In other words, the ability to hold multiple lettersounds in mind and combining them to form a word is facilitated by phonological short-term memory. Hence, phonologicalshort-term memory may play a unique role in the decoding ability beyond that played by phonological awareness.

Regarding individuals with intellectual disability, recent evidence suggests that these people have functional limitationsin their phonological short-term memory when comparing with typically developing participants (Schuchardt, Gebhardt, &Maehler, 2010; Schuchardt, Maehler, & Hasselhorn, 2011; Van der Molen, Van Luit, Jongmans, & Van der Molen, 2009; Vicariet al., 1995). At the same time, there is limited relevant research determining the contribution of verbal short-term memoryto decoding abilities in this population. Conners et al. (2001) examined differences in phonological short-term memorycapacity between stronger and weaker decoders, all of whom have intellectual disability of unspecified origin. Their initialgroup comparisons showed that although there were no differences in general intelligence between two groups, strongerdecoders were significantly better than weaker decoders in phonological short-term memory. In another study, Henry andWinfield (2010) measured the original components of working memory including phonological short-term memory andtheir relations with reading and spelling ability in 35 children with mild intellectual disability of non-specific etiology. Theresults showed that, in comparing with the other components of working memory, phonological short term memoryaccounted for the most variance in reading ability.

1.3. Rapid automated naming and decoding ability

Rapid Automated Naming (RAN) tasks originally developed by Denckla and Rudel (1974) refers to rapid efficientretrieval of a series of names of colors, objects, digits, and letters presented in random order in a 5 row � 10 column grid.Performance on the task requires attention to stimuli, memory retrieval of the phonological label, and articulating process(Klein, 2002).

Considerable research have found that RAN tasks were significantly correlated with non word decoding ability in bothtypical students and students with developmental reading disorder (Dyslexia) (e.g., Christo & Davis, 2008; Wolf & Bowers,1999; Wolf et al., 2002). However, the nature of this correlation is not well understood. Some researchers have proposed thatRAN falls into the phonological processing realm because it represents phonological code retrieval (Wagner, Torgesen,Laughon, Simmons, & Rashotte, 1993; Wagner, Torgesen, & Rashotte, 1994). Others (Bowers & Wolf, 1993; Manis,Seidenberg, & Doi, 1999; Wolf, 1991; Wolf & Bowers, 1999; Wolf, Bowers, & Biddle, 2000) have suggested that, although RANtasks share some variance with phonological awareness, they can be considered as a separate cognitive process relating todecoding ability. The researchers argued that RAN tasks are composed of attention, visual, lexical, temporal, and recognitionsub process that all contribute to RAN performance. Putting all these sub processes under the category of phonologicalawareness obscures the complexity of RAN tasks. Such an argument is also consistent with double-deficit hypothesis (Wolf &Bowers, 1999) which mentions deficits in both RAN and phonological awareness have two distinct predictive sources ofreading impairments.

With the subject of intellectual disability, Saunders and DeFulio (2007) conducted the only study concerning thecontribution of phonological awareness and RAN to word decoding ability. The researchers studied the correlation of tworapid naming tasks (RAN pictures and RAN letters) and four measures of phonological awareness (whole-rime, same firstsound, same end sound, and same middle sound) with both decoding word and non word in a sample of adult with mildintellectual disability of unspecified origin. The correlation analysis showed that both measures of phonologicalawareness and naming speed strongly correlated with decoding abilities (ranging from .37 to .65). However, no resultwas presented to show weather RAN tasks contribute to decoding ability independently or under the realm ofphonological awareness.

1.4. Summary

Regarding the importance of decoding ability as a fundamental skill to acquire the word-specific orthographicinformation necessary for skilled reading, it is essential to determine its underlying phonological processing skillsespecially in people with intellectual disability who usually suffer from reading decoding problems. A large number ofstudies have examined the contributions of phonological awareness, phonological short-term memory and rapidautomated naming to reading decoding ability in both typically developing participants and children with readingdisability. Simultaneously, a small number of studies relate to the issue in students with intellectual disability speciallythose of unspecified origin. Taken together, the results of the studies confirmed that different measures of phonologicalawareness are significantly contributed to decoding ability in participants both with and without intellectual disability. Inaddition, the results confirmed the importance of phonological short-term memory and rapid automated naming as twoother skills contributed to decoding ability. However, the results showing the nature of these contributions remaincontroversial.

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2. Study purpose

The present study mainly aimed at investigating the contributions of phonological awareness, phonological short-termmemory, and rapid automated naming to decoding ability, while controlling the effect of IQ, in a sample of adolescents andyoung adults with mild intellectual disability of unspecified origin. We hypothesize that (1) phonological awareness issignificantly correlated with decoding ability independence of phonological short-term memory, and rapid automatednaming; (2) phonological short term memory is significantly related to decoding ability independence of phonologicalawareness and rapid automated naming; (3) rapid automated naming is significantly associated with the decoding abilityindependence of phonological awareness and phonological short-term memory.

Since this study has been conducted in a Persian orthography, before going to the method, an outline of Persianorthography follows.

3. Persian orthography

Persian orthography consists of 32 alphabetic letters written from right to left. The alphabetic letters consist of 26consonants, three short vowels (/a/, /e/, /o/,) and three long vowels (/a/, /u/, /e/.) The common syllable structures in Persianlanguage are CV, CVC, and CVCC (‘‘C’’ for Consonant, and ‘‘V’’ for Vowel). Persian orthography is usually viewed as havingconsistent letter-sound correspondence rules in which each grapheme has a single pronunciation (Baluch, 1993; Baluch &Besner, 1991). However, as mentioned by Rahbari and Seneschal (2009), Persian is not entirely transparent. That is, althoughall consonants and the three long vowels are represented by letters, the three short vowels are not represented by any letter.Given this characteristic, it is possible that Persian word srd could be pronounced as /sard/, /sord/, /serd/, but, in this case,only the first pronunciation corresponds to a real word meaning cold. This characteristic may affect reading performanceespecially in beginning readers.

4. Methods

4.1. Participants

Sixty students classified by their school as having intellectual disability of unspecified origin were chosen to participate inthis study. All selected participants were Iranian males without any identified genetic syndrome and neurologicalabnormality. Participants had normal or corrected normal vision and sufficient hearing. All participants lived with their ownfamily and attended a school for special education and vocational training. Their chorological age ranges from 15 to 23 yearsold with a mean of 18.6. Their IQ scores using Raven’s Colored Progressive Matrices Test (Raven, Court, & Raven, 1986) rangedfrom 54 to 80 with a mean of 68.

4.2. Measures

4.2.1. IQ measure

The Raven’s Colored Progressive Matrices Test (Raven et al., 1986) was administered to measure the level of IQ. In this test,the participants were presented with 60 pattern/matrices composed of abstract shapes, lines, and nonverbal figures, each ofwhich of missing a piece. For each pattern, 6 choices (pieces) were presented. The participant’s task was to choose the piecethat best fit in the empty apace. Participants had unlimited time to complete this task. The determination of the scoredepended on the total number of correct choices.

4.2.2. Phonological awareness measures

We administered five phonological awareness tests from Kashani and Ghorbani (2009) including phoneme blending,phoneme segmenting, first, middle and final phoneme identification, syllable deletion, and finally phoneme deletion. Withthe phonological blending task, the participant was asked to say the word resulting from merging single phonemespronounced by the examiner. The items in the tasks included (5) one syllable, (6) two syllables, and (5) three syllables words.In phoneme segmenting task that was opposite of the previous task, the participant was asked to break into phonemes thewords pronounced by the examiner. The items used in this task were the same as in the blending task, thus the two taskswere never administered one after the other. In phoneme identification task, the examiner pronounced a word and aphoneme separately and asked the participant whether the phoneme was in the word or not. The task included 36 items andthe words used in the task had one or two syllables. In syllable deletion task, the participant was asked to say a word withoutthe first or the last syllable. The task included 16 items and the words used in the task had one or two syllables. In the first 8items, the participant was asked to delete the first syllable and in the second eight items, he was asked to delete the lastsyllable. Finally, in the phoneme deletion task, the participant was asked to delete the first or last phoneme of a word. Thistask had 16 items, and all the words used in the task had one syllable. In the first 8 items, the participant was asked to deletethe first phoneme, and in the last eight items, he was asked to delete the last phoneme. The authors (Kashani & Ghorbani,2009) initially reported the content validity ratio of the whole instrument as .85. The Cronbach alphas reported by theauthors are ranging from .50 to .98 (Kashani & Ghorbani, 2009).

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4.2.3. Rapid automated naming measures

Rapid Automated Naming (RAN) measures of numbers, letters, colors, and objects were designed by the authors based onthe original version (Denckla & Rudel, 1974). Each of the four tests of RAN consists of a chart containing five different items(i.e., five colors or five digits) presented in horizontal rows of ten items each, repeated in random order in a 5 row � 10column grid. The items used in RAN digit were 2, 3, 4, 5, and 7 which are pronounced in Parisian as /do/, /se/, /char/, /panj/, and /

haft/ respectively. The items used in RAN letter were /s/, /n/, /k/, /t/, /p/. The size of the digits and letters was 48 in Arial font.The items used in RAN color were blue, red, yellow, black, and green which are pronounced in Persian as /abi/, /qermes/, /zard/, /siah/, and /sabz/ respectively. The items used in RAN object were the pictures of ‘‘key’’, ‘‘watch’’, ‘‘scissor’’, ‘‘umbrella’’and ‘‘bag’’ which are pronounced in Persian as /kelid/, /saat/, /qeychi/, and /chatr/ respectively. The size of the pictures andcolors were approximately 3 cm � 3 cm.

Before launching the RAN tests, the examiner ensured that each participant could name the items used in the taskscorrectly. Then, he requested the participant to name the items in sequences as quickly as he can. The examiner started atimer when the participant began to name the first item on the page, then he stopped the timer when the last item wasnamed. The total time, in seconds, that the participant spent on naming all items was calculated and data was converted to aper-minute score.

4.2.4. Short-term memory measures

Phonological short-term memory was assessed using two tests including a non word repetition task from Sayyahi,Soleymani, Bakhtiyari, and Jalaie (2011), and a forward digit span task from WISC-IV adapted for Persian Language. The nonword repetition task (Sayyahi et al., 2011) included 25 meaningless words with two to six syllables. The syllable structures ofnon words were CV, CVC, and CVCC which are common in Persian orthography. In this task, the participant was asked torepeat a non word after orally presented by the examiner. The score was the number of correctly repeated non words. In theforward digit span task, the participant was asked to repeat a series of digits in the order they were presented by theexperimenter. The time duration for presenting each item was one second. The whole test consisted of 16 items increasing inlength. The first two items consisted of two digits, the following two of three digits, then there were two items for four digits,and finally the last two items consisted of 9 items. The test was discontinued after two consecutive failures. The score was thenumber of correctly reproduced series in orders they were presented.

4.2.5. Decoding ability measure

Non word reading tests, sometimes also called pseudo-words or nonsense words reading tests, have been used as puremeasures of decoding ability in different orthographies (Georgiou et al., 2008; Kirby et al., 2008; Rahbari, Seneschal, & Arab-Moghaddam, 2007; Torgesen et al., 1999; Vanderwood, Linklater, & Healy, 2008). In any language, non words used in thetests are pronounceable combinations of the letters that conforms to the language spelling rules. They are not real words, buthave similar phonetic structures used in the real words. They prevent the holistic recognition of the stimuli as they are notpart of the reader’s lexicon; thus, the only means of pronouncing them is through decoding ability (Kirby et al., 2008).

In the current study, a non word reading test was designed based on Persian orthography. In this test, a list of (38) onesyllable nonsense words from Rahbari and Seneschal (2009) and (20) two to five syllables nonsense word presented inascending difficulty, were used to assess decoding ability. Syllables in non words varied from one to five. The participantswere told that even though these were not real words, they could try to read them appropriately. When the participant readan item correctly, he received a score of 1 for that item. However, if he read the non word incorrectly (i.e., missed or addedletters/syllables, and/or replaced parts of the non word) he was given a score of 0.

4.3. Procedure

After obtaining written consents from parents and the school principal, the participants were tested individually in asmall private room located in the special school over three testing sessions that were each 35–55 min long. In session one,the Raven’s Colored Progressive Matrices Test was administered to measure the IQ. Session two included the measures ofphonological awareness and non word decoding ability. Finally, in session three, the measures of rapid automated namingand phonological short-term memory were administered. Twenty randomly selected participants were used to determinetest–retest reliability coefficients of all measures over a four-week interval. The results ranged from .74 to .85 forphonological awareness tasks; .78 to .89 for rapid automated naming tasks; .88 and .95 for measures of short-term memory;and finally .84 for non-word decoding ability task. Descriptive, correlation, and multiple regression analyses were performedusing SPSS statistical software (version18).

5. Results

Mean, standard deviation, skewness, and kurtosis of decoding ability, phonological awareness, short-term memory, andrapid automated naming measures were provided in Table 1. Skewness and kurtosis values for all measures indicated normaldistributions of scores (Laurentis, Maino, & Molteni, 2010)

The correlation coefficients between all measures were provided in Table 2. The results (Table 2) showed that the fiveitems of phonological awareness (blending, segmenting, phoneme deletion, syllable deletion, and phoneme identification)

Table 1

Mean, standard deviation, range, skewness, and kurtosis of all variables.

Variable Mean SD Range Skewness Kurtosis

Decoding ability

Non word decoding 18.72 8.02 .50–29 �.392 �.889

Rapid automated naming

RAN object 59.85 17.21 28–119 1.332 1.726

RAN letter 103.12 33.27 45–185 .600 �.300

RAN number 98.98 27.51 39–165 .595 .403

RAN color 72.27 17.11 28–109 .078 �.210

Short-term memory

Non word repetition 10.50 2.90 4–19 .273 .165

Forward digit span 5.78 1.36 4–10 .572 .123

Phonological awareness

Phoneme identification 32.76 4.05 20–36 �1.351 1.073

Phoneme deletion 10.48 4.54 00–16 �.606 �.865

Syllable deletion 8.25 3.99 00–15 .001 �1.033

Segmenting 13.31 3.8 1–16 �1.983 2.459

Blending 10.18 3.64 1–16 �.755 .151

Table 2

Correlation coefficients between all different measures.

Bel Seg PD SD PI RAN L RAN O RAN N RAN C NWR FDS NWD IQ

Bel 1

Seg .79** 1

PD .62** .72** 1

SD .49** .52** .66** 1

PI .70** .72** .70** .66** 1

RAN L .32* .30* .54** .40** .43** 1

RAN O .26* .18 .34** .30* .28 .51** 1

RAN N .33* .32 .53** .45** .45** .94** .54** 1

RAN C .075 .10 .30* .17 .22 .76** .47** .80** 1

NWR .64** .53** .45** .56** .59** .33** .42** .36** .11 1

FDS .52** .67** .50** .58** .50** .28* .48** .34** .13 .60** 1

NWD .56** .64** .66** .61** .58** .53** .47** .52** .35** .55** .56** 1

IQ .30* .33* .24** .44** .55** .30* .16 .29* .063 .35** .30* .31* 1

Bel: blending; Seg: segmenting; PD: phoneme deletion; SD: syllable deletion; PI: phoneme identification; RANL: RAN letter; RANC: RAN color; RANO: RAN

object; RANN: RAN number; FDS: forward digit span; NWR: non word repetition; NWD: non word decoding.

* Significant at .05 level.

** Significant at .001 level.

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were strongly correlated with each other (r were ranging from .52 to .72, p < .001) with an internal consistency (Cronbach’salpha) of .89. Correlation coefficients between four items of rapid automated naming (RAN letter, RAN objects, RAN colors,and RAN digits) were highly significant ranging from .47 to .94, p < .001, and the internal consistency between the items was.87. Finally, the two measures of phonological short-term memory (non word repetition task and forward digit span) weresignificantly correlated with each other with a correlation coefficient of .60, p < .001. Hence, scores on the related tasks wereaveraged to yield (a) a composite measure of phonological awareness (CPA), (b) a composite measure of rapid automatednaming (CRAN), and (c) a composite measure of phonological memory (CPM). Means and standard deviations of thecomposite scores, non word decoding scores (NWD), and IQ scores accompanied by their correlation coefficients weredisplayed in Table 3.

As Table 3 shows, there were significant inter-correlations between all three composite measures of phonologicalprocessing skills(r ranged from .38 to .70, p < .001). Moreover, the three composite measures were significantly correlatedwith IQ(r ranged from .32 to .72, p < .05, p < .001). On the other hand, non word decoding ability was significantly correlatedwith IQ (r = .32, p < .05), phonological awareness (r = .72, p < .001), phonological memory (r = .70, p < .001), and rapidautomated naming (r = .54, p < .001.

In order to get more information about the unique contribution of each phonological skill to non word decoding ability,six series of hierarchical regression analysis were conducted. The major focus of these analyses was to examine carefully theindependence of each phonological skill to predict the non word decoding ability after the effect of IQ and two otherphonological skills were controlled. For this purpose, in each series of analyses, after entering IQ at step 1, different orders ofpredictors were entered in following steps. For all series of regression analyses IQ was entered in the first step because it isargued that learning to decode is an explicit task that relies primarily on general cognitive recourses especially in peoplewith sub-normal intelligence (Levy, 2011). Table 4 shows the different steps of the hierarchical multiple regression analysesto predict decoding ability after entering IQ in the first step.

Table 3

Mean, standard deviation, and inter-correlation of IQ, non-word decoding, and the three composite measures of phonological processing skills.

Mean SD NWD CPA CPM CRAN IQ

NWD 18.72 8.02 1

CPA 15 3.30 .72** 1

CPM 8.14 1.93 .61** .70** 1

CRAN 83.54 21.17 .54** .46** .38** 1

IQ 68.05 7.30 .32* .49** .37** .26* 1

NWD, non word decoding; CPA, composite measure of phonological awareness; CPM, composite measure of phonological memory; CRAN, composite

measure of rapid automated naming.

* Significant at .05 level

** Significant at .001 level.

Table 4

Multiple regression analyses depicting the relationships between IQ, phonological awareness, short-term memory, rapid automated naming, and decoding

ability.

Step Variable entered R R squared change Significant

1 IQ .317 .100 *

First series

2 Phonological awareness .721 .420 **

3 Phonological memory .736 .022 ns

4 Rapid automated naming .769 .050 *

Second series

2 Phonological awareness .721 .420 **

3 Rapid automated naming .759 .056 *

4 Short-term memory .769 .016 ns

Third series

2 Short-term memory .618 .281 **

3 Phonological awareness .736 .16 **

4 Rapid automated naming .769 .050 *

Forth series

2 Short-term memory .618 .281 **

3 Rapid automated naming .696 .102 *

4 Phonological awareness .769 .107 **

Fifth series

2 Rapid automated naming .570 .224 **

3 Phonological awareness .759 .251 **

4 Short-term memory .769 .016 ns

Sixth series

2 Rapid automated naming .570 .224 **

3 Short-term memory .696 .16 **

4 Phonological awareness .769 .107 **

* Significant at .05 level.

** Significant at .001 level, ns no significant.

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In all series of regression analyses entering IQ at step 1 accounted for 10% of the variance in decoding ability (R2

change = .10, p < .05). Controlling the effect of IQ in the step 1, in six series of hierarchical regression analyses, differentorders of other predictors were entered in following steps.

In the first and second series of regression analyses, phonological awareness entered at the step 2 resulted in a significantchange in the variance of decoding ability (R2 change = .42, p < .001). In the first series, entering phonological memory at step3 produced no significant change in the variance of decoding ability (R2 change = .022, p > .05). However, entering rapidautomated naming at step 4 produced significant change (R2 change = .056, p < .05). In the second series of analyses, enteringrapid automated naming at step 3 produced a significant change in the variance of decoding ability (R2 change = .050,p < .05). Nevertheless, there was no significant change in the variance after entering short-term memory at step 4(R2 change = .016, p > .05).

In the third and forth series of regression analyses, after entering IQ at step 1, short-term memory entered at step 2resulted in a significant change in the variance of decoding ability (R2 change = .028, p < .05). In the third series, furthersignificant changes were produced after entering phonological awareness at step 3 (R2 change = .16, p < .001), and rapidautomated naming at step 4 (R2 change = .016, p < .05). The results of the forth series of regression analyses also showedsignificant changes in the variance of decoding ability after entering rapid automated naming at step 3 (R2 change = .102,p < .05) and phonological awareness at step 4 (R2 change = .107, p < .001).

In the fifth and sixth series of regression analyses, rapid automated naming entered at step 2 resulted in significantchange in the variance of decoding ability (R2 change = .224, p < .001). In the fifth series, phonological awareness entered atstep 3 produced a significant change in the variance of decoding ability (R2 change = .251, p < .001). Phonological memoryentered at step 4, however, was unable to cause any significant additional change (R2 change = .016, p > .05). In the sixth

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series of analyses, short-term memory entered at step 3, and phonological awareness entered at step 4 resulting insignificant changes in the variance of decoding ability. R square changes were.160, p < .001 for short-term memory, and .107,p < .001 for phonological awareness.

In summary, the results of correlation analyses (Table 3) revealed that the three inter related phonologicalprocessing skills (phonological awareness, short-term memory, and rapid automated naming) were significantlycorrelated with both IQ and decoding ability. Moreover, the results of six series of multiple regression analyses (Table 4)showed that both phonological awareness and rapid automated naming did account for significant unique contributionto decoding ability once the three other variables were entered. Short-term memory did account for a significant uniquevariance only when it was entered before phonological awareness. It means phonological short-term memory had nounique significant contribution when the effect of phonological awareness was controlled. However, entering rapidautomated naming before phonological memory did not significantly change the amount of phonological memorycontribution.

6. Discussion

It has been suggested that phonological awareness is prerequisite of reading ability (Wagner & Torgesen, 1987).Different measures of phonological awareness have been identified as strong correlates of reading decoding skills in bothtypically developing and participants with intellectual disability (Conners et al., 2001; Saunders & DeFulio, 2007; Wiseet al., 2010). In the current study, the correlation matrix also demonstrated a same pattern among participants withintellectual disability. It showed that the composite measure of phonological awareness, including segmenting, blending,phoneme identification, and phoneme and syllable deletion, was significantly linked to non-word decoding ability.Moreover, the regression analyses indicated that phonological awareness significantly contributed to decoding abilityafter controlling for IQ, phonological memory, and rapid automated naming. The findings supported our first hypothesisand, in agreement with other studies concerning both participants with and without intellectual disability, approved theidea that phonological awareness is requirement for reading decoding ability independent from other phonologicalprocessing skills and IQ.

Significant correlations between measures of phonological short-term memory and reading decoding ability have beenreported by both studies involving typically developing participants(Gathercole & Baddeley, 1993; Gathercole et al., 1991;Wagner et al., 1997), and research concerning participants with intellectual disability (Conners et al., 2001; Henry &Winfield, 2010). Consistent with these studies, our correlation matrix also revealed that phonological short-term memorymeasured by non word repletion task, and forward digit span is strongly associated with decoding ability. Furthermore, ourmultiple regression analysis indicated that phonological short-term-memory significantly contributed to decoding abilityafter the variances explained by IQ and rapid automated naming were accounted for. Nevertheless, after controlling forphonological awareness, phonological memory had no significant contribution to decoding ability. Hence, the findings didnot entirely support our second hypothesis. On the contrary, the results provided evidence to support the proposition thatverbal information maintained in short-term memory depends very directly upon the availability of underlyingphonological awareness (Muter & Snowling, 1998; Ramus et al., 2003; Wagner et al., 1997).

At a theoretical level, recent short-term memory models have distinguished between two types of informationmaintained in verbal short-term memory: order information (i.e., the sequential order in which the items are presented) anditem information (i.e., the phonological, lexical, and semantic characteristics of item). These two types of information aretypically confounded in regular verbal short-term memory tasks. However, some authors have suggested that distinctcognitive processes underlies memory for item and order information (Henson, Hartley, Burgess, Hitch, & Flude, 2003;Leclercq & Majerus, 2010; Majerus, Poncelet, Elsen, & Van der Linden, 2006). In the light of this theoretical development,Martinez Perez, Majerus, and Poncelet (2012) recently tried to determine to what extent that the item and order ofinformation are involved in the acquisition of the decoding process in typically developing participants. The researchersfound that order information but not item information independently predict reading decoding after controlling the effect ofphonological awareness, vocabulary and non verbal intelligence. Therefore, in regards to participants with intellectualdisability, further research is required to reexamine the complex mechanisms underlying decoding ability and phonologicalshort-term memory by the distinguishing item and order information stored in short-term memory.

Trying to examine the link between, RAN tasks and decoding ability in a sample of adults with intellectual disability,Saunders and DeFulio (2007) found significant moderate to large correlations between the two. Based on their correlationanalysis, the researchers concluded that both RAN and phonological awareness measures are strongly correlated withreading decoding ability. In agreement with Saunders and DeFulio (2007), the correlation matrix in our study also showed astrong relationship between RAN and decoding ability. Furthermore, our regression analysis indicated that RAN tasksuniquely contributed to decoding ability after the effects of the other variables including IQ, phonological awareness, andphonological short-term memory were accounted for. Hence, the findings supported our third hypothesis and confirmed theproposition that RAN task is a separate cognitive process related to decoding ability independence of phonologicalawareness and phonological short-term memory (Bowers, Steffy, & Tate, 1988; Bowers & Wolf, 1993; Cornwall, 1992; Felton& Brown, 1990; Manis et al., 1999). Furthermore, the results relatively support double deficits hypothesis (Wolf & Bowers,1999) which suppose that poor phonological awareness and slow rapid automated naming are two distinct sources ofreading impairments.

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7. Conclusion

The present study examined the contributions of the three well known interrelated aspects of phonological processing toreading decoding ability in participants with intellectual disability of unspecified origin. The results of the study aregenerally in line with previous research suggesting that the three aspects of phonological processing (phonologicalawareness, phonological short-term memory, and rapid automated naming) are closely related to decoding ability.Furthermore, consistent with some findings from studies involving typically developing participants, the results support thepreposition that both phonological awareness and rapid automated naming are two distinct sources of variance in decodingability, but phonological short-term memory is contributed to decoding ability under the realm of phonological awareness.

The study extended our knowledge of the association between the phonological processing skills and readingperformance in people with intellectual disability of unspecified origins. However, a limitation of the study was focusing ononly one aspect of reading performance known as non-word decoding ability. Further research is recommended to study thecontributions of phonological processing skills to other reading aspects such as reading accuracy, reading speed, and readingcomprehension. Another limitation of the current study was that the subjects who participated were 15–23 years oldadolescent or young males attending a single-sex special school. Further research is suggested to consider involving bothmale and female in different age ranges. Moreover, since the current study administered two common general measures ofphonological short-term memory, as previously mentioned, supplementary research is required to distinguish between theitem and order information stored in phonological short-term memory and reexamine their distinct contribution to readingperformance after controlling for phonological awareness and IQ in participants with intellectual disability.

Acknowledgment

The authors would like to thank Mr. Mansoor Mahmoodi, the manager of especial school for intellectually disabledstudents, for the support and facilitation during the data collection.

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