International Journal of Pediatric Otorhinolaryngology 74 (2010) 594–600

Auditory and cognitive abilities of children suspected of auditory processingdisorder (APD)

Stuart Rosen a,*, Mazal Cohen b, Iyngaran Vanniasegaram c

a UCL Speech, Hearing and Phonetic Sciences, 2 Wakefield Street, London WC1N 1PF, England, United Kingdomb Human Communication and Deafness, School of Psychological Sciences, The University of Manchester, Manchester, England, United Kingdomc Department of Audiological Medicine, St Georges Hospital, Hornchurch, Essex, England, United Kingdom

A R T I C L E I N F O

Article history:

Received 20 August 2009

Received in revised form 19 February 2010

Accepted 22 February 2010

Available online 26 March 2010

Keywords:

Auditory processing disorder (APD)

CAPD

Children

A B S T R A C T

Objective: Auditory processing disorder (APD) is typically characterised by difficulties in ‘listening’,

particularly to speech in a noisy environment, despite normal peripheral function. In school-age

children, APD has attracted considerable interest because of suspicions that it may lead to learning

difficulties, especially affecting language and literacy. Here, we evaluated auditory and cognitive abilities

in a group of children referred for an auditory evaluation on the grounds of a suspected auditory

processing disorder (susAPD), and in age-matched children who were typically developing, in order to

determine the extent to which any deficits in cognitive abilities could be related to auditory deficits.

Methods: A battery of auditory and cognitive tests was applied to 20 susAPD school-age children, all

reported as having listening/hearing problems but performing within normal limits for standard

audiometric assessments. Also tested was a group of 28 age-matched controls. The auditory tasks

consisted of two simple same/different discrimination tasks, one using speech, and one nonspeech. The

cognitive evaluation comprised a vocabulary test, a test of grammar and four non-verbal IQ measures.

Symptoms of Attention Deficit Hyperactivity Disorder (ADHD) were assessed in the susAPD group

through a standardised questionnaire.

Results: A significant proportion of susAPD children appeared to display genuine auditory deficits

evidenced by poor performance on at least one of the auditory tasks, although about 1/3 had no

detectable deficit. Children in the susAPD group scored consistently lower than the controls on cognitive

measures that were both verbal (vocabulary and grammar) and non-verbal. Strikingly, susAPD children

with relatively good auditory performance did not differ in cognitive ability from susAPD children with

poor auditory performance. Similarly, within-group correlations between auditory and cognitive

measures were weak or non-existent. Measures of ADHD did not correlate with any aspect of auditory or

cognitive performance.

Conclusions: Although children suspected of having APD do show, on average, poorer performance on a

number of auditory tasks, the presence or absence of an auditory deficit appears to have little impact on

the development of the verbal and non-verbal skills tested here.

� 2010 Elsevier Ireland Ltd. All rights reserved.

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International Journal of Pediatric Otorhinolaryngology

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1. Introduction

An auditory processing disorder (APD) is typically characterisedby difficulties in understanding speech, often in a noisy listeningenvironment, despite having a normal audiogram. In school-age

Abbreviations: APD, auditory processing disorder; susAPD, suspected auditory

processing disorder; CCMP, Consonant Cluster Minimal Pair; TDT, Tallal Dis-

crimination Task; BPVS, British Picture Vocabulary scale; TROG, Test for Reception

of Grammar; WISC, Wechsler Intelligence Scale for Children; ADHD, Attention

Deficit Hyperactivity Disorder; TOWRE, Test of Word Reading Efficiency.

* Corresponding author. Tel.: +44 20 7679 4077; fax: +44 20 7679 4238.

E-mail address: stuart@phon.ucl.ac.uk (S. Rosen).

0165-5876/$ – see front matter � 2010 Elsevier Ireland Ltd. All rights reserved.

doi:10.1016/j.ijporl.2010.02.021

children, APD has attracted considerable interest because ofsuspicions that it may lead to learning difficulties, especiallyaffecting language and literacy, and hence to poor schoolperformance.

The diagnosis of APD remains a clinical challenge. Poorperformance on APD tests does not provide sufficient evidenceof an APD. The assessment should enable the clinician to delineatethe cause of a listening problem and to separate auditory problemsfrom language learning or attention deficits which may present in asimilar way. Potential influences must be explored ranging fromperipheral auditory dysfunction, in particular a history of otitismedia with effusion in childhood associated with hearing loss [1],cross-modal sources such as attention [2], developmental factors

S. Rosen et al. / International Journal of Pediatric Otorhinolaryngology 74 (2010) 594–600 595

[3] and language-learning problems [4]. A better understanding ofthe sequelae of APD and implications for school performancewould provide a basis for selecting the appropriate remedial actionthat may be needed in each case.

In an earlier study, we investigated auditory performance in agroup of children suspected of having APD on the basis of a medicalreferral with concerns about difficulties in ‘listening’ [5]. A battery ofauditory tests was applied to these children and a control group, inthe hope of finding objective evidence of APD. As it turned out, two ofthe auditory tasks (one verbal and one non-verbal) statisticallyseparated the two groups. In the current study we hoped to gain afurther understanding of the characteristics of these children, byevaluating a subgroup on a number of measures of intelligence andlanguage ability. We have also evaluated the children for signs ofAttention Deficit and Hyperactivity Disorder (ADHD), because of theconcern that ADHD may be frequently co-morbid with, or evenindistinguishable from, APD [6,7]. A clinical history questionnairewas aimed at delineating the contribution of developmental factors,history of OME and events surrounding the birth on APD. Our goalwas to establish whether the auditory processing deficits we foundare associated with a more global cognitive deficit that may impacton the child’s educational achievements.

2. Methods

2.1. Subjects

48 children and adolescents, aged 6–14 years old, and attendingmainstream schools, participated in the main part of this study.Twenty were normal hearing children referred to the AudiologyClinic because a teacher or parent expressed concerns about theirhearing (13 males and 7 females; mean age 10.1 years � 2.1). Theremaining 28 were age-matched controls (15 males, 13 females;mean age 10.3 years � 2.9), also attending mainstream schools in thearea. The participants were all those willing to undergo further testingfrom a larger group (32 susAPD and 33 controls) who had undergone adetailed evaluation of their auditory function some months before [5].A clinical history questionnaire was completed for all children in aninterview with the child and his or her parent(s) or care giver. Fornone of the control children were concerns about hearing or listeningproblems expressed. No other criteria (except those relating to basicaudiometry, as described in the next section) were applied inparticipant selection.

2.2. Auditory assessments

In the earlier study, all 48 children had a basic audiometricevaluation comprising pure tone audiometry and tympanometry, toensure that middle ear function was intact and hearing thresholdswere in the normal range (mean hearing level at 0.5, 1, 2 and 4 kHz�20 dB HL). This was followed by four auditory processing tasks,chosen because they have previously been useful in the investiga-tion of APD, and/or in distinguishing language-impaired groups fromcontrols. Two of the tasks (simultaneous/backward masking anddichotic competing sentences) did not distinguish the controls fromthe susAPD group so will only be discussed in passing.

The tests that distinguished the two groups were the ConsonantCluster Minimal Pairs (CCMP) and Tallal Discrimination Task (TDT),both presented by computer in a forced choice, same/differentparadigm. The CCMP is a simple verbal discrimination task, similarto the popular SCAN test, consisting of 24 rhyming word pairswhich differed in their initial consonant cluster (e.g., fog/frog,smack/snack). The word pairs, with equal numbers of same anddifferent trials, were presented in a background of speech-shapednoise at a signal-to-noise ratio of �2.3 dB. The TDT is a non-verbaldiscrimination task which has been used extensively to test

auditory skills in children with language disorders [8]. The taskcomprised 20 short (50 ms) complex periodic tone pairs presentedwith a varying amount of time between the tones of each pair (0,10, 50, 100 and 400 ms). Again, equal numbers of same anddifferent trials were provided, with the two tones differing only infundamental frequency (100 Hz vs. 305 Hz). This task is clearlyaimed at testing a nonspeech ability, and thus has as much claim tobe an APD test as any.

Logistic regression was used to provide an age-corrected scorefor each listener on the two relevant auditory tasks. Using a modelof the dependence of performance on age, estimated from thecontrol data alone, a standardised residual was calculated for thescore of each listener. These residuals are independent of age, with(approximately) a mean of 0 and standard deviation of 1. They arethus directly comparable to z scores calculated from normallydistributed data. About 95% of the normal population should haveresiduals within a range of �1.96. A more detailed description of allthe tests, the results from them, and the statistical proceduresapplied, is provided elsewhere [5].

2.3. Assessments of cognitive skills, ADHD and clinical history

In addition to the auditory evaluation, all children participatingin this study had a psychometric evaluation of verbal and non-verbal cognitive abilities. The tests were chosen after consultationwith the chief Child Clinical Psychologist at St Georges’ Hospitaland carried out by a clinical psychologist. Those tests werecomprised of the British Picture Vocabulary scale (BPVS), the Testfor Reception of Grammar (TROG) and four non-verbal IQ measuresfrom the WISC (picture completion, coding, block design and objectassembly).

The assessment of ADHD was based on the ADHDT ques-tionnaire [9], demarcating the three components of ADHD:impulsivity, inattention and hyperactivity, plus an overall ADHDquotient. The questionnaire was completed in 17 of 20 children inthe susAPD group, in an interview with the child, his/her parent/carer and the Audiological Physician (author IV). Nine additionalchildren from the original susAPD group, but without cognitivescores, had scores available from the ADHDT questionnaire.

Given the centrality of literacy in the school curriculum, andclaims regarding the possible role of an APD in the genesis ofdyslexia, it would clearly be of interest to evaluate reading.Unfortunately, this was not part of our original design, but once thestudy was over, we were able to gather preliminary data over thetelephone from eight controls and seven children from the susAPDgroup using the Test of Word Reading Efficiency (TOWRE, [10]). Anadditional three children from the larger susAPD group (withoutother cognitive tests) were also tested, and these values used whenpossible.

Finally, a number of summary variables were collected from aclinical history questionnaire, documenting events surroundingthe birth, history of OME and hearing and listening difficulties in anattempt to uncover any relevant factors that may contribute to thedevelopment or presentation of APD.

3. Results

3.1. Auditory function

Fig. 1 displays a scatter plot of the standardised residuals of thetwo auditory discrimination tasks. The pattern of results is similarto that in the larger study. Performance in the susAPD group wassignificantly poorer for both measures (p < 0.001 and p < 0.03 forCCMP and TDT, respectively, in independent t-tests), with nocorrelation within groups between the two measures (p > 0.4). Ahigh proportion of susAPD children performed quite poorly (in the

Fig. 1. CCMP standardised residual z scores plotted against TDT z scores. Dashed

lines (z = �1.64) indicate scores below which only about 5% of the normal

population would be expected to score, whereas the solid lines (z = +1.64) indicate

scores which only 5% of the normal population would be expected to exceed. Note

the one susAPD data point obscured behind the control with the lowest CCMP score.

Fig. 2. Boxplots comparing the performance of the susAPD group to controls on the

two auditory and three cognitive tasks. The box indicates the inter-quartile range of

values obtained, with the median indicated by the solid horizontal line. The range of

measurements is shown by the whiskers except for points more than 1.5 box

lengths (indicated by ‘o’) or 3 box lengths (‘*’) from the upper or lower edge of the

box. Performance on all 5 measures differed significantly for the two groups

(p � 0.03 for TDT, p � 0.001 for CCMP, p � 0.01 for BPVS, p � 0.002 for non-verbal IQ

and p � 0.001 for TROG, with unequal variances assumed when required). Note that

the z scores for the auditory tasks have been transformed to IQ-like scores (mean of

100 and s.d. of 15).

S. Rosen et al. / International Journal of Pediatric Otorhinolaryngology 74 (2010) 594–600596

expected bottom 5% of the population) on one or both tasks (13/20 = 65%) whereas relatively few controls did (6/28 = 21%).The CCMP clearly provides the better separation between thetwo groups, with 9/20 (45%) susAPD listeners failing the test,but only 1/28 controls (about 4%, as would be expected). Strikingly,1/4 of the susAPD group fail both tasks, whereas none of thecontrols did. The difference in performance between the twogroups is even more clearly seen in the boxplots of Fig. 2, in whichthe distribution of scores in both auditory tasks is compared for thetwo groups.

3.2. Cognitive assessments

As Fig. 2 shows, the cognitive abilities of the susAPD group werealso worse than those of the controls, in all three main assessments(p � 0.01). The susAPD listeners also had lower standard scoresthan the controls on all four of the non-verbal IQ subtests. For oneof the tests (object assembly), the difference did not quite reachstatistical significance (p < 0.07) but was robust for the other threetests (p < 0.01).

Most of the difference between the two groups can beattributed to the control group performing at a substantiallyhigher level than the population average, with scores of 109–114on the three main assessments, nearly a full standard deviation(s.d.) higher than would be expected (p < 0.005 on all three one-sample t-tests). Of the three tests, the susAPD group performedworst on the TROG, with a score of 93.5, nearly 1/2 of a s.d. belownormal (p < 0.01). Vocabulary knowledge and non-verbal IQ were,however, within normal limits, at least on average (98.1 and 96.4,respectively, with p > 0.4).

The correlations among the cognitive tasks revealed aninteresting difference between the two groups, as shown in Table1. Both groups show a reasonably strong correlation between thetwo language measures, BPVS and TROG, but only for the susAPDgroup did non-verbal IQ correlate with any of the languagemeasures (TROG, in particular; however, the correlation with BPVSnarrowly misses significance at p = 0.062, and deleting one casewith the most extreme value of Cook’s d – a metric to identifyinfluential outliers in a regression [11] – makes the correlationhighly significant at p < 0.005). In spite of this difference in thepatterns of correlation, the two groups showed much the samedifference between their non-verbal IQ and language measures,

implying that the poorer cognitive performance by the susAPDgroup is not specific to language skills.

Some interesting patterns were found in the reading task, eventhought it was applied to relatively few children. Word and non-word reading scores were highly correlated over the entire 18children tested (r = 0.942) so we use a simple average of the two asan overall measure of reading ability. Just as for all the cognitivetests, the controls score significantly higher than expected (byabout 1 s.d. with a mean score of 116), and considerably higherthan the susAPD group. In fact, the difference between the twogroups is the highest of any of the cognitive measures, with thesusAPD group also showing significantly lower scores (mean = 90)than the expected population mean of 100 (p � 0.03). Although UKnorms are not yet available for this test, initial data suggest thatmedian scores in the UK population are somewhat higher than 100(written communications from D.V.M. Bishop, Oxford University,June 2005 and N. Harlaar, Institute of Psychiatry, King’s CollegeLondon, June 2005). Thus the susAPD group appear to be genuinelybelow average in reading, a fact which cannot only be attributed tobetter-than-average controls.

As regards correlations with other cognitive tests, the smallnumber of children tested means that even relatively largecorrelations do not reach statistical significance (e.g., r = 0.495between reading and BPVS in the susAPD group).

3.3. Relationships between auditory and cognitive assessments

Generally speaking, as Table 1 and Fig. 3 show, correlationsbetween cognitive measures and listening skills were weak or non-existent. Of 12 relevant within-group correlations (TDT/CCMP vs.non-verbal IQ/TROG/BPVS), only two Pearson correlations justreached significance (without correction for multiple compar-isons) at p < 0.05 (TDT vs. non-verbal IQ in the controls, and TROGvs. TDT in the susAPD group).

Neither of these correlations is very robust, as supported by thelack of significant correlations using the nonparametric Spear-man’s rho. Both appear to be carried solely by one or two listeners.

Table 1Pearson correlation coefficients for the three main cognitive assessments, and the

two measures of auditory function. Correlations significant at the 0.05 level in a

two-tailed test are marked with * (none were significant at p�0.01). Values for the

susAPD group are in bold italics in the lower left half of the table, while values for

the control group are in the upper right half of the table in a normal font.

nvIQ BPVS TROG TDT CCMP

nvIQ 0.087 0.230 0.391* 0.085

BPVS 0.425 0.447* 0.206 0.063

TROG 0.505* 0.469* 0.097 �0.147

TDT 0.038 0.102 0.455* 0.035

CCMP 0.025 �0.419 0.073 0.161

S. Rosen et al. / International Journal of Pediatric Otorhinolaryngology 74 (2010) 594–600 597

For the theoretically interesting correlation in the susAPD group,excising the single listener with the highest value of Cook’s d (andthe lowest TROG score) drops the variance accounted for from 20%to a non-significant 10% (p � 0.18). Excising the next most extremelistener (again the highest Cook’s d and lowest TROG) drops furtherthe variance accounted for to 2% (p > 0.5). Similarly for TDT vs.non-verbal IQ in the controls: excising the single listener with thehighest value of Cook’s d (and the lowest TDT score) drops thevariance accounted for from 15% to a non-significant 8% (p � 0.18).

In another exploration of the extent to which poor listeningskills result in poor cognitive ability, we defined two subgroupswithin each group according to auditory performance asmeasured by the mean z score on the CCMP and TDT tests. Inorder to get a reasonable balance of numbers in the twosubgroups, we used a cut-off of z = �1 in this instance. Thuslisteners with mean z scores one standard deviation or morebelow the control mean were considered to be ‘impaired’, whereasthe rest were considered ‘unimpaired’. As shown in Fig. 4, therewas little difference in the cognitive ability of the two subgroupsboth for control and susAPD groups (p > 0.1 in independent t-tests). Similarly, the difference between non-verbal IQ andlanguage measures (not shown in the figure) did not differ forimpaired and unimpaired listeners.

Although it seemed unlikely that performance in the twoauditory tasks that did not distinguish the susAPD group from the

Fig. 3. Scatter-plot matrix showing the relationships among the 3 cognitive and 2

main auditory assessments. Each subplot in the matrix is a simple scatter plot,

whose x-axis variable is given by the column, and y-axis variable is given by the

row. For example, the scatter plot in the extreme upper right depicts non-verbal IQ

as a function of performance on the consonant cluster task. The scatter plot on the

extreme lower left depicts the same relationship, but with x and y variables

exchanged. Best-fit straight lines are shown separately for the two groups of

children.

controls could be useful in predicting the different cognitiveabilities that do distinguish the two groups, we also assessed asubgrouping based on all of the auditory tasks applied. In a parallelanalysis to the one described above, we calculated the mean z scoreacross the 4 auditory tests (with a single z-score for meanperformance in the simultaneous and backward masking tasks),and classified listeners as impaired or not using a cut-off of z = �1.The results were very similar to those shown in Fig. 4, with nosignificant differences in any of the 3 cognitive tests betweenimpaired and unimpaired listeners within each listener group.

On the reading tasks, there was a trend for listeners withimpaired auditory performance to score lower than listeners withnormal auditory performance, but again the numbers in eachgroup are too small to allow much statistical power. No convincingwithin-group correlations were found between reading abilitiesand the two auditory tasks. In fact, performance on the consonantdiscrimination task was negatively correlated with reading in bothgroups, and nearly reached significance for the control group(r = �0.63, p = 0.092). All other correlations had p > 0.2. As sparseas these data are, they do show that reading itself appears to poseproblems for the susAPD group, although they provide littlecredence for the notion that auditory skills are an important factorin literacy.

Fig. 4. Boxplots comparing the performance, within susAPD and control groups, of

impaired and unimpaired listeners on three measures of cognitive ability. None of

the pairs of clustered boxplots are significantly different from one another.

S. Rosen et al. / International Journal of Pediatric Otorhinolaryngology 74 (2010) 594–600598

3.4. Relationships between ADHD and other assessments

There is much concern about the extent to which ADHD co-occurs with, or is independent of, APD, because the lack ofattention which characterises ADHD can, on its own, readilyproduce symptoms suggestive of APD (i.e., through poor perfor-mance on listening tasks [12]). Therefore, we investigated therelationships among the various measures of ADHD and perfor-mance on the listening and cognitive tasks.

For the 26 susAPD children who had the ADHD assessment, all 3measures (impulsivity, inattention and hyperactivity) correlatedhighly with one another (p < 0.001, with correlation coefficientsaround 0.8). The overall ADHD quotient covered a reasonable range(68–113, with a mean of 88.7 and s.d. of 12.7). However, there wasno correlation between any of the ADHD measures (including theADHD quotient) and performance on either of the two listeningtasks (p > 0.5). Listeners were also split into two subgroupsdepending upon the mean standardised residual value of the twoauditory scores mentioned above. As before, scores less than �1were designated as ‘impaired’ (16 listeners) while those >�1 weredesignated ‘unimpaired’ (10 listeners). None of the ADHDmeasures differed between these two subgroups (p > 0.15 inindependent t-tests). Finally, listeners were grouped into twoapproximately equal-sized sets based on their overall ADHD scorebut neither of the auditory measures differed between these twogroups (p > 0.4).

For the 17 children with the appropriate measures, correlationswere also examined between ADHD scores and cognitive skills(BPVS, TROG and non-verbal IQ). Again, no measure of ADHDcorrelated significantly with any of the three cognitive measures(p > 0.1). Furthermore, children with relatively high scores forADHD did not differ on any cognitive measure from children withrelatively low scores for ADHD. We did not investigate relation-ships between reading abilities and ADHD scores as only 6 childrenwere tested on both measures.

3.5. Analyses of clinical histories

The clinical history, although relatively informal, did reveal somenotable associations with the incidence of many problems varyingsignificantly between the susAPD and control groups (summarisedin Table 2). Strikingly, although there was a higher incidence ofreported problems in the susAPD children with impaired auditoryfunction than the susAPD children who were unimpaired (z � �1 vs.z > �1 on the mean residual of the CCMP and TDT tests), none ofthese differences were statistically significant.

As would be expected, the susAPD group reported a muchhigher incidence of auditory problems than controls (after all, aconcern about hearing/listening was the cause for referral), withthe most frequently reported being that of hearing the television,and speech in a noisy background (both reported by over half of thesusAPD group and few controls). Neither of these features differsbetween our so-called ‘impaired’ and ‘unimpaired’ listeners.

Table 2Incidence of problems noted from a clinical history and questionnaire, across groups defin

tasks (unimpaired vs. impaired). The numbers in the table indicate the percentage of ch

areas. The columns labelled ‘p’ indicate the degree to which the incidence in the two grou

asterisks indicates p<0.05, p<0.005 and p<0.001, respectively. A blank indicates p>

Controls (of 23) susAPD (of 20)

Any auditory problem 17 90

Speech-in-noise 9 55

Listening to the television 9 60

Middle ear disease 9 30

Attention/concentration 0 60

Literacy 17 70

Spoken language 0 25

There was a tendency for some association of a history of OMEwith susAPD and impaired hearing, but neither was statisticallysignificant. The ability to attend or concentrate was noted as aproblem for significantly more of the susAPD listeners, but againdid not differ significantly for impaired and unimpaired listeners.

When listeners were asked about what school subjects wereparticular weaknesses, 70% of the susAPD group reported literacy

as a particular problem but only 17% of controls. Yet again, listenerswith an objectively identified auditory impairment do not differ inthis regard from those without. In a similar manner, 25% of susAPDlisteners, but no controls, report some difficulty with spokenlanguage (e.g., delayed speech, using the wrong word, mumbling,etc.). Interestingly, the difference in incidence of spoken languageproblems was the only feature even to approach statisticalsignificance for groups defined by auditory task performance.

4. Discussion

Over half of normal hearing children who were referred to theclinic because of hearing/listening difficulties were found to havean auditory impairment. The proportion was significantly higherthan the incidence of poor listening skills found in the controls.Furthermore, the test which assessed the ability to discriminatespeech-in-noise (a word discrimination task, CCMP), the problemwhich is often said to characterise APD, distinguished the susAPDgroup from the controls best. Because our chosen auditory testswere employed in a much larger battery that precluded any testtaking too much time, each of the tests may be relatively weak indetecting impaired auditory performance. After all, there wereonly 20 trials in the nonspeech task, and 28 in the speech one, inboth of which chance performance was 50%. In view of the limitedtest battery and the phenotypic heterogeneity of APD, it issurprising that the tests worked as well as they did in separatingout the children in the susAPD group from the controls. In futurework, it would certainly make sense to increase the number ofitems in both of these tests in order to make them more sensitiveassays of ability, and to determine the extent to which theymeasure genuinely different processes.

One of the key challenges for audiologists is to distinguish anauditory problem from a language one, as both may lead to similarresults. The cognitive evaluation employed in this study comprisedverbal and non-verbal tests, and our general approach was basedon investigating correlations between skills primarily within asopposed to between groups. The underlying premise was that ifauditory deficits are the prime cause of some cognitive deficit, forexample in language, we should expect strong correlationsbetween measures of auditory processing and language skills,not only across the entire population, but within language-impaired groups as well [13]. Insofar as correlations only holdacross groups, there are two obvious possibilities. One is that theauditory deficit is causal in some cases only, with different causesresponsible for others. Alternatively, it may be that the auditorydeficit is associated with the language deficit rather than being

ed by clinical status (controls vs. susAPD) or mean performance in the two auditory

ildren in each group who were reported to have a problem in each of the particular

ps is statistically different, as determined by Fisher’s exact test. One, two and three

0.1.

p Unimpaired (of 27) Impaired (of 16) p

*** 41 69

** 26 37

*** 26 44

11 31

*** 22 37

*** 41 44

* 4 25 0.06

S. Rosen et al. / International Journal of Pediatric Otorhinolaryngology 74 (2010) 594–600 599

causal (see [14] for a similar argument regarding dyslexia andsensori-motor impairments). The analysis showed a completedissociation between auditory and cognitive tests: performance onthe word discrimination task did not correlate with either of twoexplicit measures of language ability (nor with reading), so it doesnot appear to be likely that impaired speech perceptualperformance led to impaired language. (But see [15] for a claimthat such relationships should be strong.)

The high standardised scores of the control group in the currentstudy raise reservations about the degree to which the children init really are appropriate controls. Insofar as auditory skills appearto be unrelated to measures of non-verbal IQ and languagefunction, the control group is probably a reasonable comparison.But when it comes to comparisons on standard cognitive measures,the controls are clearly inappropriate. Consider, for example,performance on the BPVS measure of vocabulary. The susAPDgroup mean fell well within normal bounds (at around 98) yet issignificantly different from the controls with a mean just above109. Such problems with control groups are far from rare, and areoften attributed to the fact that controls cannot be randomlychosen from the population at large. It appears likely that thesimple requirement of obtaining a signed permission form from aparent may be sufficient to secure an unrepresentative population.It is therefore impossible to know how to interpret the relativelylow cognitive scores in the susAPD group except throughcomparisons within the susAPD group itself (see [16] anddiscussion below).

Interestingly, the susAPD group appear to be genuinely belowaverage in reading, which is consistent with questionnaireresponses identifying literacy as a particular problem. Alongsideliteracy, the clinical questionnaires identified additional commonfactors and/or symptoms which were found in the susAPD group.These include difficulty understanding speech in noisy back-grounds, difficulty following the TV, history of OME, difficultieswith attention and with spoken language. The exact nature of theseassociations was not elucidated here due to small numbers and tothe informal nature of the clinical histories. Although nocorrelation was found between these factors and impairedlistening or cognitive function, they contribute to the emergenceof a clinical profile of a child referred to the clinic because ofsuspected APD.

There was no correlation between auditory scores and thevarious ADHD measures obtained from the ADHD questionnaire,with the implication that poor performance on the auditory testsused in this study does not simply reflect inattention and/orhyperactivity, at least as measured by the particular questionnaireused. It is important to highlight that some effort was made tominimise the effects of inattention and/or hyperactivity on theperformance on the auditory tasks by allowing participantsfrequent breaks.

Similar conclusions to ours (although not concerning theextensive cognitive measures we assessed) can be extracted froma recent retrospective study from case notes of children referred forconcerns about hearing [16]. In this group of children, 32 werediagnosed with APD (on the basis of a number of fairly typicalclinically available tests like the SCAN), whereas 57 were considerednot to have APD. However, no aetiological factor (e.g., history of otitismedia) nor incidence of reported symptoms distinguished the twogroups, just as in our within-group susAPD comparison.

In summary, it is clear that the children in our study referredwith a suspicion of APD, appear, at least on the group level, to havebeen referred with reason. Their listening abilities do seem to beimpaired, on average, and it is natural enough to suppose thiswould have an impact on academic performance were the deficitsevere enough. On the other hand, we found no relationshipbetween the observed degree of auditory impairment and the

measures of cognitive skill in the susAPD group, and a similarindependence of literacy and speech perceptual skills has beenconvincingly demonstrated in a large study of children enteringschool [17]. It may well be desirable to remediate an auditorydeficit because, for example, classroom behaviour might improve,but without the expectation that improved auditory performancewill necessarily result in improved cognitive abilities and/oracademic performance [18].

However, impaired listening may not be the only reason forreferral. Lower then average cognitive scores in the susAPD groupmay be leading to impaired academic performance, which in itself,with or without hard evidence of a listening problem, may causeconcern. It is interesting to note that, even though the controls maybe a poor comparison sample, the TROG scores of the susAPD groupare significantly lower than the expected population mean, andthere are indications that their literacy skills are relatively poortoo. Furthermore, 4 of the susAPD children had non-verbal IQscores at 76 or below, which puts them in the bottom 5% of thepopulation (no control listener scored below 80). Referrals in thesusAPD group may thus result from a variety of reasons, only sometruly auditory.

For the clinician, APD remains something of a minefield. Onething is quite clear. Children referred for suspected APD need tohave a reasonably thorough psychometric work-up. Of the foursusAPD children who had low language scores (<85 on the TROG),only one had seen a speech and language therapist, some 9 yearsbefore at age two, which ended in a diagnosis of ‘normaldevelopment’. One of the others had seen an educationalpsychologist recently. Even if it is not clear what remedial coursechildren with APD should be directed to, a referral to professionalswith more established remedial plans certainly seems in orderwhen a problem is clearly identified through whatever route.

Conflict of interest statement

None declared.

Acknowledgements

We are very grateful to: Tatiyana Tairi and Saras Swaminathanwho undertook the cognitive assessments; the Head Teachers andchildren of Harold Wood Primary School, King’s Wood School andWoodlands Preparatory School in Essex for their willingness toparticipate in the study; Andrew Faulkner for many helpfulcomments on the manuscript; Dorothy Bishop and Nicole Harlaarfor providing unpublished information about the TOWRE. Thisresearch was partially funded by Barking and Dagenham PrimaryCare Trust.

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