Understanding neurodevelopmental conditions : What parents ... · during the critical period, taking advantage of the brain’s plasticity to set development on the right course

ArmandoBertone,[email protected]

PerceptualNeuroscienceLaboratory(PNLab.ca)forAutismandDevelopment

School/AppliedChildPsychology&HumanDevelopmemtDepartmentofEducationalandCounsellingPsychology

Understandingneurodevelopmentalconditions:

Whatparentsneedtoknow

2

duringdevelopment…

neuraltubebecomesbrainandspinalcord(CNS)

100billionneurons synapseatdifferentlocationsinbrainandSC

eachmakeconnectionsto≈1000targetcells

atbirth,thehumanbrain≈350grams.• year1≈1000grams.• adultbrain≈1200-1400grams.

different,sequential processes duringcorticaldevelopment :• cellulardifferentiation• axonalgrowth• myelinization• synaptogenesis - formation ofsynapsesbetween

neurons

neurodevelopment– very complex,dynamicprocess...

3

structureofthebrain:productofsculpting asmuchasgrowth

Synapticexuberanceandpruning- afterbirth,synapticdensityincreasesdramaticallybutthisalsodiffersbyregion

• experienceexpectant dev't :pre-determined

growth(typicalcriticalperiods)• experiencedependent dev't :experience as

sculptor

criticalperiodsofdevelopment - startingwithvision,hearingandtouch,periodsforlanguageandhighercognitionoccurringlater• associatedwithcognitionandbehaviour

stageofcorticaldevelopment:naturevsnurture

brain slams on ‘plasticity brakes’ — presumably as a way to protect the newly optimized brain circuits from disruption by further input.

Hensch separates these ‘brakes’ into two categories — structural and functional. The first comprises physical structures such as the perineuronal net (PNN), a complex of macro-molecules that attach to PV interneurons around the time that a critical period ends, and that seem to restrict the extent to which a neural circuit can change. Chemical break-down of the PNNs in adult rats makes their brains prone to being rewired6.

Functional brakes are chemical compounds such as Lynx1 — a molecule, identified by Hensch and his colleagues, that shifts the bal-ance of excitation and inhibition in the cortex by dampening the effect of the neurotrans-mitter acetylcholine. Experiments in mice show that the amount of Lynx1 in the brain increases at the end of the critical period, and its removal from adult brains, like degradation of the PNNs, seems to restore neural plasticity7.

Hensch says that what he finds particularly compelling about functional brakes is that they are relatively easy to release. One example of this is a behavioural intervention developed by Roger Li and Dennis Levi, optometrists at the University of California, Berkeley, for adults with amblyopia.

People develop amblyopia when problems such as cataracts or crossed eyes disrupt input to one of their eyes during early childhood, often leaving them without three-dimensional (3D) vision. The condition is considered untreatable once the critical period has ended. But when Li and Levi got people with amblyo-pia to play 40–80 hours of video games with their good eyes patched, most of them reported substantial improvements in visual function8. Describing one subject who was born with crossed eyes and had never seen the world in

depth, Li says: “Once she found out she was able to see some 3D, she immediately began to cry.”

Hensch suggests that playing video games releases some of the brain’s functional brakes. He notes that heightened attention, which often goes along with video-game playing, has been shown to increase the activity of acetyl-choline — a surge that would counteract the damping effect of Lynx1.

WINDOWS OF OPPORTUNITYResearchers have begun experimenting with drugs to reopen the critical period. Hensch and David Hunter, an ophthalmologist at Boston Children’s Hospital, received approval in May to begin a phase I clinical trial for treating amblyopia with a drug that increases the amount of acetylcholine in the brain.

A similar study9, published in 2010 and led by neuroscientist Michael Silver of the Uni-versity of California, Berkeley, found that when people with normal vision are given a drug that increases acetylcholine levels, they show greater improvements in visual acuity than people given a placebo. And a group led by Lamberto Maffei, a neurobiologist at the Scuola Normale Superiore in Pisa, Italy, has begun phase II clinical trials for amblyopia with selective serotonin re-uptake inhibi-tors, a class of drugs often used to treat depression.

Such research makes it easy to imagine pills or shots that could aid recovery from a severe brain injury, for example, or make it easier to learn a new language or forget a terrifying memory. Lifting plasticity brakes might even be useful in treating complex disorders such as autism, says Hensch. He points to the dif-ficulty children with autism have integrating input from multiple senses at once — when looking at a person’s facial expressions while

listening to them speak, for example. Such integration may require the critical periods for each sense to have occurred in a specific developmental sequence. “I think that autism is a good example of what can go wrong when these different sensory critical periods are mistimed,” he says — a view for which there is some experimental evidence10.

For now, however, when it comes to the neural basis of complex psychiatric conditions such as autism, the experimental evidence is limited. But if tests could be created to identify risk factors for some developmental disorders, says Hensch, physicians may one day be able to deploy biologically informed interventions during the critical period, taking advantage of the brain’s plasticity to set development on the right course.

But no one in the field is suggesting that the brain’s critical periods should be tampered with casually. “When you reopen a critical period, there is, of course, always the possibility of a worse outcome,” says Alvaro Pascual-Leone, a neurologist at Harvard Medical School, point-ing out that disorders such as amblyopia occur because of harmful input during the original critical period.

And structural brakes are considerably more difficult to release than functional ones. In 2009, for example, researchers showed that chemically destroying PNNs in mice makes it easier to erase their fear memories, suggesting a potential treatment for conditions such as post-traumatic stress disorder11. But to do this in humans could cause widespread brain damage that would outweigh any benefits. After all, says Hensch, the mechanisms that the brain uses to shut down critical periods are very complex, and they require a substantial amount of energy, “which gives us a good sense that they’ve evolved for a reason”.

Stryker sounds a further note of caution. “I think it’s a romantic notion that you can replicate the critical period later in life,” he says. “Some things just don’t unhappen.” ■

Jon Bardin is a freelance writer based in New York.

1. Wiesel, T. N. & Hubel, D. H. J. Neurophysiol. 26, 1003–1017 (1963).

2. Reiter, H. O. & Stryker, M. P. Proc. Natl Acad. Sci. USA 85, 3623–3627 (1988).

3. Hensch, T. K. et al. Science 282, 1504–1508 (1998).

4. Sugiyama, S. et al. Cell 134, 508–520 (2008).5. Southwell, D. G., Froemke, R. C., Alvarez-Buylla,

A., Stryker, M. P. & Gandhi, S. P. Science 327, 1145–1148 (2010).

6. Pizzorusso, T. et al. Science 298, 1248–1251 (2002).

7. Morishita, H., Miwa, J. M., Heintz, N. & Hensch, T. K. Science 330, 1238–1240 (2010).

8. Li, R. W., Ngo, C., Nguyen, J. & Levi, D. M. PLoS Biol. 9, e1001135 (2011).

9. Rokem, A. & Silver, M. A. Curr. Biol. 20, 1723–1238 (2010).

10. Rubenstein, J. L. R. & Merzenich, M. M. Genes Brain Behav. 2, 255–267 (2003).

11. Gogolla, N., Caroni, P., Lüthi, A. & Herry, C. Science 325, 1258–1261 (2009).

OPEN AND SHUTThe human brain’s sensitivity to learning seems to crest in three broad waves. The critical periods for cortical regions devoted to vision and other senses (red) open in infancy, then close tightly. Those for language (yellow) and higher cognition (purple) open later, and never close entirely. The successive waves allow a child to acquire increasingly complex skills (grey text).

HIGHER COGNITION

SYMBOLS AND IDEASVISIONHEARINGTOUCH

SOCIAL RELATIONSHIPSTALKING

READINGMATHEMATICSINQUIRY

THINKING STRATEGIESSHARED FOCUS

MAKING INFERENCES CRITICAL THINKINGREFLECTIVE THINKING

CONSIDERED RESPONSE

LANGUAGESENSES

Birth Infancy Childhood Adolescence

Sens

itivi

ty

SOU

RC

ES: T

. HEN

SCH

; MC

CAI

N, M

.N.,

MU

STAR

D, J

.F.,

& M

CC

UAI

G, K

. EAR

LY Y

EAR

S ST

UD

Y 3

CH

. 2 (M

ARG

ARET

& W

ALLA

CE

MC

CAI

N F

AMIL

Y FO

UN

DAT

ION

, 201

1).

2 6 | N A T U R E | V O L 4 8 7 | 5 J U L Y 2 0 1 2

FEATURENEWS

© 2012 Macmillan Publishers Limited. All rights reserved

Glasser et al 2015

• agroupofconditionswith onset inthedevelopmental period.

• typicallymanifestearlyindevelopment (beforethechildentersgradeschool)

• characterizedbydevelopmentaldeficitsthatproduceimpairments ofpersonal,social,academic,and/oroccupational functioning.

• challengesvaryfromtheveryspecific(i.e.,learningmath,difficultywithattention,etc.)tomoreglobal(i.e.,socialskillsorintelligence).

• frequentlyco-occur

• notaND whenachildistemporarilydelayedinoneormoremilestones,thencatchesuptopeersor"normal"range

WhatareNeurodevelopmentalDisorders(NDs)?

5

DiagnosticandStatisticalManualofMentalDisorders,FifthEdition(DSM-5) :thestandardclassificationandcodesofmentaldisordersusedbymentalhealthprofessionalsintheUnitedStates.

IntellectualDisabilities

CommunicationDisorders

AutismSpectrumDisorder

Attention-Deficit/HyperactivityDisorder

SpecificLearningDisorder

MotorDisorders

OtherNeurodevelopmentalDisorders

DSM5:NeurodevelopmentalDisorders(NDs)

6

• oftendefinedinterms of

behaviour,notcause

• nosingle biologicalcause

• male preponderance inmostcases

• tendtorun in families

• co-morbidityistheoftenprevalent...

• gene xenvironment

interactions

Commoncharacteristicsof(NDs)

7

• NDswithknown prenatalcauseofgeneticoracquired origin:DownSyndrome,fetalalcoholsyndrome,etc.

• NDswhereatypicalneurodevelopmentisinferred :exactcauseiscomplexorevenunknown(mostofthem...)& definedintermsofbehaviour thatisobserved...

NeurodevelopmentalDisorders(NDs)

8

• Early assessment=Early intervention=best outcomes(criticalperiods)

• Itiseasierandlesscostlytoformstrongbraincircuitsduringtheearlyyearsthanitistointerveneor“fix”themlater=cortical plasticity ...

Earlyintervention

Pat Levitt (2009)

9

SpecificLearningDisorders

10

dyslexiainadultswasfirstnotedinthelatterhalfofthe19thcentury

developmentaldyslexiainchildrenwasfirstreportedin1896.

dyslexicpatients- seenbyophthalmologists,calledthedisorder“wordblindness.”

JamesHinshelwood,aScottishophthalmologist - dyslexicchildrenwereoftenexceptionally smart exceptfortheirinability toread

dyslexia(readingdisorder)Leonard Apt LectureThe Science of Reading and Dyslexia

Sally E. Shaywitz, MD, and Bennett A. Shaywitz, MD

I t is a great honor to present this lecture, which honorsthe extraordinary contributions to scholarship andteaching of Leonard Apt, MD a true renaissance man.

For more than four decades, Leonard Apt has contributedboth singular discoveries and a continuous stream of re-search findings that have significantly advanced ourknowledge in the field of pediatrics and pediatric ophthal-mology. In the words of Leonard Apt, “In academic med-icine, I have been free to question and investigate newtheories. Years from now, I’d like to be remembered as adoctor who never stopped asking ‘Why?’”

Dyslexia is characterized by an unexpected difficulty inreading in children and adults who otherwise possess theintelligence, motivation, and schooling considered neces-sary for accurate and fluent reading.2 Historically, dyslexiain adults was first noted in the latter half of the 19thcentury, and developmental dyslexia in children was firstreported in 1896. Patients with dyslexia were frequentlyseen by ophthalmologists, who called the disorder “wordblindness.” James Hinshelwood, a Scottish ophthalmolo-gist (Figure 1), who elaborated the disorder in children,noted that these children were often exceptionally smartexcept for their inability to read and proposed specialeducation programs as treatment.5

Recent epidemiological data indicate that, like hyper-tension and obesity, dyslexia fits a dimensional model. Inother words, within the population, reading ability andreading disability occur along a continuum, with readingdisability representing the lower tail of a normal distribu-tion of reading ability.6,7 Dyslexia is perhaps the mostcommon neurobehavioral disorder affecting children, withprevalence rates ranging from 5% to 10% in clinic- andschool-identified samples to 17.5% in unselected popula-tion-based samples.2 Previously, it was believed that dys-lexia affected boys primarily8; however, more recent dataindicate there is no sex predilection for dyslexia.9-11 Lon-gitudinal studies, both prospective12,13 and retrospec-tive,14-16 indicate that dyslexia is a persistent, chronic con-dition; it does not represent a transient “developmental

lag” (Figure 2). Over time, poor readers and good readerstend to maintain their relative positions along the spec-trum of reading ability.12

Dyslexia is both familial and heritable.17 Family historyis one of the most important risk factors, with 23% to 65%of children who have a parent with dyslexia reported toalso have the disorder.18 The prevalence rate among sib-lings of affected persons is approximately 40%, and amongparents of affected individuals ranges from 27% to 49%.17

This provides opportunities for early identification of af-fected siblings and often for delayed but helpful identifi-cation of affected adults. Linkage studies implicate loci onchromosomes 6 and 15,19,21 chromosome 1, and—mostrecently—on chromosome 223 for the transmission ofphonological awareness deficits and subsequent readingproblems. Whether the differences in the genetic locirepresent polygenic inheritance, different cognitive pathsto the same phenotype, or different types of dyslexia is notclear.

From the NICHD–Yale Center for the Study of Learning and Attention, New Haven, CT.Portions of this article were previously published in, and are similar to, other reviews by theauthors.1-4

Submitted March 11, 2002.Revisions accepted December 16, 2002.Reprint requests: Sally E. Shaywitz, MD, Department of Pediatrics, Yale University Schoolof Medicine, PO Box 333, New Haven, CT 06510-8064.Copyright © 2003 by the American Association for Pediatric Ophthalmology andStrabismus.1091-8531/2003/$35.00 ! 0doi:10.1016/S1091-8531(03)00002-8

FIG 1. James Hinshelwood, a pioneering Scottish ophthalmologistwho was the one of the first physicians to describe the clinicalpicture of dyslexia as well as to promise a coherent plan of man-agement.

Journal of AAPOS158 June 2003

11

DSM-IV(315.00)DiagnosticCriteria

SpecificLearningDisorder(SLD)

A. difficultylearning /usingacademicskills,asevidencedbypresenceofatleastoneoffollowingfor6months,despiteintervention..1. inaccurateorslowandeffortfulreading2. difficultyunderstandingmeanings ofwords3. difficultywspelling4. difficultieswwritten expression5. difficultiesmasteringnumber sense,number facts,orcalculations6. difficultieswmathematical reasoning

B.affected academic skills belowexpectedchron.age&causesiginterferencewacademicoroccupationalfunctioning(confirmedusingstandardizedcognitivetests).

C.learning difficulties - fullymanifestedwhendemandsforaffectedacademicskillsexceedindividual’s limited capacity(excessivelyheavy academic load)

D.learningdifficultiesnot betteraccounted forbyintellectual delay,visual/auditoryproblems,educational instruction,psychosocial adversity,etc.

specifyif:• withimpairment inreading (dyslexia),writtenexpression (dysgraphia)and/ormathematics

(dyscalculia)

SpecificLearningDisorder(SLD)(DSM-V)≈dyslexia

12

dyslexia accountsfor80%ofallcasesoflearningdisorder(aloneorincombwithdisordersinwrittenexpressionormathematics)

in2006,a“limitationrelatedtolearning”affected121,080childrenaged5to14,or3.2%ofallchildreninCanada (includesADHD)

60-80%ofindividualsdiagnosedwithreadingdisorderaremale• 2:1 to3:1moremales- genetics?

– isstrongly (54to75%)heritable,occurringinupto68%ofidenticaltwinsand50%ofindividualswhohaveaparent orsibling withdyslexia

• may,however,beconfounded withahigherincidenceofdisruptivebehaviorinmales (oftenaccompaniedbyADHD)

symptoms - inability todistinguish amongcommon letters ortoassociatecommonphonemes with letter symbols - mayoccurasearlyaskindergarten.

usualdiagnosisafter1st grade- but,maynotbeapparentuntilthe3rd,4th grade(orlater).

SLDwimpairmentinreading≈dyslexia

13

complaints centeraroundpoor schoolperformance.

generalontogeny - delay inspeaking,didnotlearnlettersbykindergarten,anddidnotbegintoreadby1st grade.

childprogressively falls behind

dysgraphia isoftenpresent - laboriousnotetaking

self-esteemisfrequentlyaffected(eveninadulthood)

negative test-takingexperiences

givensufficient time,individualswdyslexiascorewellontestsofreading comprehension.

SLDwimpairmentinreading(dyslexia):symptomology

ties (for age, intelligence, or level of education) in readingand (2) associated linguistic problems at the level of pho-nological processing. There is no one single test score thatis pathognomonic of dyslexia. As with any other medicaldiagnosis, the diagnosis of dyslexia should reflect athoughtful synthesis of all the clinical data available. Whatthe clinician is seeking is converging evidence of a phono-logically based reading disability as indicated by a disparitybetween the individual’s reading and phonological skills incontrast to his or her intellectual capabilities, age, or levelof education. Dyslexia is distinguished from other disor-ders that may prominently feature reading difficulties bythe unique, circumscribed nature of the phonological def-icit, one not intruding into other linguistic or cognitivedomains. How reading and language are assessed will re-flect the age and educational level of the patient (Tables 1and 2).

Diagnosis at School Age

Presenting complaints most commonly center aboutschool performance, eg, the child is not doing well inschool, and often parents and teachers do not appreciatethat the child’s poor academic performance stems from a

reading difficulty. Thus, an evaluation for dyslexia shouldbe considered in all children presenting with school diffi-culties, even if reading difficulty is not the chief complaint.As with most other medical disorders, the history is criticalto the diagnosis of dyslexia. Clinicians need to develop asense of the developmental pattern demonstrated by chil-dren with dyslexia. Overall, the ontogeny of dyslexia is thatof a child who may have had a delay in speaking, who didnot learn letters by kindergarten, and who did not begin tolearn to read by first grade. The child progressively fallsbehind, with teachers and parents puzzled as to why suchan intelligent child may have difficulty learning to read.The reading difficulty is unexpected with respect to thechild’s ability, age, and/or grade. Even after acquiringdecoding skills, the child generally remains a slow reader.When teachers are not informed, they may unnecessarilypressure or hurry the student. Dysgraphia is often presentand accompanied by laborious note taking. Self-esteem isfrequently affected, particularly if the disorder has goneundetected for a long period of time. Learning-disabledchildren are likely to have encountered negative test-tak-ing experiences where there was a disparity between theirknowledge and their test scores, especially on timed tests,and thus tend to exhibit more test anxiety than nondis-abled peers. Test scores may thus be artificially depressedas a result of such anxiety. Adults with strong histories ofdyslexia who have compensated for their reading disabilitydemonstrate good accuracy in reading but are less auto-matic. Compensated dyslexics take longer to apply theirdecoding skills and thus are slower readers; however, givensufficient time, they score very well on tests of readingcomprehension.

Assessment of Reading

Reading is assessed by measuring decoding and compre-hension. In the school-age child, one important element ofthe psychometric evaluation is how accurately the childcan decode words, ie, read single words in isolation. Thisis measured with standardized tests of single real-word andpseudoword reading such as the Woodcock-Johnson Psy-choEducational Battery–Revised (WJ-R) and the Wood-cock Reading Mastery Test. Difficulties often also emerge

TABLE 1. Clues To Dyslexia In School-Age Children*History

Delayed languageProblems with the sounds of words (trouble rhyming words, confusingwords that sound alike)Expressive language difficulties (mispronunciations, hesitations, word-finding difficulties)Difficulty naming (difficulty learning letters of alphabet and names ofnumbers)Difficulty learning to associate sounds with lettersHistory of reading and spelling difficulties in parents and siblings

ReadingDifficulty decoding single wordsParticular difficulty reading nonsense or unfamiliar wordsInaccurate and labored oral readingSlow readingComprehension often superior to isolated decoding skillsPoor spelling

LanguageRelatively poor performance on tests of word retrieval (name thepictured item)Relatively superior performance on tests of word recognition (point tothe pictured item)Poor performance on tests of phonological awareness

Clues most specific to young children at-risk for dyslexiaDifficulty on tests assessing: knowledge of the names of letters, theability to associate sounds with letters, and phonological awareness

Clues most specific to bright young adults with dyslexiaChildhood history of reading and spelling difficultiesAccurate but not automatic readingVery slow performance on timed reading tests (eg, Nelson-DennyReading Test)Penalized by multiple choice tests

*Clues are based on history, observations, testing, or a combination of all three.Reprinted with permission.

TABLE 2. Types of Tests Useful in Identifying Children At Risk forDyslexia at School EntryLetter identification (naming letters of the alphabet)Letter—sound association (eg, identifying words beginning with the

same letter from a list: doll, dog, boat)Phonological awareness (eg, identifying word that would remain if a

particular sound were removed: if the /k/ sound was taken awayfrom “cat”)

Verbal memory (eg, recalling a sentence or a story that was just told)Rapid naming (rapidly naming a continuous series of familiar objects,

digits, letters, or colors)Expressive vocabulary or word retrieval (eg, naming single-pictured

objectsReprinted with permission.

Journal of AAPOSVolume 7 Number 3 June 2003162 Shaywitz and Shaywitz

14

skillsneedtoreadandspellareaffectedatschoolentry

oralreading ischaracterizedbydistortions,substitutions,and/oromissions

bothoralandsilentreadingarecharacterizedbyslowness anderrors incomprehension.

dyslexiaisapersistent,chroniccondition;itdoesnot representatransient“developmentallag”=Fig

average oraboveaverage Intelligence

SLDwimpairmentinreading(dyslexia):diagnosisassessment

ties (for age, intelligence, or level of education) in readingand (2) associated linguistic problems at the level of pho-nological processing. There is no one single test score thatis pathognomonic of dyslexia. As with any other medicaldiagnosis, the diagnosis of dyslexia should reflect athoughtful synthesis of all the clinical data available. Whatthe clinician is seeking is converging evidence of a phono-logically based reading disability as indicated by a disparitybetween the individual’s reading and phonological skills incontrast to his or her intellectual capabilities, age, or levelof education. Dyslexia is distinguished from other disor-ders that may prominently feature reading difficulties bythe unique, circumscribed nature of the phonological def-icit, one not intruding into other linguistic or cognitivedomains. How reading and language are assessed will re-flect the age and educational level of the patient (Tables 1and 2).

Diagnosis at School Age

Presenting complaints most commonly center aboutschool performance, eg, the child is not doing well inschool, and often parents and teachers do not appreciatethat the child’s poor academic performance stems from a

reading difficulty. Thus, an evaluation for dyslexia shouldbe considered in all children presenting with school diffi-culties, even if reading difficulty is not the chief complaint.As with most other medical disorders, the history is criticalto the diagnosis of dyslexia. Clinicians need to develop asense of the developmental pattern demonstrated by chil-dren with dyslexia. Overall, the ontogeny of dyslexia is thatof a child who may have had a delay in speaking, who didnot learn letters by kindergarten, and who did not begin tolearn to read by first grade. The child progressively fallsbehind, with teachers and parents puzzled as to why suchan intelligent child may have difficulty learning to read.The reading difficulty is unexpected with respect to thechild’s ability, age, and/or grade. Even after acquiringdecoding skills, the child generally remains a slow reader.When teachers are not informed, they may unnecessarilypressure or hurry the student. Dysgraphia is often presentand accompanied by laborious note taking. Self-esteem isfrequently affected, particularly if the disorder has goneundetected for a long period of time. Learning-disabledchildren are likely to have encountered negative test-tak-ing experiences where there was a disparity between theirknowledge and their test scores, especially on timed tests,and thus tend to exhibit more test anxiety than nondis-abled peers. Test scores may thus be artificially depressedas a result of such anxiety. Adults with strong histories ofdyslexia who have compensated for their reading disabilitydemonstrate good accuracy in reading but are less auto-matic. Compensated dyslexics take longer to apply theirdecoding skills and thus are slower readers; however, givensufficient time, they score very well on tests of readingcomprehension.

Assessment of Reading

Reading is assessed by measuring decoding and compre-hension. In the school-age child, one important element ofthe psychometric evaluation is how accurately the childcan decode words, ie, read single words in isolation. Thisis measured with standardized tests of single real-word andpseudoword reading such as the Woodcock-Johnson Psy-choEducational Battery–Revised (WJ-R) and the Wood-cock Reading Mastery Test. Difficulties often also emerge

TABLE 1. Clues To Dyslexia In School-Age Children*History

Delayed languageProblems with the sounds of words (trouble rhyming words, confusingwords that sound alike)Expressive language difficulties (mispronunciations, hesitations, word-finding difficulties)Difficulty naming (difficulty learning letters of alphabet and names ofnumbers)Difficulty learning to associate sounds with lettersHistory of reading and spelling difficulties in parents and siblings

ReadingDifficulty decoding single wordsParticular difficulty reading nonsense or unfamiliar wordsInaccurate and labored oral readingSlow readingComprehension often superior to isolated decoding skillsPoor spelling

LanguageRelatively poor performance on tests of word retrieval (name thepictured item)Relatively superior performance on tests of word recognition (point tothe pictured item)Poor performance on tests of phonological awareness

Clues most specific to young children at-risk for dyslexiaDifficulty on tests assessing: knowledge of the names of letters, theability to associate sounds with letters, and phonological awareness

Clues most specific to bright young adults with dyslexiaChildhood history of reading and spelling difficultiesAccurate but not automatic readingVery slow performance on timed reading tests (eg, Nelson-DennyReading Test)Penalized by multiple choice tests

*Clues are based on history, observations, testing, or a combination of all three.Reprinted with permission.

TABLE 2. Types of Tests Useful in Identifying Children At Risk forDyslexia at School EntryLetter identification (naming letters of the alphabet)Letter—sound association (eg, identifying words beginning with the

same letter from a list: doll, dog, boat)Phonological awareness (eg, identifying word that would remain if a

particular sound were removed: if the /k/ sound was taken awayfrom “cat”)

Verbal memory (eg, recalling a sentence or a story that was just told)Rapid naming (rapidly naming a continuous series of familiar objects,

digits, letters, or colors)Expressive vocabulary or word retrieval (eg, naming single-pictured

objectsReprinted with permission.

Journal of AAPOSVolume 7 Number 3 June 2003162 Shaywitz and Shaywitz

Woodcock et al 1989.

represent the sounds of spoken language. In order to read, achild has to develop the insight that spoken words can be pulledapart into the elemental particles of speech (phonemes) and thatthe�letters�in�a�written�word�represent�these�sounds�(Shaywitz2003);�such�awareness�is�largely�missing�in�dyslexic�children�andadults� (Bruck�1992;� Fletcher� et� al� 1994;� Liberman�and�Shank-weiler�1991;�Shankweiler�et� al�1979;�Shaywitz�2003;�Torgesen1995;� Wagner� and� Torgesen� 1987).� Results� from� large� andwell-studied populations with reading disability confirm that inyoung�school-age�children�(Fletcher�et�al�1994;�Stanovich�andSiegel�1994)�as�well�as� in�adolescents� (Shaywitz�et�al�1999)�adeficit in phonology represents the most robust and specificcorrelate� of� reading� disability� (Morris� et� al� 1998;� Ramus� et� al2003).�Such�findings�form�the�basis�for�the�most�successful�andevidence-based interventions designed to improve reading; suchinterventions detailed in the Report of the National ReadingPanel include five critical elements: phonemic awareness; phon-ics;�fluency;�vocabulary�and�comprehension�(Report�2000).

Implications of the Phonologic Model of DyslexiaReading comprises two main processes - decoding and com-

prehension�(Gough�and�Tunmer�1986).�In�dyslexia,�a�deficit�atthe level of the phonologic module impairs the ability to segmentthe spoken word into its underlying phonologic elements andthen link each letter(s) to its corresponding sound. As a result,the reader experiences difficulty, first in decoding the word andthen in identifying it. The phonologic deficit is domain-specific;that is, it is independent of other, nonphonologic, abilities. Inparticular, the higher order cognitive and linguistic functionsinvolved in comprehension, such as general intelligence andreasoning,�vocabulary�(Share�and�Stanovich�1995),�and�syntax(Shankweiler�et�al�1995),�are�generally� intact.�This�pattern� -�adeficit in phonologic analysis contrasted with intact higher-ordercognitive abilities - offers an explanation for the paradox ofotherwise intelligent, often gifted, people who experience greatdifficulty�in�reading�(Shaywitz�1996,�2003).

According to the model, a circumscribed deficit in a lower-

order linguistic function (phonology) blocks access to higher-order processes and to the ability to draw meaning from text. Theproblem is that the affected reader cannot use his or herhigher-order linguistic skills to access the meaning until theprinted word has first been decoded and identified. Suppose, forexample, an individual who knows the precise meaning of thespoken word “apparition;” however, she will not be able to useher knowledge of the meaning of the word until she can decodeand identify the printed word on the page and it will appear thatshe does not to know the word’s meaning.

Outcome

Deficits in phonological coding continue to characterizedyslexic readers even in adolescence; performance on phono-logical processing measures contributes most to discriminatingdyslexic and average adolescent readers, and average and supe-rior�readers�as�well�(Shaywitz�et�al�1999).�Children�with�dyslexianeither spontaneously remit nor do they demonstrate a lagmechanism for “catching up” in the development of readingskills. That is not to say that many dyslexic readers do notbecome quite proficient in reading a finite domain of words thatare in their area of special interest, usually words that areimportant for their careers. For example, an individual who isdyslexic in childhood but who, in adult life becomes interested inmolecular biology might then learn to decode words that form aminivocabulary important in molecular biology. Such an individ-ual, while able to decode words in this domain still exhibitsevidence of his early reading problems when he has to readunfamiliar words, which he then does accurately but not fluentlyand�automatically�(Ben-Dror�et�al�1991;�Bruck�1992,�1994;�Leflyand�Pennington�1991;�Shaywitz�et�al�1999).�In�adolescents,�therate of reading as well as facility with spelling may be most usefulclinically in differentiating average from poor readers. From aclinical perspective, these data indicate that as children approachadolescence, a manifestation of dyslexia may be a very slowreading rate; in fact, children may learn to read words accurately,but they will not be fluent or automatic, reflecting the lingeringeffects� of� a� phonologic� deficit� (Lefly� and� Pennington� 1991).Because they are able to read words accurately (albeit veryslowly) dyslexic adolescents and young adults may mistakenlybe assumed to have “outgrown” their dyslexia. Data from studiesof children with dyslexia who have been followed prospectivelysupport the notion that in adolescents, the rate of reading as wellas facility with spelling may be most useful clinically in differen-tiating average from poor readers in students in secondaryschool, and college and even graduate school. It is important toremember that these older dyslexic students may be similar totheir unimpaired peers on untimed measures of word recogni-tion yet continue to suffer from the phonologic deficit that makesreading less automatic, more effortful, and slow. For thesereaders with dyslexia the provision of extra time is an essentialaccommodation; it allows them the time to decode each wordand to apply their unimpaired higher-order cognitive and lin-guistic skills to the surrounding context to get at the meaning ofwords that they cannot entirely or rapidly decode. With suchaccommodations, many students with dyslexia are now success-fully completing studies in a range of disciplines, includingmedicine. It is important to appreciate that phonologic difficulties indyslexia are independent of intelligence, consequently, manyhighly intelligent boys and girls have reading problems which areoften overlooked and even ascribed to “lack of motivation.”

In counseling their patients who are dyslexic, physicians

Figure 1. Trajectory of reading skills over time in nonimpaired and dyslexicreaders. Ordinate is Rasch scores (W scores) from the Woodcock-Johnsonreading test (Woodcock and Johnson 1989) and abscissa is age in years. Bothdyslexic and nonimpaired readers improve their reading scores as they getolder, but the gap between the dyslexic and nonimpaired readers remains.Thus dyslexia is a deficit and not a developmental lag. Figure derived from datain (Francis et al 1996) and reprinted from (Shaywitz 2003) with permission.

1302 BIOL PSYCHIATRY 2005;57:1301–1309 S.E. Shaywitz and B.A. Shaywitz

www.sobp.org/journal

15

developmentofphonologicalawareness(Berg&Stegelman,2003)

phonologicalawareness :askilldevelopmentfollowsapredictabledevelopmental

TypicalAgeofMasterySkill

• 3years:reciterhymes,rhymebypattern,alliteration (cat,core)

• 4yearsofage:count syllables (50%ofchildren)

• 5yearsofage:countsyllables (90%);countphonemes (<50%)

• 6years:matchinitial consonants;blend2to3phonemes;countphonemes(70%);identifyrhymes;divideonset-rimes(e.g.,c-at)

• 7years:blend3phonemes,segment3to4phonemes,spell phonetically,deletephonemes

GENERALLY:developfromfromphonemic(soundingout)towardslexical(automatic)

process...

canassesusingcognitivetesting16

examples:phonologicalawarenessassessmenttask(Cassady etal2005)

Practical Assessment Research & Evaluation, Vol 10, No 18 3 Cassady, Smith & Huber, Phonological Awareness

Table 1. Phonological Awareness Assessment Task Examples

Phonological Awareness Task

Basic Instructions Sample Item(s)

Rhyme recognition Rhymes are words that sound the same at the end... Tell me if these words rhyme.

ape-knee; dip-hip

Rhyme application Tell me a word that rhymes with:

cap

Oddity tasks: Beginning sounds

Listen to the names of these pictures. Tell me which one has a different beginning sound.

nest, soap, nails

Oddity tasks: Ending sounds

Listen to the names of these pictures. Tell me which one has a different ending sound.

bell, web, crib

Oddity tasks: Middle sounds

Listen to the names of these pictures. Tell me which one has a different middle sound.

beak, cone, heel

Blending body-codas I will say two parts of a word separately. You tell me the word.

/co/ /p/

Blending onset-rimes I will say the first sound of a word and then the rest of the word separately. Tell me the whole word

/c/ /op/

Blending phonemes I’m going to say each sound of a word slowly, then you tell me the word.

/s/ /a/ /ve/ -- “what is the word put together?”

Segmenting onset-rimesSplit the word by saying the first sound and then the rest of the word:

“Split the word coat by saying just the first sound and then the rest of the word.

Segmenting phonemes Say each sound you hear in the word job

Phoneme deletion Listen to the word ____. Take away the first sound, what is left?

Listen to the word book. Take away the /b/ sound, what is left?

Phoneme Substitution: Beginning sounds

If I change the first sound in the word man to /p/, the new word is pan.

Change the first sound in cat to /h/. What is the new word?

Phoneme Substitution: Ending sounds

If I say the word rat and change the last sound to /g/, the new word is rag.

Change the last sound in cat to /p/. What is the new word?

Phoneme Substitution: Middle sounds

If I say the word pan, change the middle sound to /i/, the new word is pin.

Change the middle sound in the word cat to /o/, what’s the new word?

Note: The phonological awareness task examples are based on the structure of the SAPA. There are variations across measures on the instructions, types of items, and number of tasks assessed.

17

phoneme :thesmallestunitof

speechthatcanbeusedtomakeoneworddifferent fromanother word.

dyscalculia :difficultyperformingmath calculations orlearning disabilitywhichaffectsmath• number-specificcognitivechallenge- numberconcepts,

combinations,andresolvingwordproblems• notcausedbyothercognitivedifficulties(i.e.,attention)

youngchildren:difficultyw• counting,troublerecognizing printednumbers,difficultytying

togethertheidea number (4)andhowitexistsintheworld(4cars),poormemory fornumbers

school-agechildren :difficultyw• learningmathfacts,developingmathproblem-solvingskills,long

termmemoryformath functions,measuring things,etc.

teenagers/adults:difficultyw• estimatingcosts(i.e.,groceriesbills)• budgeting orbalanceacheckbook,• concepts oftime (schedule,etc.)

SLDwimpairmentinmathematics(dyscalculia):symptomology

18

adultswithSLD

Manyadultshavegrownupfeelinginadequate,attributingtheirdifficultiestoagenerallackofability.• knowing thatthereisaspecificreasonfortheirdifficultiescanbeagreatrelief.• betterunderstandingoftheirstrengths aswellastheirweaknesses =importantstep

towardsbuildingself-esteemanddevelopingmoreeffectivecopingstrategies.

ManyadultsnewlydiagnosedwithSLDcouldbenefitfromcounselling• personal - understandtheirstrengths andweaknesses - self-esteem• professional - career /adultsupportgroupsmaybehelpful

Manyexcellentsupportprograms forthestudent/adultswSLDincolleges/universities• usefulforstudentstoself-identifyinordertoaccessservicesandaccommodations.

https://ldaamerica.org

• howtomanagesocial-emotionalissuesof adults with SLDs

19

interventions:school

Individualized Education Program (IEP):isawrittenplanthatdescribesthemodificationoflevelofinstructionoradaptationstothecurriculumrequiredbyaparticularstudent.

modifications :changestoWHATistaught&assessed

• meetstudentneedsthataresubstantiallydifferent fromtheprescribed gradelevel

curriculum.• Learndifferentmaterial(suchascontinuingtoworkonmultiplicationwhileclassmates

moveontofractions)• Getgraded orassessed usingadifferentstandardthantheoneforclassmates• Beexcused fromparticularprojects• alterthegrade-levellearningexpectations(forasubjectorcourse)fromtheprovincial

curriculum

accommodations :changestoHOWchildistaughtandassessed

• canbeenvironmental,physical,academic,organizational,motivational,assessment &evaluation– amountofwork,timetocompletein-classwork,levelofsupport(professionals),

difficulty(problemtype),output(#ofwordsforcomposition),alternateexpectations20

maintainrealistic expectations aboutlearningskills.• challengesdoesnotmeanthatchildwillalwaysmakereadingerrors,butmore

laborious comparedtochild'speers• readingafewpages/night– justpracticingisashort-term,tangible goal

celebrate everysuccess (ie..,witha"goodjob"or"ahighfive")• rewardprogress andeffort.• workofself-esteem!!!

phoneticawareness/spelling willcontinuetobeachallenge forachild• provideavisualphonemechart tohelpwithhomework- helpfultopairthesounds

withrelevantimages.• usedictionary,spellcheck,ortext-prediction

software• readaloudwchildoruseApp thatreadsaloud

sochildcangainunderstanding context/meaning oftext,helpwithphonetic awareness &comprehension

interventions:home/parents

21

Montreal Centre for Learning Disabilities

http://www.ldmontreal.ca

• charitable organization that aims to disseminateinformation, promote awareness and provide innovativeservices and programs to the English speaking community

• adult services

Montreal Fluency Centre

http://montrealfluency.com

• specialized after-school programming that targetsphonological skill development.

L’Institut des troubles d’apprentissage

http://institutta.com

• non-profit organization catering to persons with SLDs andtheir families.

resources

22

ADHD

23

Early1900s- ADHDwasfirstmentionedin1902byBritishpediatricianSirGeorgeStill

Childrenwholackedself-controlandshowedsymptomsofoveractivity /inattentioninschoolweresaidtohave“defectivemoralcontrol”,butwereintelligent

1900- 1950:MinimalBrainDysfunction(damage):

1950-1969:Hyperkinetic/HyperactivitySyndrome(DSM-IIof1968)

1970– 1979:RecognitionofAttentionalimpairmentandImpulsivity

1980:DiagnosticCriteria(DSM-III)and�ADD� withorwithoutHyperactivity

1987:ADDbecomesADHD(DSM-IIIR)w/mixedcriteria:

1994:ADHD(inattentive,hyperactive,combinedsubtypes)inDSM-IV

history

24

Keysymptomsfallundertwowell-documentedcategories

• Inattention

• Hyperactivity-impulsivity

UsingthesedimensionstodefineADHDoversimplifiesthedisorder• Attentionandimpulsecontrolarecloselyconnected

developmentally

Intellectual abilities

• mostchildrenwithADHD haveatleastnormalintelligence- thedifficultyliesinapplyingintelligencetoeverydaylifesituations

Impairedacademicfunctioning

• childrenwithADHDfrequentlyhavelowerproductivity,grades,andscoresonachievementtests

• attentioninvolvedinmanyacademicfunctions....

core characteristics of ADHD

25

Inabilitytosustainattention,particularlyforrepetitive,structured,andlessenjoyabletasks

• deficitsmaybeseeninoneormoretypesofattention:attentionalcapacity/selectiveattention/distractibility/sustainedattention/vigilance(acorefeature)

DSM-5 Diagnostic Criteria for ADHD - Inattention

26

Inability tovoluntarily inhibit dominant orongoing behavior• Hyperactivebehaviors: fidgetinganddifficultystayingseated/moving,running,touching

everythinginsight,excessivetalking,andpenciltapping,excessivelyenergetic,intense,inappropriate,andnotgoal-directed

• Impulsivity :inabilitytocontrolimmediatereactionsortothinkbeforeacting:cognitiveimpulsivityincludesdisorganization,hurriedthinking,andneedforsupervision– behavioral impulsivity :difficultyinhibitingresponseswhensituationsrequireit– emotional impulsivity :impatience,lowfrustrationtolerance,hottemper,quicknessto

anger,andirritability

DSM-5 Diagnostic Criteria for ADHD - Hyperactivity & Impulsivity

27

Appearspriortoage12

Persistsmorethan6months

Occursmoreoften andwithgreaterseverity comparedtochildrenofthesameageandsex(differentthresholdsformales andfemale- questionnaires)

Occuracrosstwoormoresettings(home,school,activities,tassesment,etc.)

Interferes withsocial oracademicperformance

Notexplainedbyanotherdisorder

Additional DSM-5 Diagnostic Criteria for ADHD

28

ADHD- predominantlyinattentiveorhyperactive-impulsivepresentation

Predominantlyinattentive presentation(ADHD-PI)• Inattentive,drowsy,day-dreamy,aloof,spacey,inafog,andeasilyconfused• Mayhaveco-occurringSLD:process informationslowly,havetrouble remembering

things,anddisplaylowacademicachievement

• Oftenanxious,apprehensive,socially withdrawn,andmaydisplaymood disorders

Predominantlyhyperactive–impulsivepresentation(ADHD-HI)• Primarilysymptomsofhyperactivity-impulsivity(rarestgroup)• Primarilyincludespreschoolersandmayhavelimitedvalidityforolderchildren• MaybeadistinctsubtypeofADHD-C

29

Worldwideprevalence ofADHDhasbeenestimatedat5.29% (Polanczyk etal2007)

Prevalence ratesvarywidelywithsamplingmethods• Estimates:6-7%ofschool-agechildrenandadolescentsinNorthAmericaand5%

worldwidehaveADHD• ADHDisoneofthemostcommonreferralproblemsseenatclinics

5.4-foldincreaseinprevalencefrom1979- 1996inUS• partiallyexplainedbychangesindiagnosticcriteria(DSM-IIItoDSM-IV)

ADHDpersistsinadulthoodforaboutabout50- 65%ofdiagnosedchildren(Faraone etal2006)

• persistencerelatedtoADHDsymptomseverity,numberofsymptoms,ADHDsubtype,ADHDinrelatives,psychosocialadversity,psychiatriccomorbidities,and/orparentalpsychopathology

Manyadults withADHDareundiagnosedanduntreated

ADHD- prevalenceandcourse

30

ADHDoccursmorefrequentlyinboys• girlswithADHDmaybeunder-identifiedandundertreated- less

behavioural manifestations

Ratioinclinicalsamplesis6:1withboysbeingreferredmoreoftenthangirls• ADHDingirlsmaygounrecognizedandunreported

Overallratesdecreaseinadolescenceforbothsexes- ratioremainsthesame

DSMcriteria(cutoffsandsymptoms)maybemoreappropriateforboys thangirls

Girls withADHDmaybemorelikelytodisplayinattentive/disorganizedsymptoms

Girls withADHDwhodisplayimpulsive-hyperactivebehaviors

morelikelytodevelopeatingdisordersymptoms

ADHD- gender

31

ADHD- comorbiddiagnoses- children

Upto80% ofchildrenwithADHDhaveaco-occurringpsychologicaldisorder

OppositionalDefiantDisorder(ODD)andConductDisorder (CD)• commongeneticcontributionforADHD,ODD,andCD• Familyconnections– thereisevidencefora

contributionfromasharedenvironment

Mooddisorders

• ADHDat4-6yearsisariskfactorforfuturedepressionandsuicidalbehavior

• 20-30%ofchildrenwithADHDexperience

depression

– familyriskforonedisordermayincreasetheriskfortheother

three domains; 20% did well in all three domains; and 60% hadintermediate outcomes. These findings suggest that the syn-dromic persistence of ADHD is not associated with a uniformfunctional outcome; rather, it leads to a wide range of emotional,educational, and social adjustment outcomes that can be partiallypredicted. More work is needed, however, to disentangle therole of treatment on outcome.

Comorbidity of ADHD

Childhood ADHDThroughout the life cycle, a key clinical feature observed in

patients with ADHD is comorbidity. In children, psychiatricdisorders comorbid with ADHD include oppositional defiantdisorder, conduct disorder, mood disorders (both unipolar andbipolar), anxiety disorders, and learning disorders (Kessler 2004;Pliszka 1998). Although spurious comorbidity can occur due toreferral and screening artifacts (Caron and Rutter 1991), recentreviews of the literature show that these artifacts cannot explainthe high levels of psychiatric comorbidity observed for ADHD(Angold et al 1999). Figure 1 illustrates the prevalence rates ofcommon comorbid diagnoses of childhood ADHD and howthese diagnoses are affected with respect to gender (Biedermanet al 1996, 1999; Pliszka 1998; Spencer et al 1999).

In a systematic evaluation of the impact of gender on theclinical features of ADHD, Biederman et al (2002) reported thatgirls with ADHD were at less risk for comorbid disruptivebehavior disorder than boys with ADHD. Because disruptivebehavior disorder drives referral, this finding might explain thesubstantial discrepancy in the male/female ratio between clinic-referred (10:1) and community (3:1) samples of children withADHD (Biederman et al 2002). Furthermore, this gender discrep-ancy suggests that girls with ADHD might be under-identifiedand under-treated.

Adult ADHDFollow-up studies have found that 5%–66% of children with

ADHD persist with this disorder in adulthood (Biederman et al1993). Current epidemiologic studies estimate the prevalence ofadult ADHD to be between 3% and 5% (Faraone 2004; Kessler2004). Furthermore, studies of referred and nonreferred adultswith a clinical diagnosis of childhood-onset and persistent ADHDrevealed that clinical correlates—demographic, psychosocial,psychiatric, and cognitive features—mirrored well-documentedfindings among children with ADHD (Biederman et al 1993,

2004). Lifetime prevalence rates of comorbid anxiety disorders inadults with ADHD approach 50%, whereas mood disorders,antisocial disorders, and alcohol/drug dependency also showsubstantial prevalence rates (Figure 2) (Biederman et al 1993,1994; Shekim et al 1990). Findings from a new, large sample ofmale and female adults with and without ADHD provide com-pelling evidence for the validity of adult ADHD and documentstrikingly similar phenotypic features of the disorder in bothgenders (Biederman et al 2004). Consistent with previous find-ings, this study documented high rates of mood and anxietydisorders in adults with ADHD, with a female predominance.

Genetics and ADHD

Familial InfluenceFamily studies of ADHD have consistently supported its

strong familial nature (Faraone and Doyle 2001; Faraone andTsuang 1995). Despite nosologic changes, there is remarkableagreement between early studies of children whose illness wasdefined as hyperactivity (Cantwell 1972; Morrison and Stewart1971) and subsequent studies using DSM-III and DSM-III-Rdefinitions of ADHD (Figure 3) (Biederman et al 1990; Faraoneet al 1992; Frick et al 1991; Schachar and Wachsmuth 1990). Mostfamily studies have identified a two- to eightfold increase in therisk for ADHD in parents and siblings of children with ADHD(Biederman et al 1990; Cantwell 1972; Faraone et al 1992; Fricket al 1991; Manshadi et al 1983; Morrison and Stewart 1971; Paulset al 1983; Schachar and Wachsmuth 1990; Welner et al 1977). Astudy of siblings of adults with ADHD (Manshadi et al 1983) and

Figure 1. Approximate prevalence of comorbid diagnoses in children withattention-deficit/hyperactivity disorder.

Figure 2. Approximate prevalence of comorbid diagnoses in adults withattention-deficit/hyperactivity disorder.

Figure 3. Family studies in attention-deficit/hyperactivity disorder(ADHD).

1216 BIOL PSYCHIATRY 2005;57:1215–1220 J. Biederman


32

female>male

ADHD- comorbiddiagnoses- children (cont'd)

Anxietydisorders

• about25%ofchildrenwithADHDexperienceexcessiveanxiety

• childrenwithco-occurringanxiety– Displaysocialandacademicdifficulties– Experiencegreaterlong-termimpairmentand

mentalhealthproblems

Learningdisorders

• about25%ofchildrenwithADHDhavedifficultywithreading,writingand/ormath

+speech-relateddifficulties

• difficultyunderstandingothers’speech• excessiveandloudtalking• frequentshiftsandinterruptionsinconversation• inabilitytolisten• inappropriateconversations• speechproductionerrors


Comorbidity of ADHD







Genetics and ADHD








Biederman 2005

female>male

33

ADHD- comorbiddiagnoses- adults

Manychildren withADHDdonotoutgrowproblems andsomecangetmuchworse

Atleast50%ofclinic-referredelementary

schoolchildrencontinuetodealwithADHDintoadolescence

Adultchallenges (Shawetal.,2012)

• druguse/addictivebehaviour,• academicoutcomes,• antisocialbehaviours,• socialfunction• occupationBUT

• Someindividuals eitheroutgrow orlearntocopewiththeirdisorderbyadulthood

• ADHDisestablishedasanadultdisorder


Comorbidity of ADHD







Genetics and ADHD








Biederman 2005

34

female>male

ADHD- genetics

ADHDrunsinfamilies

Family studies:• siblingriskincreases2- 5x• 3- 5xincreasedlikelihoodthatparent is

affected (9- 35%)

Twin studies

• 75%heritabilityestimatesforhyperactive-impulsiveandinattentivebehaviors

Specific gene studies• Genesmaycontributetotheexpression

ofADHD– focusondopamine regulation

a study of children of adults with ADHD both documented veryhigh rates of ADHD in the families of adults with ADHD(Biederman et al 1995a). These and other data suggest thatpersistent ADHD might be a useful phenotype for moleculargenetic studies (Faraone et al 2000).

Attention to comorbid psychiatric disorders in these familystudies also provides evidence for the genetic heterogeneity ofADHD. Results of analyses from independent samples of chil-dren with DSM-III attention-deficit disorder (Biederman et al1990) and DSM-III-R ADHD (Biederman et al 1992) suggest that1) ADHD and major depression share common familial vulner-abilities (Biederman et al 1991b); 2) ADHD children with conductdisorders and bipolar disorders (Faraone et al 1991, 1997, 2001a;Wozniak et al 1995) might be a distinct familial subtype ofADHD; and 3) ADHD is familially independent from anxietydisorders (Biederman et al 1991a) and learning disabilities (Faraoneet al 1993; Goodman and Stevenson 1989). Thus, stratification byconduct and bipolar disorders might divide the universe ofchildren with ADHD into more familially homogeneous sub-groups. On the other hand, major depressive disorder might bea nonspecific manifestation of different ADHD subtypes.

Twin and Adoption StudiesBecause ADHD is believed to be highly genetic, studies of

twins have been used to establish its heritability, or the degree towhich this disorder is influenced by genetic factors (Coolidge etal 2000; Edelbrock et al 1995; Gillis et al 1992; Gjone et al 1996;Goodman and Stevenson 1989; Hudziak et al 2000; Kuntsi andStevenson 2001; Levy et al 1997; Martin et al 2002; Nadder et al1998; Sherman et al 1997; Silberg et al 1996; Stevenson 1992;Thapar et al 1995; Willcutt et al 2000; Willerman 1973). Based onnumerous studies of twins, which varied considerably in meth-odology and definitions of ADHD, the mean heritability forADHD was shown to be .77 (Figure 4).

Adoption studies of ADHD also implicate a genetic etiology.Early studies showed that the adoptive relatives of hyperactivechildren are less likely to have hyperactivity or associateddisorders than are the biologic relatives of hyperactive children(Cantwell 1975; Morrison and Stewart 1973). In a recent study,Sprich et al (2000) reported that the adoptive relatives of adoptedADHD probands had rates of ADHD and other associateddisorders that were lower than those observed in the biologicalrelatives of nonadopted ADHD probands, and similar to those

found in relatives of control probands. Biological relatives ofchildren with ADHD also perform more poorly on standardizedmeasures of attention than do adoptive relatives of children withADHD (Alberts-Corush et al 1986).

Molecular Genetics StudiesTwo approaches are used to evaluate the genetic etiology of

ADHD: 1) the genome scan, which examines all chromosomallocations without a priori guessing as to which genes underlieADHD; and 2) the candidate gene approach, which examinesone or more genes based on theory and empirical evidence(Faraone et al 2005). A genomewide linkage scan in 204 nuclearfamilies (853 individuals and 270 affected sibling pairs) suggeststhat regions 16p13 and 17p11 likely harbor risk genes for ADHD(Ogdie et al 2003).

Cook et al (1995) observed an association between ADHDand the 480-bp allele (or genotype) in the dopamine transportergene (DAT). Additional polymorphisms in intron 9 and exon 9were examined, with a trend for biased transmission of the480-bp allele of VNTR polymorphism (Barr et al 2001). Thedopamine transporter was found to be elevated by approxi-mately 70% in adults with ADHD, according to single photonemission computed tomography (Dougherty et al 1999). By far,the gene most strongly implicated in ADHD is the 7-repeat alleleof the human dopamine receptor D4 gene (DRD4), confirming astrong dopamine component in the pathogenesis of ADHD(Faraone et al 2001b).

Other Factors Contributing to the Etiology of ADHD

Biological AdversitySeveral biologic factors have been proposed as contributors

to ADHD, including food additives/diet, lead contamination,cigarette and alcohol exposure, maternal smoking during preg-nancy, and low birth weight. Although the Feingold Diet forADHD was popularized by the media and accepted by manyparents, systematic studies showed that this diet was ineffectiveand that food additives do not cause this disorder (Conners1980). Several investigators have shown that lead contaminationcan cause distractibility, hyperactivity, restlessness, and lowerintellectual functioning; however, lead does not account for themajority of ADHD cases, and many children with high leadexposure do not develop ADHD. An emerging literature docu-ments that maternal smoking and alcohol exposure duringpregnancy, low birth weight, and psychosocial adversity areadditional independent risk factors for ADHD (Biederman et al1995b; Mick et al 2002b).

Pregnancy and delivery complications (i.e., toxemia, eclamp-sia, poor maternal health, maternal age, fetal postmaturity,duration of labor, fetal distress, low birth weight, antepartumhemorrhage) seem to predispose for ADHD (Sprich-Buckminsteret al 1993). It is theoretically compelling to explore maternalsmoking as a risk factor for ADHD, because nicotinic receptorsmodulate dopaminergic activity, and dopaminergic disruption isbelieved to be involved in the pathophysiology of ADHD.Animal studies have shown a positive correlation betweenhyperactivity and chronic exposure to maternal nicotine intakeduring pregnancy (Fung and Lau 1989; Hagino and Lee 1985;Johns et al 1982; Richardson and Day 1994; Van De Kamp andCollins 1994). Several studies documented that maternal smokingduring pregnancy is an independent risk factor for ADHD(Biederman et al 1995b; Mick et al 2002a; Milberger et al 1996).

Figure 4. Heritability of attention-deficit/hyperactivity disorder (ADHD).

J. Biederman BIOL PSYCHIATRY 2005;57:1215–1220 1217



Comorbidity of ADHD


patients with ADHD is comorbidity. In children, psychiatricdisorders comorbid with ADHD include oppositional defiantdisorder, conduct disorder, mood disorders (both unipolar andbipolar),�anxiety�disorders,�and�learning�disorders�(Kessler�2004 ;Pliszka�1998).�Although�spurious�comorbidity�can�occur�due�toreferral�and�screening�artifacts�(Caron�and�Rutter�1991),�recentreviews�of�the�literature�show�that�these�artifacts�cannot�explainthe high levels of psychiatric comorbidity observed for ADHD(Angold�et�al�1999).�Figure�1�illustrates�the�prevalence�rates�ofcommon comorbid diagnoses of childhood ADHD and howthese�diagnoses�are�affected�with�respect�to�gender�(Biedermanet�al�1996,�1999;�Pliszka�1998;�Spencer�et�al�1999).

In a systematic evaluation of the impact of gender on theclinical�features�of�ADHD,�Biederman�et�al�(2002)�reported�thatgirls with ADHD were at less risk for comorbid disruptivebehavior disorder than boys with ADHD. Because disruptivebehavior disorder drives referral, this finding might explain thesubstantial discrepancy in the male/female ratio between clinic-referred (10:1) and community (3:1) samples of children withADHD�(Biederman�et�al�2002).�Furthermore,�this�gender�discrep-ancy suggests that girls with ADHD might be under-identifiedand under-treated.


ADHD�persist�with�this�disorder�in�adulthood�(Biederman�et�al1993).�Current�epidemiologic�studies�estimate�the�prevalence�ofadult�ADHD�to�be�between�3%�and�5%�(Faraone�2004 ;�Kessler2004 ).�Furthermore,�studies�of�referred�and�nonreferred�adultswith a clinical diagnosis of childhood-onset and persistent ADHDrevealed that clinical correlates—demographic, psychosocial,psychiatric, and cognitive features—mirrored well-documentedfindings� among� children� with� ADHD� (Biederman� et� al� 1993,

2004 ).�Lifetime�prevalence�rates�of�comorbid�anxiety�disorders�inadults with ADHD approach 50%, whereas mood disorders,antisocial disorders, and alcohol/drug dependency also showsubstantial�prevalence� rates� (Figure�2)� (Biederman�et� al� 1993,1994 ;�Shekim�et�al�1990).�Findings�from�a�new,�large�sample�ofmale and female adults with and without ADHD provide com-pelling evidence for the validity of adult ADHD and documentstrikingly similar phenotypic features of the disorder in bothgenders�(Biederman�et�al�2004 ).�Consistent�with�previous�find-ings, this study documented high rates of mood and anxietydisorders in adults with ADHD, with a female predominance.

Genetics and ADHD


strong� familial� nature� (Faraone� and�Doyle� 2001;� Faraone� andTsuang�1995).�Despite�nosologic�changes,� there� is� remarkableagreement between early studies of children whose illness wasdefined�as�hyperactivity�(Cantwell�1972;�Morrison�and�Stewart1971)� and� subsequent� studies� using� DSM-III� and� DSM-III-Rdefinitions�of�ADHD�(Figure�3)�(Biederman�et�al�1990;�Faraoneet�al�1992;�Frick�et�al�1991;�Schachar�and�Wachsmuth�1990).�Mostfamily studies have identified a two- to eightfold increase in therisk for ADHD in parents and siblings of children with ADHD(Biederman�et�al�1990;�Cantwell�1972;�Faraone�et�al�1992;�Fricket�al�1991;�Manshadi�et�al�1983;�Morrison�and�Stewart�1971;�Paulset�al�1983;�Schachar�and�Wachsmuth�1990;�Welner�et�al�1977).�Astudy�of�siblings�of�adults�with�ADHD�(Manshadi�et�al�1983)�and





www.sobp.org/journal Biederman 2005

35

Current models ofADHD:complicated andnotcompletely understood,but..• implicationdopaminergic andnoradrenergic system

imbalances relatedtocoresymptoms

consensus...prefrontal lobe dysfunction andtheconnectionsbetweenthefrontal lobe andkeysubcortical regions underlieADHD

Medicationsincreaseneurotransmissioninthesesystems...• dopaminergic:Adderal,Ritalin,Concerta• noradrenergic :Strattera

– notapsychostimulant- selectivenorepinephrinereuptakeinhibitor- SNRI)

– Alternative- forkidswhoexperiencelotsofirritabilityonstimulants

liberationtypei.e.,immediatevsSlow-releaseinitialdosei.e.,5mgvs20mgdurationofactioni.e.,4vs12hrs

ADHD- pharmacology

36

ADHD compared with controls. These longitudinal studieshave shown a developmental delay of cortical thickness inADHD, with greatest differences between ADHD and controlsin maturation of the middle prefrontal cortex. Interestingly,normalization of volumes in different brain regions such as theparietal cortex and the hippocampus parallel clinical improve-ment of symptoms, whereas progressive volume loss of cer-ebellar regions and hippocampus were associated with persis-tent symptoms (59).

Imaging studies are also beginning to study familial pat-terns of brain structure and function. Brain endophenotypesrefer to brain characteristics shared by ADHD patients andtheir siblings and likely to be involved in the liability to thedisorder. Activation pattern of the ventral prefrontal cortexand reduced striatal activity have been identified as possiblebrain endophenotype candidates (63,64).

Neurocognitive models of ADHD. The dual pathway modelof ADHD (25,65) links inattention and deficits in executivefunctions to impairments in prefrontal-striatal circuits whereashyperactivity may be consecutive to dysfunctions of rewardresponse and motivation, related to a frontal-limbic system.Multiple pathways to ADHD symptoms are also pointed out inanother model suggesting that a poor adjustment of behaviorto environmental cues may arise from deficient signaling ofthe prefrontal cortex by subcortical and posterior systems (i.e.a failure to detect discrepancies between current and expectedcontext because of a failure in bottom-up mechanisms) orfrom an intact signaling but inefficient top-down control(66,67).

From genes to brain structure and function. Striatal acti-vation patterns have been linked to DAT1 genotype throughhigher levels of DAT expression in carriers of the 10-R allele

(64). Gene effects have also been shown on brain structurewith DRD4 and DAT1 genotypes influencing the volume ofthe prefrontal cortex and the volume of the caudate nucleus,respectively (68). Neuroimaging methods may not only con-tribute to further document gene effects on brain function andstructure but also provide insight into environmental or GxEeffects in the near future (69).

Recent genetic findings suggest that a variety of genescould have, via their rare variants, a similar impact on proteincomplexes. Modifications of proteins in neuronal structuressuch as the dendritic spine could account for an intermediatephenotype (i.e. changes in dendritic spine morphology) lead-ing to an abnormal synaptic transmission. Such molecular andsubcellular phenotypes can be common to a variety of distinctrare variants (Fig. 2). A key issue for future research is tounderstand how a diversity of neuropsychiatric phenotypescan be generated by overlapping genotypes.

Novel strategies for pathophysiological analyses ofADHD. Animal models are one of the most promising ap-proaches to study molecular pathophysiology of ADHD. Ifmodels that may recapitulate the full phenotypic spectrum ofa psychiatric disorder are currently out of reach, creation ofphenotypic components is feasible (70). Table 2 illustrates themain animal models related to ADHD (71–75).

New perspectives are expected from using top-down andbottom-up cognitive paradigms in experiments with primates.Such paradigms can be transposed to rodents allowing exper-imental analysis of the role of the prefrontal cortex in decisionmaking using models attainable to genetic modifications (76).

Figure 2. A same intermediate phenotype can be generated by variantsidentified in many genes. The figure illustrates how a variety of genes couldhave a similar impact on protein complexes neuronal structures such as thedendritic spine. Similar changes in dendritic spine morphology could consti-tute an intermediate phenotype involved in abnormal synaptic transmission.

Figure 1. Schematic representation of functional circuits involved in thepathophysiology of ADHD. Here are summarized the attentional network(green), the fronto-striatal network (yellow), the executive function network(black), the fronto-cerebellar network (red), and the reward network (blue).

73RNEUROBIOLOGY OF ADHD

37

TheCanadianADHDResourceAlliance(CADDRA)

Thereisnosingle test toidentifyADHD

Clinical Interview

• diagnosticassessment ofprimary complaint• medical,psychiatric&developmental History• detailededucational history• detailedfamily &social history

Behavioural assessment• observation (interview/in-class,etc)• questionnaires

Psycho-educational /Neuropsychologicalassessment• intellectual functioning

• achievement

• mostly "executivefunctioning/frontal"tests• organization,attention(sustained,selective,

distributed),workingmemory(recall/interference),inhibition,self-regulation/monitoring,etc.

ADHD - establishing diagnosis - multifactorial

38

Nigg (2005)inameta-analysisidentifiedthemostcommonabnormalitiesinvariousneuropsychologicaltasksinADHD(listedbyEffectSize):

ADHD- neuropsychologicaltestsensitivetoADHD

CPTpressbarexceptafterX

explain a range of behavioral and physiologic observations.Recent theories have been similar but more closely related topsychopharmacology, again emphasizing disruption in the as-cending noradrenergic neurons that support signal/noise detec-tion�(McCracken�1991;�Figure�1B).�Sergeant�et�al�(1999),�drawingon�Pribram�and�McGuinness� (1975),� suggested� that� responsesearly in the task are particularly informative. Thus, appearance ofreaction time or accuracy deficits early on tasks (e.g., commonlyobserved slow and variable reaction time on initial task trials;Oosterlaan�et�al�1998)�is�one�source�of�support�for�an�arousalmodel. Early and recent electroencephalogram and evokedresponse potential findings tend to support this model as well(Barry�et�al�2003a,�2003b),�in�that�they�reveal�excess�slow-waveactivity in children with ADHD.

Closely related to this conception of arousal is the ability toalert rapidly to novel stimuli. That ability is also theorized todepend on a right-lateralized vigilance network with noradren-ergic�involvement�(Posner�and�Petersen�1990).�Data�on�alertingtherefore also might support an under-arousal model or enable itto be reformulated. Some data suggest such alerting is deficientin children with ADHD and their biologic but not adoptiverelatives�(Nigg�et�al�1997),�but�two�other�studies�found�smallereffects� on� this� probe� (reviewed� by� Huang-Pollock� and� Nigg2003).

Perhaps the best performance support for an arousal deficit inADHD comes from consistent findings of deficit on the contin-uous performance test d-prime parameter, a consensus index ofarousal�as�defined�in�the�theories�cited�here�(Losier�et�al�1996;�seeTables�1�and�2).�Arousal�thus�is�a�quite�viable�candidate�for�an

ADHD neurocognitive deficit. Questions remain, however, ow-ing to lack of time on task data in many published cognitivestudies�(Sergeant�et�al�1999).

Activation and ADHD. In the cognitive tradition, activationwas historically viewed as a left-lateralized process involvingdopaminergic neurons in response to motor preparation forresponse� output� (Pribram� and� McGuinness� 1975).� Whereasarousal is related to early-stage information processing, activa-tion is related to response preparation and readiness to respond.It is a tonic rather than a phasic process. To some extent,activation�is�related�to�the�concept�of�sustained�attention�(Posnerand�Peterson�1990),� except� that� the�emphasis� is�on� sustainedreadiness�of�motor�preparation�(Pribram�and�McGuinness�1975;Tucker�and�Williamson�1984).

Confusion therefore often ensues regarding the relationshipbetween activation, vigilance, and sustained attention. Histori-cally, these concepts have had a parallel handling and have filledsimilar roles in information processing theories, even thoughthey�are�not�isomorphic.�Thus�what�Posner�and�Petersen�(1990)call “vigilance” is also often referred to as “sustained attention”(Mirsky�and�Duncan�2001).�It�refers�to�the�ability�to�maintain�a

Figure 1. (A) Schematic view of subcortical and cortical regions, with dopa-mine pathways highlighted. The mesocortical pathway running from sub-stantial nigra on to prefrontal cortex is important in executive functioning aswell as in motivation and emotion. The mesolimbic pathway, projecting tonucleus accumbens, is often identified with reward motivation and rein-forcement learning. The nigrostiatal pathway projecting to basal ganglia isoften identified with motor control. (B) Schematic view of noradrenergicprojections to prefrontal cortex and cerebellum. Adapted and reproducedwith�permission�from�http://www.mastersofpediatrics.com/cme/cme2003/lecture5_2.asp.

Table 2. Selected Meta-analytic Findings in Neuropsychology of ADHDVersus Non-ADHD Children

Measure Effect Size (d)

Spatial Working Memory (Spatial Span) .75a to .85b to 1.14b

Response Suppression (Stop TaskSSRT/SSRT Slope)

.61a to .64c to .94d

Signal Detection (CPT d-prime) Arousal .72e

Stroop Naming Speed .69f

Full Scale IQ .61g

Set Shifting (Trails B Time) .55a to .59g to 0.75d

Planning (Tower of London/Hanoi) .51a to .69a

Mazes .58a

Verbal Working Memory .51a to .41b

Decision Speed on Go-Task .49c

WCST Perseverations .35g/.36a to .53h

Fluency .27d

Stroop Interference .25f

Covert Visual Spatial Orienting .20i

See�Table�1�for�task�descriptions.�The�effect�size�“d”�indicates�the�stan-dard deviation unit difference in group means; it is computed as m1 -m2/mean SD. ADHD, attention-deficit/hyperactivity disorder; SSRT, stop signalreaction time; CPT, continuous performance task; IQ, intelligence quotient;WCST, Wisconsin Card Sort Test.

aWillcutt et al 2005 (2005).bMartinussen, in press (verbal working memory [WM] storage d ! .4,

verbal WM executive d ! .54, visual WM storage d ! .85, visual WM centralexecutive d ! 1.14).

cOosterlaan�et�al�1998.dPennington�and�Ozonoff�1996.eLosier�et�al�1996.fvan�Mourik�et�al,�in�press.gFrazier�et�al�2004.hRomine�et�al�2004.iHuang-Pollock�and�Nigg�2003.

J.T. Nigg BIOL PSYCHIATRY 2005;57:1424–1435 1429


39

Lessthan50%ofkidswithADHDreceive

treatment

• Ofthosewhodomanydiscontinue...

Theprimary treatment approachcombines:• Parent management training• Educational intervention• Stimulantmedication

ADHD - treatment

40

Establish/maintain structure asmuchaspossible !• followa routine - Establishsimple/predictableritualsformeals,homework,play,and

bed.• use clocks/timersthroughouthome- allowenoughtimeforhomework,gettingreadyin

thea.m.,transitionaltimes(b/nfinishingplayandbedtime).• simplify(balance)schedule- keepbusybut nottoomanyactivities• createaquietplace - quietspacewithnodistractions• be neat&organized- asmuchaspossible...

Rulesmustbeclearandsimple• writedownruleseasilyunderstood bychild- hangthemup/available.• followup everytimewitharewardorconsequence(+ve reinforcement!)– no

food/toys,useimmediaterewards,canchartrewards/pointsystem

Homework ...• graduallybuildontimeexpendedduringtaskswithoutbreaks.• providestep-by-stepinstruction,specificallyforlonger,morelaboriouswork.

Trytoeatandsleepaswellaspossible...

interventions:home/parents

41

42

Canadian ADHD Resource Alliance (CADDRA)http://www.caddra.ca/

CADDRA is a Canadian non-industry, not-for-profit,independent association. An alliance of healthcareprofessionals supporting patients with ADHD and theirfamilies.

LeRegroupement desAssociationsPANDAduQuébec

http://www.associationpanda.qc.ca

Quebec-basedassociationwhoseaimistoaidpersonswithADHDandtheirfamilies.

resources

43

ASD

44

Bleuler (1911)• describedwithdrawalfromsocialrelationsintoa

richfantasylifeseeninindividualswithschizophrenia

• derivedfrom- autos(self)andismos (condition)

Kanner (1943)• casehistoryof11children(case1=DonaldT)• innattention ofoutsideworld=“extremeautistic

aloneness”• socialisolation,stereotypedbehavior,resistance

tochange,echolalia• « infantileautism »• congenitalinnature

Aspergersyndrome(1943):anotherformof« autism »

Kanner (1943)

45

DSMI(1952)Schizophrenicreaction,childhoodtype“psychoticreactionsinchildren,manifestingprimarilyautism …”

DSMII(1968)�[autismwasnotmentioned;thewordappearsonlyunderthefollowingcategory]•295.8 Schizophrenia,childhoodtype

Thiscategoryisforcasesinwhichschizophrenicsymptomsappearbeforepuberty.Theconditionmaybemanifestedbyautistic,atypicalandwithdrawnbehavior…”

Rutter(1968)- arguedautismdifferedformschizophrenia•higherM/Fratio•absenceofdelusionsandhallucinations•stablecourse(norelapse/improvement)•needbetterdiagnosticcriteriaforresearch

DSMIII(1980)- effectoninclusioncriteriaforresearch•diagnosticcriteriaforInfantileAutism

DSMIV(1994)- inlargercategoryof“PervasiveDevelopmentalDisorders”•autisticdisorder•Aspergersyndrome•pervasivedevelopmentaldisorder- nototherwisespecified(PDD-NOS)•Rett’ssyndrome(rare)•childhooddisintegrativedisorder

definitionofautism(ASD)

46

Autism:Then andNow

WendyStone,PhD;MindInstituteLectureSeries,2013

CDC researchers collect health and school records for 8-year-old children who live in select U.S. counties. These researchers are part of the Autism and Developmental

Disabilities Monitoring Network

THEN(1980’s):

• Prevalenceconsiderablylow≈3-4per10000

• Largelyunknowninpopculture

• Emphasisonintellectualdisability

• Feweducationalinterventions

• Oneautismjournal

NOW(2015):

• Prevalence1in59children,1in42boysinUS(CDC,2018)

• Largeawareness,extensivemediacoverage

• Littleemphasisonintellectualimpairment

• Recognizedheterogeneity/neurodiversity

• MANYautismjournals

Autism:ThenandNow

48

QuickTime™ and a decompressor

are needed to see this picture.





























scientific journals pop magazines

Autism:empiricalevidencevs popculture?

49

• Autismisnotrare

• Neurodevelopmental condition

• Traditionallycharacterizedasadisorderofsocialimpairment

• Highlyheritable

• No biologicalmarker

• Outcomes arevariable

• EveryonewithASDisdifferent=heterogeneity

Autism:Factswedoknow

TheAutisticBrainbyNatashaAldred ©

50

DSM 5– diagnosticcriteria

DSM 5

severitylevel

• howmuchsupport

“clinicalspecifiers“• wlang impairment?

• w intelimpairment?

=dimensionality

associatedfeatures• knowgenetics• epilepsy• DD

Mottron etal.,2007

behaviorsmanifestedinavariablemanner- oftenpresentdifferentprofiles- ‘autisms’- uniquestrengthsandweaknesses

differalongthreemainaxes:

1) Language

• 10- 20%neverdevelopabilitytocommunicateverbally(accompaniedbyseveredelay)

2) Cognitivedevelopment

• difficulttoassessÞ language/socialchallengesinterferewithcognitiveassessments

• IQvariable:acrossdomains/verbal vsnon-verbal• savants :co-occurrenceofcognitivedelaywithparticular

ability(10%)

3) Symptomseverity

• severe tomild

• profileschangeasafunctionofdevelopment

BehaviouralandcognitiveHeterogeneity=Spectrum

Stephen Wiltshire, 2009http://www.youtube.com/watch?v=dAfaM_CBvP8

52

nosingletestÞ diagnosisbasedentirelyonbehaviouralmanifestations

ASDÞ diagnosedbyamultidisciplinaryteamusingstandardizedinstruments

Developmentalhistory

AutismDiagnosticInterview(ADI-R)• Semi-structured,ParentInterview

Behaviour

AutismDiagnosticObservationSchedule(ADOS-2)• Childobservation

Cognitiveassessment

Clinicalexpertiseinvolved...

Diagnosis:Assessment

www.vcuautismcenter.org

53

Diagnosis:AssessmentofSymptoms

Parent Report

• ModifiedChecklistforAutisminToddlers(M-CHAT)• SocialCommunicationQuestionnaire(SCQ)• SocialResponsivenessScale(SRS)

Teacher Report

• AutismBehaviorChecklist(ABC)• SocialResponsivenessScale(SRS)

ChildObservationandRating

• ChildhoodAutismRatingScale(CARS)

54

Diagnosis:timeline

Parentalconcernsaboutchild‘s

developmentemerge

ASDdiagnosisgiven

BIRTH 1 2 3 4 5 6

Delayeddiagnosis

age of child (years)

WendyStone,PhD;MindInstituteLectureSeries,2013

55

Infrequentidofcomorbid psychiatric disorders inASD- diagnosticovershadowing

N=112(98malesor7:1ratio)meanageof11.5years• 50:PDD;62:childhoodautism

mostcommon disorders

• socialanxietydisorder(29.2%),ADHD (28.2%),andoppositional,defiantdisorder(28.1%).

identifysymptomconstellationsmeetingdiagnostic(DSM)criteria.• suggestthatASDdiagnosisshouldbefollowedby

systematicassessmentofotherpsychiatricconditions

• improvetargetedintervention

comorbidity

understood.7,8 Delineating psychiatric comorbidity mayidentify targets for specific intervention that couldreduce overall impairment and improve quality of life.The infrequent identification of comorbid psychia-

tric disorders in ASD may be due to the samediagnostic overshadowing identified for intellectualdisability in which psychiatric symptoms are attributedto the intellectual disability.9 Specific challenges tocomorbid psychiatric assessment in ASD are the wideIQ range and communication problems, which makepersonal interviewing difficult and may produceuncertainty among caregivers about their ability tomake inferences regarding mental state. Comorbidpsychiatric problems were first reported in a number ofstudies using unstandardized assessments10Y12 andsubsequently confirmed by questionnaires studies inboth children13Y15 and adults.16,17 These studiessuggest that as many as three fourths may reachthreshold for caseness,18 a finding supported by studiesusing structured interviews that show high rates ofanxiety19,20 and affective disorders.19,21,22 To date, thecommon, standardized psychiatric interview toolsavailable have not been used to identify otherpsychiatric disorders among children with ASDs.More recently Leyfer et al.23 reported high rates oflifetime psychiatric disorders in children with autism,using a new interview, the Autism ComorbidityInterview-Parent and Lifetime Version, modifiedfrom the Schedule of Affective Disorders and Schizo-phrenia for School-Age Children.24 With the mostcomprehensive coverage of psychiatric disorders, justless than three fourths met criteria for one or moreDSM-IV disorders, with the median number ofdiagnoses being three.However, none of the studies using standardized

assessments of psychiatric disorder have involvedpopulation-representative samples. In our epidemiolo-gical sample, two thirds of those receiving an ASDdiagnosis had not been diagnosed as such by localservices (although almost all of them had otherdiagnoses), indicating that clinical ascertainment isincomplete and possibly biased.1 We make use ofthis epidemiological sample of children with well-characterized ASD to determine whether the prevalenceof commonDSM-IV child psychiatric disorders is as highas previous reports suggest. We explore whether reportedchild, family, and contextual risk factors for psychiatricdisorders reported in children without ASDs are also

associated in this population. To our knowledge, this isthe first report of structured assessments using apopulation-derived sample.

METHOD

Sample

The Special Needs and Autism Project sample was drawn from atotal population cohort of 56,946 children. All of those with acurrent clinical diagnosis of pervasive developmental disorder (N =255) or considered to be at risk for being an undetected case byvirtue of having a Statement of Special Educational Needs (N =1,515) were surveyed using the Social Communication Question-naire (SCQ25). A Statement of Special Educational Needs is a legaldocument issued by U.K. education authorities when childrenrequire significant additional support in school due to any learning

TABLE 1Prevalence of DSM-IV Disorders

Disorder3-Mo Point

Prevalence/100 95% CI

Any disorder 70.8 58.2Y83.4Any main disordera 62.8 49.8Y75.9Any emotional disorderb 44.4 30.2Y58.7Any anxiety or phobic disordersc 41.9 26.8Y57.0Generalized anxiety disorder 13.4 0Y27.4Separation anxiety disorder 0.5 0Y1.6Panic disorder 10.1 0Y24.8Agoraphobia 7.9 3.0Y12.9Social anxiety disorder 29.2 13.2Y45.1Simple phobia 8.5 2.8Y14.1Obsessive-compulsive disorder 8.2 3.2Y13.1

Any depressive disorder 1.4 0Y3.0Major depressive disorder 0.9 0Y2.3Dysthymic disorder 0.5 0Y1.4

Oppositional or conduct disorder 30.0 14.9Y45.0Oppositional defiant disorder 28.1 13.9Y42.2Conduct disorder 3.2 0Y7.1

Attention-deficit/hyperactivitydisorder

28.2 13.3Y43.0

Other disordersd 24.7 14.1Y35.3Enuresis 11.0 4.1Y17.7Encopresis 6.6 1.8Y11.4Tourette syndrome 4.8 0.1Y9.5Chronic tic disorder 9.0 3.3Y14.6Trichotillomania 3.9 0Y10.3

Note: CIs = confidence intervals.a Includes attention-deficit/hyperactivity disorder, oppositional

and conduct disorders, and any emotional disorder.b Includes all anxiety disorders, phobias, and mood disorders.c Includes anxiety disorders, panic disorder, phobias, and

obsessive-compulsive disorder.d Includes Tourette syndrome, chronic tics, trichotillomania,

enuresis, and encopresis.

SIMONOFF ET AL.

922 WWW.JAACAP.COM J. AM. ACAD. CHILD ADOLESC. PSYCHIATRY, 47:8, AUGUST 2008

56

Commontargetsymptoms:

aggression/selfinjuriousbehaviour (SIB)/irritability

• neuroleptics,psychostimulants• Anticonvulsantmedications

inattentionandhyperactivity

• Methylphenidate(Ritalin),neuroleptics

anxietyandrepetitivebehaviors

• Fluoxetine(Prozac- antidepressant– SSRI)• Fluvoxamine(Luvox - antidepressant)• Risperidone/Aripiprazole(Risperdal/Abilify -

antipsychotic)

Sleepdisturbance,tics,depressionetc

oxytocin???• peptidesofthehumanneuroendocrinesystem• effectssocialcognition• clinicaltrials…

Interventions:behaviorsandpharmacology

McPheeters etal.,201157

earlyintensivebehavioralintervention

• UCLA/Lovaas model– ABA(Lovaas,1987).• a systematicapproachtoskillacquisition- discretetrialtraining(DTT)• reinforcementofspecificskill,brokendownandlearnedinstep-by-stepmanner• Pivotalresponsetraining(PRT)targetsskillsthatareimportant(orpivotal)formanyotherskills• http://www.youtube.com/watch?v=iyCx-OLzgJw

school-basedtreatmentapproaches

• TEACCH(treatmentandeducationofautisticandcommunicationrelatedhandicappedchildren): based onthe« autism culture »

• “structuredteaching”- deliveredwithinspecialeducationclassroomsettings.• usesstrengths(usuallyvisual)ofchild• http://www.youtube.com/watch?v=ddGLJ2r4rcw

socialinterventions

• socialskillsgroups

communicationinterventions

• sensoryintegrationtherapy– brushing(touch),weightedvests(proprio),swings,spinning(vestibular)

behavioralinterventions

58

http://www.thetransporters.com/

cognitioninautism:intelligence

CDC,2014,Tsatsanis,2011

longstandingnotionofintellectualimpairment,but…

largeCDCstudy(2014) :• 31%hadintellectualdisability(IQ≤70).• 23%wereintheborderlinerange(IQ=71-85).• 46%hadavg /aboveavg intellectualability(IQ>85).

unevenprofileinASDé Performance-basedIQ:i.e.,blockdesignê VerbalbasedIQ;i.e.,vocabulary

WechslerIntelligenceScales(WIS)• conventional• widelyavailable• relyonverbalinstructions

Dawsonetal.,2007;Soulieresetal.,2009

In contrast, autistics typically demonstrate a marked peak onone of the nonverbal subtests, Block Design. On the Block

Design subtest, the examinee is shown a two-dimensional red-and-white geometric design, and the task is to reproduce thatdesign by assembling a set of colored blocks. The Block Design

subtest is time limited and scored for accuracy.How should one interpret such peaks and troughs in autistics’

Wechsler subtest scores? One commonsense notion is that thepeaks correspond to the intellectual skills that epitomize autis-

tics, the cognitive tasks on which they excel. However, for manyyears, these peaks were classified as ‘‘islets of ability . . . regardedas something of a myth or else as merely an interesting but

theoretically unimportant fact’’ (Shah & Frith, 1993, p. 1351).Then, in the 1990s, the peaks were imbued with theoretical im-

portance. Exceptional performance on the Block Design subtest,along with exceptionality in rapidly disembedding a target figurefrom a complex background, drawing ‘‘impossible’’ figures, and

perceiving pitch, as well as many savant skills, were all inter-preted as a unified deficit: ‘‘weak central coherence,’’ the ten-

dency to focus on details at the expense of configuration (Happe,1999; Heaton, Hermelin, & Pring, 1998; Shah & Frith, 1983).

We empirically tested this construal of autistics’ intellectualstrengths as low-level perceptual penchants resulting from high-level conceptual deficits by administering an intelligence test

widely regarded to be a preeminent measure of high-level an-

alytical reasoning, the Raven’s Progressive Matrices (Raven,

Raven, & Court, 1998). This test comprises 60 items, dividedinto five sets of increasing complexity. All items have a similar

format: A matrix of geometric designs with one cell of the matrixleft blank is presented with six or eight alternatives for the

matrix’s completion. Minimal instruction is required for thisputatively nonverbal test.

The Raven’s Progressive Matrices has been empirically dem-

onstrated to assay the ability to infer rules, to manage a hierarchyof goals, and to form high-level abstractions (Carpenter, Just, &

Shell, 1990). Broadly recognized as a paramount metric of rea-soning and problem solving, the Raven’s Progressive Matrices is

believed to be a ‘‘paradigmatic’’ measure of fluid intelligence(Mackintosh, 1998, p. 228), and fluid-intelligence tasks are pro-posed to require coordinated executive function, attentional con-

trol, and working memory (Blair, 2006; Kane & Engel, 2002;Newman & Just, 2005). The Raven’s Progressive Matrices occu-

pies psychometric centrality among tests of cognitive ability; inSnow, Kyllonen, and Marshalek’s (1984) classic diagram, whichsummarizes the intercorrelations among numerous tests of cog-

nitive ability, simple, domain-specific tests lie along the periph-ery, and Raven’s Progressive Matrices occupies the center, as the

most complex and general single test of intelligence.Descriptions of the cognitive processes required to solve

Raven’s Progressive Matrices and to perform fluid-intelligencetasks read like compendia of the cognitive processes that au-tistics are assumed to lack. For example, whereas autistics are

expected to perform adequately on simple tests of executivefunction and working memory, they are expected to lack the

cognitive abilities required to perform well on more complexassays of cognition (Minshew, Webb, Williams, & Dawson,2006). Autistics are assumed to excel at tests of rote memory or

low-level pattern matching, but to be disproportionately chal-lenged by tests of high-level integration or abstraction (Cour-

chesne & Pierce, 2005; Just, Cherkassky, Keller, & Minshew,2004). Indeed, it has been specifically predicted that autistics

should be disproportionately impaired in fluid reasoning (Blair,2006; Pennington & Ozonoff, 1996), but this prediction hasnever been submitted to empirical scrutiny. Our goal was to

directly examine these claims.

METHOD

Subjects

Autistic ChildrenThis group comprised 38 autistic children (35 males, 3 females)between 7 and 16 years of age (M 5 10.39, SD 5 2.69). They

were diagnosed at the Pervasive Developmental DisordersSpecialized Clinic at Riviere-des-Prairies Hospital, Montreal,Canada. All met diagnostic criteria for autistic disorder, rather

than any of the other diagnostic categories of the Diagnostic andStatistical Manual of Mental Disorders, fourth edition (e.g.,

pervasive developmental disorder not otherwise specified or

Fig. 1. Mean subtest scores of the 38 autistic children on the WechslerIntelligence Scale for Children–Third Edition.

658 Volume 18—Number 8

Autistic Intelligence

cognitioninautism: WISCcognitiveprofile

NaderAM,Jelenic P,Soulières I(2015)

RelativeStrength:i.e.,BD- non-verbalreasoning,perceptualorganization,patternrecognitionRelativeWeakness:i.e.,CO- verbal,socialknowledge,socialobservationability,society'srules,etc.

presented no speech delay (first words at or before 24 months AND first phrases at or before36 months). Among the 30 Asperger children, 26 were characterized by both ADI-R andADOS-G, two by ADI-R only and two by ADOS-G only. Of the 28 Asperger participants whohad ADI-R, 25 scored above the cut-off for autism and three scored slightly under (1 in ADI--Communication area and 2 in ADI-Social area). All Asperger participants who had ADOS-Gscored above the cut-off for autism.

Typically developing children. Typically developing participants selected from the data-base were all recruited from the community (e.g. surrounding schools and community services)and had a typical academic background. Furthermore, they were screened using a semi-struc-tured interview; participants with a personal or family (1st degree) history of psychiatric, neuro-logical or other medical conditions potentially affecting brain development were identified andtheir data were excluded.

MeasuresTheWISC is an individually-administered test battery that assesses intelligence in school-agechildren (6 years to 16 years 11 months). The Wechsler Intelligence Scale for Children– 3rd

edition[17]comprises 10 core subtests that compute VIQ and PIQ, which, when combined,yield the FSIQ (M 100 and SD 15). The Verbal scale includes Vocabulary, Similarities, Compre-hension, Arithmetic and Digit Span subtests, whereas the Performance scale includes Block

Table 2. WISC-IV cognitive profile.

Autistic children Asperger children Typical children

Sample size (sex) 51 (49M, 2F) 15 (12M, 3F) 42 (29M, 13F)

Mean (SD) Mean (SD) Mean (SD)

Age 10.6 (2.7) 10.6 (2.6) 9.6 (2.3)

Range 7–15 7–15 6–15WISC-IV FSIQ 90.7 (12.4) 98.3 (12.4) 103.3 (13.5)

VCI 85.6 (16.1) 110.5 (10.5) 103.3 (16.3)

Similarities 8.4 (2.4) 12.5 (2.0)** 10.6 (3.3)

Comprehension 5.8 (3.0)* 9.3 (2.0) 9.2 (3.0)*

Vocabulary 8.2 (3.6) 13.3 (3.2)** 11.7 (3.5)**PRI 105.8 (13.3) 101.3 (15.9) 105.2 (11.7)

Block Design 11.0 (3.1)** 9.5 (2.5) 9.9 (3.2)*Matrix Reasoning 11.7 (2.9)** 10.4 (2.7) 10.8 (2.5)

Picture Concept 10.0 (2.8)** 10.5 (2.0) 11.6 (2.3)**

WMI 87.8 (16.9) 92.7 (15.0) 99.4 (12.6)

Digit Span 7.6 (3.3)* 8.3 (3.1) 9.2 (2.5)*

Letter-Number Sequencing 7.8 (3.2)* 9.3 (1.5) 9.2 (2.4)

PSI 91.5 (14.1) 85.2 (9.3) 101.6 (13.2)

Coding 7.7 (2.7)* 6.7 (1.9)* 10.2 (2.5)

Symbol Search 9.3 (3.3) 8.1 (2.0)* 10.5 (3.0)

WISC-IV: Demographic characteristics and cognitive profile of autistic, Asperger and typical children who completed the WISC-IV.*Relative weakness.**Relative Strength.FSIQ: Full Scale Intelligence Quotient, VCI: Verbal Comprehension Index, PRI: Perceptual Reasoning Index, WMI: working Memory Index, PSI:Processing Speed Index.

doi:10.1371/journal.pone.0144645.t002

WISC-IV Cognitive Profile in Autism Spectrum Children

PLOS ONE | DOI:10.1371/journal.pone.0144645 December 16, 2015 5 / 16

cognitioninautism:WISCvsRPMRavenProgressiveMatrices

assessfluidintelligence,reasoning&novelproblem-solvingabilities

self-paced

minimalverbalinstructions

PERCEPTION IN AUTISM

Does WISC-IV Underestimate the Intelligence of AutisticChildren?

Anne-Marie Nader • Valerie Courchesne •

Michelle Dawson • Isabelle Soulieres

! Springer Science+Business Media New York 2014

Abstract Wechsler Intelligence Scale for Children(WISC) is widely used to estimate autistic intelligence

(Joseph in The neuropsychology of autism. Oxford Uni-

versity Press, Oxford, 2011; Goldstein et al. in Assessmentof autism spectrum disorders. Guilford Press, New York,

2008; Mottron in J Autism Dev Disord 34(1):19–27, 2004).

However, previous studies suggest that while WISC-III andRaven’s Progressive Matrices (RPM) provide similar esti-

mates of non-autistic intelligence, autistic children perform

significantly better on RPM (Dawson et al. in PsycholSci 18(8):657–662, doi:10.1111/j.1467-9280.2007.01954.

x, 2007). The latest WISC version introduces substantial

changes in subtests and index scores; thus, we askedwhether WISC-IV still underestimates autistic intelligence.

Twenty-five autistic and 22 typical children completed

WISC-IV and RPM. Autistic children’s RPM scores weresignificantly higher than their WISC-IV FSIQ, but there

was no significant difference in typical children. Further,

autistic children showed a distinctively uneven WISC-IVindex profile, with a ‘‘peak’’ in the new Perceptual Rea-

soning Index. In spite of major changes, WISC-IV FSIQcontinues to underestimate autistic intelligence.

Keywords Autism ! Children ! Intelligence ! Wechslerscales ! Raven’s progressive matrices ! Abstract reasoning

Introduction

Autism is a neurodevelopmental variant often associatedwith intellectual disability, but at reported rates which vary

widely, even across autistic cohorts born at similar times in

the same country (e.g., 15 % in Williams et al. 2008, vs.55 % in Baird et al. 2006). The DSM-5 requires an autism

spectrum diagnosis to specify whether it is accompanied by

intellectual disability, yet the text refers to autistics’‘‘(often uneven) intellectual profile’’ (APA 2013, p. 51),

which suggests that assessing autistic intelligence is not

necessarily straightforward.1 Indeed, findings that themeasured intelligence of autistic individuals varies—

sometimes dramatically—according to which instrument is

used are among the most durable in the history of autismresearch, but also among the most overlooked as to their

full implications.Both Raven’s Progressive Matrices (RPM) and Wechs-

ler scales are major instruments used to estimate human

intelligence, yet they are strikingly different in how theyare structured and administered. Wechsler involves the

individual administration of several subtests, some of them

culture-specific, which assess a limited number of specificabilities considered to reflect latent general abilities. RPM

is a one-format 60-item matrix reasoning test which min-

imizes the need for task instructions, for culture- or expe-rience-specific abilities, and for other specific abilities

which may be important (e.g., fine motor or speech skills)

A.-M. Nader ! V. Courchesne ! M. Dawson ! I. Soulieres (&)Riviere-des-prairies Hospital, Centre d’Excellence en TroublesEnvahissants du Developpement de l’Universite de Montreal(CETEDUM), 7070 Blvd Perras, Montreal, QC H1E 1A4,Canadae-mail: [email protected]

A.-M. Nader ! V. Courchesne ! I. SoulieresPsychology Department, University of Quebec at Montreal,C.P. 8888, succursale Centre-Ville, Montreal H3C 3P8, Canada

V. CourchesnePsychology Department, University of Montreal, C.P. 6128,succursale Centre-ville, Montreal H3C 3J7, Canada

1 To reduce unhelpful biases, we use ‘‘autistic’’ and similar accurate,respectful terminology. See, e.g., Sinclair (1999).

123

J Autism Dev Disord

DOI 10.1007/s10803-014-2270-z

analyses were conducted on participant samples addition-ally matched on mean RSPM task response times. Thismatching process was achieved by excluding results fromthe three fastest autistic participants and the five slowestnon-autistic participants, resulting in equivalent meanresponse times in final groups comprising 12 autistic and13 non-autistic participants.

All participants gave written informed consent and werecompensated for their participation in accordance withprotocol # 06-07 018 approved by the Regroupement Neu-roimagerie/Quebec IRB. Exclusion criteria were: uncorrect-able visual impairment; current use of psychoactive orvasoactive medications; and use of drugs or alcoholexceeding 2 drinks per day. All structural scans werereviewed by a neurologist to rule out the presence of anyanatomical abnormalities. Additionally, non-autistics werescreened through a questionnaire for any personal or fami-lial neurological or medical conditions known to affectbrain function. Groups were matched on age, sex, manualpreference and full-scale IQ.

Clinical characterization

The autistic participants were recruited from theresearch database of the Pervasive Developmental Disor-ders Specialized Clinic of Riviere-des-Prairies Hospital(Montreal, Canada). A multidisciplinary evaluation basedon DSM-IV criteria is performed at the clinic, includingthe Autism Diagnostic Interview-Revised (ADI-R; Lord etal., 1994], the Autism Diagnosis Observation Schedulemodule 3 or 4 [ADOS-G; Lord et al., 2000], clinical evalua-tion and psychometric testing. Twelve autistic participantswere characterized with both standardized diagnosticinstruments, and three were characterized with the ADIand a clinical interview based on an ADOS-G assessment.Individuals with no history of speech delay, echolalia orpronoun reversal, and who therefore also met criteria forAsperger syndrome, were excluded from the sample.

Psychometric characterization

Full-scale IQ scores were derived from Wechsler Scalesof Intelligence (WISC-III or WAIS-III) scores; autistics inthe performance matched sample had a mean IQ of 101.5and non-autistics 105.31. The corresponding scores for theentire sample were 99.73 and 106.22. Manual preferencewas estimated using the Edinburgh Handedness Inven-tory. There was no significant difference between the twogroups in IQ or manual preference (Table I).

Task Descriptions

Pattern matching task

To allow comparison with a task requiring minimal rea-soning, we developed a self-paced 60-item pattern match-ing task that had similar spatial and temporal propertiesto the RSPM problems, with a target stimulus displayedabove 8 possible answers (Fig. 1A). The stimulus was pre-sented until the participant responded. In this self-paced,variable epoch length design, individual problem presenta-tions were separated by periods of fixation whose durationvaried from 4 to 7 sec, following an exponentialdistribution.

RSPM task

We used a slightly modified version of the original, 60-item, untimed, paper version of the RSPM. The RSPMproblems are matrices of related geometric designs, fromwhich the final (right-hand bottom) entry is missing andmust be chosen from an array of 8 possible answers (Fig.1B,C). In the original version of the test, simple or figuralitems at the beginning progress to more difficult and com-plex analytic items. We made modifications to the originalRSPM by: (1) horizontally shifting the rows of possibleanswers, respectively to the left and right, to simplify themapping of answers made by pressing buttons with theleft or right hand; and (2) reducing non-specific temporaleffects by presenting the 60 RSPM items in a

Figure 1.Sample stimuli for the pattern matching and RSPM tasks. (A) Pattern matching problems requiredmatching the global pattern presented at the top of the screen with one of the patterns presented inthe 2 rows below. (B) and (C) RSPM task problems were the 60 items of Raven’s Standard ProgressiveMatrices. The task required selecting the correct answer from the alternatives presented at the bottomof the screen. An example of a figural problem is shown in (B) and of an analytic problem in (C).

r Reasoning in Autism r

r 4085 r







Task Descriptions



RSPM task




r 4085 r







Task Descriptions



RSPM task




r 4085 r

Pattern

Figural

Analytical

significantly higher than their FSIQ, VCI, WMI, and PSI

(all p \ .05).The typical children also showed discrepancies between

indexes but with a different profile (p \ .001, n2 = .257).

Their mean FSIQ was 110.3 (SD 14.8), with similar PRI(110.7; SD 12.4), VCI (112.8; SD 18.3) and PSI (105.3; SD

13.2) scores. Their WMI (99.9; SD 11.9) score was sig-

nificantly lower than their FSIQ (p \ .05), PRI (p \ .001)and VCI (p \ .05). See Table 2 for WISC-IV FSIQ and

index scores in both groups.

RPM Versus WISC-IV: Group Percentile Comparison

The autistic child group’s RPM score was at the 60th

percentile, compared to WISC-IV FSIQ at the 21st per-

centile, which represents a discrepancy of 39 percentilepoints between tests. For the typical child group, RPM

score was at the 73rd percentile, very close to their full-

scale WISC-IV score, at the 75th percentile. See Fig. 1,which also shows group WISC-IV index scores in

percentiles.

RPM Versus WISC-IV: Individual Percentiles

Individual scores on RPM and full-scale WISC-IV areshown for autistic and typical children in Fig. 2.

While no autistic child scored over the 90th percentile

on WISC-IV, more than one-fourth (28 %) did on RPM;and while only 28 % of the autistic children scored at or

above the 50th percentile on the WISC-IV, nearly two-

thirds (64 %) of the group did so on RPM. Four (16 %) ofthe autistic children would be judged as intellectually

disabled according to their WISC-IV scores, but none

would be so judged on RPM. Indeed, all autistic childrenscoring in the WISC-IV intellectual disability range per-

formed at the 10th percentile or higher on RPM. Finally,

only 20 % of the autistic children showed a discrepancy of10 percentiles or less between the two tests, while 20 %

displayed a discrepancy of 50 percentile points or more,

their RPM scores being higher. In contrast, the majority(64 %) of the typical children showed an under-10 per-

centile point difference between the two tests, and only one

typical child achieved a discrepancy greater than 50 per-centile points between full-scale WISC-IV and RPM

scores.

In statistical comparisons, Wilcoxon signed-rank testsindicated that the autistic children’s RPM scores were

significantly higher than their WISC-IV full scale IQ

(p \ .0005; r = .611), VCI (p \ .0005; r = .618), WMI(p \ .005; r = .438) and PSI (p \ .0005, r = .605) scores.

The only WISC-IV index score that did not significantly

differ from their RPM score was the PRI (p = .14). Unlikethe autistic children, the typically developing children did

Fig. 1 For each group, performance in percentiles on WISC-IVFSIQ, the 4 WISC-IV indexes, and RPM

Fig. 2 Distribution of individual scores on full-scale WISC-IV andRPM in percentiles for a autistic and b non-autistic (typical) children.Data points to the left of the lower diagonal lines representparticipants whose RPM scores were greater than their full-scaleWISC IV scores; data points to the left of the top diagonal linesrepresent participants whose RPM scores were more than 50percentile points greater than their full-scale WISC-IV scores

J Autism Dev Disord

123

ASD = widespread disorder of association cortex, development of connectivity,only secondarily as a behavioral disorder

“systems-levelapproach“

abnormalitiesingeneticcodeforbraindevelopment¯

abnormalmechanismsofbraindevelopment¯

structuralandfunctionalabnormalitiesofbrain¯

cognitiveandneurologicabnormalities¯

behavioralsyndrome

neurogenetic condition:wherepolygeneticchangesaffectdevelopmentoftheneuralnetworksunderlyingaffect,cognition,language andperception,

• definethepathophysiologyfromgenetobehavior• ultimatelysupportthedevelopmentofinterventionsatmultiplelevelsof

thesequence(medication,cognitionbehaviour).

origin:functionalconnectivity(FC)hypotheses

Transitioning:employment

SpecificchallengesfacedbyadultswithASDinthecontextofjobseekingandemploymentaremanyandvaried;

• understandingcomplexjobapplicationmaterials• ‘thinkingontheirfeet’inaninterview• acclimatizingtonewproceduresandroutines• remembering andfollowing instructions• respondingflexiblytounexpected situations• planningandjugglingmultipletasks

• communicatingeffectively/interactingsocially withco-workers;• managingsensorysensitivitiesintheworkplace

EmploymentinwhichadultswithASDmayperformextremelywell;• workrequiring visualthinking• systematicinformationprocessingorprecisetechnicalabilities(e.g.architect,librarian,computerprogrammer).

caremustbetakennottostereotypethevocationalinterestsandcapabilities ofadultswithASD

StudiessuggestthatthatadultswithASDexhibitmanyexemplarycharacteristicsasemployees;• honesty,efficiency,precision,consistency,lowabsenteeism,andadisinterest in‘officepolitics’

However… areemployerssensitivetoabilitiesandchallengesofadultswASDintheworkplace?

63

Transitioning:employment

large-scalestudylookingintotheworkinglivesofadultswhohaveanautismspectrumdisorderwithnoco-occurringintellectualdisability.

havingajobisnotsimplyameanstoanend($),rather,adultswithADandHFA(likemanyotherpeople)viewworkprimarilyasanopportunitytoapplytheirknowledge,skillsandinterestsinawaythatisbothself- fulfillingandhasintrinsicvalue. BUT...

• 72%ofparticipantsreportednotreceivinganyspecificsupportatworkforASD-relateddifficulties

• 66%would havelikedsuchhelp(i.e.,employer,agencies,etc.) 64

ORIGINAL PAPER

Employment Activities and Experiences of Adultswith High-Functioning Autism and Asperger’s Disorder

Susanna Baldwin • Debra Costley • Anthony Warren

Published online: 9 April 2014! Springer Science+Business Media New York 2014

Abstract There is limited large-scale empirical researchinto the working lives of adults who have an autism spectrum

disorder with no co-occurring intellectual disability. Drawing

on data from a national survey, this report describes theemployment activities and experiences of 130 adults with

Asperger’s Disorder (AD) and high functioning autism (HFA)

in Australia. Outcome measures include current occupation;occupational skill level and alignment with educational

attainment; type of job contract; hours of work; support

received to find work; support received in the workplace; andpositive and negative experiences of employment. The find-

ings confirm and expand upon existing evidence that adults

with AD and HFA, despite their capacity and willingness towork, face significant disadvantages in the labour market and

a lack of understanding and support in employment settings.

Keywords Autism ! Asperger’s Disorder ! Highfunctioning ! Employment ! Overeducation

Introduction

Numerous research studies have found that adults with

autism spectrum disorders (ASD) experience challenges in

securing and sustaining competitive employment (Barnhill2007). As a group, they are more likely to be unemployed

(without a job), underemployed (in jobs that underutilise

their knowledge, skills and experience) and ‘malemployed’(in jobs for which they are expressly unsuited) than the

population at large (Romoser 2000; Muller et al. 2003;

Hurlbutt and Chalmers 2004; Robertson 2010; Seltzer et al.2011). Related to this, they demonstrate a comparatively

high level of job switching, resulting in fragmented work

histories that may limit their potential for ongoingemployment and career development, and in turn contrib-

ute to stress, depression, isolation, and financial insecurity

(Goode et al. 1994; Muller et al. 2003).The specific challenges faced by adults with ASD in the

context of job seeking and employment are many and

varied. They may include understanding complex jobapplication materials; ‘thinking on their feet’ in an inter-

view; acclimatising to new procedures and routines;

remembering and following instructions; responding flex-ibly to unexpected situations; planning and juggling mul-

tiple tasks; communicating effectively with co-workers;interacting socially; and managing sensory sensitivities in

the workplace (Beardon and Edmonds 2007; Hillier et al.

2007; Stuart-Hamilton et al. 2009; Robertson 2010).Stankova and Trajkovski (2010) note that these gener-

alised deficits mean some types of work are likely to be

unsuitable for the majority of adults with ASD. Forexample, they may not cope well in jobs that require

immediate and rapid processing of requests or demands,

such as a cashier, a cook, a waiter or a receptionist. Theyare also more likely to struggle in busy or noisy environ-

ments, such as fast food restaurants and factories.

On the other hand, there are jobs in which adults withASD may perform extremely well; notably those requiring

visual thinking, systematic information processing or

This study was approved by the Autism Spectrum Australia (Aspect)Research Approvals Committee.

S. Baldwin ! D. Costley (&) ! A. WarrenAutism Spectrum Australia (Aspect), PO Box 361, Forestville,NSW 2087, Australiae-mail: [email protected]

S. BaldwinAutism Spectrum Australia (Aspect), PO Box 770, Seven Hills,NSW 1730, Australiae-mail: [email protected]

123

J Autism Dev Disord (2014) 44:2440–2449

DOI 10.1007/s10803-014-2112-z

ORIGINAL PAPER

Employment Activities and Experiences of Adultswith High-Functioning Autism and Asperger’s Disorder

Susanna Baldwin • Debra Costley • Anthony Warren

Published online: 9 April 2014! Springer Science+Business Media New York 2014

Abstract There is limited large-scale empirical researchinto the working lives of adults who have an autism spectrum

disorder with no co-occurring intellectual disability. Drawing

on data from a national survey, this report describes theemployment activities and experiences of 130 adults with

Asperger’s Disorder (AD) and high functioning autism (HFA)

in Australia. Outcome measures include current occupation;occupational skill level and alignment with educational

attainment; type of job contract; hours of work; support

received to find work; support received in the workplace; andpositive and negative experiences of employment. The find-

ings confirm and expand upon existing evidence that adults

with AD and HFA, despite their capacity and willingness towork, face significant disadvantages in the labour market and

a lack of understanding and support in employment settings.

Keywords Autism ! Asperger’s Disorder ! Highfunctioning ! Employment ! Overeducation

Introduction

Numerous research studies have found that adults with

autism spectrum disorders (ASD) experience challenges in

securing and sustaining competitive employment (Barnhill2007). As a group, they are more likely to be unemployed

(without a job), underemployed (in jobs that underutilise

their knowledge, skills and experience) and ‘malemployed’(in jobs for which they are expressly unsuited) than the

population at large (Romoser 2000; Muller et al. 2003;

Hurlbutt and Chalmers 2004; Robertson 2010; Seltzer et al.2011). Related to this, they demonstrate a comparatively

high level of job switching, resulting in fragmented work

histories that may limit their potential for ongoingemployment and career development, and in turn contrib-

ute to stress, depression, isolation, and financial insecurity

(Goode et al. 1994; Muller et al. 2003).The specific challenges faced by adults with ASD in the

context of job seeking and employment are many and

varied. They may include understanding complex jobapplication materials; ‘thinking on their feet’ in an inter-

view; acclimatising to new procedures and routines;

remembering and following instructions; responding flex-ibly to unexpected situations; planning and juggling mul-

tiple tasks; communicating effectively with co-workers;interacting socially; and managing sensory sensitivities in

the workplace (Beardon and Edmonds 2007; Hillier et al.

2007; Stuart-Hamilton et al. 2009; Robertson 2010).Stankova and Trajkovski (2010) note that these gener-

alised deficits mean some types of work are likely to be

unsuitable for the majority of adults with ASD. Forexample, they may not cope well in jobs that require

immediate and rapid processing of requests or demands,

such as a cashier, a cook, a waiter or a receptionist. Theyare also more likely to struggle in busy or noisy environ-

ments, such as fast food restaurants and factories.

On the other hand, there are jobs in which adults withASD may perform extremely well; notably those requiring

visual thinking, systematic information processing or

This study was approved by the Autism Spectrum Australia (Aspect)Research Approvals Committee.

S. Baldwin ! D. Costley (&) ! A. WarrenAutism Spectrum Australia (Aspect), PO Box 361, Forestville,NSW 2087, Australiae-mail: [email protected]

S. BaldwinAutism Spectrum Australia (Aspect), PO Box 770, Seven Hills,NSW 1730, Australiae-mail: [email protected]

123

J Autism Dev Disord (2014) 44:2440–2449

DOI 10.1007/s10803-014-2112-z

moment’; (3) ‘I think I will need more support with this in

the future’; (4) ‘I don’t need any support with this’.

Support Received in the Workplace

Participants were asked to respond ‘Yes’ or ‘No’ to the

question: ‘‘Are you receiving any support at work related to

your autism spectrum disorder?’’ Those who responded‘Yes’ were asked to provide brief details about the kind of

support they were receiving.In a separate survey item, participants were asked to

respond ‘Yes’ or ‘No’ to the question: ‘‘Would you like to

have more support at work?’’ Participants could answer‘Yes’ to this question even if they had previously stated

that they were currently receiving support. Those who

responded ‘Yes’ were asked to provide brief details aboutthe kind of support they would like to receive.

Positive and Negative Experiences of Employment

Participants were asked to provide a brief written

description of the ‘‘three best things’’ and ‘‘three worstthings’’ about their work and employment experiences to

date. A coding framework was subsequently devised to

group the responses into thematic categories. The frame-work was drafted by one of the authors and reviewed by

colleagues to ensure agreement on the conceptual grouping

of responses. The data coding process was undertaken byindividual members of the research team, following which

selected portions of coding were checked and verified by a

colleague. Any instances of disputed codes were discussedverbally until agreement was reached.

Results

Type of Occupation

All eight of the ANZSCO major occupational groups were

represented in the study sample (Table 2). The highestproportions of participants were found in the groups

Clerical and Administrative Workers, Labourers, and Pro-

fessionals, which between them accounted for over two-thirds (68 %) of the adults in the study.

Participants were employed in a wide range of specific

occupations within these high-level groupings. Whilst therewas a notable trend towards scientific, technical, and

information-based jobs within the study sample (e.g. ICT

technicians, business analysts, and administrators), therewere also many professions that did not conform to these

more ‘stereotypical’ categories associated with adults with

ASD, including teaching, complementary medicine, hos-pitality and catering, retail, and gardening.

Qualifications, Occupational Skill Level

and Overeducation

Table 3 shows the distribution of participants by highest

educational qualification to date.

Table 4, in the column headed ‘All’, shows the distri-bution of participants across occupational skill levels in

respect of their current employment. The majority of par-

ticipants were distributed between jobs at skill levels 1, 4and 5, with smaller numbers working in jobs aligned with

skill levels 2 and 3.

The subsequent columns in Table 4 break down partic-ipants into three groups according to the match (or mis-

match) between their occupational skill level and their

highest qualification level. Participants were classed asbeing ‘at parity’ if the skill level equivalent to their highest

educational qualification matched the skill level of their

current job as specified by ANZSCO. They were classed as‘undereducated’ if their highest qualification fell below the

skill level of their current job, and as ‘overeducated’ if it

exceeded it.

Table 2 Occupation by ANZSCO major group

Occupation major group n %

Clerical and administrative workers 29 22.8

Labourers 29 22.8

Professionals 28 22.0

Technicians and trades workers 16 12.6

Community and personal services workers 12 9.4

Managers 7 5.5

Sales workers 3 2.4

Machinery operators and drivers 3 2.4

Total 127 100

Missing data: n = 3

Table 3 Highest qualification

AQF qualification level ANZSCO skilllevelequivalent

n %

Bachelor degree or higher 1 24 19.4

TAFE Diploma or Advanced Diploma 2 36 29.0

TAFE Certificate III–IV 3 14 11.3

TAFE Certificate II–III or HSC 4 38 30.6

TAFE Certificate I or SchoolCertificate

5 12 9.7

Total 124 100

Missing data: n = 6

2444 J Autism Dev Disord (2014) 44:2440–2449

123

In total, 26 % of the study participants were found to be

at parity relative to the skill requirements of their jobs,while 28 % were working in jobs whose skill requirements

exceeded those of their formal qualifications (most likely

indicating that they had gained additional skills throughexperience and/or on-the-job training). The remaining

46 % of participants were classed as overeducated.

Job Contract and Hours of Work

Table 5 shows the distribution of participants across typesof job contract and range of hours normally worked per

week.

A comparison of these data with national employmenttables suggests, in the first place, that adults with AD and

HFA are overrepresented in casual positions of employ-

ment. As indicated in Table 6, 32 % of study participantswere working on a casual basis at the time of the survey; in

contrast, 21 % of the Australian labour force as a whole ismade up of casual workers (ABS 2012a). The rate of casual

employment within the study sample increases to 35 %

when the self-employed group is excluded (as it is in the

ABS calculation). Conversely, the proportion of permanent

and fixed-term employees in the study population (61 %when the self-employed group is excluded) is notably

lower than the corresponding national table of 79 % (ABS

2012a).Within the study sample, casual employment was

strongly associated with lower skilled work: 83 % of

individuals working on casual contracts were in jobsequating to ANZSCO skill level 4 or 5.

In addition, it appears that adults with AD and HFA tend

to work reduced hours relative to the population as awhole. Table 6 indicates that 29 % of study participants

were working 15 h or less per week at the time of com-

pleting the survey, while approximately half (51 %) were

Table 4 Occupational skilllevel, overeducation andundereducation

Missing data: n = 13a Small numbers should benoted and row percentagesregarded with due caution

Occupational skill level (current job) All Parity Undereducated Overeducated Row total

1 n 36 10 26 – 36

% 30.8 27.8 72.2 – 100

2a n 10 5 4 1 10

% 8.5 50.0 40.0 10.0 100

3a n 7 – 1 6 7

% 6 – 14.3 85.7 100

4 n 31 7 2 22 31

% 26.5 22.6 6.5 71.0 100

5 n 33 8 – 25 33

% 28.2 24.2 – 75.8 100

Column total n 117 30 33 54 117

% 100 25.6 28.2 46.2 100

Table 5 Type of job contractand normal weekly hours

Missing data: n = 3 (contract);n = 1 (hours)

n %

Type of job contract

Permanent 65 51.2

Fixed-term 8 6.3

Casual 40 31.5

Apprenticeship 3 2.4

Self-employed 11 8.7

Total 127 100.0

Normal weekly hours

1–15 37 28.7

16–30 26 20.2

31? 66 51.2

Total 130 100.0

Table 6 Positive experiences of employment

Theme Sub-themes %

Self-actualisation Opportunity to apply and developknowledge, skills and interests

Freedom to be independent, autonomous orcreative

Sense of being accepted and valued

Making a difference in the lives of others orin society

65

Social andcollegialfactors

Positive relationships with colleagues

Enjoyable interactions with clients andcustomers

45

Job roles andwork content

Enjoyment of particular job roles and worktasks

Favourable working conditions (e.g.physical Environment, location, hours ofwork)

36

Pay and benefits Earning money

Benefits and ‘perks’ (e.g. leave allowance,company car, travel opportunities)

28

J Autism Dev Disord (2014) 44:2440–2449 2445

123

working 31 h or more. In contrast, the most recent national

data showed that just 11 % of the overall Australianworkforce was working 15 h or less per week, with 69 %

working 30 h or more (ABS 2012b).

Past, Present and Future Job-Seeking Support

Fewer than half (41 %) of participants indicated that theyhad received any kind of assistance or support to get their

current job. Within this group, 32 % of individuals hadbeen supported by Disability Employment Services and

19 % by Centrelink. In addition, 30 % reported having

received informal support from their family or friends.3

Over half (54 %) of participants indicated a need for

some level of support to help them find a (new) job, either

presently or in the future. There was no significant rela-tionship between the skill level of an individual’s current

job and their expression of a need for job seeking support.

Of this group, 37 % stated that they were alreadyreceiving an adequate level of support to find a (new) job.

Support Received in the Workplace

Almost three quarters (72 %) of participants stated that

they were not currently receiving any specific support atwork for difficulties associated with their ASD. Of the

subset of respondents who were receiving support and who

provided further information about this (n = 29), only fourreferred to assistance from external agencies. Other com-

ments generally related to specific accommodations and

adjustments made within the workplace, including modi-fications to job content and working conditions (e.g.

offering flexible hours, arranging special lighting, permit-

ting exemption from customer-facing tasks) and tailoredsupervision strategies (e.g. providing written instructions,

‘checking in’ regularly, showing leniency when the indi-

vidual is having a ‘bad day’).Approximately two-thirds (66 %) of participants indi-

cated that they would like to receive more support at work

related to their ASD. Those who elaborated on this answerwith written comments tended to convey a strong desire for

greater recognition, understanding and respect of their

needs within the workplace by others. A further subsetwithin this group consistently noted a need for more

effective support in developing their social and communi-

cation skills, as well as the desire to access workplacecounselling.

Positive and Negative Experiences of Employment

Participants recorded a total of 347 positive comments

(‘best things’) and 309 negative comments (‘worst things’)

relating to their past and present employment experiences.Following the review and coding process described in the

Method section, the positive comments were categorised

into four key themes (Table 6) and the negative commentsinto six key themes (Table 7). The tables indicate, for each

theme, the proportion of participants who recorded at least

one comment classified to that theme.4

Three of the themes identified in these analyses

appeared to bear some relationship to participants’ occu-

pational skill level. First, the higher the designated skilllevel of an individual’s job, the more likely they were to

describe work as a means of self-actualisation, and to

identify this as one of the ‘three best things’ about theiremployment experiences to date. 84 % of participants

working at skill level 1 recorded a comment coded to this

theme, in contrast to 64 % of those at skill level 4 and53 % of those at skill level 5 (v2 = 8.372, p \ 0.05).5

Table 7 Negative experiences of employment

Theme Sub-themes %

Job roles and workcontent

Dissatisfaction with job roles and worktasks (e.g. boring, repetitive orunfulfilling work)

Poor working conditions (e.g. physicalenvironment, location, hours of work)

49

Workingrelationships

Misunderstanding, criticism, ill-treatment or exclusion by others

Difficulties in communicating with orrelating to others

46

Health and well-being issues

ASD-specific issues (e.g. sensorysensitivities, anxiety)

Other physical and mental healthconcerns

35

Performance anddevelopment issues

Lack of adequate instruction, training orsupport

perceived unfair discipline or dismissal

21

Organisationalfactors

Unfavourable organisational systemsand practices (e.g. bureaucracy,favouritism)

Negative workplace culture (e.g. highturnover, excessive ‘office politics’)

14

Pay and conditions Unsatisfactory pay

Poor employment conditions (e.g. notenough leave)

5

3 Percentages are not mutually exclusive due to instances of multiplesources of support being accessed.

4 As participants could record up to three comments in both the‘positive’ and ‘negative’ streams, the percentages shown in Tables 6and 7 are not mutually exclusive and do not sum to 100.5 Participants working at skill levels 2 and 3 were excluded from thisand the following analysis due to small numbers.

2446 J Autism Dev Disord (2014) 44:2440–2449

123

bornin1933:@2/3yearsofage• unusualmemoryforvisualinformation• happywhenalone,avoidedcontact• movement/languagenotspontaneous- repetitivebehaviors(hands,fingers,etc.),echolalia,etc.

in2010waslocated…• learnedtogolf(23years),driveacar(25years),avidtraveler,etc.• spontaneouslanguageproduction,routineimportant,etc.

protectivefactorsinfluencedthenatureandcourseofdevelopment…• family�ssocio-economic($)• socialsituation- acceptedasdifferent/smallcircleoffriends/samefriendsallhislife,etc.

Case#1 :« DonaldT »in2010,77yearsold

Finalthoughts…development

TheAtlantic,2010 65

SuggestedReadingandResources

SuggestedReading:

•Autism:Averybriefintroduction,Uta Frith•TheAutisticBrain,TempleGrandin•LookMeintheEye,JohnElderRobison•TheReasonIJump,NaokiHigashida &DavidMitchell•Thecuriousincidentofthedoginthenight-time,MarkHaddon•LoveAnthony,LisaGenova

Resources:

www.autismspeak.org

https://sfari.org

http://www.theabilityhub.org/

66

THANK YOU

67

Documents

Understanding neurodevelopmental conditions : What parents ... · during the critical period, taking advantage of the brain’s plasticity to set development on the right course