ADHD Symptoms in Children With Mild Intellectual Disability

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  • Copyright @ 2007 American Academy of Child and Adolescent Psychiatry. Unauthorized reproduction of this article is prohibited.

    ADHD Symptoms in Children With MildIntellectual Disability




    Objectives: To determine whether the nature and correlates of attention-deficit/hyperactivity disorder (ADHD) symptoms

    are different in subjects with mild intellectual disability (ID) compared to subjects with average ability. Method: From a

    general population sample of 2,726 12- to 15-year-olds, a stratified subsample was selected to enrich for mild ID. A total of

    192 subjects were included in the analyses. ADHD symptoms and other emotional/behavioral problems were measured

    with the parent and teacher Strengths and Difficulties Questionnaire and IQ with the WISC-III-UK), and social

    communication difficulties were assessed by a short version of the Social Communication Questionnaire and academic

    attainments by the Wechsler Quicktest. Results: There was a negative linear relationship between ADHD symptoms and

    IQ (" =j.087, p < .001). The relationship could not be explained by inappropriate rater expectations. Neither the profiles of

    ADHD symptoms nor the comorbidity with emotional/behavioral problems differed according to the presence of ID. When

    IQ was accounted for, the group difference in attainments was nonsignificant. Conclusions: ADHD symptoms are

    increased in people with ID. We found no evidence that this increase can by explained by inappropriate expectations or by

    confounding associations with other emotional/behavioral or cognitive problems. J. Am. Acad. Child Adolesc. Psychiatry,

    2007;46(5):591Y600. Key Words: attention-deficit/hyperactivity disorder, mental retardation, epidemiology, comorbidity,

    childhood, intellectual disability.

    Hyperactivity syndromes and disorders (DSM-IVattention-deficit/hyperactivity disorder [ADHD] andICD-10 hyperkinetic disorder [HKD]) include symp-toms of overactivity, inattention, and impulsivity. Asneuropsychiatric conditions, it is assumed that ADHDand HKD also affect cognition. It has long been

    recognized that children with ADHD have as a groupIQs that are roughly 7 to 12 points below the popu-lation mean (Crosbie and Schachar, 2001; Mariani andBarkley, 1997). However, it is not clear whether themean difference is due to an overall shift in the IQdistribution among those with ADHD or to an increasein ADHD among those with intellectual disability(ID). Within the average intelligence population,ADHD symptoms are correlated with lower ability(Kuntsi et al., 2004), but it is not known whether thisrelationship continues into the mental retardation orID range.Previous epidemiological studies of ADHD and

    HKD have suggested these disorders may be increasedin individuals with ID, but there are flaws with eachstudy. Emerson (2003) used the 1999 Survey of theMental Health of Children and Adolescents in GreatBritain (Meltzer et al., 2000) to report rates of HKD inthose with global learning disability of 8.7% comparedto 0.9% to the rest of the general population sample, a10-fold increase in risk. However, the definition of

    Accepted December 3, 2006.Dr. Simonoff and Ms. Wood are with the Department of Child and

    Adolescent Psychiatry, King_s College London, Institute of Psychiatry, London;Dr. Pickles is with the Biostatistics Group, Division of Epidemiology and HealthScience, University of Manchester, Manchester, UK; Dr. Gringras is with Guy_sand St. Thomas_ Hospitals NHS Trust, London; and Dr. Chadwick is with theDepartment of Psychology, King_s College London, Institute of Psychiatry,London.

    This study was supported by project grant 058599 from the Wellcome Trust toDr. Simonoff. The authors thank all of the young people and families whoparticipated in the study and also the researchers who collected the data.

    Correspondence to Dr. Emily Simonoff, Department of Child and AdolescentPsychiatry, Box 85, Kings College London, Institute of Psychiatry, De CrespignyPark, London SE5 8AF, UK; e-mail:

    0890-8567/07/4605-05912007 by the American Academy of Childand Adolescent Psychiatry.

    DOI: 10.1097/chi.0b013e3180323330


  • Copyright @ 2007 American Academy of Child and Adolescent Psychiatry. Unauthorized reproduction of this article is prohibited.

    learning disability employed was not based on anintellectual ability measure but rather used parentalaccounts of serious learning concerns and/or attendanceat schools for learning difficulties, provided teacherinformation was not contradictory. A Dutch study usedthe Diagnostic Interview Schedule for Children toassess a large sample of Dutch school-age childrenattending special schools for the educable (IQ ~60Y80)and trainable (IQ

  • Copyright @ 2007 American Academy of Child and Adolescent Psychiatry. Unauthorized reproduction of this article is prohibited.

    of the Cognitive Abilities Test (CAT; Thorndike and Hagen, 1986).This represented 92.3% of the students on the rolls of theparticipating schools. The CAT is a paper-and-pencil test ofintellectual ability. We used four subtests: verbal classification,sentence completion, figure classification, and figure synthesis. Theitems for the age-appropriate level (level D) were augmented withtwo items from each of the three lower levels (A, B, and C) toimprove scoring at the lower end of the distribution. A total scorebased on all four subtests was regressed against age in months. Thisage-regressed score correlated 0.76 with Full Scale IQ on the WISC-III-UK in the present study. A stratified random sample was drawnfor in-depth evaluation, selecting all of those scoring in the lowest5th centiles of the CAT (high-risk group, n = 133), 17% from thosescoring between the 6th and 25th centiles (moderate-risk group, n =93), and 3% of those scoring above the 25th centile (low-risk group,n = 78). The study received ethical approval from the Institute ofPsychiatry/South London and Maudsley Trust and the Guy_sHospital Research Ethics Committees.


    The in-depth psychometric assessment used nine WISC-III-UKsubtests (Wechsler, 1992): vocabulary, similarities, information,comprehension, and digit span as verbal subtests and picturecompletion, picture arrangement, object assembly, and block designas the nonverbal subtests. Verbal IQ was substituted for Full ScaleIQ for three children unable to complete many of the performancesubtests because of physical disability. The Wechsler Quicktest(Wechsler, 1996) was used to assess attainments. Eight subtests ofthe Children_s Memory Scale (Cohen, 1997) were included to assessboth immediate and delayed verbal and visual recall as well asdelayed recognition: dot locations, stories, faces, and word pairs,immediate and delayed.Children_s emotional and behavioral problems were screened

    using the parent-, teacher-, and self-report versions of the Strengthsand Difficulties Questionnaires (SDQ) giving scales of emotional,conduct, hyperactivity and peer relationship problems, andprosocial behavior (Goodman, 1997). Only the parent and teacherresponses were used in the present analyses because the self-reportmeasure has not been validated among those with ID. The SDQ iswidely used as a brief screening instrument for child psychiatricproblems and its psychometric properties have been established inseveral samples, including the United Kingdom (Goodman, 2001)and the United States (Bourdon et al., 2005). The five hyperactivity(ADHD) items were restless, overactive, cannot stay still for long;constantly fidgeting or squirming; easily distracted, concentrationwanders; thinks things out before acting (reverse-scored); and seestasks through to the end, good attention span (reverse-scored). Atotal (parent + teacher) score was generated; where data from onesource but not the other were missing (in 12 parent and 14 teacherSDQs), an imputed score from that informant was generated basedon the score from the other informant. This was possible because ofthe relatively high correlation (0.53) between parent and teacherscores. The mean imputed parent score for hyperactivity was 4.40and was the same for the unimputed mean; for teachers, theimputed mean was 4.37 compared with 4.49 for the unimputedscores. The published algorithms employing parent and teacherSDQ scores (Goodman et al., 2004) was used to generate thetrichotomous classification of unlikely, possible, and probableHKD. This classification was collapsed into a binary grouping ofdubious (including the unlikely and possible cases) and probablecategories. These algorithms have been compared with research

    diagnoses from the semistructured Development and Well-beingAssessment; for HKD, the combined parent-teacher algorithmshowed a sensitivity of 85% to 87% (Goodman et al., 2000).Hyperactivity subscales from parent and teacher questionnaires weregenerated: overactivity (restless, fidgets; cannot stay still for long)scores ranged from 0 to 8; inattention (easily distracted; goodattention span) 0 to 8; and impulsivity (thinks things through beforeacting) 0 to 4. The impact scale for the SDQ was calculated fromthe sum of responses to four questions from the stem BDo thedifficulties interfere with the child_s life in the following areas?[Respondents rated this on a 4-point scale (0 = not at all, 1 = only alittle, 2 = quite a lot, 3 = a great deal). Parents were asked to rate thisin relation to home life, friendships, classroom learning, and leisureactivities, whereas teachers rated the last three only. In addition, thequestion BDo the difficulties upset or distress your child?[ (rated onthe same 4-point scale) was added to the impact score. Parentalimpact scores ranged from 0 to 15 and teacher impact scores from 0to 12.Comorbid emotional and behavioral problems were examined

    using the SDQ domains of emotional and conduct symptomscombined for parents and teachers as described for hyperactivity.The total score on an abbreviated (20 items) version of the parent-reported Social Communication Questionnaire (Rutter et al., 2003)was used as an index of autism spectrum symptoms. Theabbreviated version was developed jointly with the first author ofthe original version (M.R.) and included items with high loadingsfrom each of the four domains described in the original factoranalysis (Berument et al., 1999). The purpose of including thisabbreviated measure was to gain a dimensional measure of autismspectrum symptoms, which are known to be associated with ID.The inclusion of this scale in the present analyses allowedexploration of the relationship between ADHD and autisticsymptoms, which many clinicians believe is stronger than wouldbe expected by chance. All of the behavioral scales were prorated ife30% items were missing.


    Data reduction was implemented using SAS version 8.1/8.2.Two stages of adjustment were made. The first stage was to accountfor the nonparticipation of some schools and of some individualswithin participating schools. The second stage was to account forthe CAT score selective two-phase sampling design. In the first stagethe screened sample was adjusted to match data for all Croydon statepublic schools on national standard assessments in school year 9 (age13+), the seven-category Key Stage 3 (KS3) mathematics grades.These were available in aggregate form by sex for both participatingand nonparticipating local authority schools and individually for1,097 subjects from the participating schools. A hot-deckimputation procedure drew CAT scores from a pool of matcheddonors (individuals with a CAT score from the same type of school,special versus other, school year, and mathematics KS3 grade) toimpute CAT scores for all nonparticipants that would be consistentwith the known aggregate and individual KS3 data. These imputedscores were then used to calculate inverse probability weights(Pickles and Dunn, 1988) for completion of a CAT screen. Thesesteps made the weighted screen sample representative of pupilsattending all local authority schools in Croydon. In the second stagea further weighting adjustment method was used to account for thetwo-phase design. The weighting and imputation allowed accountto be taken of differential response rates by school, KS3performance, sex, and school year, and, in addition for in-depth



  • Copyright @ 2007 American Academy of Child and Adolescent Psychiatry. Unauthorized reproduction of this article is prohibited.

    measures, by CAT performance. Analyses used the robust estimatorof the parameter covariance matrix that not only took account of theweights but possible correlation resulting from clustering by schooland heteroscedasticity of errors in regression (Binder, 1983). Thislast feature is desirable when examining, as we did in the presentstudy, skewed distributions common to symptom scores. All of theanalyses were undertaken in Stata version 7/8 (StataCorp, 2003).


    Of the 304 subjects invited to participate in the in-depth evaluation, 204 (67%) consented to do so.Participation was significantly greater in those at lowrisk (64/78, 82%) than that in the moderate-risk(60/93, 65%, odds ratio [OR] = 2.5, p = .01) and thehigh-risk groups (80/133, 60%, OR = 3.0, p < .001). Ofthose taking part in the in-depth study, 12 onlycommenced education in a school in which Englishwas the first language at age 11 or later (the time oftransfer to secondary school in the United Kingdom).Previous exploratory analyses suggested that their IQresults may be falsely lowered because of difficulties withEnglish, and they were therefore excluded from allsubsequent analyses, reducing the sample size to 192.Themean age for participation in the screening was 13.7years (SD 0.64, range 11.9Y16.0 years) and for the in-depth assessment 14.2 years (SD 0.8, range 12.5Y16.1years). There were 125 males and 67 females in the in-depth study. Full Scale IQ ranged from 40 to 137. IQwas classified in two ways: first, by IQ

  • Copyright @ 2007 American Academy of Child and Adolescent Psychiatry. Unauthorized reproduction of this article is prohibited.

    (95% CIs 0.3%Y7.1%); and IQ >90, 0.01 (95% CIs0%Y5.1%).

    We explored whether ratings of ADHD symptomswere subject to bias among children with lower IQ. Wehypothesized that informants not taking properaccount of children_s lower than average developmentallevel may rate the child as having more ADHDsymptoms than would occur if developmental levelwere accounted for. To examine parental responses abinary variable of parental discrepancy betweenmeasured IQ and parental beliefs regarding abilitywas generated. During the interview parents were askedto rate their child_s academic ability in one of fivecategories: a lot above average, above average, average,below average, or well below average. Expectations weredefined as discrepant w...


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