Psychiatric telephone interview with parents for screening of childhood Autism—Tics, Attention-deficit Hyperactivity Disorder and Other Comorbidities (A-TAC): preliminary reliability and validity

Article (PDF Available)inThe British Journal of Psychiatry 187(3):262-7 · October 2005with67 Reads
DOI: 10.1192/bjp.187.3.262 · Source: PubMed
Abstract
Reliable, valid and easily administered screening instruments would greatly facilitate large-scale neuropsychiatric research. To test a parent telephone interview focused on autism - tics, attention-deficit hyperactivity disorder (ADHD) and other comorbidities (A-TAC). Parents of 84 children in contact with a child neuropsychiatric clinic and 27 control children were interviewed. Validity and interrater and test - retest reliability were assessed. Interrater and test - retest reliability were very good. Areas under receiver operating characteristics curves between interview scores and clinical diagnoses were around 0.90 for ADHD and autistic spectrum disorders, and above 0.70 for tics, learning disorders and developmental coordination disorder. Using optimal cut-off scores for autistic spectrum disorder and ADHD, good to excellent kappa levels for interviews and clinical diagnoses were noted. The A-TAC appears to be a reliable and valid instrument for identifying autistic spectrum disorder, ADHD, tics, learning disorders and developmental coordination disorder.
BackgroundBackground Reliable, valid and easilyReliable, valid and easily
administered screeninginstrumentsadministered screeninginstruments
would greatly facilitate large-scalewou ld greatly facilita te large-scale
neu r opsych i a t ric research .neu r opsychi a tric research .
AimsAims To t est a par e ntt elephoneTo test a parenttelephone
interview focused on autism^tics,interview focused on autism^tics,
attention-deficit hyperactivity disorderattention-deficit hyperactivity disorder
(ADHD) and other comorbidit ies(ADH D) and other comorbidities
(A^TA C).(A^TA C).
MethodMethod Parents of 84 chi ldren inParents of 84 children in
contact with a child neuropsychiatric cl iniccontact with a child neuropsychiatric clinic
and 27 control children were interviewed.and 27 controlchildrenwere interviewed.
Validity andinterrater andtest^retestValidity andinterrater andtest^retest
reliability were assessed.reliability were assessed.
ResultsResults Interrater andtest^retestInterrater andtest^retest
reliability were very good. Areas underreliability wereverygood. Areasunder
receiver operatingcharacteristics curvesreceiveroperating characteristics curves
betweeninterview scores andclinicalbetweeninterview scores andclinical
diagnoses were around 0.90 for ADHDdiagnoses were around 0.90 for ADHD
and aut ist ic spectrum disor ders, andand autistic spectrum disorders, and
above 0.70 for tics, learni ng disor ders andabove 0.70 for tics, learning disorders and
developmen tal coordi nat ion disorder.developmen tal coordi nat ion disorder.
Us ing opt imal cut -off scores for autisticUs ing opti mal cu t -off scores for au tisti c
spectrum disorder and ADHD, good tospectrum disorder and ADHD, good to
exce llentkappa levels for in t ervi ews andexcel lent kappa leve ls for int erv iews and
clinicaldiagnoses werenoted.clinicaldiagnoses were noted.
ConclusionsConclusions The A^TAC appears toThe A^TAC appears to
be a reliab le and val i d instrumen t forbe a reliable and val idinstrumen t for
iden tifyi ng au tistic spectrum disorder,iden tifyi ng au tistic spectrum disorder,
ADHD , tics, learning disorders andADHD , tics, learning disorders and
developmen tal coordi nat ion disorder.developmen tal coordi nat ion disorder.
Declaration of interestDeclaration of interest None .None.
F u ndin g deta iledin Ack no wledg e me nts .Fu ndin gde tailed i n Ack no wledg e me nts .
Telephone interviews with good psycho-Telephone interviews with good psycho-
metric properties have been developed formetric properties have been developed for
attention-deficit hyperactivity disorderattention-deficit hyperactivity disorder
(ADHD) and general psychopathology in(ADHD) and general psychopathology in
childhood (Nadderchildhood (Nadder et al.et al., 1998; Rohde, 1998; Rohde etet
al.al., 1998; Holmes, 1998; Holmes et al.et al., 2004), but one as-, 2004), but one as-
sessing traits related to autistic spectrumsessing traits related to autistic spectrum
disorders and comorbid psychiatric prob-disorders and comorbid psychiatric prob-
lems has been lacking. A number of paperlems has been lacking. A number of paper
screening instruments for autistic spectrumscreening instruments for autistic spectrum
disorder exist, including the Checklist fordisorder exist, including the Checklist for
Autism in Toddlers (CHAT; Baron-CohenAutism in Toddlers (CHAT; Baron-Cohen
et al.et al., 1992), the Asperger Syndrome, 1992), the Asperger Syndrome
Screening Questionnaire (ASSQ; Ehlers &Screening Questionnaire (ASSQ; Ehlers &
Gillberg, 1993), the Autism ScreeningGillberg, 1993), the Autism Screening
Questionnaire (ASQ; BerumentQuestionnaire (ASQ; Berument et alet al,,
1999) and the Autism Quotient (AQ;1999) and the Autism Quotient (AQ;
Baron-CohenBaron-Cohen et alet al, 2001), but these assess, 2001), but these assess
only narrow autism/Asperger syndromeonly narrow autism/Asperger syndrome
and do not take into account the most com-and do not take into account the most com-
mon coexisting problems. The Autism–mon coexisting problems. The Autism–
Tics, ADHD and Other ComorbiditiesTics, ADHD and Other Comorbidities
Inventory (A–TAC) is a comprehensiveInventory (A–TAC) is a comprehensive
screening interview, evaluated for reliabil-screening interview, evaluated for reliabil-
ity and validity as a parent telephone inter-ity and validity as a parent telephone inter-
view for autistic spectrum disorders,view for autistic spectrum disorders,
ADHD, tic disorders, developmental co-ADHD, tic disorders, developmental co-
ordination disorder and specific learningordination disorder and specific learning
disorders. Results from parent interviewsdisorders. Results from parent interviews
blinded to clinical diagnoses are comparedblinded to clinical diagnoses are compared
with parent interviews regarding healthywith parent interviews regarding healthy
control children.control children.
METHODMETHOD
Development and designDevelopment and design
of the interviewof the interview
The telephone interview is based on aThe telephone interview is based on a
screening questionnaire developed at thescreening questionnaire developed at the
Department of Child and AdolescentDepartment of Child and Adolescent
Psychiatry, Goteborg University, Sweden,Psychiatry, Go
¨
teborg University, Sweden,
for the purpose of screening general popu-for the purpose of screening general popu-
lations in research and mental health sur-lations in research and mental health sur-
veys. The 178-item A–TAC questionnaireveys. The 178-item A–TAC questionnaire
contains all symptoms listed in thecontains all symptoms listed in the
DSM–IV (American Psychiatric Association,DSM–IV (American Psychiatric Association,
1994) symptom criteria of childhood-onset1994) symptom criteria of childhood-onset
neuropsychiatric disorders, a selection ofneuropsychiatric disorders, a selection of
DSM–IV symptoms listed for other psychi-DSM–IV symptoms listed for other psychi-
atric disorders, and additional items includ-atric disorders, and additional items includ-
ing symptoms listed in the Gillberg &ing symptoms listed in the Gillberg &
Gillberg (1989) algorithm for Asperger syn-Gillberg (1989) algorithm for Asperger syn-
drome, and questions or aspects included indrome, and questions or aspects included in
published questionnaires for screening orpublished questionnaires for screening or
diagnosis of autistic spectrum disordersdiagnosis of autistic spectrum disorders
and general psychiatric disorders such asand general psychiatric disorders such as
the ASSQ (Ehlers & Gillberg, 1993), thethe ASSQ (Ehlers & Gillberg, 1993), the
Asperger Syndrome Diagnostic InterviewAsperger Syndrome Diagnostic Interview
(ASDI; Gillberg(ASDI; Gillberg et alet al, 2001) and the Five, 2001) and the Five
to Fifteen Questionnaire (Kadesjoto Fifteen Questionnaire (Kadesjo et alet al,,
2004).2004).
The telephone interview is highly struc-The telephone interview is highly struc-
tured, with four possible ratings for eachtured, with four possible ratings for each
item: ‘yes’; ‘yes, previously’ (both scoreditem: ‘yes’; ‘yes, previously’ (both scored
as 1 in this study); ‘yes, to some extent’as 1 in this study); ‘yes, to some extent’
(scored as 0.5 in this study); and ‘no’. It(scored as 0.5 in this study); and ‘no’. It
is intended for use with parents as infor-is intended for use with parents as infor-
mants and lay persons as interviewers.mants and lay persons as interviewers.
The interview is preceded by a shortThe interview is preceded by a short
introduction to inform the parent that theintroduction to inform the parent that the
interview concerns problems or difficultiesinterview concerns problems or difficulties
that the child is either experiencing nowthat the child is either experiencing now
or has experienced earlier in life. Theseor has experienced earlier in life. These
problems or difficulties must be pronouncedproblems or difficulties must be pronounced
compared with other children of the samecompared with other children of the same
age. The parent is also asked to write downage. The parent is also asked to write down
the four response alternatives, to have themthe four response alternatives, to have them
visually available throughout the interview.visually available throughout the interview.
In this validation study, the parents wereIn this validation study, the parents were
also specifically asked to provide no morealso specifically asked to provide no more
facts about the child than those that thefacts about the child than those that the
interviewer enquired about. This was ininterviewer enquired about. This was in
order to assure masking of the interviewerorder to assure masking of the interviewer
to the child’s diagnostic status. The timeto the child’s diagnostic status. The time
for completing the interview varied fromfor completing the interview varied from
15 min to 35 min.15 min to 35 min.
Particip antsParticip ants
The parents of 118 children and adoles-The parents of 118 children and adoles-
cents (aged 7–18 years) were asked tocents (aged 7–18 years) were asked to
participate in the study, and parents ofparticipate in the study, and parents of
112 accepted. One of these had to be112 accepted. One of these had to be
excluded becauseexcluded because of language difficulties.of language difficulties.
Of the 111 children,Of the 111 children, 84 (32 girls and 5284 (32 girls and 52
boys, mean age 11.5 years) were patientsboys, mean age 11.5 years) were patients
at the Child Neuropsychiatric Clinic inat the Child Neuropsychiatric Clinic in
Goteborg. They were either under investi-Go
¨
teborg. They were either under investi-
gation at the time of the study or hadgation at the time of the study or had
recently been investigated. Children withrecently been investigated. Children with
any diagnosed or suspected chromosomalany diagnosed or suspected chromosomal
or genetic medical disorder other thanor genetic medical disorder other than
high-functioning individuals with fragile Xhigh-functioning individuals with fragile X
or CATCH 22 (cardiac defects, abnormalor CATCH 22 (cardiac defects, abnormal
facies, thymic hypoplasia, cleft palate,facies, thymic hypoplasia, cleft palate,
hypocalcaemia and a deletion on chromo-hypocalcaemia and a deletion on chromo-
some 22) were excluded.some 22) were excluded.
262262
BRITISH JOURNAL OF PSYCHIATRYBRITISH JOURNAL OF PSYCHIATRY (2005), 187, 262^267(2005), 187, 262^267
Psychiatri c telephone interview with parentsPsychiatri c telephone interview with parents
for screening of childhood autism ^ tics,for screening of childhood autism ^ tics,
at tenti on-deficit hyperactiv ity d isorderattenti on-defi cit h yperacti vity disorder
and other como rbi d ities (A^TAC)and other como rbi d ities ( A^ TAC)
Preliminary reliability and validityPreliminary reliability and validity
SARA LINA HANSSON, ANNIKA SVA NSTROM ROJVALL, MA RIA RASTAM,SAR A LINA HANSSON, ANNIK A SVANSTRO
«
MRO
«
JVALL , M ARIA RA STAM,
C ARINA GILLBERG, CHRISTOP HER GILLBERG a nd HENRIK ANCKARSAT ERCAR I NA GILLB ERG, CHRIS TOPHER GILLB ERG and HE NRI K ANCKARSA
«
TER
S CR EE NING OF CHILDHOOD AUTIS MS C RE ENING OF CHIL DHOOD AUT IS M
Twenty-seven children (10 girls, 17Twenty-seven children (10 girls, 17
boys, mean age 12.2 years, range 9–17)boys, mean age 12.2 years, range 9–17)
constituted a comparison group of healthyconstituted a comparison group of healthy
children without any known assessment orchildren without any known assessment or
treatment for child and adolescent mentaltreatment for child and adolescent mental
health problems. The comparison caseshealth problems. The comparison cases
were children of staff at the Child Neuro-were children of staff at the Child Neuro-
psychiatric Clinic, the Department of Childpsychiatric Clinic, the Department of Child
and Adolescent Psychiatry and the Depart-and Adolescent Psychiatry and the Depart-
ment of Forensic Psychiatry in Goteborg,ment of Forensic Psychiatry in Go
¨
teborg,
and of their acquaintances. After all the in-and of their acquaintances. After all the in-
terviews had been completed, parents wereterviews had been completed, parents were
again contacted and asked for informationagain contacted and asked for information
about earlier psychiatric problems or con-about earlier psychiatric problems or con-
tacts with child psychiatry or psychologytacts with child psychiatry or psychology
departments.departments.
Interview procedureInterview procedure
Two medical students (one 4th year, oneTwo medical students (one 4th year, one
5th year) completed the 111 telephone in-5th year) completed the 111 telephone in-
terviews. They were masked to diagnosisterviews. They were masked to diagnosis
of the target cases and to possible psychi-of the target cases and to possible psychi-
atric history of the comparison cases. Theatric history of the comparison cases. The
two interviewers conducted ten of the inter-two interviewers conducted ten of the inter-
views together, during which they tookviews together, during which they took
turns, interviewing five parents each (allturns, interviewing five parents each (all
target cases) while the other listened andtarget cases) while the other listened and
filled in the questionnaire independently.filled in the questionnaire independently.
The results obtained were then comparedThe results obtained were then compared
in order to analyse interrater reliability.in order to analyse interrater reliability.
Ten of the interviewees (eight target cases,Ten of the interviewees (eight target cases,
two comparison cases) were contactedtwo comparison cases) were contacted
again 6–8 weeks after the first interviewagain 6–8 weeks after the first interview
and asked to participate in a second inter-and asked to participate in a second inter-
view; they were informed that the purposeview; they were informed that the purpose
of the second interview was to determineof the second interview was to determine
if responses would vary over time. Theseif responses would vary over time. These
parents had not been informed at the firstparents had not been informed at the first
interview that they would be contactedinterview that they would be contacted
again. The interviewers were still maskedagain. The interviewers were still masked
to diagnoses (target group) as well as toto diagnoses (target group) as well as to
prior psychiatric problems (comparisonprior psychiatric problems (comparison
group). All clinical information wasgroup). All clinical information was
collected after all the interviews had beencollected after all the interviews had been
completed.completed.
Diagnostic processDiagnostic process
Diagnoses assigned during investigations atDiagnoses assigned during investigations at
the clinic were based on medical history,the clinic were based on medical history,
physical examination (including a neuro-physical examination (including a neuro-
motor assessment) by a physician withmotor assessment) by a physician with
expertise in neuropsychiatry, and psycho-expertise in neuropsychiatry, and psycho-
logical examination by a trained neuro-logical examination by a trained neuro-
psychologist. In all children, an assessmentpsychologist. In all children, an assessment
of cognitive level was made with a testof cognitive level was made with a test
battery appropriate for the child’s mentalbattery appropriate for the child’s mental
age (Doll, 1965; Griffiths, 1970; Leiter,age (Doll, 1965; Griffiths, 1970; Leiter,
1980; Wechsler, 1992). Children with1980; Wechsler, 1992). Children with
significant school achievement problemssignificant school achievement problems
were also examined by an educational spe-were also examined by an educational spe-
cialist using tests of reading and writingcialist using tests of reading and writing
skills, observation of the child at school,skills, observation of the child at school,
and interviews with the child’s teachersand interviews with the child’s teachers
about school performance and behaviour.about school performance and behaviour.
Structured instruments, such as the AutismStructured instruments, such as the Autism
Diagnostic Interview – Revised (ADI–R;Diagnostic Interview – Revised (ADI–R;
LordLord et alet al, 1994), the Diagnostic Interview, 1994), the Diagnostic Interview
for Social and Communication Disordersfor Social and Communication Disorders
(DISCO; Leekam(DISCO; Leekam et alet al, 2002; Wing, 2002; Wing et alet al,,
2002), the Childhood Autism Rating Scale2002), the Childhood Autism Rating Scale
(Schopler(Schopler et alet al, 1988), the ASDI (Gillberg, 1988), the ASDI (Gillberg
et alet al, 2001) and the ADHD Rating Scale, 2001) and the ADHD Rating Scale
(DuPaul(DuPaul et alet al, 1998) were used as appropri-, 1998) were used as appropri-
ate, although not the sole basis for a diag-ate, although not the sole basis for a diag-
nosis. For each case that fulfilled DSM–IVnosis. For each case that fulfilled DSM–IV
criteria for a specific condition, the physi-criteria for a specific condition, the physi-
cian in charge was asked to complete acian in charge was asked to complete a
diagnostic protocol specifying otherdiagnostic protocol specifying other
possible comorbid diagnoses.possible comorbid diagnoses.
A ttrition analysisAttrition analysis
Six of the initially contacted 118 parentsSix of the initially contacted 118 parents
declined to participate in the study: twodeclined to participate in the study: two
lacked motivation for further explorationlacked motivation for further exploration
following the clinical investigation andfollowing the clinical investigation and
diagnosis of their children; one declineddiagnosis of their children; one declined
owing to a difficult life situation; and threeowing to a difficult life situation; and three
parents did not supply a reason. One inter-parents did not supply a reason. One inter-
view could not be completed owing toview could not be completed owing to
language difficulties. All seven cases oflanguage difficulties. All seven cases of
non-completion were from the targetnon-completion were from the target
group.group.
Statistical analyse sStatistical analyses
The interview ratings were coded on aThe interview ratings were coded on a
three-point scale: 0 indicating normalitythree-point scale: 0 indicating normality
(‘no’), 0.5 indicating some abnormality(‘no’), 0.5 indicating some abnormality
(‘yes, to some extent’) and 1.0 indicating(‘yes, to some extent’) and 1.0 indicating
abnormality or earlier abnormality (‘yes’abnormality or earlier abnormality (‘yes’
or ‘yes, previously’). Sum scores were calcu-or ‘yes, previously’). Sum scores were calcu-
lated for each diagnostic category. Inter-lated for each diagnostic category. Inter-
rater and test–retest reliability wasrater and test–retest reliability was
assessed through intraclass correlationsassessed through intraclass correlations
between dimensional ratings within eachbetween dimensional ratings within each
category. The intraclass correlation co-category. The intraclass correlation co-
efficient (ICC), defined as (varianceefficient (ICC), defined as (variance
between subject)/(variance between subjectbetween subject)/(variance between subject
+variance of error), includes both random+variance of error), includes both random
errors and systematic differences, but is alsoerrors and systematic differences, but is also
dependent on the range of the variabledependent on the range of the variable
measured. The ICC ranges from 0 (nomeasured. The ICC ranges from 0 (no
agreement) to 1 (perfect agreement); valuesagreement) to 1 (perfect agreement); values
above 0.75 indicate excellent reliability,above 0.75 indicate excellent reliability,
0.4–0.75 indicate fair to poor reliability,0.4–0.75 indicate fair to poor reliability,
and values below 0.4 indicate poor reli-and values below 0.4 indicate poor reli-
ability (Fleiss, 1986). Diagnostic validityability (Fleiss, 1986). Diagnostic validity
for the neuropsychiatric disorders, wherefor the neuropsychiatric disorders, where
the prevalence of disorders was sufficientlythe prevalence of disorders was sufficiently
high for these calculations, were assessedhigh for these calculations, were assessed
first through a receiver operating character-first through a receiver operating character-
istics (ROC) curve, where clinical diagnosisistics (ROC) curve, where clinical diagnosis
was the dependent variable and the tele-was the dependent variable and the tele-
phone interview sum score the independentphone interview sum score the independent
predictor. The area under the curve (AUC)predictor. The area under the curve (AUC)
is a measure of the overall predictiveis a measure of the overall predictive
validity of the instrument wherevalidity of the instrument where
AUCAUC¼0.50 signals random prediction,0.50 signals random prediction,
0.600.6055AUCAUC440.70 poor, 0.700.70 poor, 0.7055AUCAUC44
0.800.80 fair, 0.80fair, 0.8055AUCAUC440.90 good and0.90 good and
AUCAUC440.90 excellent validity (Tape,0.90 excellent validity (Tape,
2004). The inflection point of the curve is2004). The inflection point of the curve is
the optimal cut-off value of the dimensionalthe optimal cut-off value of the dimensional
independent variable for a categoricalindependent variable for a categorical
decision in the dependent variable withdecision in the dependent variable with
maximal sensitivity and specificity. Thesemaximal sensitivity and specificity. These
cut-offs were then used for calculatingcut-offs were then used for calculating
four-field tables comparing the diagnosticfour-field tables comparing the diagnostic
results for the telephone interviews andresults for the telephone interviews and
the clinical assessments through Cohen’sthe clinical assessments through Cohen’s
kappa, values above 0.60 indicating goodkappa, values above 0.60 indicating good
correspondence (Altman, 1991). All statis-correspondence (Altman, 1991). All statis-
tics were calculated with the Statisticaltics were calculated with the Statistical
Package for the Social Sciences, versionPackage for the Social Sciences, version
11.0, using a significance level of11.0, using a significance level of PP550.05.0.05.
RESULTSRESULTS
The interrater reliability was excellentThe interrater reliability was excellent
overall (Table 1). The test–retest reliabilityoverall (Table 1). The test–retest reliability
(Table 2) was highly significant for all(Table 2) was highly significant for all
assessed dimensions, and good for mostassessed dimensions, and good for most
aspects of the neuropsychiatric disorders,aspects of the neuropsychiatric disorders,
although slightly lower for attention defi-although slightly lower for attention defi-
cits and anxiety problems and considerablycits and anxiety problems and considerably
lower for some of the less commonlower for some of the less common
conditions, such as obsessive–compulsiveconditions, such as obsessive–compulsive
disorder, sleeping problems and eatingdisorder, sleeping problems and eating
disorders.disorders.
Validity in screening andValidity in screening and
establishing cut-off scoresestablishing cut-off scores
A ROC curve (Fig. 1) plotting the sum ofA ROC curve (Fig. 1) plotting the sum of
the DSM–IV criteria (independent variable)the DSM–IV criteria (independent variable)
and a diagnosis within the autism spectrumand a diagnosis within the autism spectrum
(dependent variable) yielded an AUC of(dependent variable) yielded an AUC of
0.88. The addition of the Gillberg &0.88. The addition of the Gillberg &
Gillberg (1989) criteria for Asperger syn-Gillberg (1989) criteria for Asperger syn-
drome did not improve the screening fordrome did not improve the screening for
any diagnosis in the autism spectrum, yield-any diagnosis in the autism spectrum, yield-
ing a ROC curve plot with an AUC of 0.88.ing a ROC curve plot with an AUC of 0.88.
The best match was achieved with a cut-offThe best match was achieved with a cut-off
score of 4.5, yielding a four-field table withscore of 4.5, yielding a four-field table with
34 (31%) true positives, 57 (51%) true34 (31%) true positives, 57 (51%) true
negatives, 16 (14%) false positives and 4negatives, 16 (14%) false positives and 4
(4%) false negatives. Cohen’s(4%) false negatives. Cohen’s kk for thisfor this
model was 0.63 (model was 0.63 (PP550.001). The sensitivity0.001). The sensitivity
was 0.89, the specificity 0.78, the positivewas 0.89, the specificity 0.78, the positive
263263
HANSSON ET ALHANS SON E T AL
264264
Ta b l e 1Ta b l e 1 Results of interrater reliabil ity analysisResults of interrater reliability analysis
A^TAC dime nsi onA^T A C dimension A^T A C scoreA^T A C sco re Interrater differenceInterrater difference ICCICC
2,12,1
PP
Number of itemsNumber of items RangeRange Med ianMed ian MaximumMaxi m um Mean (s .d. )Mean (s.d.) 95% CI95% CI
Attention-deficit disorderAttention-deficit disor der 990^90^9 5.55.5 00 0 (0)0 (0) 0 to 00to0 1.001.00 550.000 10.000 1
Hyperact i vity disor derHyperactivity disorder 990^90^9 3.03.0 00 0 (0)0 (0) 0 to 00to0 1.001.00 550.000 10.000 1
ADHDADHD 2020 0^19.50^19.5 9.59.5 00 0 (0)0 (0) 0 to 00to0 1.001.00 550.000 10.000 1
Dev el opme ntal coo rd i nat ion disorde rDev elop me ntal coor d i nation disord e r 330^30^3 0.50.5 00 0 (0)0 (0) 0 to 00to0 1.001.00 550.00010.000 1
AutismAutism
Social interaction deficitsSocial interaction deficits 440^40^4 1.51.5 00 0 (0)0 (0) 0 to 00to0 1.001.00 550.000 10.000 1
Communication deficitsCommunication deficits 440^40^4 1.01.0 00 0 (0)0 (0) 0 to 00to0 1.001.00 550.00010.000 1
Flexibility problemsFlexi b il ity proble ms 440^40^4 1.01.0 00 0 (0)0 (0) 0 to 00to0 1.001.00 550.00010.000 1
Asperger syndromeAsperger syndrome 66 0^60^6 2.02.0 00 0 (0)0 (0) 0 to 00to0 1.001.00 550.00010.000 1
Autistic spectrum disorders (total)Autistic spectrum disorders (total) 1818 0^160^16 6.56.5 00 0 (0)0 (0) 0 to 00to0 1.001.00 550.00010.000 1
TicsTics 220^20^2 0.00.0 00 0 (0)0 (0) 0 to 00to0 1.001.00 550.000 10.000 1
Learning disordersLearning disorders 440^40^4 1.51.5 7711 770.1 (0.31 )0.1 (0.31) 770.73 to 0.530.73 to 0.53 0.970.97 550.000 10.000 1
Sleep disordersS leep disor ders 220^20^2 0.00.0 00 0 (0)0 (0) 0 to 00to0 1.001.00 550.00010.000 1
School problemsSchool problems 220^20^2 0.00.0 00 0 (0)0 (0) 0 to 00to0 1.001.00 550.00010.000 1
Separation anxietySeparation anxiet y 880^50^5 0.500.50 770.500.50 770.05 (0.15)0.05 (0.1 5) 770.36 to 0.260.36 to 0.26 0.990. 99 550.00010.000 1
Obsessive^compulsive diso rderObsessive^compulsive disorder 220^20^2 0.00.0 00 0 (0)0 (0) 0 to 00to0 1.001.00 550.00010.000 1
Anxiet y disordersAnxiety disorders 550^50^5 0.50.5 00 0 (0)0 (0) 0 to 00to0 1.001.00 550.00010.000 1
Eatin g problemsEating problems 550^30^3 0.00.0 00 0 (0)0 (0) 0 to 00to0 1.001.00 550.00010.000 1
Depressi onDepression 770^40^4 0.00.0 00 0 (0)0 (0) 0 to 00to0 1.001.00 550.000 10.000 1
Conduct disor derConduct disord er 1111 0 ^100^10 1 .51.5 00 0 (0)0 (0) 0 to 00to0 1.001.00 550.00010.000 1
ADHD, attention-deficit hyperactivity disorder; A^TAC, Autism^Tics, ADHD and Other Comorbidities Inventory; ICC, intraclass correlation coefficient.ADHD, attention-deficit hyperactivity disorder; A^TAC, Autism^Tics, ADHD and Other Comorbidities Inventory; ICC, intraclass correlation coefficient.
Ta b l e 2Ta b l e 2 Results of test^retest analysesResults of test^retest analyses
A^TAC dime nsi onA^T A C dimension A^T A C scoreA^TAC score Differe nceDifference ICCICC
2,12,1
PP
Number of itemsNumber of items RangeRange Med ianMed ian MaximumMaxi m um Mean (s .d. )Mean (s.d.) 95% CI95% CI
Attention-deficit disorderAttention-deficit disor der 990^90^9 5.55.5 3 .53.5 0.80 (1.81)0.80 (1.81) 772.75 to 4.352.75 to 4.35 0.780.78 0.00240.0024
Hyperact i vity disor derHyperactivity disorder 990^90^9 3.03.0 22 0.22 (1.27)0.22 (1.27) 772.49 to 2.492.49 to 2.49 0 .910.9 1 0.000 10.000 1
ADHDADHD 2020 0^19.50^19.5 9.59.5 5.55.5 0.90 (2.82)0.90 (2.82) 774.63 to 6.434.63 to 6.43 0.880.88 0.00020.0002
Dev el opme ntal coo rd i nat ion disorde rDev elop me ntal coor d i nation disord e r 330^30^3 0.50.5 1.51.5 770.25 (0.54)0.25 (0.54) 771.31 to 0.811.31 to 0.81 0.870.87 0.00020.0002
AutismAutism
Social interaction deficitsSocial interaction deficits 440^40^4 1.51.5 11 0.30 (0.35)0.30 (0.35) 770.39 to 0.990.39 to 0.99 0.940.94 550.00010.000 1
Communication deficitsCommunication deficits 440^40^4 1.01.0 110.00(0.62)0.00 (0.62) 771.21 to 1.211.21 to 1.21 0.860.86 0.00030.0003
Flexibility problemsFlexi b il ity proble ms 440^40^4 1.01.0 1.51.5 0.00 (0.78)0.00 (0.78) 771.53 to 1.531.53 to 1.53 0.830.83 0.00080.0008
Asperger syndromeAsperger syndrome 66 0^60^6 2.02.0 110.05(0.55)0.05 (0.55) 771.03 to 1.131.03 to 1.13 0.940.94 550.000 10.000 1
Autistic spectrum disorders (total)Autistic spectrum disorders (total) 1818 0^160^16 6.56.5 3.53.5 0.35 (1.53)0.35 (1.53) 772.65 to 3.352.65 to 3. 35 0. 930.93 550.00010.000 1
TicsTics 220^20^2 0.00.0 0.50.5 770.10 (0.2 1 )0.10 (0.21) 770.51 to 0.3 10.51 to 0.3 1 0. 970.97 550.000 10.000 1
Learning disordersLearning disorders 440^40^4 1.51.5 110.00(0.53)0.00 (0.53) 771.04 to 1.041.04 to 1.04 0.940.94 550.000 10.000 1
Sleep disordersS leep disor ders 220^20^2 0.00.0 110.05(0.55)0.05 (0.55) 771.03 to 1.131.03 to 1.13 0.780.78 0.00250.0025
School problemsSchool problems 220^20^2 0.00.0 110.10(0.39)0. 10 (0.39) 770.66 to 0.860.66 to 0.86 0.900.90 0.00010.0001
Separation anxietySeparation anxiet y 880^50^5 0.500.50 22 770.15 (0.82)0.15 (0.82) 771.75 to 1.551.75 to 1.55 0.860.86 0.00040.0004
Obsessive^compulsive diso rderObsessive^compulsive disorder 220^20^2 0.00.0 11 770.05 (0.44)0.05 (0.44) 770.91 to 0.810.91 to 0.81 0.580.58 0.03020.0302
Anxiet y disordersAnxiety disorders 550^50^5 0.50.5 1.51.5 0.10 (0.70)0.10 (0.70) 771.27 to 1.471.27 to 1.47 0.770.77 0.00300.0030
Eatin g problemsEating problems 550^30^3 0.00.0 11 770.15 (0.53)0.15 (0.53) 771.19 to 0.891.19 to 0.89 0.570.57 0.03460.0346
Depressi onDepression 770^40^4 0.00.0 11 770.00 (0.92)0.00 (0.92) 770.92 to 0.920.92 to 0.92 0.940.94 550.00010.0001
Conduct disor derConduct disord er 1111 0 ^100^10 1 .51.5 3.03.0 770.82 (1 .05)0.82 (1.05) 771.24 to 2.881.24 to 2.88 0.930.93 550.00010.000 1
ADHD, attention-deficit hyperactivity disorder; A^TAC, Autism^Tics, ADHD and Other Comorbidities Inventory; ICC, intraclass correlation coefficient.ADHD, attention-deficit hyperactivity disorder; A^TAC, Autism^Tics, ADHD and Other Comorbidities Inventory; ICC, intraclass correlation coefficient.
S CR EE NING OF CHILDHOOD AUTIS MS C RE ENING OF CHIL DHOOD AUT IS M
predictive value 0.68 and the negative pre-predictive value 0.68 and the negative pre-
dictive value 0.93. A cross-tabulation ofdictive value 0.93. A cross-tabulation of
all specific diagnostic categories within theall specific diagnostic categories within the
autism spectrum with their respectiveautism spectrum with their respective
DSM–IV criteria in the interview (withoutDSM–IV criteria in the interview (without
any adjustment of cut-off levels) showedany adjustment of cut-off levels) showed
much poorer performance; for autismmuch poorer performance; for autism
kk¼0.22 (0.22 (PP¼0.011), for Asperger syndrome0.011), for Asperger syndrome
kk¼0.27 (0.27 (PP¼ 0.002) and for pervasive devel-0.002) and for pervasive devel-
opmental disorders not otherwise specifiedopmental disorders not otherwise specified
kk¼0.07 (0.07 (PP¼0.418).0.418).
For ADHD the AUC was 0.90 for theFor ADHD the AUC was 0.90 for the
DSM–IV symptoms and increased to 0.91DSM–IV symptoms and increased to 0.91
with the addition of the A–TAC questionswith the addition of the A–TAC questions
‘Does he/she alternate between exaggerated‘Does he/she alternate between exaggerated
activity and passivity?’ and ‘Does he/she getactivity and passivity?’ and ‘Does he/she get
excited by having a number of personsexcited by having a number of persons
around?’ (Fig. 2). The optimal cut-off wasaround?’ (Fig. 2). The optimal cut-off was
eight A–TAC symptoms, which yielded aeight A–TAC symptoms, which yielded a
distribution of 58 (52%) true positives, 36distribution of 58 (52%) true positives, 36
(32%) true negatives, 12 (11%) false(32%) true negatives, 12 (11%) false
positives and 5 (5%) false negatives;positives and 5 (5%) false negatives;
Cohen’sCohen’s kk¼ 0.68 (0.68 (PP550.001). The sensitivity0.001). The sensitivity
was 0.92, the specificity 0.75, the positivewas 0.92, the specificity 0.75, the positive
predictive value 0.83 and the negativepredictive value 0.83 and the negative
predictive value 0.88.predictive value 0.88.
For tic disorders (Tourette syndrome orFor tic disorders (Tourette syndrome or
chronic tics) the AUC was 0.84 (Fig. 3) andchronic tics) the AUC was 0.84 (Fig. 3) and
the optimal cut-off was two symptoms,the optimal cut-off was two symptoms,
which yielded a distribution of 7 (6%) truewhich yielded a distribution of 7 (6%) true
positives, 86 (77%) true negatives, 13positives, 86 (77%) true negatives, 13
(12%)(12%) false positives and 5 (5%) false nega-false positives and 5 (5%) false nega-
tives;tives; kk¼ 0.35 (0.35 (PP550.001). The sensitivity0.001). The sensitivity
was 0.58, the specificity 0.87, the positivewas 0.58, the specificity 0.87, the positive
predictive value 0.35 and the negativepredictive value 0.35 and the negative
predictive value 0.95.predictive value 0.95.
For learning disorders the AUC of theFor learning disorders the AUC of the
ROC curve was 0.74 (Fig. 4) and theROC curve was 0.74 (Fig. 4) and the
optimal cut-off was 3.5 symptoms, whichoptimal cut-off was 3.5 symptoms, which
yielded a distribution of 8 (7%) trueyielded a distribution of 8 (7%) true
positives, 88 (80%) true negatives, 5 (5%)positives, 88 (80%) true negatives, 5 (5%)
false positives and 10 (9%) false negatives;false positives and 10 (9%) false negatives;
kk¼0.44 (0.44 (PP550.001). The sensitivity was0.001). The sensitivity was
0.44, the specificity 0.95, the positive0.44, the specificity 0.95, the positive
predictive value 0.62 and the negativepredictive value 0.62 and the negative
predictive value 0.90.predictive value 0.90.
For developmental coordination disor-For developmental coordination disor-
der the AUC of the ROC curve was 0.71der the AUC of the ROC curve was 0.71
(Fig. 5) and the optimal cut-off was 1.5(Fig. 5) and the optimal cut-off was 1.5
symptoms, which yielded a distribution ofsymptoms, which yielded a distribution of
14 (13%) true positives, 63 (57%) true14 (13%) true positives, 63 (57%) true
negatives, 27 (24%) false positives and 7negatives, 27 (24%) false positives and 7
(6%) false negatives;(6%) false negatives; kk¼0.27 (0.27 (PP¼0.002).0.002).
The sensitivity was 0.67, the specificityThe sensitivity was 0.67, the specificity
0.70, the positive predictive value 0.340.70, the positive predictive value 0.34
and the negative predictive value 0.90.and the negative predictive value 0.90.
DIS CUSS IONDIS CUSS ION
This preliminary validation and reliabilityThis preliminary validation and reliability
study showed that the A–TAC telephone in-study showed that the A–TAC telephone in-
terview was reliable in terms of interraterterview was reliable in terms of interrater
agreement (as expected, since the interviewagreement (as expected, since the interview
is highly structured and the ratings wereis highly structured and the ratings were
simultaneous) and also test–retest agree-simultaneous) and also test–retest agree-
ment. Because of the low prevalence ofment. Because of the low prevalence of
general child psychiatric diagnoses in thegeneral child psychiatric diagnoses in the
study group, it was not possible to assessstudy group, it was not possible to assess
the interview’s capacity for identifyingthe interview’s capacity for identifying
conditions such as depression, anxiety,conditions such as depression, anxiety,
eating disorders or obsessive–compulsiveeating disorders or obsessive–compulsive
disorder. For the neuropsychiatric disor-disorder. For the neuropsychiatric disor-
ders, however, particularly for autisticders, however, particularly for autistic
spectrum disorders and ADHD, the instru-spectrum disorders and ADHD, the instru-
ment appeared to work well. Kappa valuesment appeared to work well. Kappa values
over 0.60 when comparing two entirelyover 0.60 when comparing two entirely
different diagnostic procedures (a laydifferent diagnostic procedures (a lay
265265
Fig. 1Fig. 1 Receiver operating characteristics curve forReceiver operating characteristics curve for
the relationship between the sum of DSM^IV autismthe relationship between the sum of DSM^IVautism
it ems and a diag n os i s in the aut ism spectrum (areaitems and a diagnosis in the autism spectrum (area
under curve 0.88). Diagonal segments are producedunder curve 0.88). Diagonal segments are produced
by ties.by ties.
Fig. 2Fig. 2 Receiver operating characteristics curve forReceiver operating characteristic s curve for
the relationship between the sum of DSM^IVthe relationship between the sum of DSM^IV
attention-deficit hyperactivity disorder (ADHD)attention-deficit hyperactivity disorder (ADHD)
items and a diagnosis of ADHD (area under curveitems and a diagnosis of ADHD (area under curve
0.9 1).0.91).
Fig. 3Fig. 3 Receiver operating characteristics curve forReceiver operating characteristics curve for
the relationship between the sum of tic disorderthe relationship between the sum of tic disorder
questions and a diagnosis of chronic tic disorderqu estions and a diag nosis of chronic ti c d iso rde r
(area under curve 0.84).(area under curve 0.84).
Fig. 4Fig. 4 Receiver operating characteristics curve forReceiver operating characteristics curve for
the relationship between the sum of learning disor-the relationship between the sum of learning disor-
der questions and a d ia gnosis of learn ing d iso rde rder questions and a diagnosis of learning disorder
(area under curve 0.74).(area under curve 0.74).
Fig. 5Fig. 5 Receiver operating characteristics curve forReceiver operating characteristics curve for
the re lat ionship between the sum of developmentalthe relationship between the sum of developmental
q uestions and a diagnosis of developmentquestions and a diagnosis of development
coordination disorder (area under curve 0.71).coordination disorder (area under curve 0.71).
HANSSON ET ALHANS SON E T AL
person administering a structured interviewperson administering a structured interview
vv. comprehensive neuropsychiatric assess-. comprehensive neuropsychiatric assess-
ment by a team of clinical specialists) canment by a team of clinical specialists) can
be considered very good. It is also open tobe considered very good. It is also open to
argument which gold standard should beargument which gold standard should be
chosen for this kind of study. In order tochosen for this kind of study. In order to
validate a telephone interview, it mightvalidate a telephone interview, it might
seem to be more appropriate to use ratingseem to be more appropriate to use rating
scores from DISCO and ADI–R algorithmsscores from DISCO and ADI–R algorithms
rather than clinical diagnosis as an externalrather than clinical diagnosis as an external
validation criterion. Kappa values for tics,validation criterion. Kappa values for tics,
learning disorders and developmental coor-learning disorders and developmental coor-
dination disorder were lower, with AUCs indination disorder were lower, with AUCs in
the fair range of prediction, probablythe fair range of prediction, probably
reflecting too narrow a range of possiblereflecting too narrow a range of possible
responses, resulting in poor resolution. Aresponses, resulting in poor resolution. A
possibly less stringent clinical diagnosticpossibly less stringent clinical diagnostic
assessment might also be at the root of thisassessment might also be at the root of this
problem.problem.
We are now pursuing the further devel-We are now pursuing the further devel-
opment of this instrument through theopment of this instrument through the
incorporation of more questions under eachincorporation of more questions under each
domain, to provide both screening ques-domain, to provide both screening ques-
tions and a wider set of more detailedtions and a wider set of more detailed
questions with dimensional symptomquestions with dimensional symptom
ratings for those who screen positive. Thisratings for those who screen positive. This
instrument will be further validated ininstrument will be further validated in
other neuropsychiatric patient groups, inother neuropsychiatric patient groups, in
general child and adolescent psychiatrygeneral child and adolescent psychiatry
groups, and in the normal population.groups, and in the normal population.
ACKNOWLEDGEMENTSACKNOWLEDGEMENTS
The study was supported by research grants fromThe study was supported by research grants from
Alcohol Research Council of the Swedish AlcoholAlcohol R esear ch Cou ncil of t he S w edis h Alc ohol
Retailing Monopol y, the Wilhelm and Marti naRetaili n g Monopoly, the Wil hel m and Martina
Lundber g Research F ou nda tion, the Frim urareLundberg Research Fou nda tion, the Frim urare
Barnh u sdire ktione n Research F ou nda tion and theBarn h usdir ektionen Research F oundat i on and the
Swedish National Research Council.Swedish National Research Council.
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266266
CLINICAL IMPLICATIONSCLINICAL IMPLICATIONS
&&
The Autism^Tics, Attention-Deficit Hyperactivity Disorder and OtherThe Autism^Tics, Attention-Deficit Hyperactivity Disorder and Other
Comorbidit ies In vent ory (A^TAC) telephone interview may be used for screening inComorbidit ies Invent ory (A^ T A C) telephone interview may be used for screening in
research and mental health surveys to assess autistic spectrum disorders andresearch and mental health surveys to assess autistic spectrum disorders and
common comorbid conditions.common comorbid conditions.
&&
The A^TAC does not require expert interviewers.The A^TAC does not require expert interviewers.
&&
The number of symptoms affirmed in the A^TAC may be used as a dimensionalThe number of symptoms affirmed in the A^TAC may be used as a dimensional
measu re of the probabil ity of a cli ni cal d iagnosis.measur e of the probabi l ity of a clin i cal diag nos is.
LIMI TAT IONSLIMITAT IONS
&&
The study group was small, and the controls were notrandomly recruited from theThe study groupwas small, and the controls were notrandomly recruited from the
general population because of ethical considerations.general population because of ethical considerations.
&&
It is unclear whether clinical diagnoses or results on established instrumentsIt is unclear whet he r clin ical d iagnoses or results on estab l ished inst ruments
should be used as the gold standard in validation studies such as this.should be used as the gold standard in validation stud ies such as this.
&&
Pa rents wait i ng for clin i cal investi gati ons may be more prone to desc ri be proble msParents waiting for clinical investigations may be more prone to describe problems
in the i r children than other pare nts.in t hei r chi ld ren t han other parents.
SARA LI NA HANSSON, MD , ANN I KA SVANSTROM ROJV ALL, MD , MA RIA RAST AM , MD , PhD, CARINASA RA LI N A HAN SSO N , MD, ANN IKA SV A NS TR O
«
MRO
«
JV ALL, MD , MARIA RASTAM, MD , PhD, CARI NA
GILLBERG, MD, PhD, Department of Child and Adolescent Psychiatry,Goteborg University, Sweden;GILLBERG, MD, PhD, Department of Child and Adolescent Psychiatry,Go
«
teborg University, Sweden;
CHRIST OPHER GILLBERG, MD , PhD , Department of Child and Adolescent Psychiatry, Goteborg University,CH R I STOPHER G IL LBERG, MD, PhD, Department of Child and Adolescen t Psych i at ry,Go
«
teborg Un iversi ty,
Sweden and St Georges Hospital Medical School London,UK; HENRIK ANCKARSATER, MD, PhD,Sweden and S t Georges Hosp ital M ed ical Schoo l London ,UK; H E NRIK A NCKAR SA
«
TE R, M D, PhD,
Department of Child and Adolescent Psychiatry and Institute of Clinical Neuroscience,Department of ForensicDepartment of Child and Adolescent Psychiatry and Institute of Clinical Neuroscience,Depar tment of Forensic
Psychiatry,Goteborg University, SwedenPsychiatry,Go
«
teborg University, Sweden
Correspondence: Henrik Anckarsater, Forensic Psychiatric Clinic,University Hospital of Malmo, SegeCorrespondence:Henrik Anckar sa« ter, Forensic Psychiatric Clinic,University Hospital of Malmo
«
,Sege
Park, 8A, S-205 02 Malmo, Sweden.Tel: +46 40 334031; fax: +46 40 334127; e-mail:Park, 8A, S-205 02 Malmo
«
,Sweden.Tel: + 46 40 334031 ; fax : + 46 40 33412 7 ; e - mail:
henrik.anckarsaterhenrik.anckarsater@@ska ne.seskane.se
(First received19 March 2004, final revision 14 September 2004, accepted 29 September 2004)(First received19 March 2004, final revision 14 September 2004, accepted 29 September 2004)
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    • "ADHD and autistic traits were assessed with the Autism—Tics, AD/HD, and other Comorbidities inventory (A-TAC) [39][40][41]which is a parental telephone interview for assessing neuropsychiatric problems in children. All interviews were conducted by professional interviewers who had undergone a brief introduction to psychiatry and twin research. "
    [Show abstract] [Hide abstract] ABSTRACT: Autism spectrum disorder (ASD) and attention-deficit/hyperactivity disorder (ADHD) are neurodevelopmental disorders thought to have both genetic and environmental causes. It has been hypothesized that exposure to elevated levels of prenatal testosterone is associated with elevated traits of ASD and ADHD. Assuming that testosterone levels from a dizygotic male twin fetus may lead to enhanced testosterone exposure of its co-twins, we aimed to test the prenatal testosterone hypothesis by comparing same-sex with opposite-sex dizygotic twins with respect to neurodevelopmental symptoms. Neuropsychiatric traits were assessed in a population-based twin cohort from the Child and Adolescent Twin Study in Sweden (CATSS). Parental interviews were conducted for 16,312 dizygotic twins, 9 and 12 years old, with the Autism—Tics, ADHD, and other Comorbidities inventory (A-TAC). Girls with a female co-twin had an increased risk of reaching the cut-off score for ADHD compared with girls with a male co-twin. Both boys and girls with a female co-twin displayed a larger number of traits related to attention deficit and repetitive and stereotyped behaviors than those with a male twin. In girls, this also extended to social interaction and the combined measures for ASD and ADHD, however, with small effect sizes. Our results are reverse to what would have been expected from the prenatal testosterone hypothesis but consistent with a previous study of ASD and ADHD traits in dizygotic twins. The seemingly protective effect for girls of having a twin brother may be an effect of parent report bias, but may also be an unexpected effect of sharing the intrauterine environment with a male co-twin.
    Full-text · Article · Dec 2016
    • "In the present study we used data from the CATSS, earlier described in Garcia et al. [14], whose parents were interviewed by telephone using the Autism—Tics, ADHD ,and other Comorbidities inventory [21] when the twins were 9 or 12 years of age. At the age of 15, the twins completed a battery of questionnaires that were sent by mail (overall response rate 48 %), including the short version (125 items) of the Temperament and Character Inventory. "
    [Show abstract] [Hide abstract] ABSTRACT: Background: The character higher order scales (Self-directedness, Cooperativeness, and Self-transcendence) in the Temperament and Character Inventory are important general measures of health and well-being (Cloninger, 2013). Recent research has found suggestive evidence of common environmental influence on the development of these character traits during adolescence. The present article expands earlier research by focusing on the internal consistency and the etiology of traits measured by the lower order sub-scales of the character traits in adolescence. Method: The twin modeling analysis of 423 monozygotic pairs and 408 same sex dizygotic pairs estimated additive genetics (A), common environmental (C), and non-shared environmental (E) influences on twin resemblance. All twins were part of the on-going longitudinal Child and Adolescent Twin Study in Sweden (CATSS). Results: The twin modelling analysis suggested a common environmental contribution for two out of five Self-directedness sub-scales (0.14 and 0.23), for three out of five Cooperativeness sub-scales (0.07-0.17), and for all three Self-transcendence sub-scales (0.10-0.12). Conclusion: The genetic structure at the level of the character lower order sub-scales in adolescents shows that the proportion of the shared environmental component varies in the trait of Self-directedness and in the trait of Cooperativeness, while it is relatively stable across the components of Self-transcendence. The presence of this unique shared environmental effect in adolescence has implications for understanding the relative importance of interventions and treatment strategies aimed at promoting overall maturation of character, mental health, and well-being during this period of the life span.
    Full-text · Article · Mar 2016
    • "In Study III, higher levels of ADHD symptoms during childhood were associated with more ADHD symptoms during adolescence. Given that the A-TAC interview showed good predictive validity for ADHD, this was not surprising (Hallerod et al., 2010; Hansson et al., 2005; Larson et al., 2010; Larson et al., 2013). Our finding that girls and boys reported somewhat different problem profiles also replicates results from previous longitudinal followups . "
    [Show abstract] [Hide abstract] ABSTRACT: ABSTRACT Childhood neurodevelopmental problems (NDPs; encompassing attention deficit hyperactivity disorder [ADHD], autism spectrum disorder [ASD], tic disorder [TD], learning disorder [LD], and developmental coordination disorder [DCD]), affect around 10% of children worldwide. ADHD is the most common disorder, with an estimated prevalence between 5 and 10%. Based on its relatively high prevalence and associated impairments and adverse outcomes, ADHD is considered a major public health problem. The etiology of ADHD is multifactorial, including both genetic and environmental factors. ADHD affects both boys and girls in various areas of functioning; including academic, cognitive, psychosocial, and mental health. Previous longitudinal research on ADHD has rarely included aspects of comorbidity in relation to such outcomes. Also, it remains unclear how genetic and environmental factors influence the association between ADHD and internalizing problems during childhood and adolescence. To avoid the potentially artificial demarcation of a diagnostic cut-off, several studies have assessed the degree of core ADHD-symptoms rather than the clinical diagnosis. Such work indicates that subthreshold levels of ADHD may also be associated with negative outcomes such as poorer academic achievements, lower self-esteem, and relationship problems. A particular challenge for society lies in the fact that only children who are clinically assessed and diagnosed with ADHD may be entitled to care and support, when in fact individuals with subthreshold level symptoms might also benefit from such interventions. The general aim of this thesis was to investigate how childhood symptoms of ADHD affect psychosocial outcomes in adolescence, with a special focus on gender differences. We used data from a population-based cohort of twins, who were assessed for the presence of NDP symptoms during childhood and followed up at age 15. Study I investigated the diagnostic predictive validity of the screening-interview A-TAC, an instrument that is used throughout all studies in this thesis. The results demonstrated that A-TAC is an effective screening tool for NDPs, and that it can be used for the purpose of predictive assessment in the general population. Overall, A-TAC demonstrated satisfactory psychometric properties as a screening instrument. Study II examined the association between childhood signs of ADHD and/or other NDPs (at age 9 or 12) and psychosocial outcomes at age 15. The results demonstrated that symptoms of NDPs or other mental health problems at the age of 9 or 12 were associated with a higher degree of psychosocial problems during adolescence. Despite the presence of comorbidity, childhood ADHD symptoms stood out as the most important risk factor for later antisocial development and impaired daily functioning. Study III examined if different levels of ADHD symptoms were differentially associated with psychosocial problems in adolescent boys and girls. ADHD symptoms as well as their associated negative outcomes were dimensionally distributed in the study cohort. Girls and boys displayed somewhat different risk profiles, even after controlling for other neuropsychiatric symptoms. Study IV explored the relative contribution of genetic and environmental influences associated with childhood ADHD and internalizing problems to symptoms of internalizing problems during adolescence. ADHD and internalizing problems were associated. There was a gender difference in the genetic explanation of internalizing problems at age 15. In both boys and girls, both new genetic and new environmental factors emerged in adolescence. In summary, childhood symptoms of ADHD turned out to be the most important risk factor for adolescent antisocial behavior and impaired daily functioning, despite the presence of comorbid symptoms. During adolescence, increasing levels of ADHD-related symptoms were associated with increasing levels of psychosocial problems. Girls and boys displayed somewhat different risk profiles, e.g. girls displayed more internalizing symptoms and seemed to have a higher risk for drug misuse. The finding that ADHD symptoms were associated with higher drug misuse in girls motivates particular attention and active screening routines. The findings also point to the need for increased awareness and further study of the complex etiologic and developmental relationship between internalizing symptoms and ADHD.
    Thesis · Nov 2015 · Annals of General Psychiatry
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