J. Child Psychol. Psychiat. Vol. 39, No. 3, pp. 347–354, 1998

Cambridge University Press

' 1998 Association for Child Psychology and Psychiatry

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The Longitudinal Stability of Psychiatric Problems in Childrenwith Hemiplegia

Robert Goodman

Institute of Psychiatry, London, U.K.

A representative sample of 328 children with hemiplegia was assessed by behaviouralscreening questionnaires completed by parents and teachers ; just under half were alsoindividually assessed. Four years later, 90% of the samplewere followed up by questionnaire.There was substantial continuity across time for most measures of psychopathology.Depending on the measures used, around 70% of children who were psychiatric ‘‘cases ’’initially were still cases 4 years later. In addition, around 30% of children who were notpsychiatric cases initially had become cases 4 years later. In the preschool years, externalisingsymptoms were predictive of later conduct and hyperactivity problems, whereas emotionalsymptoms were not predictive of later problems. In the school years, hyperactivity wasparticularly predictive of continuing psychiatric problems. Neurological, cognitive, demo-graphic, and family factors did not add much predictive power once allowance had beenmade for the severity and type of the initial psychiatric problems. Since the psychiatriccomplications of childhood hemiplegia are persistent as well as common, they warrantincreased clinical and research attention. All children with hemiplegia deserve carefulmonitoring for psychiatric problems, with a view to early intervention or the deployment ofpreventative approaches.

Keywords: Psychiatric disorder, prognosis, childhood hemiplegia, longitudinal stability.

Abbreviations: BCL: Behaviour Checklist ; LHR: London Hemiplegia Register ; PBC: Pre-school Behaviour Checklist.

Introduction

Children with cerebral palsy and other chronic braindisorders have a substantially higher rate of psychiatricproblems than do children with chronic disorders ordisabilities that are not secondary to brain abnor-malities—strongly suggesting the existence of directbrain-behaviour links in addition to any indirect effects ofchronic disability and stigmatisation (Breslau, 1985;Rutter, Graham, & Yule, 1970; Seidel, Chadwick, &Rutter, 1975). One recent study of children with hemi-plegic cerebral palsy showed that around half of themhad clinically significant psychiatric disorders (Goodman& Graham, 1996; Goodman & Yude, 1997)—a par-ticularly striking finding since the physical disabilityassociated with hemiplegia is relatively mild, and mosthemiplegic children are of normal intelligence and attendmainstream schools.

Despite the high rate of psychiatric problems amongchildren with cerebral palsy, there have been practicallyno studies of how persistent these disorders are. Onenotable exception is the longitudinal study of Breslau andMarshall (1985), which involved a 5-year follow-up of

Requests for reprints to: Dr R. Goodman, Department ofChild and Adolescent Psychiatry, Institute of Psychiatry, DeCrespigny Park, London SE5 8AF, U.K.

children with cystic fibrosis or a chronic brain disorder.Whereas the adjustment of children with cystic fibrosisimproved as they grew older, greater stability of problemswas evident among the children with brain disorders.Among children who were severely psychiatricallyimpaired at the time of their first assessment, theproportion who were still severely psychiatricallyimpaired 5 years later was 61% for children with braindamage but only 29% for children with cystic fibrosis.

The present longitudinal study applied widely used andwell-validated psychiatric measures to a representativesample of children with hemiplegia. Four questions areaddressed. First, how likely are children with hemiplegiato grow out of, or into, psychiatric problems? Second,which sorts of early symptoms best predict later symp-toms? Focusing early interventions on the symptomdimension with greatest predictive power may be aparticularly efficient way of reducing subsequent symp-toms. Third, is persistence influenced by non-psychiatricfactors such as gender, intelligence, side of hemiplegia,severity of hemiplegia, family adversity, or social class?Finally, is it possible to predict future psychiatric prob-lems sufficiently accurately to identify an ‘‘at-risk’’group who would potentially benefit from early inter-ventions, as opposed to the remainder who are at toolow a risk to warrant such help? This paper does notaddress the issue of whether the psychiatric problemsof children with brain disorders are more persistent than

347

348 R. GOODMAN

comparable psychiatric problems in neurologically intactchildren—this question will be addressed in a subsequentpaper.

Materials and Methods

The London Hemiplegia Register (LHR) ascertained anepidemiological sample of 461 London children with a clinicaldiagnosis of hemiplegia, all of whom were aged 16 or under atthe time of ascertainment ; the sample’s characteristics arecomparable to those of previous epidemiological samples ofchildren with hemiplegia (Goodman & Yude, 1996a). All LHRsubjects were evaluated by parent and teacher questionnaires,with a sample of 149 hemiplegic children aged between 6 and 10also being individually assessed using neurological, neuro-psychological, and neuropsychiatric measures ; these individu-ally assessed children were representative of hemiplegic childrenof their age (Goodman & Yude, 1996a). The present study is a4-year follow-up of non-overlapping preschool and school-agesamples from the LHR.

Preschool Sample

The preschool sample comprised the 88 children from theLHR who were aged between 2±5 and 4±9 years at the time theywere initially assessed (T1). At least one behavioural screeningquestionnaire was completed on each of these children: theBehaviour Checklist (BCL; Richman, 1977) was completed byparents on 89% of the sample, and the Preschool BehaviourChecklist (PBC; McGuire & Richman, 1986) was completed bynursery teachers or other preschool professionals on 73% of thesample. These subjects were all aged over 5 at follow-up (T2),when questionnaires were sent to parents and teachers anaverage of 4±1 years later (SD 0±8 years, 95% range 2±7–5±4years). Both the parent and teacher follow-up questionnairesincorporated a modified Rutter behavioural screening ques-tionnaire that included all the original items from the Rutterquestionnaire, interspersed with additional items on children’sstrengths (Goodman, 1994). The teacher questionnaire alsoincluded seven hyperactivity items from the Conners teacherrating-scale (Conners, 1969; Taylor & Sandberg, 1984). Parentsand teachers were also asked to estimate at what age level thechild was operating in terms of intellectual and scholasticability. Follow-up questionnaires were obtained from 86% ofparents and 88% of teachers, with at least one follow-upquestionnaire being available on 92% of the sample.

Full School-age Sample

The school-age sample comprised the 240 children from theLHR who were aged between 5±0 and 11±9 years at the time theywere initially assessed (T1)—the upper limit being chosen toensure that they were still attending school and eligible forteacher questionnaires at the 4-year follow-up (T2). The T1 andT2 questionnaires for both parents and teachers included anitem on mental age and a modified Rutter questionnaire(Goodman, 1994). The T1 and T2 teacher questionnaire alsoincluded seven hyperactivity items from the Conners teacherrating-scale (Conners, 1969; Taylor & Sandberg, 1984). At leastone Rutter questionnaire was completed on each of thesechildren at T1: a parent version on 91% of the sample, and ateacher version on 93% of the sample. Follow-up was anaverage of 4±4 years later (SD 1±0 year, 95% range 2±5–6±4years). T2 parent questionnaires were obtained on 83% of thesample and T2 teacher questionnaires were obtained on 84% ofthe sample, with at least one T2 questionnaire being availableon 90% of the sample.

The BCL, PBC, and Rutter questionnaires were scored in thestandard manner to extract total deviance scores and to

determine which subjects were and were not psychiatric ‘‘cases ’’(McGuire & Richman, 1986; Richman, 1977; Rutter, 1967;Rutter, Tizard, & Whitmore, 1970). Although the version oftheRutter questionnaires used in the study interspersed the orig-inal Rutter items with additional items on children’s strengths,the Rutter scores were calculated by summing all the originalRutter items without including any of the novel items; aprevious study of the individually studied children with hemi-plegia demonstrated that the optimal caseness cut-off using thisprocedure was exactly the same as the standard caseness cut-offfor the unmodified Rutter questionnaire (Goodman, 1994). Inthe LHR sample, caseness determined from modified Rutterquestionnaires corresponded well (sensitivity 71%, specificity70%), with caseness determined by individual psychiatric evalu-ation using a method of demonstrated reliability and validity(Goodman, 1994; Goodman, Yude, Richards, & Taylor,1996). Separate conduct, emotional, and hyperactivity scoreswere extracted from the Rutter questionnaires, with the first twoalso being used to determine whether cases were conduct oremotionally disordered (Rutter, 1967; Rutter, Tizard, et al.1970; Schachar, Rutter, & Smith, 1981). The seven Connersitem were summed to generate a supplementary hyperactivityscore (Taylor & Sandberg, 1984).

Individually-assessed School-age Sample

The school-age sample included all 149 children who wereindividually assessed at T1; complete T1 data were available on141 of these children, of whom 135 (96%) had been followed upby a T2 parent questionnaire and 133 (94%) had been followedup by a T2 teacher questionnaire. T1 measures of these childrenused in the present analyses include IQ, parental social class(manual or non-manual), symptom scores from a standardisedsemi-structured interview with parents (the Parental Account ofChild Symptoms; Taylor, Schachar, Thorley, & Wieselberg,1986), whether or not the child attended a special school,whether or not the child lived in a single-parent family, side ofhemiplegia, and summary measures of neurological severity andadverse family factors ; these measures are not described indetail here, having been described more fully previously(Goodman & Graham, 1996; Goodman & Yude, 1996b). Inbrief, the summary rating of neurological severity—the N scoredescribed in Goodman and Yude (1996b)—was generated fromfive variables : degree of hemiparesis, presence and type ofseizure disorder, presence of bilateral involvement, head cir-cumference, and time of onset. The presence of some bilateralsigns in a substantial minority of children with a clinicaldiagnosis of hemiplegia is well recognised. The summary ratingof adverse family factors was generated from four variables :parental criticism of the child, lack of parental warmth for thechild, poor parental child management skills, and maternalpsychiatric morbidity (Goodman & Graham, 1996).

For the individually assessed children, a variable on change inepilepsy status was generated from T1 and T2 parent ques-tionnaire information on seizures and anticonvulsants (supple-mented where possible by interview and case note information).Children were defined as having epilepsy if they had hadseizures in the previous 2 years or were maintained onanticonvulsants. Resolution of epilepsy between T1 and T2 wasscored 1; no change in epilepsy status (whether present orabsent) was scored 0; and a new onset of epilepsy between T1and T2 was scored ®1.

In the intensively studied sample of 149 children aged 6 to 10,psychometrically assessed IQ correlated very highly with ratioIQs (100¬mental age}chronological age) based on parent andteacher estimates of mental age (r¯±76 for psychometric IQand parent-based ratio IQ; r¯±78 for psychometric IQ andteacher-based ratio IQ; Goodman & Yude, 1996a). In the

349PERSISTENCE OF PSYCHIATRIC SYMPTOMS

present study ratio IQs were used as covariates for someanalyses. Because the high correlation between ratio IQs andpsychometric IQs was only demonstrated for hemiplegic chil-dren aged 6 to 10, the ratio IQs used in this study were based onT2 estimates of mental age for the preschool group (aged 5 to 9at the time) and on T1 estimates of mental age for the school-age group (aged 5 to 11 at the time).

Analyses

All bivariate correlational analyses were performed usingboth Pearson and Spearman correlation coefficients. The twosets of analyses generated similar findings and conclusions. Formost of the bivariate analyses, the Pearson correlation coeffi-cients are presented since they are more easily compared withthe reported partial correlation coefficients (covarying forintelligence). Though the reported regression analyses werecarried out on untransformed scores evenwhen the distributionswere not normal, similar findings and conclusions were obtainedwhen the analyses were repeated using transformed scores(e.g. logarithmic transformations). Individual symptoms at T1were not used as predictors in the regression analyses. With105 different questionnaire and interview-based symptomsmeasured at T1, there was a high likelihood that including themas predictors in all the regression analyses would have generatedmany spurious findings. Both conceptually and clinically itmade better sense to predict from symptom scores tapping thethree best recognised dimensions of psychopathology: emotion-al symptoms, conduct problems, and hyperactivity. Totaldeviance scores were also included as predictors in the regressionanalyses to see if these would take precedence over the morespecific symptom scores. If the domain-specific scores are ofroughly comparable predictive value, then the total score willhave the greatest predictive value (since error variance isreduced by a larger number of component items). Consequently,if specific scores take precedence over total scores, this is strongevidence for domain specificity in predictive power. Thestandardised regression (beta) coefficients are presented forsignificant effects to facilitate comparisons of effect sizes.

Results

Preschool Follow-up

Total problem score. The average age of the childrenin the preschool follow-up was 3±5 years (SD¯ 0±6) at T1and 7±6 years (SD¯ 1±2) at follow-up. The correlationsbetween the total problem scores at T1 and T2 were ±57for parent-derived scores (N¯ 70, p!±001) and ±34 forteacher-derived scores (N¯ 55, p¯±01). These correla-tions were only slightly attenuated when IQ was enteredas a covariate, with partial correlations between T1 andT2 total problem scores of ±55 for parent-derived scoresand ±34 for teacher-derived scores. Parent-teacher corre-lations across time were substantially lower and not sig-nificant : the correlation between parent-reported prob-lems at T1 and teacher-reported problems at T2 was ±09,while the correlation between teacher-reported problemsat T1 and parent-reported problems at T2 was ±18.

Individual items. Table 1 shows which preschoolparent items predicted parent-reported problems at T2.Externalising and toileting problems at T1 predictedmore externalising problems at T2. Though conduct andhyperactivity problems at T2 had generally similarpredictors, early reports of poor concentration, attention-seeking behaviour, and indistinct speech were morepredictive of subsequent hyperactivity, whereas tantrums,

clinginess, and speech delay were more predictive ofsubsequent conduct problems. Emotional problems at T2were significantly predicted by appetite and sleepproblems at T1, but not by misery, worries, or fears at T1.

Table 2 shows which items reported by nursery teachers(or other preschool professionals) at T1 predictedteacher-reported problems at T2. Six oppositional-defiant problems at T1 predicted subsequent conduct andhyperactivity problems. Problems at T1 with attention oractivity were not significant predictors of subsequentexternalising problems. There were no significant pre-dictors of subsequent emotional problems. When thescores on the six oppositional-defiant items were summedto generate an oppositional-defiant score, this correlated±57 with the total problem score at T2 (N¯ 55,p!±001)—falling slightly to a partial correlation of±48 once IQ had been entered as a covariate.

Caseness. Applying the standard cut-offs on thescales, parent-derived caseness at T1 was a significantpredictor of parent-derived caseness at T2. Of the childrenwho were cases at T1, 68% (25}33) were cases at T2. Bycomparison, 39% (13}37) of the children who were notcases at T1 were cases at T2 (continuity-adjusted χ#¯4±5, df 1, p¯±034).

Teacher-derived caseness at T1 was not a significantpredictor of teacher-derived caseness at T2: of thechildren who were cases at T1, 56% (10}18) were cases atT2, as compared with 46% (17}37) of children who hadnot been cases at T1 (continuity-adjusted χ#¯ 0±1, df 1,n.s.). By contrast, high preschool scores for oppositional-defiant behaviours were predictive. Thus according totheir preschool teacher, roughly half the sample had anoppositional-defiant score of 0 or 1 (reflecting no oppo-sitional-defiant problems or just one possible area ofproblems) and 34% (10}29) of these children were casesat T2. The remaining half of the sample had a higheroppositional-defiant score and 65% (17}26) of thesechildren were cases at T2 (continuity-adjusted χ#¯ 4±1,df 1, p¯±044).

School-age Follow-up

Total problem scores. The average age of the childrenwas 7±9 years (SD¯ 2±0) at initial assessment and 12±2years (SD¯ 1±9) at follow-up. As shown in Table 3, themean level of problem scores did not significantly changebetween T1 and T2, with the exception of small butsignificant falls in the hyperactivity scores. In no instancedid the change in score over time correlate significantlywith the initial age of the subjects ; neither did graphicalexamination of the relationship between age and changesuggest any systematic linear or quadratic trend.

Table 4 shows the correlation between T1 and T2scores for each of the questionnaire-based symptomscores. These correlations were only slightly attenuatedwhen IQ was entered as a covariate. For example, thecorrelation between the T1 and T2 total problem scorefell from ±67 to ±63 for parent-derived scores, and from ±41to ±39 for teacher-derived scores. Longitudinal cross-rater correlations were somewhat lower but still highlysignificant except for the emotional scores. For example,the correlation between total parent-reported problemsat T1 and total teacher-reported problems at T2 was ±25

350 R. GOODMAN

Table 1Items in Preschool Parent Questionnaire that Predicted a Parent-reported Scores at T2(N¯ 70)

Spearman correlationb with parent-reported problem at T2

Predictive T1(preschool) item

Totaldeviance

scoreEmotional

scoreConduct

scoreHyperactivity

score

Poor appetite 22 29* 14 16Faddy eater 12 32** ®07 08Hard to get to sleep 22 34** 07 09Night wakenings 19 24* 07 ®09Worries ®17 05 ®25* ®30*Bed wetting 32* ®02 24 34*Day wetting 42*** 05 40** 41**Soiling 45*** 18 39** 37**Overactive 33** 02 41*** 47***Poor concentration 23 01 25* 46***Hard to handle 35** 02 33** 41***Attention seeking 16 11 19 29*Tantrums 33** 22 24* 19Clingy 25* 18 26* 10Speech indistinct 21 ®12 21 37**Not speaking in sentences 21 ®09 28* 21Problems playing with others 36** 18 18 18

a The following items were not significantly correlated with any T2 scores : sleeps with parents,misery, fears, and sibling relationships.

b Decimal point not shown. Significant correlations underlined: * p!±05; ** p!±01;*** p!±001.

Table 2Items in Preschool Teacher Questionnaire that Predicted a Teacher-reported Scores atT2 (N¯ 55)

Spearman correlationb with teacher-reported problem at T2

Predictive T1(preschool) item

Totaldeviance

scoreEmotional

scoreConduct

score

Hyperactivityscore

(Rutter)

Hyperactivityscore

(Conners)

Aggression 47*** 27 55*** 47*** 55***Spiteful 38** 07 51*** 39** 43**Defiant 43** 02 40** 31* 43**Interferes with others 35** 04 41** 41** 44***Tantrums 38** 08 31* 20 37**Destructive 32* 13 40** 32* 43**Speech indistinct}absent 39** 05 27* 29* 29*Not liked by others 13 ®18 28* 17 16

a The following items were not significantly correlated with any follow-up scores : activity level,poor concentration, wetting, soiling, attention-seeking, solitary, whining, easily upset, oftenvacant, misery, withdrawal, fearful, repetitive habits.

b Decimal point not shown. Significant correlations underlined. * p!±05; ** p!±01;*** p!±001.

Table 3Changes in Symptom Scores a in School-age Children between T1 and T2

Parent ratings (N¯ 190) Teacher ratings (N¯ 188)

T1 T2 T1 T2

Total deviance score 13±7 (7±4) 13±4 (8±0) 9±0 (6±4) 9±6 (6±6)Emotional score 2±7 (1±9) 2±7 (2±0) 2±1 (1±7) 2±4 (1±8)Conduct score 1±7 (1±7) 1±7 (2±0) 1±3 (1±9) 1±3 (2±0)Hyperactivity score (Rutter) 2±1 (2±0) 1±8 (1±9)** 1±9 (2±0) 1±5 (1±8)*Hyperactivity score (Conners) — — 6±5 (5±0) 5±6 (4±6)*

a Mean score (SD) and significance of change: matched sample t-test : * p!±05; ** p!±01.

351PERSISTENCE OF PSYCHIATRIC SYMPTOMS

Table 4Longitudinal Stability of Behaviour Deviance Scores in School-age Children

T1*T2 correlations

MeasureParent

ratings (N¯ 190)Teacher

ratings (N¯ 188)

Total deviance score ±67*** ±41***Emotional score ±48*** ±20**Conduct score ±58*** ±34***Hyperactivity score (Rutter) ±62*** ±38***Hyperactivity score (Conners) — ±48***

* p!±05; ** p!±01; *** p!±001.

Table 5Significant T1 Predictors of T2 Scores in Multiple Regression Analyses, and TheirStandardised Regression (Beta) Coefficients

Predicting to Adj R# T1 Predictors Beta (SE ) p a

Parent ratings at T2 (N¯ 135)Total deviance score (PR) ±52 Total deviance score (PR) ±53 (±07) ***

Hyperactivity (PI) ±29 (±07) ***

Emotional score (PR) ±23 Emotional score (PR) ±28 (±10) **Total deviance score (PR) ±27 (±10) **

Conduct score (PR) ±37 Conduct score (PR) ±41 (±08) ***Hyperactivity (PI) ±32 (±08) ***

Hyperactivity score (PR) ±51 Hyperactivity (PI) ±39 (±08) ***Hyperactivity (PR) ±25 (±08) **Gender ±19 (±06) **Hyperactivity (TC) ±17 (±07) *

Teacher ratings at T2 (N¯ 133)Total deviance score (TR) ±25 Hyperactivity (TC) ±37 (±08) ***

IQ ®±24 (±08) **Epilepsy changes ®±22 (±08) **

Emotional score (TR) None

Conduct score (TR) ±18 IQ ®±21 (±09) *Conduct score (TR) ±21 (±08) *Hyperactivity (PI) ±20 (±09) *

Hyperactivity (TR) ±24 Hyperactivity (TC) ±41 (±08) ***Gender ±25 (±08) **

Hyperactivity (TC) ±36 Hyperactivity (TC) ±30 (±08) ***Gender ±26 (±07) ***IQ ®±23 (±08) **Hyperactivity (PI) ±17 (±08) *

a Probability in full model : * p!±05; ** p!±01; *** p!±001.PR¯parent Rutter ; PI¯parent interview; TR¯ teacher Rutter ; TC¯ teacher Conners.

(N¯ 191, p!±001), whereas the correlation betweentotal teacher-reported problems at T1 and total parent-reported problems at T2 was ±28 (N¯ 186, p!±001).

Caseness. Using parent-derived measures, ‘‘caseness ’’at T1 was highly predictive of caseness at T2: of thechildren who were cases at T1, 76% (81}107) were stillcases at T2, whereas only 23% (19}82) of the childrenwho were not cases at T1 had become cases by T2(continuity-adjusted χ#¯ 49±3, df 1, p!±001). The per-sistence of caseness was not significantly related towhether the type of disorder was initially characterised asa conduct disorder or an emotional disorder : of thosewith a conduct disorder at T1, 78% (32}41) still had adisorder at T2; whereas of those with an emotionaldisorder at T1, 74% (49}66) still had a disorder at T2(continuity-adjusted χ#¯ 0±1, df 1, n.s.)

Similar effects were evident from teacher-derived case-ness ratings. Of the children who were cases at T1, 69%(56}81) were still cases at T2, whereas only 38% (19}82)of the children who were not cases at T1 had becomecases by T2 (continuity-adjusted χ#¯ 16±5, df 1, p!±001).Once again, the persistence of caseness was not signifi-cantly related to whether the type of disorder was initiallycharacterised as a conduct disorder or an emotionaldisorder : of those with a conduct disorder at T1, 69%(31}45) still had a disorder at T2; whereas of those withan emotional disorder at T1, 67% (26}39) still had adisorder at T2 (continuity-adjusted χ#¯ 0, df 1, n.s.)

Individually studied sample. For the individuallystudied children, stepwise multiple regression analyseswere used to examine which variables at T1 madean independent contribution to predicting the nine

352 R. GOODMAN

questionnaire-based symptom scores at T2 (see Table5). The predictors were 13 T1 symptom scores, 8 back-ground factors, and 1 change score. The 13 T1 symptomscores comprised 9 questionnaire-based scores—the T1counterparts of the dependent variables—plus 4 symp-tom scores from the standardised semi-structured parentinterview at T1: a hyperactivity score, an emotionalscore, a conduct score, and a total score. The eightbackground factors were: gender, social class, parentingsituation, type of schooling, adverse family factors, IQ,side of hemiplegia, and severity of neurological involve-ment. The change score reflected change in seizure statusbetween T1 and T2. In case the relationship with T1symptom scores was nonlinear, the analyses summarisedin Table 5 were repeated after including quadratic termsfor all 13 T1 scores in each of the 9 multiple regressionanalyses (thus generating 117 opportunities for a quad-ratic term to be significant). Only 3 of these 117 possiblequadratic effects were significant at p!±05; since this wasaround the level expected from chance alone, the quad-ratic terms were omitted and the simpler linear modelpresented.

As can be seen from Table 5, most T2 scores werepredicted by their T1 counterparts. T1 hyperactivityscores had particularly marked predictive power: five T2scores were predicted by the interview-based hyper-activity score at T1, whereas no T2 score was predicted bythe other interview-based scores ; five T2 scores werepredicted by at least one questionnaire-based hyper-activity score at T1, whereas no more than two T2 scoreswere predicted by any one of the other categories ofquestionnaire-based scores. The predictive power ofhyperactivity was even evident across setting (school orhome). Thus the T1 hyperactivity score from the parentinterview predicted two T2 teacher scores : the conductscore and the Conners’ hyperactivity score. Conversely,the T1 teacher Conners’ hyperactivity score predicted theT2 parent hyperactivity score.

Only two background factors and the change scorewere significant predictors of T2 psychiatric measuresonce the effects of T1 psychiatric measures had beenallowed for. Being female was associated with a greaterdecrease in all three hyperactivity scores (by about 0±5SD). Higher IQ was associated with a greater decrease inteacher-reported conduct, hyperactivity and total scores(by about 0±1 SD for a 15-point increase in IQ).Resolution of epilepsy was associated with a decrease (byabout 0±4 SD) in teacher-reported total scores ; a newonset of epilepsy had the opposite effect.

Discussion

Reliable and well-validated measures were used in thisstudy to examine the persistence of psychiatric problemsin a large epidemiological sample of hemiplegic children.Despite these strengths, there are two reasons for re-garding the study’s findings as preliminary. First, thestudy was primarily based on screening questionnairesrather than on detailed individual assessments—thoughit is reassuring that questionnaire and interview measurescorrelated well in this sample (Goodman, 1994). Inaddition, the follow-up measures were entirely derived

from parent and teacher reports—self-reports might havetold a different story. With these reservations, the studyhas provided partial answers to the four questions posedin the Introduction.

Persistence of Psychiatric Problems

How likely were children with hemiplegia to grow outof psychiatric problems? In this study, around 70% ofchildren initially classified as psychiatric ‘‘cases ’’ werestill cases 4 years later ; the only exception to this rule wasthe lack of predictive value of caseness defined frompreschool teacher reports, unless these were focused onoppositional-defiant behaviour. The persistence of psy-chiatric problems was not primarily attributable to a linkbetween these problems and low intelligence. The con-tinuity in parent-reported problems may have been partlyattributable to a rater effect, since the same parent usuallyrated the child on both occasions. Rater effects could notaccount for the continuity of teacher-reported problemssince the initial and follow-up ratings were made bydifferent teachers, often in different schools. An im-portant message for clinicians is that when a child withhemiplegia has psychiatric problems, it is often inap-propriate to reassure the parents that their child will soongrow out of these problems without additional help.

How likely were children with hemiplegia to grow intopsychiatric problems? In this study, around 30% ofchildren who were not cases initially had become cases 4years later. Professionals such as paediatricians andphysiotherapists who come into regular contact withchildren with hemiplegia should not stop enquiring aboutpossible emotional and behavioural disorders just be-cause the child has not previously had this sort ofdisorder.

Predictive Symptoms

Which early symptoms best predict later symptoms?Among preschool children with hemiplegia, subsequentconduct and hyperactivity problems were predicted byparent reports of overactive, inattentive, and difficultbehaviour, and by teacher reports of oppositional anddefiant behaviour. By contrast, preschool reports ofworries, fears, and misery had no predictive value. Sinceexternalising problems among hemiplegic preschoolersare both common and persistent, there is obviously astrong case for careful monitoring of these problems inthe preschool years so that problems in this area can berecognised and treated at an early stage. There is alsoa case for investigating the utility of preventative ap-proaches such as parent training groups in child manage-ment techniques.

Among schoolchildren with hemiplegia, symptoms ofrestlessness and inattentiveness were particularly strongpredictors of persisting psychiatric problems. One poss-ible explanation is that organically driven hyperactivity iscommonly a hemiplegic child’s main entry route intoother types of psychiatric problems (particularly exter-nalising problems). Clinical experience suggests that thehyperactivity of hemiplegic schoolchildren is commonlyresponsive to stimulants ; it would be of great practical

353PERSISTENCE OF PSYCHIATRIC SYMPTOMS

and theoretical interest to know whether the use ofmedication to reduce these children’s hyperactivity com-monly prevented the emergence of other psychiatricproblems.

Predicting Persistence from Non-psychiatricFactors

Is persistence influenced by background factors suchas gender, intelligence, side of hemiplegia, severity ofhemiplegia, family adversity, or social class? A previouscross-sectional survey has shown that the presence ofpsychiatric symptoms among hemiplegic children isstrongly predicted by a variety of background factors,including intelligence, neurological severity, and adversefamily factors (Goodman & Graham, 1996). By con-trast, the findings of this study suggest that the prognosisof psychiatric problems is largely independent of back-ground factors once the severity and type of the initialproblems have been taken into account. The exceptionswere that girls had a better prognosis for hyperactivitysymptoms, and that more intelligent children had aslightly better prognosis for teacher-reported exter-nalising problems. In addition, improvement or deterio-ration in epilepsy status was associated with some parallelchanges in teacher-reported problems.

At the initial assessment, there was an associationbetween psychiatric problems and a summary measure ofadverse family factors (tapping parental mental illness,coldness to the child, criticism of the child, and poor childmanagement skills). It is interesting, therefore, thatadverse family factors did not seem to influence prog-nosis, i.e. high family adversity did not appear to enhancethe onset of new problems or retard the remission ofexisting problems. This suggests that adverse familyfactors are more likely to be consequences than causesof the children’s psychiatric problems—an importantconclusion since the parents of hemiplegic childrencommonly feel to blame (and blamed) for theirchild’s psychiatric problems: a dispiriting and seeminglyunfounded view that is all too often reinforced byprofessionals.

Identifying a High-risk Group for Interventions

Is it possible to predict future psychiatric problemssufficiently accurately to identify an ‘‘at-risk’’ group whowould potentially benefit from early interventions, asopposed to the remainder who are at too low a risk towarrant such help? The study succeeded in identifyingseveral high-risk groups, but did not identify any low-riskgroups. At any age, children with identified psychiatricproblems were likely to continue having problems foryears. There is certainly a good case for targeting thesechildren for early interventions. At the other extreme,though, even those hemiplegic children without psy-chiatric disorders initially were still at a medium risk ofdeveloping such disorders subsequently. In these cir-cumstances, trials of preventative approaches—such asbehavioural surveillance and advice in the preschoolyears—might reasonably be targeted on all hemiplegic

children; it does not currently seem possible to identify asubgroup of hemiplegic children who are at such low riskof psychiatric problems that proactive monitoring andintervention are not warranted.

Acknowledgements—The study was funded by the MedicalResearch Council, the Wellcome Trust, and Scope. I am verygrateful to them; to the children, parents and teachers who gaveso generously of their time; and to Carole Yude, Bob Adak,Suzanne Pemberton, and Judith Elliott for their contributionsto the study.

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Manuscript accepted 19 March 1997