Quality-of-life and psychosocial outcome following

Brain Injury, August 2012; 26(9): 1072–1083

ORIGINAL ARTICLE

Quality-of-life and psychosocial outcome following childhood arterial ischaemic stroke

FIADHNAIT O’KEEFFE1, VIJEYA GANESAN2, JOHN KING1, & TARA MURPHY3 Brain Inj Downloaded from informahealthcare.com by University College London on 08/22/12 For personal use only.

1

Research Department of Clinical, Health and Educational Psychology, 2Institute of Child Health, University College London, London, UK, and 3Department of Clinical Neuropsychology, Great Ormond Street Hospital for Children NHS Trust, London, UK

(Received 8 June 2011; revised 8 December 2011; accepted 23 January 2012)

Abstract Objectives: This study investigates psychosocial outcome and quality-of-life in children who have experienced arterial ischaemic stroke (AIS), using a multidimensional and multi-perspective approach. It also examines the predictors of qualityof-life following childhood AIS. Method: Forty-nine children between 6–18 years of age were recruited from a specialist childhood stroke clinic. Children, their parents and their teachers rated the child’s quality-of-life. Questionnaires rating the child’s self-esteem, behaviour and emotions were administered. Each child also underwent a neuropsychological assessment. Results: The findings show that child-, parent- and teacher-rated health-related quality-of-life (HRQoL) is significantly lower than comparative norms following childhood AIS, across all domains (physical, emotional, social, school and cognitive functioning). Predictors of HRQoL include neurological severity, executive function, self-esteem and family functioning. Conclusions: Improved screening, services and interventions are necessary to monitor longer-term outcome and provide support for children who have experienced AIS and their families. Keywords: Childhood stroke, quality-of-life, family functioning

Introduction Arterial Ischaemic Stroke (AIS) affects 3/100 000 children a year [1] and is increasingly recognized as a significant cause of childhood disability in up to three quarters of survivors [2, 3]. Children living with disability or chronic health conditions are at a significantly greater risk for behavioural and emotional adjustment problems compared to healthy children [4, 5]. Their parents and siblings are also at risk for adjustment difficulties [6] and experience lower quality-of-life (QoL) [7]. Negative consequences of poor parental well-being have been shown to, in turn, influence children’s health and adjustment [8].

Previous studies have reported physical disabilities and functional impairments in three quarters of survivors of childhood stroke [2, 9, 10]. Neuropsychological vulnerabilities have been highlighted in a number of recent studies, particularly in the areas of processing speed, working memory, higher-level language and executive functions [11–14]. Ravens-Sieberer and Bullinger [15] described health-related QoL (HRQoL) as ‘A psychological construct which describes the physical, mental, social, psychological and functional aspects of wellbeing and function from a patient perspective’ (p. 399). Research with young people with

Correspondence: Dr Fiadhnait O’Keeffe, Research Department of Clinical, Educational and Health Psychology, University College London, Gower Street, London WC1E 6BT, UK. Tel: þ353 86 3523408. Fax: +44 207 9161989. E-mail: [email protected] ISSN 0269–9052 print/ISSN 1362–301X online ß 2012 Informa UK Ltd. DOI: 10.3109/02699052.2012.661117

Brain Inj Downloaded from informahealthcare.com by University College London on 08/22/12 For personal use only.

Quality-of-life following childhood AIS disabilities and neurological disorders, such as epilepsy and brain tumours, report lower QoL than those without disabilities [16–19]. Specifically, three studies that investigated HRQoL after childhood stroke have shown that it is reduced in a variety of domains [2, 20, 21]. Furthermore, parental psychosocial wellbeing was also shown to be adversely affected [21]. Predictors of HRQoL included young age at time of stroke, neurological severity (severe disability/extensive brain injury), gender and cognitive function [2, 10, 20, 21]. Previous studies have been limited by a range of methodological issues including small numbers and heterogeneity in the populations studied and administering only parentproxy rather than child-rated measures. This study reports HRQoL in children and young people who have experienced AIS in the UK, using a multiperspective approach, including key areas of potential cognitive, behavioural and emotional difficulty, family factors including SES, family functioning and parental well-being and relates these to HRQoL.

Method Participant Children were recruited from a specialist paediatric stroke clinic in London, UK. Inclusion criteria were: (i) aged 6–18 years at assessment; (ii) diagnosis of AIS beyond the neonatal period, with neuroradiological confirmation; and (iii) English speakers. Sixty-four children met the inclusion criteria and were considered eligible. Forty-nine children and young people (30 males) took part. Ages ranged between 6–18 years at assessment (M ¼ 11.08, SD ¼ 3.65). Demographic and clinical characteristics of the participants are presented in Table I. The neurological severity ratings indicate that half the sample (49%) showed normal or reflex asymmetry only and 51% showed hemiparesis (weakness on one side of the body), either mild (able to do isolated finger movements) or severe (unable to do isolated finger movements). Over half the participants had recurrent transient ischaemic attacks (‘mini-strokes’) or stroke (n ¼ 27, 55.1%); 26.5% (n ¼ 13) had a history of seizures, with seven participants currently taking anti-convulsant drugs (14.3%). Ten children had state-funded, individual specialized support at mainstream school (20.8%). Over half the group were on a state special educational needs register (n ¼ 28, 58.3%) and almost half had individualized educational plans (IEPs) to support their learning (n ¼ 23, 47.9%).

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Table I. Demographic and clinical characteristics of the sample. Clinical characteristics n Age at stroke onset, M (SD) Age at stroke onset, Range Age at assessment, M (SD) Age at assessment, Range Time since stroke onset, M (SD)

49 5.08 (3.67) 4 months–15.66 years 11.08 (3.65) 6.0–18.4 years 6.0 (3.41)

Sex, n (%) males SES, M (SD) SES 1: Management/Professional SES 2: Intermediate SES 3: Small employers SES 4: Lower supervisory/ Technical SES 5: Routine/Unemployed

30 (61.2%) 2.65 (1.81) 23 (50%) 2 (4.3%) 3 (6.5%) 4 (8.7%)

Aetiology/ Identified risk factors, n (%) Sickle Cell Disease Moyamoya Chicken pox/Other infection (e.g. shingles) Cerebrovascular abnormality identified Cardiac abnormality identified Other (e.g. Dissection) Unknown/None identified Neurological Severity Motor Score, M (SD) 1: Normal or only reflex asymmetry, n (%) 2: Mild hemiparesis, can do isolated finger movements, n (%) 3: Severe hemiparesis, cannot do isolated finger movements, n (%) Lateralization of stroke, n (%): Left Right Bilateral Handedness (Right), n (%) Changed handedness since stroke, n (%) Recurrent stroke or TIAs, n (%) History of seizures, n (%) Currently taking Anti-epileptic Drugs, n (%) Education: State-funded individual support at school, n (%) Specialized individual educational plans, n (%) Extra help in school, hours, M (SD)

14 (30.4%) 7 (14.3%) 10 (20.4%) 11 (22.4%) 9 (18.4%) 3 (6.1%) 5 (10.2%) 4 (8.2%) 1.73 (.81) 24 (49%) 14 (28.6%)

11 (22.4%)

23 (46.9%) 21 (42.9%) 5 (10.2%) 29 (61.7%) 18 (40.9%) 27 (55.1%) 13 (26.5%) 7 (14.3%)

10 (20.8%) 28 (58.3%) 4.05 (6.69)

TIA, transient ischaemic attack.

Measures Quality-of-life. The Paediatric Quality-of-Life Inventory 4.0 (PedsQL) [22, 23] was used to assess HRQoL. In the absence of any standardized teacher proxy-rated HRQoL forms, age-appropriate

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parent proxy-rated PedsQL versions were also administered to children’s teachers, as in FelderPuig et al. [24]. The Cognitive Functioning scale from the Multidimensional Fatigue Scale [25] was also included, due to its relevance for children who have experienced a stroke. Self-esteem. The Culture-Free Self-Esteem Inventory 3rd Edition (CFSEI III) [26] was used to assess self-esteem in children. It is normed for children and young people between the ages of 6–18 years. It assesses self-esteem in five areas: academic, general, parent/home, social and personal. There are ageappropriate versions available for 6–8, 9–12 and 13–18 years. Socioeconomic status. SES was derived from occupation and employment status information, according to the National Statistics Socio-economic Classification (NS-SEC) [27]. The self-coded version was used. Family functioning. The Family Impact Module (FIM) [28] of the PedsQL is a parent self-report measure of the impact of their child’s chronic health condition on their own QoL and on family functioning. The FIM assesses family impact across eight areas: physical, emotional, social and cognitive functioning, communication, worry, daily activities and family relationships. The FIM has shown good internal consistency and good reliability. Parental health and well-being. The General Health Questionnaire-12 (GHQ-12: [29]) was completed by parents. This is a validated, widely used measure of subjective health status in adults. Neuropsychological status. The Wechsler Abbreviated Scale of Intelligence (WASI) [30] was administered as a measure of general intellect. The Wechsler Individual Achievement Test 2nd Edition (WIAT- II) [31] reading comprehension and reading speed sub-test was administered as a measure of academic attainment. The Oral Expression sub-test from the Wechsler Objective Language Dimension (WOLD) [32] was administered. Sub-tests from the Test of Everyday Attention for Children (TEA-Ch) [33] were administered as a standardized test of attention. The Annett Peg-moving task (APT) [34] was used to assess hand function and motor skill of each hand. Six sub-tests from the Handedness Test [35] were selected and used as a bilateral functional motor task. The Delis-Kaplan Executive Function System (D-KEFS) [36] Trail Making Test (TMT) was used as an executive function task to assess

cognitive flexibility and set-shifting. The Behaviour Rating Inventory of Executive Function (BRIEF) [37] was administered to children, parents and teachers to assess everyday executive function behaviour. The Strengths and Difficulties Questionnaire (SDQ) [38] was administered to children, parents and teachers to assess emotional and behavioural functioning. Statistical analysis Quantitative analysis was conducted using SPSS (version 17.0). In order to assess whether group means on HRQoL and psychosocial measures were lower for children following AIS, one-sample t-tests were conducted with the means from the participants of the childhood AIS group and compared to available standardized test norms. To adjust for multiple testing and restrict family-wise error to the chosen alpha while maximizing power, the Holm-Bonferroni sequential method was adopted. Alpha of 0.05 was divided by the number of tests in each comparison (k). The p-values were listed in order from smallest to largest. The first and smallest p-value was compared to 0.05/k and if its value was less than alpha/k, the null hypothesis was rejected. The next smallest p-value was then compared to alpha/k 1. This is continued until the p-value can no longer be rejected. This method was adopted within each comparison and correlational analysis [39, 40]. In order to explore the correlates of HRQoL following childhood AIS, a two-stage process was adopted. First, exploratory correlational analysis was conducted. The potential correlates were considered at three levels: (1) medical (neurological severity); (2) neuropsychological (standardized test data) and (3) behavioural (questionnaire data). Neurological severity was selected as an a priori predictor. The correlates with the highest associations with HRQoL (child and parent-rated) at each level were selected as predictor variables for a three-step hierarchical multiple regression to examine the significant factors that predict HRQoL. Results Section A: Health-related quality-of-life following childhood stroke. Do self and proxy rated HRQoL scores differ significantly from population norms? Table II presents child-rated, parent-rated and teacher-rated HRQoL scores for the participants compared with UK population norms [41]. Child and parent-proxy ratings of HRQoL across all domains (physical, emotional, social and school) were significantly lower than norms, indicating lower HRQoL. Teacher-rated levels of HRQoL were significantly lower than parent norms across all domains, with the exception of emotional functioning.

Quality-of-life following childhood AIS

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Table II. Health-related quality-of-life for clinical sample compared to UK normative means.


Scale

Mean UK sample (SD) [41]

Mean clinical sample (SD)

t

95% CI Lower Bound

95% CI Upper Bound

Effect size (Cohen’s d)

Child report n Physical Emotional Social School Psychosocial Total

1033 88.51 78.49 87.65 78.87 81.84 83.89

(11.62) (17.94) (16.46) (15.89) (13.21) (11.84)

48 73.23 66.46 70.10 64.27 67.35 69.26

(18.88) (21.31) (25.73) (18.51) (19.25) (17.66)

– 5.61* 3.91* 4.72* 5.47* 5.22* 5.74*

20.76 18.22 25.02 19.97 20.08 17.71

9.79 5.84 10.07 9.23 8.90 7.45

1.3 0.7 1.1 0.9 1.1 1.2

(large) (medium) (large) (large) (large) (large)

Parent report n Physical Emotional Social School Psychosocial Total

665 89.06 78.28 86.82 81.52 82.21 84.61

(12.27) (15.54) (15.42) (16.09) (12.67) (11.19)

49 64.22 60.82 66.23 60.41 62.48 63.29

(30.88) (25.36) (27.49) (23.11) (22.60) (24.27)

– 5.63* 4.82* 5.24* 6.39* 6.11* 6.15*

33.71 24.75 28.49 27.75 26.22 28.29

15.97 10.18 12.69 14.47 13.24 14.35

2.0 1.1 1.3 1.3 1.5 1.9

(large) (large) (large) (large) (large) (large)

39 69.17 73.44 73.59 60.32 67.80 69.75

(24.59) (20.32) (18.39) (23.20) (16.84) (15.50)

— 4.85* 1.47 4.49* 5.71* 5.35* 5.99*

28.21 11.52 19.19 28.72 19.87 19.89

11.57 1.84 7.27 13.68 8.95 9.84

1.6 0.3 0.9 1.3 1.1 1.6

(large) (small) (large) (large) (large) (large)

Teacher report n Physical Emotional Social School Psychosocial Total

(Parent norms) 665 89.06 (12.27) 78.28 (15.54) 86.82 (15.42) 81.52 (16.09) 82.21 (12.67) 84.61 (11.19)

*Significant comparisons after Holm-Bonferroni adjustment. CI, Confidence Interval.

Looking specifically at the area of cognitive problems, child, parent and teacher ratings were all significantly lower than US norms (see Table III). The intercorrelations between the child-, parentand teacher-rated PedsQL scores were all significant. The highest agreement was between the parent- and teacher-rated scores (r ¼ 0.748, p < 0.001). Childand parent-rated scores showed the next largest correlation (r < 0.64, p < 0.001). The lowest agreement was between the child-rated and teacher-rated PedsQL scores (r ¼ 0.503, p < 0.001). Comparisons between the clinical sample for self and parent-proxy rated PedsQL scores and those of a US sample with chronic health conditions [42] are presented in Table IV. For child-rated PedsQL, none of the domains were significantly different from the chronically-ill sample. For parent-proxy rated PedsQL, the physical domain was significantly lower than the chronically-ill sample. Section B: High/low HRQoL comparisons—Do children with low HRQoL ratings differ from high HRQoL ratings across neurological, neuropsychological and behavioural measures? The participants were divided into a Low HRQoL group and High HRQoL group, based on a median

split of the Total child-rated PedsQL score (Median ¼ 69.56). This led to the formation of two groups, a Low HRQoL (n ¼ 22) and a High HRQoL (n ¼ 27) group. Looking firstly at impact of special education needs, a Chi-Square analysis revealed that there was a significant association between the Low and High HRQoL grouping and whether or not the child had an individualized educational plan (IEP) (2(1) ¼ 8.27, p < 0.01); 65.2% of children with an IEP were in the Low HRQoL group, compared to 24% without an IEP. In order to investigate performance between the Low HRQoL and High HRQoL group across a range of neurological, neuropsychological and behavioural measures, a series of Independent-samples t-tests were conducted. Details of the means, standard deviations, t-statistics, confidence intervals and effect sizes are presented in Table V. The Low HRQoL group had a significantly higher rating for neurological severity compared to the High HRQoL group. The mean FSIQ and VIQ of the Low HRQoL group fell in the Low Average range and were significantly lower than those of the High HRQoL group. Mean PIQ scores did not differ significantly between the groups, although the Low HRQoL mean PIQ scores also fell in the Low Average range. Both Reading Comprehension and

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Table III. Cognitive scale for clinical sample compared to US normative means.

Scale

Mean US healthy sample (SD)


t

95% CI Lower Bound

95% CI Upper Bound


Child report n Cognitive Functioning

52 81.14 (17.43)

48 68.05 (24.03)

Parent report n Cognitive Functioning

3.78*

20.07

6.11

0.8 (large)

(Parent norms) 102 90.72 (15.15)

49 63.01 (27.84)

Teacher report n Cognitive Functioning

6.97*

35.71

19.72

1.8 (large)

102 90.72 (15.15)

38 58.66 (28.69)

6.89*

41.49

22.63

2.1 (large)


Table IV. Health-related quality-of-life for clinical sample compared to US sample with chronic health conditions.

Scale

Mean US chronic health conditions (SD)


t

95% CI Lower Bound

95% CI Upper Bound


Child report n Physical Emotional Social School Psychosocial Total

574 79.47 69.32 76.36 68.27 71.32 74.16

(17.07) (21.36) (21.57) (19.05) (17.13) (15.38)

48 73.23 66.46 70.10 64.27 67.35 69.26

(18.88) (21.31) (25.73) (18.51) (19.25) (17.66)

2.29 0.93 1.68 1.50 1.43 1.92

11.72 9.05 13.73 9.37 9.56 10.03

0.76 3.33 1.22 1.38 1.62 0.23

0.4 0.1 0.3 0.2 0.2 0.3

(medium) (small) (small) (small) (small) (small)

Parent report n Physical Emotional Social School Psychosocial Total

831 76.99 71.08 75.06 65.58 71.04 73.14

(20.20) (19.75) (21.75) (20.75) (17.32) (16.46)

49 64.22 60.82 66.23 60.41 62.48 63.29

(30.88) (25.36) (27.49) (23.11) (22.60) (24.27)

2.89* 2.83 2.25 1.57 2.65 2.84

21.64 17.55 16.55 11.81 15.05 16.82

3.90 2.98 0.94 1.47 2.07 2.88

0.6 0.5 0.4 0.3 0.6 0.6

(medium) (medium) (medium) (small) (medium) (medium)


Reading Speed mean scores were significantly lower for the Low HRQoL group than the High HRQoL group. On the response inhibition task (Walk/Don’t Walk), the Low HRQoL group performed significantly worse than the High HRQoL group. The overall Attention Composite score for the Low HRQoL group was significantly lower than that of the High HRQoL group. The Low HRQoL group performed worse on the Motor Speed task on the D-KEFS Trails than the High HRQoL group. On the behavioural and psychological measures, children in the Low HRQoL group rated their overall stress (internalizing and externalizing symptoms) on the SDQ as significantly higher than

children in the High HRQoL group. The Low HRQoL group also had significantly lower global self-esteem ratings (in the Low Average range) than the High HRQoL group. Parents rated children in the Low HRQoL group as having significantly more difficulties on the BRIEF and SDQ than the High HRQoL group. Teachers’ scores did not differ significantly between the Low and High HRQoL groups on the BRIEF and SDQ. In terms of impact on the family, the Low HRQoL group had a significantly greater impact on family functioning, as indicated by a lower PedsQL Family Impact score, than the High HRQoL group. Parents of children in the Low HRQoL group also rated their


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Table V. Low HRQoL compared to high HRQoL on neuropsychological and behavioural measures.

Domain Age at stroke onset Neurological Severity General Intellect WASI


Academic Attainment WIAT Language WOLD Attention TEA-Ch

Executive Function/ Attention D-KEFS TMT Motor Function Self-Esteem (CF-SEI) Executive Function BRIEF

Behaviour SDQ

Family Impact PedsQL FIM Parents Well-Being GHQ

Measure Age in years (SD) Neurological Motor Severity Rating FSIQ VIQ PIQ Reading Comprehension Reading Speed Oral Expression Sky Search Attention Score Score Sky Search DT Score DT Walk/ Don’t Walk Attention Composite Score Letter Number Sequencing Motor Speed Total Motor Functioning Score Global Self-esteem Score Parent Rated BRI MI GEC Teacher Rated BRI MI GEC Child Rated, Total Stress Parent Rated, Total Stress Teacher Rated, Total Stress Total Family Functioning GHQ

t

95% CI Lower Bound

95% CI Upper Bound

0.15 2.93**

1.98 0.03

2.30 0.93

2.39* 2.22* 1.85 3.38**^

16.77 16.18 15.91 24.11

1.43 0.78 0.65 6.10

0.7 0.7 0.5 1.0

103.95 (16.25) 91.5 (12.73)

2.15* 1.34

22.31 12.07

0.60 2.44

0.8 (large) 0.4 (medium)

(3.11) (4.07) (3.47) (4.24) (2.68) (2.42)

7.59 (3.20) 7.84 (3.21) 4.83 (4.29) 8.04 (3.17) 6.65 (3.38) 7.33 (2.13)

1.29 2.01a 1.37 1.67 3.01** 2.41*

3.14 4.42 4.14 4.27 4.90 2.95

0.69 0.01 0.80 0.41 0.96 0.26

0.4 0.6 0.4 0.5 0.9 0.7

7.14 (4.77) 9.29 (3.12) 8.64 (2.34)

7.74 (3.08) 11.26 (1.41) 10.42 (1.75)

0.43 2.45* 2.95**

3.38 3.62 3.01

2.20 0.33 0.56

0.2 (small) 0.8 (large) 0.9 (large)

86.05 (15.97)

104.80 (11.57)

4.65**^

26.88

10.63

1.3 (large)

65.14 (15.86) 61.48 (12.33) 63.57 (13.84)

51.52 (13.23) 52.26 (12.86) 52.37 (13.45)

3.27**^ 2.51* 2.83**

5.42 1.82 3.23

21.99 16.62 19.18

0.9 (large) 0.7 (medium) 0.8 (large)

58.11 (12.27) 62.26 (13.30) 61.74 (12.57)

54.43 (14.24) 59.14 (14.97) 58.05 (14.81)

0.87 0.69 0.84

4.88 5.99 5.16

12.23 12.23 12.53

0.1 (small) 0.2 (small) 0.3 (small)

16.45 (5.66)

10.74 (5.40)

3.35**^

2.27

9.16

1.0 (large)

16.41 (7.50)

9.19 (5.81)

3.80**^

3.40

11.05

1.1 (large)

8.63 (5.57)

6.73 (5.41)

1.11

1.57

5.38

0.4 (medium)

62.09 (21.70)

79.87 (22.95)

2.13*

29.97

5.59

0.8 (large)

2.68 (3.26)

0.92 (2.28)

2.13*

0.85

3.43

Low HRQoL

High HRQoL

5.17 (3.9) 2.00 (0.76)

5.01 (3.5) 1.52 (0.80)

87.05 88.41 89.41 84.67

(11.72) (10.98) (14.10) (13.24)

92.50 (13.77) 86.68 (12.08) 6.37 5.63 3.16 6.11 3.72 5.73

96.15 96.89 97.04 99.77

(14.40) (14.95) (14.51) (16.67)

Effect size (Cohen’s d) — 0.6 (medium) (medium) (medium) (medium) (large)

(medium) (medium) (medium) (medium) (large) (medium)

0.6 (medium)

*p < 0.05, **p < 0.01, ^comparisons that remain significant after Holm adjustment. a p ¼ 0.051. CI, Confidence Interval.

own well-being as worse than the parents of children in the High HRQoL group. Section C: What are the relationships between child-, parent- and teacher- rated behaviour measures? Table VI presents the correlation matrix for child-, parent- and teacher-rated behaviour measures. There were strong associations found between all child- and parent-rated questionnaire measures. Lower self-ratings of children’s self-esteem was

associated with higher ratings of internalizing and externalizing symptoms (child- and parent-rated SDQ), increased levels of everyday executive function behaviours (parent-rated) and poorer family functioning. Poorer parental well-being was associated with greater overall internalizing and externalizing symptoms and everyday executive dysfunction behaviour in children (child-, parent- and teacherrated). Poorer parental well-being was also found to have a negative impact on family functioning. Teacher ratings on internalizing and externalizing

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F. O’Keeffe et al. Table VI. Correlation matrix for child-, parent- and teacher-rated behaviour measures.

Domains Child Self-esteem, CF-SEIc Overall Behaviour, SDQc Overall Behaviour, SDQp Executive Function, GECp Parental Well-being, GHQp Family Functioningp Overall Behaviour, SDQT

Overall Behaviour, SDQc

Overall Behaviour, SDQp

Executive Function, GECp

Parental Well-being, GHQp

0.798**^

0.586**^ 0.579**^

0.450** 0.475**^ 0.820**^

0.307* 0.398** 0.507**^ 0.448**

Family Functioningp 0.478**^ 0.479**^ 0.652**^ 0.672**^ 0.687**^

Overall Behaviour, SDQT

Executive Function, GECT

0.116 0.214 0.362* 0.331* 0.223 0.264

0.053 0.195 0.365* 0.438** 0.448** 0.427** 0.708**^


*p < 0.05, **p < 0.01; ^Significant comparisons after Holm-Bonferroni adjustment. c ¼ Child-rated; p ¼ Parent-rated; T ¼ Teacher-rated.

symptoms (teacher-rated SDQ) were not found to be associated with either child-rated measures of self-esteem or behaviour, but were associated with parent-rated symptoms (parent-rated SDQ) and everyday executive function behaviours (parentand teacher-rated GEC). Section D: What are the relationships between HRQoL measures and outcome variables? Table VII presents the correlation matrix for both child- and parent-proxy rated HRQoL scores with selected variables. For child-rated HRQoL, there was a strong positive association found between HRQoL and global self-esteem. Greater internalizing and externalizing symptoms (parent-rated SDQ) and executive function difficulties (parent-rated BRIEF Global Executive Composite GEC) were associated with lower HRQoL. Higher child-rated HRQoL was also associated with increased family functioning and better parental well-being. Higher levels of parent-proxy rated HRQoL were significantly associated with lower levels of neurological severity rating, higher general intellect, higher levels of sustained attention, response inhibition, higher attention composite score and family functioning. Better HRQoL was strongly associated with fewer executive function difficulties (parent-rated). Higher parent-proxy rated HRQoL was associated with higher self-esteem (child-rated). Higher HRQoL was also associated with better family functioning ratings and better parental well-being. Section E: Which variables significantly predict the variance in HRQoL? Predictor variables for child-rated PedsQL HRQoL were explored more specifically within a hierarchical regression model with the following three steps: the a priori hypothesized predictor (neurological severity) was selected for Step One. The strongest neuropsychological variable correlates of child-rated HRQoL

Table VII. Correlation matrix for PedsQL scales and neuropsychological measures.

Domains Age at stroke onset Neurological Severity SES General Intellect (FSIQ) Oral Expression (WOLD) Sustained Attention (Score) Response Inhibition (Walk Don’t Walk) Attention Composite Score Global Self-Esteem (Child-rated) Total Overall Stress (SDQ Parent-rated) Executive Function (GEC Brief Parent-rated) Executive Function (GEC Brief Teacher-rated) Total Family Functioning (FIM Parent-rated) Parental Well-being (GHQ)

Child-rated PedsQL 0.038 0.246 0.139 0.361* 0.193 0.263 0.399*

Parent-rated PedsQL 0.115 0.496**^ 0.240 0.464**^ 0.307* 0.434**^ 0.467**^

0.285 0.754**^

0.426**^ 0.551**^

0.564**^

0.794**^

0.454**^

0.805**^

0.027

0.443**

0.461**^ 0.375**

0.796**^ 0.587**^

*p < 0.05, **p < 0.01, ^Significant comparisons after HolmBonferroni adjustment.

were selected for Step Two (Full-scale IQ and response inhibition). An additional Step Three was added to include behavioural questionnaire data, again selecting the strongest correlates—Global Selfesteem and Total Overall Stress Internalizing/ Externalizing symptoms (SDQp Parent-rated). In this model, neurological severity did not predict a significant amount of the variance for child-rated HRQoL (3.7% variance predicted, ns). After neuropsychological variables were included (full-scale IQ and response inhibition), the model as a whole explained 23.1% of the variance in child-rated HRQoL [F(3, 39) ¼ 3.596, p < 0.05; DR2 ¼ 19.4%, p < 0.05]. At Step Three (adding behavioural questionnaire SDQp and global self-esteem) the model as

Quality-of-life following childhood AIS Table VIII. Hierarchical multiple regression for Child-rated PedsQL.

Table IX. Hierarchical multiple regression for Parent-rated PedsQL.

(Standardized Beta)

B


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SE B

Step 1 Constant Neurological Severity

75.7 4.31

6.67 3.56

Step 2 Constant Neurological Severity Full Scale IQ Response Inhibition

34.06 2.75 0.34 1.31

Step 3 Constant Neurological Severity Full Scale IQ Response Inhibition SDQP Self-EsteemC

4.07 2.97 0.07 0.93 0.13 0.74

B

SE B

(Standardized Beta)

0.19

Step 1 Constant Neurological Severity

89.09 14.30

7.39 3.96

0.48**

18.15 3.40 0.20 0.87

0.12 0.28 0.25

Step 2 Constant Neurological Severity Full Scale IQ Attention Composite

32.12 13.65 0.39 2.95

20.63 3.49 0.24 1.33

0.46** 0.22 0.30*

18.35 2.38 0.15 0.61 0.31 0.14

0.09 0.58 0.18 0.06 0.72**

74.77 7.62 0.00 0.87 0.48 0.42 0.50

18.49 1.87 0.13 0.75 0.35 0.09 0.18

0.26** 0.00 0.09 0.15 0.40** 0.32**

Adj R2 ¼ 0.012 for Step 1; DR2 ¼ 0.194 for Step 2, *p < 0.05; DR2 ¼ 0.433 for Step 3, **p < 0.01.

Step 3 Constant Neurological Severity Full Scale IQ Attention Composite SDQP Family Functioning Executive Function GECP

Adj R2 ¼ 0.211 for Step 1; DR2 ¼ 0.205 for Step 2, **p < 0.01; DR2 ¼ 0.429 for Step 3, **p < 0.01.

a whole explained 66.4% of the variance in child-rated HRQoL (F(5, 39) ¼ 13.438, p < 0.001; DR2 ¼ 43.3%, p < 0.001). Global self-esteem was the only significant unique predictor that made a significant contribution to the final model. Table VIII displays the standardized betas, the Betas and their significance for each model. A three-step hierarchical multiple regression analysis was also conducted in order to refine the model for parent-rated HRQoL, controlling for the effects of neurological severity and neuropsychological variables. The a priori hypothesized predictor (neurological severity) was again selected for Step One. The neuropsychological variable correlates were selected for Step Two (Full-scale IQ and attention composite). Step Three included behavioural questionnaire data, again selecting the strongest correlates—parent-rated Total Overall Stress Internalizing/Externalizing symptoms (SDQp), parent-rated Global Executive Composite BRIEF (GECp) and Family Functioning. Neurological Severity significantly predicted 22.8% of the variance in parent-proxy rated HRQoL [F(1, 45) ¼ 13.019, p < 0.001]. After neuropsychological variables were included, the model explained 43.3% of the variance in parent-proxy rated HRQoL [F(3, 45) ¼ 10.693, p < 0.001; DR2 ¼ 20.5%, p < 0.01]. After behavioural questionnaires were included, the model as a whole explained 86.2% of the variance [F(6, 45) ¼ 40.714, p < 0.001; DR2 ¼ 42.9, p < 0.01]. Although in the previous steps, attention composite score and neurological severity made significant contributions, in the final model, only neurological severity, family functioning and parent-rated everyday behavioural executive

functioning (GECp) made significant contributions to the model. Table IX displays the standardized betas, the Betas and their significance for each step in the model.

Discussion Health-related QoL for a group of children who had experienced childhood AIS was significantly lower than UK norms across all domains for both childrated and parent-proxy rated versions. This suggests that both parents and children view the impact of AIS on the child’s life as wide-ranging and significantly detrimental to HRQoL, consistent with previous research [2, 20, 21]. Comparing to children with other health conditions, parent-rated HRQoL for children with AIS was significantly lower on the physical domain. Given that half the children (51%) in the current study had neurological motor severity ratings in the mild–severe range, lower ratings on the physical domain of the PedsQL are not surprising. Teachers’ measures of HRQoL for children following AIS in the school setting showed that their perceptions of the child’s HRQoL was significantly lower than UK parent norms on all domains, with the exception of emotional functioning. As Friefeld et al. [20] showed, school was the lowest rated domain for HRQoL on the generic core scales of the PedsQL by children, parents and their teachers, making teacher-ratings of HRQoL all the more relevant. Future research could develop teacher standardized norms for the PedsQL, similar to


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those available for the SDQ. This is likely to provide a more sensitive and relevant comparison of teacherrated HRQoL than comparing to parent norms. Inter-correlations between child-, parent- and teacher-rated PedsQL showed that the highest agreement in scores was between parent and teacher proxy-rated versions, followed by child–parent correlations. Child–teacher correlations were significantly associated but showed the weakest association. These correlations are significantly stronger than those found in Felder-Puig et al. [24] in a large sample (n ¼ 620) of healthy Austrian school children, where inter-correlations ranged between 0.3–0.4 for child–parent, child–teacher and parent–teacher comparisons. In the current study, 21% of the children had specific funding for special needs and more than half had an Individual Education Plan (IEP)—an over-representation when compared with a typically-developing population. Furthermore, having special educational needs identified by an IEP was found to be associated with lower HRQoL. It may be that there is significantly more communication between home, school and health professionals, following AIS in childhood. This sharing of information may be associated with the higher agreement between children, parents and teachers around the child’s needs and HRQoL. Inclusion of the cognitive functioning domain on the PedsQL provides new and valuable information for children who have experienced AIS. Childreport, parent- and teacher-proxy ratings of cognitive functioning were all significantly lower than norms. This indicates that, from all perspectives, cognitive difficulties are significantly impacting children’s everyday HRQoL following stroke. Teachers rated cognitive functioning as lower than any other domain. This suggests that teachers perceive that the cognitive difficulties experienced by children and young people following stroke strongly affects their HRQoL. Grouping the children into high- and low-rated HRQoL resulted in clinically meaningful findings. Children in the low HRQoL group differed significantly from the high HRQoL group across a wide range of neuropsychological and behavioural measures. For example, those with low HRQoL ratings had significantly higher ratings of neurological severity (indicating more severe hemiparesis), lower general intellectual and verbal abilities, lower abilities in reading comprehension, reading speed, processing speed and attention. There were also significant differences on behavioural measures of everyday executive function ratings, self-esteem and overall internalizing and externalizing behaviour, with the children in the low HRQoL group having higher levels of executive dysfunction, lower self-esteem and

higher levels of stress. All these differences represented medium-to-large effect sizes. In terms of impact on the family, parents of children with lower HRQoL ratings also rated family functioning and their own well-being as significantly lower than parents of children with higher HRQoL ratings. Gordon et al. [21] also showed that social, communication and emotional difficulties in children with AIS were associated with poorer parental well-being. In other areas of paediatric research, lower quality-of-life has been found to be associated with lower family functioning [43–45]. This study is the first to look at the impact of wider environmental and psychosocial factors on childhood stroke and vice versa. Poor parental mental health has been shown to influence children’s health and adjustment following spina bifida [8]. The strong inter-relationships found in this research between child- and parent-rated well-being, behaviour and family functioning clearly point to the potentially reciprocal influence of child and parents’ psychological health. This is an area that deserves further attention, due to the possible negative consequences for both. For child-rated HRQoL, higher quality-of-life was associated with higher levels of self-esteem, fewer internalizing and externalizing difficulties and better executive function. Associations between higher child-rated HRQoL and better family functioning and parental well-being were also found, underscoring the importance of assessing parental wellbeing and family factors. For parent proxy-rated HRQoL, higher levels of HRQoL were found to be significantly associated with milder neurological severity and stronger cognitive function (i.e. intellect, attention, fewer executive function difficulties) and higher levels of self-esteem. Focusing on significant predictors of child-rated HRQoL, neuropsychological variables explained 23.1% of the variance. The addition of behaviour and emotional variables explained 66.4% of the variance. Global self-esteem was the only variable that was a unique predictor of child-rated HRQoL. Neurological severity alone predicted 22.8% of the variance in parent proxy-rated HRQoL. Severity of neurological outcome or physical disability predicted HRQoL in previous studies of childhood stroke [2, 20, 21]. Including neuropsychological variables in the model explained a further 20.5% of variance. With the addition of parent-rated internalizing and externalizing behaviour, executive function behaviour and family functioning, 86.2% of the variance of parent-rated HRQoL was explained. HRQoL research with childhood epilepsy also found that global executive functioning difficulties were associated with increased risk of lower QoL [46]. Greater internalizing and externalizing symptoms, low self-esteem and family factors


Quality-of-life following childhood AIS were found to be associated with lower QoL in a group of children with a range of psychiatric problems [47]. SES, gender and age of stroke onset were not found to be significantly associated with HRQoL outcome in the current study, contrary to previous findings [2, 20]. Both studies that have previously found associations with gender and age of stroke onset had larger sample sizes (e.g. n ¼ 100 in Friefeld et al. [20]; n ¼ 76 in Cnossen et al. [2]). Perhaps with a larger sample size, factors such as age of stroke onset and sex may be significant correlates of HRQoL. As a group there is a significant risk of lower quality-of-life following childhood AIS than comparative norms. Children with greater physical disabilities and higher ratings of neurological severity following stroke are at risk of lower HRQoL. Aside from neurological severity, executive function behaviour was a unique predictor of parent proxy-rated HRQoL. Global self-esteem was the only variable that significantly uniquely contributed to the model for predictors of child-rated HRQoL. This strongly indicates that self-esteem and general executive functioning should be routinely screened in clinics for children following AIS. The findings from the current research also indicate that family functioning and parental wellbeing are significantly impacted following childhood stroke. Clinicians should screen for parental wellbeing and family functioning, particularly for the families of the most impaired children. Local support services for parents and siblings should be recommended, where appropriate. As has been shown, predictors of child- and parent proxy-rated HRQoL differ. From parents’ perspectives, a wider range of factors contributed to their perceptions of the child’s HRQoL. These included physical disability, cognitive and behavioural child factors, but also wider family functioning. From a child’s perspective, how they feel about themselves is the key factor in predicting their own perceptions of their HRQoL. Targeted cognitive and psychosocial interventions should be developed and evaluated to assess their impact on improving the lives of children who have experienced AIS. Psychosocial interventions, perhaps aimed at improving self-esteem, emotional regulation and social difficulties, may also prove successful in either individual or group formats. Elements of a holistic intervention model such as that proposed by Marcantuono and Prigatano [48] that includes both psychosocial and cognitive rehabilitation could be investigated for efficacy with childhood AIS. A larger sample size would have allowed for more detailed statistical analysis, particularly the

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investigation of associational results that approached statistical significance, testing more complex regression models and more selective inclusion criteria. However, the sample size is considerable given the relative rarity of childhood AIS and it is worth emphasizing the homogeneity of the group, as previous studies of childhood stroke have included children with cerebral haemorrhage or those with lesions accrued in the newborn period. The current study has made contributions to the areas of quality-of-life, cognitive and behavioural outcomes following childhood AIS. This study is the first to include teacher ratings of HRQoL, behaviour and executive function with children following stroke. In terms of HRQoL, using UK norms, this research confirms previous findings that HRQoL is significantly lowered following childhood AIS, across a range of measures, including the cognitive functioning domain. Predictors of HRQoL differ according to perspective. Parentproxy rated HRQoL predictors include neurological, neuropsychological and behavioural variables. Child-rated HRQoL is significantly predicted by their self-esteem. A significant relationship between a child’s HRQoL, parental well-being and family functioning has also been highlighted. Improved screening, services and interventions are necessary to monitor longer-term outcome and provide support for children who have experienced AIS and their families.

Acknowledgements Special appreciation to all the children, parents and teachers who gave up their time to participate in this study. Declaration of Interest: The authors report no conflicts of interest. This research was part-funded by the University of London Central Research Fund, Graduate School University College London and the Research Department of Clinical, Health and Educational Psychology University College London for the first author (F. O’Keeffe).

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