Intellectual Ability 10 Years after Traumatic Brain Injury in Infancy and Childhood: What Predicts Outcome?

Abstract

The long-term consequences of child traumatic brain injury (TBI) are poorly understood, but there are indications of ongoing deterioration in skills with time since injury. This study investigated outcomes up to 10 years post-injury, to determine the influences of injury severity, injury age, and environment. The study design was prospective and longitudinal. Participants included consecutive admissions to the Royal Children's Hospital, Melbourne, Australia. Children sustaining TBI between 2 and 12 years of age (n=76) were recruited on admission and divided according to injury severity (mild, moderate, and severe) and injury age (2–7 years and 8–12 years). Cognitive abilities were evaluated using standard measures of intellectual function (IQ) acutely and at 12 months, 30 months, and 10 years post-injury. At 10 years, mean IQs for survivors fell within the low average to average range. There were no significant effects of injury severity, injury age, or time since injury. In contrast, elevated rates of impairment were identified in association with severe TBI (global deficits), and early injury (non-verbal deficits). Impairments in processing speed were related to injury severity and age at injury. Predictors of 10-year outcome included pre-injury and social factors, injury age, and family function. Child survivors of serious TBI are at elevated risk of cognitive impairment, with recovery continuing into the third year post-injury. However, between 30 months and 10 years post-insult, children appear to make appropriate developmental gains, contrary to the speculation that these children “grow into their deficits.”

Introduction

T raumatic brain injury (TBI) is a major cause of mortality and disability worldwide, occurring at an annual rate of around 500 per 100,000 children, and with preschool children at particular risk (Crowe et al., 2009; Kraus, 1995). Contrary to the traditional early plasticity view, which argues that children's brains are flexible and can reorganize after insult with minimal consequences, there is now evidence that the diffuse pathology caused by child TBI may have more serious and persisting consequences than those seen after adult insults, due to the immaturity of the young brain and the potential of early insult to disrupt ongoing brain development and associated cognitive development (Anderson et al., 2005; Giza and Prins, 2006). Current estimates suggest that as many as one-third of survivors will sustain residual impairment and require ongoing intervention and support into adolescence and adult life (Kraus, 1995), leading to substantial personal and economic burdens for the young person, family, and community.

While such significant consequences are now confirmed during the first few years post-insult (Anderson et al., 2005; Jaffe et al., 1993; Taylor et al., 2002), no study to date has prospectively and systematically followed the progress of children with TBI into late adolescence and early adulthood. Of note, in contrast to anecdotal clinical reports and empirical studies describing significant, injury-related sequelae within the first 5 years post-injury, several retrospective studies of adult survivors of child TBI have documented surprisingly good outcomes on neurobehavioral measures, regardless of injury severity or age at insult (Anderson et al., 2011; Cattelani et al., 1998; Nybo and Koskiniem, 1999), raising the possibility of recovery of neurobehavioral skills in adolescence or early adulthood.

The nature of the deficits seen in the early years post-childhood TBI is now well established, with outcomes closely linked to injury severity (Anderson et al., 2005; Ewing-Cobbs et al., 1997, Levin et al., 1988). Mild TBI is associated with few residual impairments (Asarnow et al., 1995; Ponsford et al., 1999; Yeates et al., 2009), while more severe TBI is characterized by reduced intellectual capacity, impaired attention, memory, and slowed speed of processing (Anderson and Moore, 1995; Babikan and Asarnow, 2009; Catroppa et al., 2007; Ginsfeldt and Emanuelson, 2010; Power et al., 2007; Yeates et al., 2001) and academic failure (Catroppa and Anderson, 2007; Ewing-Cobbs et al., 1988; Taylor et al., 2003) consistent with the functions of the brain regions most vulnerable in TBI. These deficits may potentially interfere with development, reducing the child's ability to acquire knowledge and skills, causing increasing gaps between the abilities of injured children and those of their peers. Secondary deficits in academic progress, social and emotional adjustment, and quality of life may also emerge (Kinsella et al, 1995,1997; Romema et al., in press; Yeates and Taylor, 2006; Yeates et al., 2007). The risks of such disruptions are thought to be particularly significant in infancy and very early childhood, when the brain is developing rapidly and when the child's task is to acquire and consolidate the knowledge and skills necessary for success in adult life, and this is evidenced in a number of studies (Anderson et al., 2006, 2009a,2011; Anderson and Moore, 1995). Other factors identified as contributing to early outcome include premorbid cognitive and learning abilities, family function, and access to rehabilitation (Dennis et al., 1995,2007,2009; Yeates et al., 2010,2004).

Using a prospective, longitudinal design, this study examined the relationship between injury severity, age at injury, and recovery. Based on our earlier results with this sample (Anderson et al., 1997,2005,2009b), we predicted that: (1) children sustaining early TBI (≤7 years old) would achieve poorer outcomes than children with later injuries (≥8 years); (2) severe injury would be linked to the greatest impairment at 10 years; (3) children with severe TBI would demonstrate slower recovery trajectories to 10 years; and (4) pre-injury abilities and environmental factors would contribute to 10-year outcomes.

Methods

Participants

This study represents a 10-year follow-up of a sample of children with TBI originally recruited from consecutive admissions to the neurosurgical ward at the Royal Children's Hospital, Melbourne, Australia (RCH), between 1993 and 1997, immediately following their injuries. Details of the original sample and recruitment strategies have been described previously (Anderson et al., 1997,2005). Seventy-six children (48 males) with TBI participated in this 10-year follow-up, comprising 63% of the original sample (Anderson et al., 2004). Inclusion criteria for the 10-year follow-up study were: (1) age at injury 2 years 0 months to 12 years 11 months; (2) documented evidence of TBI, including a period of altered consciousness; (3) able to complete cognitive evaluation; and (4) completion of acute, 12-month, 30-month, and 10-year evaluations. Exclusion criteria were: penetrating head injury; non-accidental injury; previous TBI; or pre-existing physical, neurological, psychiatric, or developmental disorder. During the initial recruitment period, 170 children were admitted to the RCH with a diagnosis of TBI. Twenty children did not meet recruitment criteria and 27 declined to participate. A total of 122 children participated in the initial study. At 10 years post-TBI, 24 participants could not be located, and 22 declined to participate, resulting in a sample of 76 young people. Comparison of the demographic and injury characteristics and pre-injury adaptive function for participating and non-participating groups (with groups based on our original sample) identified no group differences. These data are provided in Tables 1 and 2.

Table 1.

Attrition Analysis Comparing Patients Seen and Not Seen at 10-Year Follow-Up for the ETBI and LTBI Groups

	Seen at 10 years	Not seen at 10 years
ETBI group	n=40	n=56
Age at injury (years), mean (SD)	2.00 (2.68)	2.60 (2.71)
Family SES, mean (SD)	1.75 (2.15)	2.52 (2.25)
Acute GCS, mean (SD)	4.02 (5.50)	5.31 (5.46)
Male, no. (%)	25 (62.50)	24 (60.71)
Severity, no. (%)
Mild	7 (17.5)	10 (17.9)
Moderate	20 (50.0)	28 (50.0)
Severe	13 (32.5)	18 (32.1)
VABS adaptive functioning: pre-injury, mean (SD)	111.58 (15.85)	110.63 (14.78)
LTBI group	n=36	n=38
Age at injury (years), mean (SD)	10.47 (1.22)	10.41 (1.60)
Family SES, mean (SD)	4.29 (1.04)	4.48 (0.87)
Acute GCS, mean (SD)	5.54 (6.34)	6.00 (6.44)
Male, no. (%)	23 (63.9)	31 (81.58)
Severity, no. (%)
Mild	13 (36.1)	13 (34.2)
Moderate	17 (47.2)	16 (42.1)
Severe	6 (16.7)	9 (23.6)
VABS: pre-injury, mean (SD)	104.87 (15.96)	105.49 (13.90)

SES measured as described by Daniel, 1983. No significant differences were found between those seen and not seen at 10 years.

ETBI, early traumatic brain injury; LTBI, late traumatic brain injury; GCS, Glasgow Coma Scale; SES, socio-economic status; VABS, Vineland Adaptive Behavior Scale: Composite score; SD, standard deviation.

Table 2.

Demographic Characteristics of the 10-Year Sample According to Age at Injury and Injury Severity

	ETBI group			LTBI group
	Mild	Moderate	Severe	Mild	Moderate	Severe
No. (%)	7	20	13	13	17	6
No. males, no. (%)	3 (42.9)	13 (65.0)	9 (69.2)	9 (69.2)	9 (52.9)	5 (83.3)
Injury age, mean (SD)	4.68 (1.60)	5.07 (2.05)	4.47 (1.95)	10.35 (1.24)	10.34 (1.16))	11.11 (1.32)
Age at 10-year follow-up, mean (SD)	14.39 (1.2)	15.45 (33.36)	15.27 (2.96)	18.85 (1.64)	19.05 (1.42)	19.95 (1.57)
VABS pre-injury, mean (SD)	116.71 (21.58)	117.90 (10.25)	102.62 (17.05)	103.70 (19.95)	103.81 (15.09)	106.67 (9.27)
FSIQ acute, mean (SD)	98.00 (15.70)	103.10 (16.87)	90.77 (23.36)	103.54 (6.92)	96.65 (14.10)	85.50 (17.70)
SES acute, mean (SD)	4.17 (0.96)	4.31 (0.54)	4.08 (1.05)	4.12 (1.10)	4.23 (0.86)	5.08 (1.04)
Intact family unit, no. (%)	6 (85.7)	19 (99.3)	9 (69.2)	10 (76.9)	14 (82.4)	4 (66.7)
FFQ intimacy pre-injury, mean (SD)	60.50 (21.04)	65.75 (4.98)	63.46 (8.01)	59.31 (10.40)	66.79 (4.35)	69.20 (1.92)

SES measured as described by Daniel, 1983.

VABS, Vineland Adaptive Behavior Scale: Composite score; FSIQ, Full Scale Intellectual Quotient; SES, socio-economic status; FFQ, Family Function Questionnaire; SD, standard deviation; ETBI, early traumatic brain injury; LTBI, late traumatic brain injury.

The children were divided into groups based on age at injury and injury severity: early TBI (ETBI: n=40, 2 years 0 months to 7 years 11 months old at injury), and late TBI (LTBI: n=36, 8 years 0 months to 12 years 11 months old at injury). The age categorization was based on theoretical models and on recent research supporting substantial changes in cerebral and cognitive development in infancy and prior to age 8 years, with more gradual development from 8–12 years of age (Giedd et al., 1999; Gogtay et al., 2004). There is also now growing evidence to support different patterns of functional recovery in children younger than 2 years old, between 2 and 8 years old, and older (Anderson et al., 2005,2009a,2010a,2010b).

Severity groups were derived from a combination of measures, including period of altered consciousness (Glasgow Coma Scale [GCS]; Teasdale and Jennett, 1974), and the presence of radiological and neurological abnormalities: (1) mild TBI (n=20; GCS score on admission 13–15, no evidence of mass lesion on CT/MRI scans, and no neurologic deficits); (2) moderate TBI (n=37; GCS score on admission 9–12, and/or mass lesion or other evidence of specific injury on CT/MRI, and/or neurological impairment); and (3) severe TBI (n=19; GCS score on admission 3–8, and mass lesion or other evidence of specific injury on CT/MRI, and/or neurological impairment). GCS scores (on admission) and standardized neurosurgical observations were recorded every half hour, and then every 4 h, with recording continuing until the child regained consciousness. CT/MRI scans were reported by a pediatric neuroradiologist and neurosurgeon who were blinded to the injury status of the participant.

According to the requirements of the RCH Human Research Ethics Committee, information packs describing the study were provided to families during their child's hospital admission. Participants were children for whom signed consent was obtained and who met inclusion criteria. Once families had given consent, demographic questionnaires and the Vineland Adaptive Behavior Scale (VABS; Sparrow et al., 1994) were completed by the parents, based on pre-injury functioning. Children were evaluated once acute neurological dysfunction/post-traumatic amnesia had resolved (0–3 months post-injury). Review evaluations were conducted at 12 months, 30 months, and 10 years post-injury.

Measures

Injury and demographic variables

Children's medical and developmental histories, parental education and occupation, and family make-up were documented. During hospitalization, GCS score, length of coma, and neurological abnormalities were assessed and recorded by the child's medical team and surgical interventions were recorded. Identification of neurological deficits (e.g., seizures, hemiparesis, or cranial nerve dysfunction) was based on standard neurological examinations. Environmental factors (socioeconomic status [SES] and family function) were also assessed, given the previously reported relevance of such variables to recovery post-TBI. SES was coded using Daniel's scale of occupational prestige (Daniel, 1983), which rates parent occupation on a scale of 0–6.9, with a high score representing low SES. Family factors were measured (at all time points) using the Family Function Questionnaire (FFQ; Noller, 1988), which includes three scales: Intimacy, Conflict, and Parenting Style. For the FFQ, higher scores reflect greater dysfunction.

Pre-injury abilities

The VABS (Sparrow et al., 1994) was completed by parents during initial hospital admission, based on the child's pre-injury functioning. The Total Adaptive Behavior score was derived and employed in the analyses (M=100, SD=15), with higher scores representing better adaptive skills.

Post-injury cognitive abilities

Acute, 12 months, and 30 months

The choice of acute, 12-month, and 30-month IQ assessment tools was dependent on the child's age: Bayley Scales of Infant Development (BSID; Bayley, 1969, for children<30 months old); Wechsler Preschool and Primary Scale of Intelligence–Revised (WPPSI-R; Wechsler, 1989, for children 30 months–6.5 years old); and Wechsler Intelligence Scale for Children–Third Edition (WISC-III; Wechsler, 1991, for children>6.5 years old). Summary indices of cognitive ability were derived from each of these measures (FSIQ: M=100, SD=15), with higher scores representing better cognitive skills.

Of note, children injured prior to 30 months of age received the BSID at the acute assessment. This measure provides a global index of intellectual ability only. Thus only FSIQ data were available for the total sample at acute assessment. For the 12-month and 30-month time points all children completed either the WPPSI-R or WISC-III, which provide the following additional scores: Verbal IQ (VIQ) and Performance IQ (PIQ) (M=100, SD=15), and index scores (Verbal Comprehension: VC; Perceptual Organization: PO; Freedom from Distractibility: FFD; Processing Speed: PS) (M=10, SD=3).

10-Year follow-up

Age-appropriate Wechsler tests were administered at the 10-year follow-up: WISC-III (Wechsler, 1991), or Wechsler Adult Intelligence Scale-III (WAIS-III; Wechsler, 1997). VIQ, PIQ, and FSIQ, and index scores (VC, PO, FFD, and PS) were also calculated.

10-Year neuroimaging (MRI)

Image acquisition. All MR images were acquired with a 1.5-T Avanto scanner (Siemens Medical Systems, Malvern, PA), with the following sequence: T1-weighted sagittal SPGR acquisition (TR=1920, TE=3.93, NEX=1) with 1.0-mm contiguous slices, and T2-weighted TSE axial acquisition of slices 4 mm thick (TR=4850, TE=103, NEX=2). Scans were then coded by two pediatric neuroradiologists who independently rated the location of pathology as frontal, extrafrontal, subcortical, or a combination of these.

Statistical analysis

All analyses were performed using SPSS (version 17.0). Participating and non-participating samples were compared to examine potential biases in the 10-year follow-up sample, with no significant differences identified. For those participating at 10 years post-TBI, the ETBI and LTBI groups were compared, using one-way analysis of variance (ANOVA), or the Pearson chi-square test, with respect to demographic, pre-injury, psychosocial, and injury-related variables, to identify group differences that might influence post-injury function.

Repeated-measures ANOVA (full factorial model: age×severity×time) was conducted on IQ scores and IQ indices to investigate the effects of age at injury and injury severity over the 10 years post-injury. For each repeated-measures ANOVA, residuals were assessed, and in all instances models provided a good fit. Given the small cell sizes and overall sample size, as well as the exploratory nature of the study, we chose to err on the side of generosity when determining levels for statistical significance, using a cut-off of p=0.05. We also reported effect sizes (partial eta-squared) for these analyses, with values of 0.06 considered medium, and>0.14 large effects. Note that due to differences for FFQ between participating and non-participating groups at 10 years (see below), analyses were also conducted using the FFQ as a covariate. As including FFQ as a covariate in analyses did not alter results, these analyses are not further reported.

Individual impairment scores for each IQ variable were also derived, to examine the proportion of children in each severity group demonstrating impairment at 10 years. Classifications were as follows: (1) normal=a score of ≥90; (2) mild impairment=80–90; and (3) moderate/severe impairment=< 80. Based on technical data provided in the IQ test manuals, it is expected that 25% of the population will achieve an IQ score below 90, and 8.9% below 80. These expectations were employed to interpret rates of impairment. Chi-square analyses were conducted on these data. Due to small numbers in some cells, the mild and moderate/severe impairment groups were collapsed for these analyses.

Multiple regressions were performed to investigate predictors of 10-year outcome. Correlations among independent variables were calculated to identify multicollinearity. Not unexpectedly, given the design of the study, age at injury, age at testing, and time since injury were highly correlated, as were injury factors. As a result, the variables used in these analyses were: injury variables (GCS score and neurological signs), social/environmental factors (SES and FFQ), acute child function (FSIQ at 10 years), developmental factor (injury age), and pre-injury adaptive ability (pre-injury VABS score).

Results

Sample characteristics

Analyses of group differences for demographic factors revealed little of significance, other than those expected for age at injury [F_(1,70)=199.83, p<0.001], and age at assessment [F_(1,70)=50.83, p<0.001]. In the LTBI group a significant difference was found for FSIQ acute, with the mild group scoring significantly higher than the severe group [F_(2,35)=4.18, p=0.024]. Also in the LTBI group, a significant severity effect was detected for FFQ intimacy pre-injury [F_(2,31)=4.92, p=0.014]. The mild group were significantly lower on this measure than the moderate group (p=0.034) and the severe group (p=0.041). No differences were identified for gender, SES, or VABS pre-injury.

Expected group differences were evident for injury characteristics: GCS [F_(2,37)=17.43, p=0.001]; duration of coma [χ² _(2,40)=32.52, p=0.003]; abnormal CT/MRI findings [χ² _(2,40)=22.14, p<0.001]; presence of neurological signs [χ² _(2,40)=16.45, p<0.001]; and surgical interventions [χ² _(2,40)=10.27, p=0.006]. Most injuries for the mild TBI group occurred as a result of falls (all from >3 meters), with motor vehicle accidents more common in the severe TBI group (see Table 3 for injury characteristics).

Table 3.

Injury and Medical Characteristics of the Sample According to Age at Injury and Injury Severity

	ETBI group			LTBI group
	Mild (n=7)	Moderate (n=20)	Severe (n=13)	Mild (n=13)	Moderate (n=17)	Severe (n=6)
GCS on admission, mean (SD)	13.57 (1.51)	10.85 (3.92)	5.69 (2.14)	14.15 (1.35)	11.71 (2.95)	6.33 (1.37)
Coma characteristics
No LOC, no. (%)	5 (71.4)	12 (60.0)	0	3 (23.1)	6 (35.3)	0
< 1 h, no. (%)	2 (28.6)	7 (35.0)	3 (23.1)	10 (76.9)	11 (64.7)	1 (16.7)
1–24 h, no. (%)	0	0	0	0	0	5 (83.3)
> 24 h, no. (%)	0	1 (5.0)	10 (76.9)	0	0	0
Cause of injury^*
MVA: passenger, no. (%)	0	1 (5.0)	3 (23.1)	0	2 (11.8)	0
MVA: pedestrian, no. (%)	0	2 (10.0)	4 (30.8)	2 (15.3)	3 (17.6)	5 (83.3)
MVA: bike, no. (%)	0	1 (5.0)	1 (7.7)	6 (46.2)	7 (41.2)	1 (16.7)
Fall, no. (%)	7 (100.0)	14 (70.0)	3 (23.1)	5 (38.5)	1 (5.9)	0
Blow, no. (%)	0	2 (10.0)	2 (15.3)	0	4 (23.5)	0
CT/MRI findings, acute
Fracture, no. (%)	2 (28.6)	9 (45.0)	8 (61.5)	1 (7.7)	8 (47.1)	3 (50.0)
Cerebral bleed, no. (%)	0	7 (35.0)	7 (36.2)	0	9 (52.9)	2 (33.3)
Site of pathology
Frontal only, no. (%)	1 (14.3)	2 (10.0)	5 (38.5)	0	3 (17.6)	0
Extrafrontal only, no. (%)	1 (14.3)	5 (25.0)	2 (15.3)	0	2 (11.8)	2 (33.3)
Frontal+extrafrontal, no. (%)	0	0	2 (15.3)	0	1 (5.9)	0
Subcortical, no. (%)	0	0	1 (7.7)	0	0	1 (16.7)
Cortical+subcortical, no. (%)	0	0	1 (7.7)	0	1 (5.9)	3 (50.0)
None, no. (%)	4 (81.6)	12 (60.0)	2 (15.3)	13 (10.0)	9 (52.9)	0
Neurosurgical intervention, no. (%)	0	6 (30.0)	9 (69.2)	0	8 (47.1)	5 (83.3)
Neurological signs, no. (%)	0	9 (45.0)	12 (92.3)	0	6 (35.3)	5 (83.3)

LOC, loss of consciousness; GCS, Glasgow Coma Scale; CT, computed tomography; MRI, magnetic resonance imaging; MVA, motor vehicle accident; SD, standard deviation; ETBI, early traumatic brain injury; LTBI, late traumatic brain injury.

Intellectual abilities

Repeated-measures ANOVA for FSIQ identified no significant differences for severity, age at injury, or time since injury, and no significant interactions (Fig. 1). Similarly, for PIQ, no significant main effects or interactions were found. For VIQ, a significant main effect of time was detected (Wilk's Λ=0.881, F_(2,69)=4.65, p=0.013, η² =0.12), indicating that across injury age and severity there was a significant trend towards improved verbal function with time since injury. Inspection of group means indicates that consistent increments across time points were evident on Verbal IQ for all LTBI groups and the severe ETBI group (Table 4).

FIG. 1.

Recovery trajectories in the 10 years following childhood traumatic brain injury for injury severity and injury age. Data were collected acutely and at 12 months and 30 months (ETBI, early traumatic brain injury; LTBI, late traumatic brain injury; Mod, moderate; IQ, intelligence quotient).

Table 4.

Intelligence Quotients According to Age at Injury and Injury Severity Group

	ETBI group			LTBI group
	Mild	Moderate	Severe	Mild	Moderate	Severe
	(n=7)	(n=20)	(n=13)	(n=13)	(n=17)	(n=6)	Λ, F, P, η²
Full Scale IQ^a							Λ=0.96,F_(3,68)=0.86, p=0.46, η² =0.037
Time 1, mean (SD)	98.00 (15.70)	103.10 (16.87)	90.77 (23.36)	103.54 (6.92)	96.65 (14.10)	85.50 (17.70)
Time 2, mean (SD)	96.14 (12.25)	103.15 (13.36)	92.31 (15.36)	104.62 (10.04)	98.35 (14.10)	95.83 (11.32)
Time 3, mean (SD)	96.43 (12.11)	100.70 (12.33)	90.85 (15.60)	104.92 (8.95)	99.53 (17.78)	97.33 (13.35)
Time 4, mean (SD)	98.86 (16.50)	102.40 (16.39)	91.85 (17.32)	102.69 (14.94)	98.06 (17.09)	99.67 (9.09)
Verbal IQ							Λ=0.881,F_(2,69)=0.4.646, p=0.013, η² =.119
Time 2, mean (SD)	95.00 (8.33)	101.10 (13.25)	84.00 (28.18)	97.38 (10.47)	92.47 (13.20)	93.67 (10.41)
Time 3, mean (SD)	92.29 (9.83)	98.15 (12.48)	91.00 (12.25)	97.69 (11.22)	93.53 (17.57)	93.50 (12.79)
Time 4, mean (SD)	95.57 (13.48)	103.30 (14.58)	94.92 (16.11)	100.31 (11.99)	95.41 (16.23)	96.33 (9.65)
Performance IQ							Λ=0.978,F_(2,69)=0.775, p=0.465, η² =0.022
Time 2, mean (SD)	97.71 (16.88)	104.85 (13.13)	93.69 (18.42)	112.62^* (12.09)	105.65 (15.25)	99.50 (13.81)
Time 3, mean (SD)	102.43 (16.68)	103.25 (11.99)	91.08 (17.65)	112.62^* (10.75)	106.47 (18.10)	102.67 (15.29)
Time 4, mean (SD)	102.86 (21.04)	103.50 (15.68)	89.77 (20.04)	105.54 (19.94)	101.12 (16.41)	104.33 (10.29)

Only Full Scale IQ was available for time point 1 because the Bayley Scales of Infant Development for the youngest children did not separate Verbal IQ and Performance IQ.

Upon examining index scores a similar pattern emerged, with no significant effects or interactions present for PO, FFD, or PS, but a main effect of time for VC (Wilk's lambda=0.838, F_(2,66)=6.36, p=0.003, η² =0.162), consistent with improvements in verbal comprehension skills for all groups with time since injury. Of note, all group mean scores were within 1 standard deviation of the mean, suggesting no severe deficits at a group level.

Rates of residual intellectual impairment at 10 years

We also examined the proportion of children experiencing cognitive impairment (IQ<90; Table 5), as described above. As previously noted, population expectations indicate that 25% of children will fall within this range. Cell sizes in some groups were too small for analysis, so we separated analysis of impairment associated with severity (Table 6a), and age at injury (Table 6b). Comparison of severity groups found no significant group differences, and visual inspection of the data demonstrated a lack of the predicted dose-response relationship for several measures (PIQ, PO, and FFD). Children with severe TBI did record approximately twice the expected rate of impairment for PIQ (42.1%), VC (43.8%), and PS (53.3), while those with moderate TBI were also at higher-than-expected risk of impairment for FFD (41.9%).

Table 5.

IQ Indexes According to Age at Injury and Injury Severity Groups

	ETBI group			LTBI group
	Mild	Moderate	Severe	Mild	Moderate	Severe	F, p, ES
Verbal Comprehension							Λ=0.838,F_(2,66)=6.360, p=0.003, η² =0.162
Time 2, mean (SD)	9.29 (1.61)	10.08 (2.18)	8.52 (2.27)	9.06 (1.86)	8.41 (2.44)	9.05 (1.54)
Time 3, mean (SD)	8.54 (1.66)	9.42 (2.19)	8.27 (2.40)	9.19 (1.79)	8.50 (3.14)	9.30 (2.37)
Time 4, mean (SD)	9.43 (2.36)	10.45 (2.98)	8.63 (2.93)	10.00 (2.61)	9.44 (3.16)	9.90 (2.20)
Perceptual Organization							Λ=1.00,F(2,65)=.011, p=.989, η² =.000
Time 2, mean (SD)	10.00 (2.68)	10.70 (2.15)	9.72 (3.02)	11.94 (2.01)	10.90 (2.91)	11.53 (1.68)
Time 3, mean (SD)	10.90 (2.92)	10.32 (1.99)	9.42 (3.01)	11.97 (1.93)	10.81 (3.32)	11.27 (2.30)
Time 4, mean (SD)	10.76 (3.06)	10.93 (2.41)	8.92 (3.52)	11.39 (2.93)	10.23 (3.12)	12.33 (2.06)
Freedom from Distractibility							Λ=.985,F(2,67)=.499, p=.609, η² =.015
Time 2, mean (SD)	9.36 (1.46)	9.52 (2.09)	9.08 (1.68)	9.88 (2.32)	8.91 (2.26)	9.83 (1.81)
Time 3, mean (SD)	8.43 (1.97)	10.30 (2.49)	9.35 (2.40)	10.17 (2.40)	9.59 (3.03)	10.17 (0.98)
Time 4, mean (SD)	8.62 (2.52)	9.63 (2.94)	9.41 (2.66)	10.17 (2.01)	8.83 (2.54)	10.11 (1.43)
Processing Speed							Λ=.993,F(2,66)=.244, p=.784, η² =.007
Time 2, mean (SD)	9.29 (2.29)	9.85 (1.93)	7.85 (4.03)	11.58 (2.72)	10.59 (2.04)	8.60 (2.97)
Time 3, mean (SD)	9.86 (1.86)	10.40 (2.07)	6.50 (1.84)	11.33 (2.33)	10.50 (2.50)	8.50 (3.45)
Time 4, mean (SD)	9.64 (2.81)	10.15 (2.97)	7.73 (4.09)	9.96 (2.18)	10.09 (2.25)	8.60 (2.41)

Indexes not available for time point 1 because they were not provided by Bayley Scales of Infant Development.

Table 6a.

Percentage Impaired by Injury Severity

	Mild	Moderate	Severe
Verbal IQ	2 (25%)	10 (27.0)	6 (31.6)	χ² _(2,76)=0.224, p=0.447
Performance IQ	6 (30)	7 (18.9)	8 (42.1)	χ² _(2,76)=3.451, p=0.089
Full Scale IQ	5 (25)	11 (29.7)	6 (31.6)	χ² _(2,76)=0.226, p=0.447
Verbal Comprehension	5 (27.8)	10 (28.6)	7 (43.8)	χ² _(2,69)=1.354, p=0.254
Perceptual Organization	4 (20)	5 (14.3)	5 (33.3)	χ² _(2,70)=2.381, p=0.152
Freedom from Distractibility	5 (26.3)	13 (41.9)	3 (17.6)	χ² _(2,67)=3.321, p=0.095
Processing Speed	6 (30)	9 (25)	8 (53.3)	χ² _(2,71)=3.954, p=0.069

Table 6b.

Percentage Impaired by Age at Injury

	ETBI	LTBI
Verbal IQ	10 (25%)	11 (30.6)	χ² _(1,76)=0.292, p=0.295
Performance IQ	15 (37.5)	6 (16.7)	χ² _(1,76)=4.110, p=0.021
Full Scale IQ	11 (27.5)	11 (30.6)	χ² _(1,76)=0.086, p=0.385
Verbal Comprehension	11 (29.7)	11 (34.4)	χ² _(1.69)=0.170, p=0.340
Perceptual Organization	9 (25.0)	5 (14.7)	χ² _(1,70)=1.158, p=0.141
Freedom from Distractibility	14 (40.0)	7 (21.9)	χ² _(1,67)=2.552, p=0.056
Processing Speed	13 (33.3)	10 (31.3)	χ² _(1,71)=0.035, p=0.426

ETBI, early traumatic brain injury; LTBI, late traumatic brain injury.

Comparison of the ETBI and LTBI groups indicated that earlier injury was associated with higher risk of impaired PIQ, with a trend toward higher rates for FFD (40% versus 21.9%). Impairment rates were greater than 10% higher than expected for the ETBI group for PIQ (37.5%) and FFD (40%), and for the LTBI group for VC (34.4%). Elevated risk of impairment was also identified for both groups for PS (ETBI=33.3; LTBI=31.3).

Predictors of 10-year intellectual outcomes

Regression analyses were conducted for the IQ variables, with independent variables including injury (GCS and neurological signs), developmental (injury age), pre-injury (VABS), and environmental (SES and FFQ) factors (Table 7). For FSIQ, the regression model was significant, but explained only 13.7% of the variance, with SES and VABS the significant predictors. Similarly, a significant model was identified for VIQ (13% of variance), with SES and VABS again contributing. The model for PIQ was significant (13.8% variance), this time with injury age and FFQ related to 10-year performance. For index scores, only the PS model was significant (13.6% of variance explained), with FFQ identified as providing significant input.

Table 7.

Predictors of 10-Year Outcomes

10 year outcomes	R²	Adj R²	F	p	Significant predictors	B	SEB	β	p
Full Scale IQ	0.228	0.137	2.504	0.034	SES	−3.907	2.044	−0.239	0.062
					VABS	0.219	0.120	0.239	0.072
Verbal IQ	0.221	0.130	2.415	0.039	SES	−4.770	1.931	−0.310	0.017
					VABS	0.258	0.113	0.299	0.026
Performance IQ	0.229	0.138	2.519	0.033	FFQ	0.489	0.231	0.267	0.040
					Injury age	1.2449	0.684	0.238	0.074
Verbal Comprehension	0.202	0.005	2.156	0.063	SES	−0.907	0.354	−0.325	0.014
Perceptual Organization	0.206	0.110	2.156	0.063	Injury age	0.267	0.113	0.318	0.022
Freedom from Distractibility	0.183	0.087	1.908	0.097	VABS	0.053	0.019	0.373	0.008
Processing Speed	0.229	0.136	2.504	0.034	FFQ	0.103	0.040	0.329	0.013

The model included: Glasgow Coma Scale score, neurological signs, injury age, Vineland Adaptive Behavior Scale total pre-injury (VABS), socio-economic status (SES), and Family Functioning Questionnaire Intimacy (FFQ).

Discussion

This study reports data from the 10-year follow-up for 76 children who suffered a TBI between 2 and 12 years of age. Children were evaluated acutely, and at 12 months, 30 months, and 10 years post-TBI. The 10-year follow-up sample comprised children who completed assessments at all four time points and represented 63% of the original sample. There were no differences identified on demographic or injury variables between the original sample and 10-year follow-up sample for injury or demographic variables. Similarly, comparison of injury and demographic characteristics of the ETBI and LTBI groups detected no differences, with the exception of better family function and IQ for children with mild TBI and later age at injury.

Contrary to study predictions and previous research (Anderson and Moore, 1995; Anderson et al., 2005; Taylor et al., 2002), factors established as critical to outcome in the early years following child TBI (e.g., severity, age, and time) were not consistently identified as significant predictors of 10-year outcome in this study.

Injury severity

The expected dose-response relationship (i.e., more severe injury and poorer performance) was evident for cognitive abilities at acute post-injury assessment (Anderson et al., 2005,2009a), but was less clear by 10 years for all groups, with the exception of the severe ETBI group, which achieved mean IQs and index scores within the average range. Injury effects were further considered by examining rates of impairment at 10-year follow-up across severity groups. Once again, no significant dose-response relationship was detected, although there was a trend for children with severe TBI to be more likely to demonstrate impaired non-verbal skills (PIQ: p=0.089; PO: p=0.095), and reduced speed of processing (PS: p=0.069). In addition, a greater-than-expected proportion of children with severe TBI recorded impaired performances across verbal and non-verbal abilities and processing speed, with rates greater than 40% in each area. Children with moderate TBI displayed an elevated risk of impaired attention/working memory (FFD: 41.9%).

Injury age

More recently, age-at-injury effects have been documented consistently in the literature (Anderson and Moore, 1995; Ewing-Cobbs et al., 1989,1997), and also at early time points for this sample (Anderson et al., 1995). However, no significant effects were identified at the group level at 10 years post-TBI. Of note, the trend toward poorer performance in the ETBI severe group remains, as illustrated in Figure 1, with this group recording the poorest intellectual ability at all time points, and showing little evidence of recovery. This age effect was not observed for less severe injuries. Analysis of cognitive impairment rates at 10 years did identify overall higher levels of impairment in association with ETBI. Children with ETBI were at greater risk of impaired non-verbal skills, with rates approximately double that for the LTBI group (PIQ: ETBI 37.5% and LTBI 16.7%; PO: ETBI 25% and LTBI 14.7%), A trend toward greater impairment was also seen for attention/working memory skills (ETBI 40% and LTBI 21.9%). Both the ETBI and LTBI groups showed an elevated risk of impaired processing speed, with approximately one-third of all children performing within the impaired range. These findings suggest that age at injury may be most closely associated with more fluid cognitive skills, including non-verbal tasks and attention and working memory, potentially reflecting the relatively immature state of the brain regions underlying these skills during early childhood (Blakemore and Choudry, 2006; Giedd et al., 1999; Gogtay et al., 2004).

Recovery trajectories

Recovery profiles were relatively consistent across groups, regardless of injury severity or age at injury, with no evidence to suggest slower recovery trajectories for any group. Of note, for verbal skills (VIQ and VC) a significant time effect was identified, but with all groups demonstrating higher standard scores at 10 years than those recorded at 12 months. As illustrated in Figure 1, while acute cognitive skills showed wide variation linked to injury severity and injury age, from 30 months to 10 years post-injury skill levels were mostly stable. As these scores take age-related development into account, stable performance over time may be interpreted as a reflection of ongoing development in keeping with age expectations. Further, our findings suggest that the pattern and magnitude of cognitive impairment present at 12 months post-TBI may provide a reliable indicator of long-term outcome. Of clinical importance, this pattern of results argues against the notion that children “grow into” their deficits, or fall further behind their age peers with time since injury. Rather, it would appear that deficits present at 12 months persist, but there is evidence of ongoing progress in keeping with development.

Predictors of 10-year outcome

Examination of potential predictors of 10-year intellectual outcomes indicated that, while models were significant, they were unable to explain the majority of the variance. For most outcome domains only a small proportion of variance was explained (approximately 13%). Pre-injury skills and SES were the only significant contributors to overall cognitive ability and verbal skills, while earlier injury age was predictive of poorer non-verbal abilities. Family dysfunction was related to lower non-verbal skills and processing speed, and pre-injury function contributed to attention/working memory. Injury severity and neurological signs did not emerge as significantly related to any of these outcomes. These findings are largely consistent with previous work both in TBI and normal development, which show a clear link for verbal skills and socio-demographic factors (Anderson et al., 2006; Yeates et al., 2010), as well as the importance of pre-injury function to level of post-injury abilities. As noted above, the association between early insult and poorer fluid cognitive skills has also been previously reported (Dennis, 1989; Walsh et al., 1985); however, the additional contribution of family function is novel. One potential explanation for this link may be found in the literature describing the cognitive impacts of early deprivation (Belsky and de Haan, 2011). These authors describe specific non-verbal problems in children whose early development has been disrupted by drastically impoverished environments, and cite evidence that such cognitive profiles can be correlated with alterations to brain architecture.

While this study is the first to prospectively follow a substantive sample of children over an extended period, such longitudinal designs are prone to attrition and sample bias, as reported in other studies of child TBI (Ewing-Cobbs et al., 2004; Yeates et al., 2005). We believe that collection of acute injury and demographic data at the time of insult ensured that we were able to identify sample bias issues, with few significant differences identified between participating and non-participating groups on demographic and injury variables. A related issue is a relatively small sample size, which had an impact on statistical power, and limited the potential to fully investigate the many factors that may impact long-term outcomes. While we have considered effect sizes in an attempt to determine whether significant effects would be present in a larger sample, future research using larger samples is indicated. A further problem faced by longitudinal child studies is the lack of available measures to cover the age span of interest. To maximize the reliability of our findings, we focused on IQ measures, due to their robust psychometric properties, and the availability of comparable tests across the age range of our study. However, it has been argued that IQ is relatively insensitive to neurobehavioral impairments, and in isolation may limit the ability to consider recovery trajectories across other functional domains, such as attention and executive function. While this may be a serious limitation in adult research, for children, in whom cognitive skills are developing, even IQ is likely to be impacted by brain insults (Dennis et al., 2009). In support of this proposition, we have found similar patterns of results for attention and executive function as well as educational outcomes in the current sample (Beauchamp et al., 2011; Catroppa et al., 2009,2011). Categorizing age at injury is also controversial. We classified our sample into two age groups, based on key stages of brain development derived from the developmental neurosciences literature (Giedd et al., 1999; Giza and Prins, 2006; Gogtay et al., 2004), and previous research identifying these age groups as demonstrating different responses to brain injury (Anderson and Moore, 1995; Anderson et al., 2005,2009b,2010a,2010b). These two age groups did not differ with respect to key demographic (SES, gender, or pre-injury ability) or injury variables (severity, location of pathology, or neurological signs). The mechanism of injury, however, was different across age groups, with more children in the ETBI group sustaining injury due to falls, and more children with LTBI injured in motor vehicle accidents. Evidence now suggests that different injury mechanisms may result in different consequences. While our data suggest no differences in the injury variables documented, this factor needs to be acknowledged when considering the age-at-injury effects described. Future research with larger samples may be able to evaluate the questions of age at injury, and injury mechanism effects in a more fine-grained manner.

Conclusions

At 10 years post-injury survivors of child TBI demonstrate overall average to low average cognitive abilities, with no significant group effects for severity, injury age, or time since injury. In contrast, elevated rates of impairment are present, with severe TBI related to an increased risk of deficits across the range of cognitive domains, and early injury primarily linked to poorer non-verbal abilities. Increased risk of processing speed deficits is also related to both more severe injury and younger injury age. These seemingly contradictory findings indicate the need for caution if relying solely on the results of group analyses when interpreting the consequences of child TBI. Predictors of 10-year outcome included pre-injury and social factors, injury age, and family function. Contrary to previous speculation that these children grow into their deficits, between 30 months and 10 years post-insult recovery appears to stabilize, and children begin to make appropriate developmental gains.

Footnotes

Acknowledgments

This research was supported by grants from the Australian National Heath and Medical Research Council and the Victorian Government Operational Infrastructure Support Program.

Author Disclosure Statement

No competing financial interests exist.

References

Anderson

, Moore

1995. Age at injury as a predictor of outcome following pediatric head injury. Child Neuropsychol., 1:187–202.

Anderson

, Brown

, Newitt

, Hoile

2011. Long-term outcome from childhood traumatic brain injury: Intellectual ability, personality and quality of life. Neuropsychology, 25:176–184.

Anderson

, Catroppa

, Dudgeon

, Morse

, Haritou

, Rosenfeld

2006. Understanding predictors of functional recovery and outcome thirty-months following early childhood head injury. Neuropsychology, 20:42–57.

Anderson

, Catroppa

, Morse

, Haritou

, Rosenfeld

2005. Functional plasticity or vulnerability following early brain injury? Pediatrics, 116:1374–1382.

Anderson

, Catroppa

, Morse

, Haritou

, Rosenfeld

2009b. Intellectual outcome from preschool traumatic brain injury: A 5-year prospective, longitudinal study. Pediatrics, 124:pe1064–pe1071.

Anderson

, Jacobs

, Spencer-Smith

, Coleman

, Anderson

, Williams

, Greenham

, Leventer

2010a. Does early age at brain insult predict worse outcome? Neuropsychological implications. J. Ped. Psychol., 35:716–727.

Anderson

, Morse

, Catroppa

, Haritou

, Rosenfeld

2004. Thirty-month outcome from early childhood head injury: A prospective analysis of neurobehavioral recovery. Brain, 127:2608–2620.

Anderson

, Morse

, Klug

, Catroppa

, Haritou

, Rosenfeld

, Pentland

1997. Predicting recovery from head injury in young children. J. Int. Neuropsychol. Soc., 3:568–580.

Anderson

, Spencer-Smith

, Coleman

, Anderson

, Williams

, Greenham

, Leventer

R.J.

, Jacobs

2010b. Children's executive functions: Are they poorer after very early brain insult. Neuropsychologia, 48:2041–2050.

10.

Anderson

, Spencer-Smith

, Leventer

, Coleman

, Anderson

, Williams

, Greenham

, Jacobs

2009a. Childhood brain insult: Can age at insult help us predict outcome? Brain, 132:45–56.

11.

Anderson

, Spencer-Smith

, Wood

2011. Do children really recover better? Neurobehavioural plasticity after early brain insult. Brain EPub 10.1093/brain//awr103.

12.

Asarnow

R.F.

, Satz

, Light

, Zaucha

, Lewis

, McCleary

1995. The UCLA study of mild closed head injuries in children and adolescents, in: Traumatic Head Injury in Children. Broman

S.H.

, Michel

M.E.

Oxford University Press: New York, 117–146.

13.

Babikian

, Asarnow

2009. Neurocognitive outcomes and recovery after pediatric TBI: Meta-analytic review of the literature. Neuropsychology, 22:283–296.

14.

Bayley

1969. Bayley Scales of Infant Development: Birth to two years. The Psychological Corporation: San Antonio.

15.

Beauchamp

, Catroppa

, Godfrey

, Morse

, Rosenfeld

J.V.

, Anderson

2011. Selective changes in executive functioning ten years after severe childhood traumatic brain injury. Dev Neuropsychol., 36:578–595.

16.

Belsky

, de Haan

2011. Parenting and children's brain development: the end of the beginning. J. Child Psychol. Psychiat., 52:409–428.

17.

Blakemore

, Choudry

2006. Development of the adolescent brain: Implications for executive function and social cognition. J. Child Psychol. Psychiat., 47:296–312.

18.

Catroppa

, Anderson

2007. Recovery in memory function, and its relationship to academic success, at 24 months following pediatric TBI. Child Neuropsychol., 13:240–261.

19.

Catroppa

, Anderson

, Godfrey

, Rosenfeld

J.V.

2011. Attentional skills 10 years post pediatric traumatic brain injury (TBI) Brain Inj., 25:858–869.

20.

Catroppa

, Anderson

V.A.

, Morse

S.A.

, Haritou

, Rosenfeld

2007. Children's attentional skills 5 years post-TBI. J. Ped. Psychol., 32:354–369.

21.

Catroppa

, Anderson

, Morse

S.A.

, Haritou

, Rosenfeld

2009. Outcome and predictors of functional recovery five years following pediatric traumatic brain injury (TBI) J. Ped. Psychol., 33:707–718.

22.

Catroppa

, Anderson

V.A.

, Muscara

, Morse

S.A.

, Haritou

, Rosenfeld

, Heinrich

L.M.

2009. Educational skills: Long-term outcome and predictors following paediatric traumatic brain injury. Neuropsychol. Rehab., 19:716–732.

23.

Cattelani

, Lombardi

, Brianti

, Mazzucchi

1998. A. Traumatic brain injury in childhood: Intellectual, behavioural and social outcome into adulthood. Brain Inj., 12:283–296.

24.

Crowe

, Babl

, Anderson

, Catroppa

2009. The epidemiology of paediatric head injuries: Data from a referral centre in Victoria, Australia. JPCH, 46:346–350.

25.

Daniel

1983. Power, Privilege and Prestige: Occupations in Australia. Longman-Chesire: Melbourne, 1983.

26.

Dennis

, Francis

, Cirino

, Scharchar

, Barnes

, Fletcher

2009. Why OQ is not a covariate in studies of neurodevelopmental disorders. J. Int. Neuropsychol. Soc., 15:331–343.

27.

Dennis

1989. Language and the young damaged brain. Clinical Neuropsychology and Brain Function: Research, Measurement and Practice. Boll

, Bryant

B.K.

American Psychological Association: Washington, 85–124.

28.

Dennis

, Wilkinson

, Koski

, Humphreys

R.P.

1995. Attention deficits in the long term after childhood head injury. Traumatic Head Injury in Children. Broman

S.H.

, Michel

M.E.

Oxford University Press: New York, 165–187.

29.

Dennis

, Yeates

K.O.

, Taylor

H.G.

, Fletcher

J.M.

2007. Brain reserve capacity, cognitive reserve capacity, and age-based functional plasticity after congenital and acquired brain injury in children. Cognitive Reserve. Stern

Taylor & Francis: New York, 53–83.

30.

Ewing-Cobbs

, Barnes

, Fletcher

J.M.

, Levin

H.S.

, Swank

P.R.

, Song

2004. Modeling of longitudinal academic achievement scores after pediatric traumatic brain injury. Dev Neuropsychol., 25:107–133.

31.

Ewing-Cobbs

, Fletcher

J.M.

, Levi

H.S.

, Francis

D.J.

, Davidson

, Miner

M.E.

1997. Longitudinal neuropsychological outcome in infants and preschoolers with TBI. J. Int. Neuropsychol. Soc., 3:581–591.

32.

Ewing-Cobbs

, Fletcher

J.M.

, Levin

H.S.

, Iovino

, Miner

M.E.

1998. Academic achievement and academic placement following traumatic brain injury in children and adolescents: A two-year longitudinal study. J. Clin. Exp. Neuropsychol., 20:769–781.

33.

Ewing-Cobbs

, Miner

M.E.

, Fletcher

J.M.

, Levin

H.S.

1989. Intellectual, language and motor sequelae following closed head injury in infants and preschoolers. J. Ped. Psychol., 14:531–547.

34.

Giedd

, Blumenthal

, Jeffries

, Castellanos

, Liu

, Zijdenbos

, Paus

, Evans

, Rapoport

1999. Brain development during childhood and adolescence: A longitudinal MRI study. Nature Neuroscience, 2:861–863.

35.

Ginsfeldt

, Emanuelson

2010. An overview of attention deficits after paediatric traumatic brain injury. Brain Inj., 24:1123–1134.

36.

Giza

C.C.

, Prins

M.L.

2006. Is being plastic fantastic? Mechanisms of altered plasticity after developmental traumatic brain injury. Dev. Neurosci., 28:364–379.

37.

Gogtay

, Giedd

, Lusk

, Hayashi

, Greenstein

, Vaituzis

, Nugent

, Herman

, Clasen

, Toga

2004. Dynamic mapping of human cortical development during childhood through early adulthood. Proc. Nat. Acad. Sci., 101:8174–8179.

38.

Jaffe

K.M.

, Fay

G.C.

, Polissar

N.L.

, Martin

K.M.

, Shurtlef

H.A.

, Rivara

J.B.

, Winn

1993. Severity of pediatric traumatic brain injury and neurobehavioral recovery at one year—A cohort study. Arch. Phys. Med. Rehab., 74:587–595.

39.

Kinsella

, Prior

, Sawyer

, Murtagh

, Eisenmajer

, Anderson

, Bryan

, Klug

1995. Neuropsychological deficit and academic performance in children and adolescents following TBI. J. Ped. Psychol., 20:753–767.

40.

Kinsella

, Prior

, Sawyer

, Ong

, Murtagh

, Eisenmajer

, Bryan

, Anderson

, Klug

1997. Predictors and indicators of academic outcome in children 2 years following traumatic brain injury. J. Int. Neuropsychol. Soc., 3:608–616.

41.

Kraus

J.F.

1995. Epidemiological features of brain injury in children. Traumatic Head Injury in Children. Broman

S.H.

, Michel

M.E.

Oxford University Press: New York, 117–146.

42.

Levin

H.S.

, High

W.M.

, Ewing-Cobbs

, Fletcher

J.M.

, Eisenberg

H.M.

, Miner

M.E.

, Goldstein

F.C.

1988. Memory functioning during the first year after closed head injury in children and adolescents. Neurosurgery, 22:1043–1052.

43.

Noller

1988. ICPS Family Functioning Scales. Unpublished manuscript. University of Queensland.

44.

Nybo

, Koskiniem

1999. Cognitive indicators of vocational outcome after severe traumatic brain injury (TBI) in childhood. Brain Inj., 13:759–766.

45.

Ponsford

, Willmott

, Rothwell

, Cameron

, Ayton

, Nelms

, Curran

, Ng

K.T.

1999. Cognitive and behavioural outcomes following mild traumatic head injury in children. J. Head Trauma Rehabil., 14:360–372.

46.

Power

, Catroppa

, Coleman

, Ditchfield

, Anderson

2007. Do lesion site and severity predict deficits in attentional control after preschool traumatic brain injury (TBI)? Brain Inj., 21:279–292.

47.

Romema

, Crowe

, Anderson

(in press)Social outcomes following child TBI: A systematic review.

48.

Sparrow

, Balla

D.A.

, Cicchetti

D.V.

1984. Vineland Adaptive Behavior Scales: Interview Edition. Survey Form Manual. American Guidance Services: Circle Pines, Minnesota.

49.

Taylor

H.G.

, Yeates

K.O.

, Wade

S.L.

, Drotar

, Stancin

, Minich

2002. A prospective study of short- and long-term outcomes after traumatic brain injury in children: Behavior and academic achievement. Neuropsychology, 16:15–27.

50.

Taylor

H.G.

, Yeates

K.O.

, Wade

S.L.

, Drotar

, Stancin

, Montpetite

2003. Long-term educational interventions after traumatic brain injury in children. Rehab. Psychol., 48:227–236.

51.

Teasdale

, Jennett

1974. Assessment of coma and impaired consciousness. Lancet, 2:81–84.

52.

Walsh

1985. Neuropsychology: A Clinical Approach. Churchill: Edinburgh.

53.

Wechsler

1997. Manual for the Wechsler Adult Intelligence Scale-III. Psychological Corporation: New York.

54.

Wechsler

1989. Manual for the Preschool and Primary Intelligence Scale-Revised. Psychological Corporation: New York.

55.

Wechsler

1991. Manual for the Wechsler Scale of Children's Intelligence-III. Psychological Corporation: New York.

56.

Yeates

, Armstrong

, Janusz

, Taylor

H.G.

, Wade

, Stancin

2005. Long-term attention problems in children with traumatic brain injury. J. Am. Acad. Child Adolesc. Psychiat., 44:574–584.

57.

Yeates

K.O.

, Taylor

H.G.

2006. Behaviour problems in school and their educational correlates among children with traumatic brain injury. Exceptionality, 14:141–154.

58.

Yeates

K.O.

, Bigler

E.D.

, Dennis

, Gerhardt

C.A.

, Rubin

K.H.

, Stancin

, Taylor

H.G.

, Vannatta

2007. Social outcomes in childhood brain disorder: A heuristic integration of social neuroscience and developmental psychology. Psychol. Bull., 133:535–556.

59.

Yeates

K.O.

, Taylor

H.G

, Barry

C.T.

, Drotar

, Wade

S.L.

, Stancin

2001. Neurobehavioural symptoms in childhood closed-head injuries: Changes in prevalence and correlates during the first year post-injury. J. Ped. Psychol., 26:79–91.

60.

Yeates

K.O.

, Taylor

H.G

, Cherrtkoff

, Stancin

, Wade

2010. The family environment as a moderator of psychosocial outcomes following traumatic brain injury in young children. Neuropsychology, 24:345–356.

61.

Yeates

K.O.

, Swift

, Taylor

H.G.

, Wade

S.L.

, Drotar

, Stancin

, Minich

2004. Short- and long-term social outcomes following pediatric traumatic brain injury. J. Int. Neuropsychol. Soc., 10:412–426.

62.

Yeates

K.O.

, Taylor

H.G.

, Rusin

, Bangert

, Dietrich

, Nuss

, Wright

, Nagin

D.S.

, Jones

B.L.

2009. Longitudinal trajectories of post-concussive symptoms in children with mild traumatic brain injuries and their relationship to acute clinical status. Pediatrics, 123:735–743.