Investigating parenting factors,traumatic brain injury and callous and unemotional traits among high school students in a South African setting

Abstract

Aggressogenic parenting styles are associated with increased rates of callous and unemotional traits, and in turn, with antisocial behaviours. Traumatic brain injury is also associated with antisocial behaviour, but not callous and unemotional traits specifically. No study has previously investigated these three variables, aggressogenic parenting, traumatic brain injury, and callous and unemotional traits, in a single study. The study setting was Cape Town, South Africa. The sample included high school boys (N = 54), aged 13–21 years in an observational, descriptive study. We hypothesised that boys who reported that they had sustained a traumatic brain injury and who had been exposed to aggressogenic parenting would display increased levels of callous and unemotional traits, and that those with traumatic brain injury but had experienced positive parenting would display lower levels of such traits. The main measures included the Comprehensive Health Assessment Tool, the Inventory of Callous/Unemotional traits, and the Alabama Parenting Questionnaire. Results show that almost 41% (22/54) of participants reported sustaining a traumatic brain injury. Aggressogenic parenting significantly moderated callous and unemotional traits only in participants with traumatic brain injury, F(1.46) = 4.76, p = .03, while positive parenting and substance use did not. In conclusion, traumatic brain injury in the presence of aggressogenic parenting is associated with greater callous and unemotional traits in this sample of adolescent boys.

Keywords

Adolescence antisocial crime parenting traumatic brain injury

Crime rates in South Africa are high and increased from 2016/2017 to 2017/2018 (Statistics South Africa, 2018), with highest rates found in lower socio-economic status (SES) communities (Gardner et al., 2015). Many South African youths find themselves within such low-SES settings, where males aged 12–22 years especially face high exposure to crime and violence alongside poverty, relative to the general population (Bhorat et al., 2017; De Lannoy et al., 2015; Gardner et al., 2015). However, youth are not only witness to and victims of crime but are also among the leading perpetrators thereof (du Plessis et al., 2015; Statistics South Africa, 2018). A well-established predictive factor of criminal involvement in individuals is the presence of antisocial behaviours (Gardner et al., 2015). Callous and unemotional (CU) traits, characterised by a lack of empathy and low affect, in turn predict antisocial behaviour (Mann et al., 2015; Viding et al., 2012) and this tends to occur at higher rates in males than females (Larsson et al., 2008) and within lower SES settings (Piotrowska et al., 2015).

Style and methods of parenting have been found to have important and long-lasting effects on children’s behaviour that continue into adolescent and young adult years (Ward et al., 2015). Early work on types of parenting styles revealed three clusters that are still influential in parenting research today – authoritative, authoritarian, and permissive parenting styles (Baumrind, 1966, 1971). Maccoby and Martin (1983) expanded on this seminal work and conceptualised that support and control made up a framework operating on two dimensions: responsiveness and demandingness. In light of this framework, they defined four styles of parenting: authoritarian (low support, high control; discipline with demands and low child autonomy), authoritative (high support and control), permissive (high support and low control; a lack of monitoring, control, and discipline, yet it is warm and nurturing), and neglecting (low support and control). Their research indicated that any style that is not authoritative may lead to increased risk of associated negative outcomes. In particular, authoritarian and permissive styles have been found to be linked to negative psychosocial developmental outcomes and behavioural problems over time (Fernandez, 2009; Flouri & Midouhas, 2017).

Research investigating the relevance and prominence of the four styles has shown that at least in Western culture, there is a strong evidence base for the existence and pertinence of these styles (Power, 2013). Although sometimes clusters may differ between three or four parenting clusters, little to no evidence has indicated more types of parenting styles than those described by Baumrind, and Maccoby and Martin (Roman et al., 2016). Indeed, parenting research in South Africa has used these three/four styles successfully and found them relevant and useful for study in this context (Kritzas & Grobler, 2005; Latouf, 2008; Makwakwa, 2011; Roman et al., 2016).

For the purposes of this study, aggressogenic parenting was taken to include dimensions: inconsistent discipline, and corporal punishment, and monitoring and supervision from the Alabama Parenting Questionnaire (APQ; Frick, 1991), as informed by characteristics that fall under parenting styles associated with negative outcomes, namely, the high control, discipline with demands and low child autonomy under authoritarian parenting; the lack of monitoring, control, and discipline under permissive styles; and low support and control that characterise neglecting parenting styles.

There is a large pool of research establishing links between antisocial behaviour and CU traits, and aggressogenic parenting styles (Viding et al., 2012; Waller et al., 2018). As noted, aggressogenic parenting styles include harsh or coercive parenting, parenting that is low in warmth, and poor supervision (Waller et al., 2013). Harsh discipline has been reported as a strong predictor of antisocial behaviours (e.g., high levels of aggression) in children as young as 5 years old (Leibbrandt et al., 2012). Furthermore, parenting styles involving violence from parents towards children are also associated with higher levels of antisocial behaviours in children (Ward et al., 2015). While there are few national studies of parenting in South Africa, rates of corporal punishment by caregivers – a form of harsh, coercive parenting – range from 18% upwards (Ward et al., 2018). Studies on CU traits and aggressogenic parenting styles in this context are however lacking.

In addition, there is an association between traumatic brain injury (TBI) and antisocial behaviour (Andrews et al., 1998; Tomaszewski et al., 2014; Williams et al., 2018), which may be moderated by parenting style (Chavez Arana et al., 2020). Parenting style has been found to moderate functional impairments in children with TBI across cognitive and social domains, where children parented with a permissive (negative) style of parenting are significantly more likely to display these impairments over time, in comparison with those who experience more positive parenting (Wade et al., 2016). These differences in cognitive and social behavioural outcomes between children with TBI and controls become consistently more pronounced under extreme authoritarian and permissive parenting styles (Yeates et al., 2010).

However, as yet, there is a dearth of research on TBI and CU traits, despite the link of both to antisocial behaviour (Andrews et al., 1998; Tomaszewski et al., 2014; Williams et al., 2010). Developing countries like South Africa are postulated to have higher rates of TBI than developed world countries (Dewan et al., 2018), making South Africa an ideal location to explore such research.

In sum, aggressogenic parenting styles are associated with increased rates of CU traits, and both TBI and CU traits are associated with antisocial behaviour, but no previous study has investigated these three variables together.

Aim and hypotheses

The aim of this study was to investigate whether parenting styles towards youth who report having sustained a TBI moderate the presence of CU traits. Specifically, we investigated whether adolescents who report having sustained a TBI, and who have been exposed to more positive parenting styles, as measured by the APQ, would report lower rates of CU traits than those with TBI who had been exposed to aggressogenic parenting behaviours.

We hypothesised that (1) youth who report having sustained a TBI, who had been exposed to a positive parenting style, would report lower levels of CU traits; and (2) youth who report having sustained a TBI, who had been exposed to an aggressogenic parenting style, would report higher levels of CU traits.

Method

The study was cross-sectional and quantitative. The independent variables in this study were (self-reported) TBI (yes/no) and style of parenting to which participants had reportedly been exposed (positive/aggressogenic). The dependent variable was the CU trait score.

Participants

Participants were recruited through purposive sampling from two high schools in low- to middle-SES areas within Cape Town. Specific schools were selected based on their proximity to the university, and a previous research association with one of the schools. Participants were English- or Afrikaans-speaking males, aged 13–21 years.

Instruments

Alcohol, Smoking, and Substance Involvement Screening Test

The Alcohol, Smoking, and Substance Involvement Screening Test (ASSIST) is a self-report questionnaire with eight items designed to assess levels of substance use in the 3 months preceding the test. The measure screens for a range of substances, including, but not limited to, alcohol, tobacco, and cannabis. The World Health Organization (WHO) ASSIST Working Group (2002) designed the ASSIST in 2010, with the goal of creating a standardised measure with which to assess levels of substance abuse worldwide. It has high levels of reliability and validity (a = .83, Kaiser–Meyer–Olkin [KMO] = .77; Simelane-Mnisi & Mji, 2017). Seeing as the measure was created with a global population in mind, and has been tested in an African population, it is suited to the South African context (Humeniuk et al., 2010; Simelane-Mnisi & Mji, 2017).

Alcohol Use Disorders Identification Test

The Alcohol Use Disorders Identification Test (AUDIT) is a 10-item questionnaire that was developed by the WHO to measure alcohol consumption, dependence, and associated complications (Babor et al., 1992). It is particularly aimed at health care practitioners, but it can and has been successfully self-administered or administered by non-health care professionals. The AUDIT has high internal consistency and reliability (Cronbach’s alpha = .80), and these properties have been tested and found to be retained in South African samples (Meneses-Gaya et al., 2010; Peltzer et al., 2011).

Beck Depression Inventory

The Beck Depression Inventory (BDI) is a widely utilised tool used to assess levels of depression. Both psychological and physical symptoms of depression are assessed. It is a self-report measure with 21 items using a 4-point Likert scale. Standard cutoff scores are as follows: scores between 0 and 9 indicate normal functioning, 10–19 indicate mild to moderate depression, and 20 and above indicate severe depression (Beck et al., 1996). The test has good psychometric properties, including high validity (Cronbach’s alpha = .96) and test–retest reliability scores (Cronbach’s alpha = .73–.96; Beck et al., 1996; Wang & Gorenstein, 2013). In addition, the BDI has been used successfully and widely in South Africa and was thus suited to the context (Khumalo & Plattner, 2019; Stellenberg & Abrahams, 2015).

TBI measure

Comprehensive Health Assessment Tool

The Comprehensive Health Assessment Tool (CHAT) is a standardised measure used to screen for health complications. It was originally designed with a young offender population in mind. It includes four sections: physical health, mental health, substance misuse, and neurodisability (Chitsabesan et al., 2014). We used the CHAT to distinguish between adolescents who have sustained a TBI and those who have not. An advantage of this tool is that it measures frequency and severity of each TBI (if there has been more than one). The CHAT has good psychometric properties when compared to other health assessment tools, and high reliability and validity when assessing presence of TBI (Chitsabesan et al., 2015). This measure has previously been used in South Africa (Nkoana et al., 2020).

Demographic questionnaire

This short questionnaire was used to assess the individual participants’ socioeconomic environment. Questions pertaining to the participants’ age, residential area, number of individuals residing within the household, number of rooms within the household, and the type of materials out of which the house was made were used to determine the SES of participants

Parenting measure

APQ

The APQ is a two-part self-report questionnaire whereby the participant in question is asked to rank his responses to 42 items on a 5-point Likert scale. There are two separate questionnaires for youth and their parents. For the purposes of this study, only the high school boys were asked to complete this questionnaire, due to difficulty obtaining responses from parents. The questionnaire is used to assess parenting styles in five subcategories: involvement, positive parenting, monitoring/supervision, inconsistent discipline, and corporal punishment (Frick, 1991). High factorial validity has been found between these categories (Maguin et al., 2016). Internal consistency is adequate and test–retest reliability is good (r = .84–.90; Dadds et al., 2003). The APQ is a commonly used measure, with multiple translated versions in use. This measure has been successfully used to assess parenting in South African studies (Lachman et al., 2013). For the purposes of this study, the five categories were grouped into two larger categories of positive and aggressogenic parenting for better operationalisation. Positive parenting and involvement were grouped as positive parenting, while monitoring/supervision, inconsistent discipline, and corporal punishment were grouped under aggressogenic parenting, allowing for two parenting scores.

Antisocial behaviour measure

Inventory of Callous and Unemotional Traits

The Inventory of Callous and Unemotional Traits (ICU) is made up of 24 items that measure levels of aggression and antisocial behaviour across three subsections, including callousness, unemotionality, and uncaring tendencies (Frick, 2004). Each item is rated on a 4-point Likert scale and the participants are required to rank their responses to statements as such. Some items require reverse scoring. The ICU has been found to have good psychometric properties (e.g., reliability) even in cross-cultural settings (Cronbach’s alpha = .77) and reliable in detecting antisocial tendencies in adolescents (Kimonis et al., 2014; Mooney, 2010). Although this measure has only been used in an unpublished South African study, a study investigating cross-cultural properties of the ICU found it to retain its psychometric properties in varied cultural settings, and we therefore consider it appropriate for our context and purposes (Feilhauer et al., 2012; Ockhuizen, 2014).

The total score for the ICU is 72, with the optimal cutoff score of 28 reported for youth self-report form. However, we did not apply a stringent cutoff score, but considered scores comparatively (Docherty et al., 2017).

Procedure

All boys who met the inclusion criteria were invited to participate in the study. Parental consent was sought for those who were below age 18. Informed consent (for those aged 18 or above) and assent (for those below age 18) was obtained prior to interviewing participants. All measures were administered in an interview style with each participant. Each participant was interviewed individually in an empty classroom where there was no risk of disruption or violation of confidentiality. At the end of the interview, the researchers provided each participant with a R50 food shopping voucher.

Ethical considerations

Ethical approval was obtained from the Research Ethics Committee of the Psychology Department at the University of Cape Town, and permission to test in schools from the Western Cape Department of Education.

Data analysis

We analysed the study data using the Statistical Package for the Social Sciences Version 25.

We first ran descriptive statistics for the correlations between, age, the control variables (BDI, AUDIT, ASSIST, age), the predictor variables (TBI and parenting style), and the outcome variable (CU traits). We then ran two hierarchical moderation analyses to determine whether boys with TBI (yes/no) who had been exposed to more positive/aggressogenic parenting styles (both through self-report) reported fewer/more CU traits, respectively. To allow aggressogenic and positive parenting to be on the same scale when running our analyses for better operationalisation and comparison, we represented aggressogenic and positive parenting as percentages of the total possible score. Thus, each participant’s aggressogenic score was divided by 95, which represents the total possible score for aggressogenic parenting and each positive parenting score by 130, which represents the total possible score for positive parenting. We controlled for depression, substance use, and age in these analyses.

For both moderation analyses, all control variables and age were entered as a block, followed by TBI, and then by either positive or aggressogenic parenting style, with the interaction term entered as the final block. Some studies have shown that substance use and depressive symptoms in adolescents may increase the likelihood of displaying antisocial behaviours (Hemphill et al., 2015; Park et al., 2010). In addition, age has a significant impact on antisocial behaviours in that the period of adolescence is associated with a significantly higher degree of antisocial behaviours compared to other phases in an individual’s lifespan (Eme, 2016; Henry et al., 1993). Although all our participants were adolescents, the age range was quite large (13–21), and thus it was necessary to control for age. It was, therefore, necessary to consider these potential confounding variables in the study.

Results

Sample characteristics

The sample size was N = 54 and included high school boys in Grades 8 to 12, aged 13–21 at the time of testing. About 40% of the sample (n = 22) reported having sustained a TBI at some point in their lifetime, of which 54.5% had experienced a loss of consciousness, 4.5% of those for less than 5 min, 27% between 5 and 30 min, 9% between 30 min to 1 hr, and 9% between 1 hr and 24 hr, and 4.5% for longer than twenty-four hours. In all, 77.2% experienced feeling dazed and confused after the injury. Participants resided in predominantly low-SES areas, with 63% of participants residing in high-density informal settlements.

Comparing TBI and no-TBI groups

There were no significant differences between the no-TBI and TBI groups in terms of substance use, where 66% and 91% of participants in each group reported substance use, respectively (ASSIST; χ² = 1.571; p = .216). The results of comparisons for alcohol consumption, CU traits, depression, and parenting styles for the TBI and no-TBI groups are presented in Table 1. There were also no significant between-group differences for these variables. Depression scores for both groups were in the mild depression range of 14–19 on the BDI-II (Beck et al., 1996) and scores for the ICU for both groups were below the cutoff score of 28 (higher scores present greater likelihood of offender-like behaviour, including antisocial, aggressive, and violent behaviour; Docherty et al., 2017).

Table 1.

Descriptive statistics and between-groups analysis for TBI versus non-TBI groups.

Variable	No-TBI	TBI	F	p
Variable	(n = 32)	(n = 22)	F	p
Age (years)
M (SD)	15.56 (1.831)	15.68 (2.05.6)	0.050	.824
Range	13 – 21	13 – 21
Alcohol use (AUDIT)
M (SD)	5.94 (6.334)	6.27 (6.700)	0.843	.843
Callous and Unemotional Traits (ICU)
M (SD)	20.84 (5.280)	21.59 (7.551)	0.184	.670
Depression (BDI-II)
M (SD)	15.41 (9.821)	15.86 (9.478)	0.029	.865
Aggressogenic parenting (%)
M (SD)	49.05 (12.451)	52.92 (10.647)	1.415	.240
Positive parenting (%)
M (SD)	61.97 (17.081)	61.05 (16.571)	0.040	.843

Note. For the variables, means are presented with standard deviations in parentheses. TBI: traumatic brain injury; AUDIT: Alcohol Use Disorders Identification Test; ICU: Inventory of Callous and Unemotional traits; BDI-II: Beck Depression Inventory.

Correlations

TBI was positively and weakly correlated to aggressogenic parenting (r = .16, p = .12) and negatively and weakly correlated to positive parenting (r = −.028, p = 42). Positive parenting was significantly negatively correlated with CU scores (r = −.26, p = .02). The associations between aggressogenic parenting and CU traits (r = −.02, p = .41), and TBI and CU traits (r =-.2, p = .33), were not significant. These correlations are presented in Table 2.

Table 2.

Bivariate correlations for the study measures for the total sample (N = 54).

Variable	Alphas	1	2	3	4	5	6	7	8
1. Age		–
2. Substance use (ASSIST)^a		.338**	–
3. Alcohol use (AUDIT)	.782	.463**	.432**	–
4. CU traits (ICU)	.575	.165	.150	.114	–
5. Depression (BDI-II)	.837	.236*	.249*	.430**	.101	–
6. TBI (y/n)^a		.031	.171	.028	.024	.024	–
7. Aggressogenic parenting (%)	.776	.313*	.253*	.467**	.029	.422**	.163	–
8. Positive parenting (%)	.922	−.351	−.209	−.284*	−.263*	−.407**	−.028	−.139	–

Note. ICU: Inventory of Callous and Unemotional traits; ASSIST: Alcohol, Smoking, and Substance Involvement Screening Test; AUDIT: Alcohol Use Disorders Identification Test; BDI-II: Beck Depression Inventory; TBI: traumatic brain injury.

Categorical variables.

Correlation is significant at the .05 level (one-tailed). **Correlation is significant at the .01 level (one-tailed).

Cronbach’s alphas for measures of alcohol use, depression, and positive and aggressogenic parenting ranged from .776 to .922, as shown in Table 2, which are in the generally acceptable range (Tavakol & Dennick, 2011). However, the alpha for the measure of CU traits was lower than the acceptable level. Even though these results are not consistent with psychometric properties reported in previous studies (e.g., Kimonis et al., 2014; Mooney, 2010), the ICU is the only measure specifically designed to measure CU traits. Furthermore, a recent meta-analytic review of the ICU notes that internal consistency of the measure might be undermined by the unemotional subscale specifically, rather than all three subscales (Cardinale & Marsh, 2020).

Moderation analyses

We ran two separate hierarchical regression moderation analyses where for both analyses, depression, substance use, and age were controlled for in the first block; TBI was added in the second; positive or aggressogenic parenting in the third; and the interaction term of variables positive or aggressogenic parenting and TBI was entered in the final block, respectively. The outcome variable was CU traits for both moderation analyses (see Tables 3 and 4).

Table 3.

Hierarchical moderation analysis: Positive parenting and TBI as predictors and CU traits (ICU) as outcome variable (N = 54).

Block	Variables	R²	R² change	F change	Unstandardised coefficients β	SE	p	B
Block 1	Substance use (ASSIST)	.039	.039	0.501	1.465	2.352	.73	.098
	Alcohol use (AUDIT)				0.402	0.526		.123
	Depression (BDI-II)				0.033	0.101		.050
	Age				−0.007	0.184		−.007
Block 2	TBI	.041	.001	0.073	0.490	1.810	.78	.039
Block 3	Positive parenting	.084	.043	2.200	−0.069	0.046	.14	−.237
Block 4	Interaction term	.087	.003	0.172	−0.037	0.089	.68	−.078

Note. The first row represents the model in which the controls were added. Each row after that represents each outcome variable in addition to the controls for the final model statistics. TBI: traumatic brain injury; CU traits: Callous and Unemotional Traits; ICU: Inventory of Callous and Unemotional traits; ASSIST: Alcohol, Smoking, and Substance Involvement Screening Test; AUDIT: Alcohol Use Disorders Identification Test; BDI-II: Beck Depression Inventory.

Table 4.

Hierarchical moderation analysis: Aggressogenic parenting and TBI as predictors and CU traits (ICU) as outcome variable (N = 54).

Block	Variables	R ²	R ² change	F change	Unstandardised coefficients β	SE	P	β
Block 1	Substance use (ASSIST)	.039	.039	0.501	1.465	2.352	.73	1.46
	Alcohol use (AUDIT)				0.402	0.526		−.007
	Depression (BDI-II)				0.033	0.101		.033
	Age				−0.007	0.184		−.040
Block 2	TBI	.041	.001	0.073	0.490	1.810	.78	.039
Block 3	Aggressogenic parenting	.046	.005	0.236	−0.046	0.096	.63	−.083
Block 4	Interaction term	.135	.090	4.765	0.362	0.166	.03*	.374

p < .05.

Positive parenting and TBI

Overall, the positive parenting model was not statistically significant, F(7, 46) = .62, p = .73. Furthermore, there was no moderation effect present and thus positive parenting did not moderate CU traits in children with or without TBI, all as reported by participants.

Aggressogenic parenting and TBI

Similarly, the aggressogenic parenting model was not significant overall, F(7, 46) = .1.02, p = .42, and explained 13.5% of the variance. As shown in Table 2, none of the variables significantly predicted CU scores by themselves – however, there was a moderation effect present as the interaction term significantly predicted CU scores. The interaction term explained 9% of the variance, F(1, 46) = 4.76, p = .03. Therefore, there was a moderating effect present and thus reported aggressogenic parenting moderated CU traits in children with reported TBI (see Figure 1).

Figure 1.

Scatter plot showing the interaction between aggressogenic parenting and CU traits for youth who had sustained TBIs and controls.

The moderation analysis indicated that only in the presence of aggressogenic parenting did participants with TBI exhibit more CU traits than those without TBI. Figure 1 is a visual attempt at understanding the interaction, with the test of moderation acting as the interaction term in the model. The analysis tells us that the difference between no TBI and TBI is significant based on the test of the interaction. From a simple slopes analysis, the trend for the TBI group is 0.26, with a 95% confidence interval of −0.01 to 0.52 (p = .119). There appears to be marginal evidence that the slope for TBI children is positive, and that for no-TBI group (−0.11), the slope is likely flat (95% confidence interval [CI] = −0.3 to 0.08, p = .176). However, each group slope is not significantly different from 0.

Discussion

Crime levels in South Africa, and especially within low-SES communities, are exceedingly high (Statistics South Africa, 2018). Youth and particularly adolescent males within these communities are among the leading victims and perpetrators of criminal activity (du Plessis et al., 2015; Statistics South Africa, 2018). The presence of antisocial behaviours is associated with an increased likelihood of criminal activity (Moffitt, 2018). Two established predisposing factors towards antisocial behaviours associated with criminal activity are (1) presence of a TBI, due to its associated neurological and subsequent behavioural pathologies (Ilie et al., 2014); and (2) harsh discipline and other techniques associated with poor parenting style (Ward et al., 2015). Considering the high levels of TBI among South African youth residing in low-SES communities, and the context of extreme crime levels in the country, it is important to establish whether certain parenting styles further predispose children with TBI to involvement in criminal activities (Naidoo, 2013; Statistics South Africa, 2018).

A worryingly high 41% of the sample reported having sustained a TBI. These figures are consistent with other research on prevalence of TBIs in South Africa and other developing world countries and reflect the high frequencies of common mechanisms of TBI in the country (Dewan et al., 2018; Naidoo, 2013; Statistics South Africa, 2018). The number of complicated mild TBIs are, however, very high relative to other samples in high-income countries (Williams et al., 2018).

There were no significant differences between the TBI and non-TBI groups regarding CU traits, nor differences in styles of parenting. There was a weak negative correlation between positive parenting and ICU scores; however, the regression analysis indicated that positive parenting did not significantly predict CU traits. The moderation analysis indicated that while positive parenting did not moderate CU traits in children with TBI, aggressogenic parenting significantly moderated ICU scores in children with TBI and explained 9% of the variance in the model.

Regarding the first finding, it is possible that cultural differences affected the measures; also, since parents may use both aggressogenic and positive parenting approaches with the same child, it is possible that the aggressogenic effects outweigh the positive effects.

The second finding, however, suggests that parenting may be an important intervention point for children with TBI. These findings are consistent with the literature reviewed, indicating that poor parenting exacerbates the negative social effects of TBI and increases levels of antisocial behaviours. This outcome is in contrast to the non-significant findings regarding the impact of good parenting on children with TBIs in terms of antisocial outcomes. This could suggest that South African children with TBIs are more susceptible to the effects of poor parenting including discipline, monitoring and supervision, and corporal punishment, typically delivered by parents, but not as susceptible to the effects of good parenting. This could potentially be due to wide networks of social support and thus less reliance on parents for positive social support than children in other settings. However, South African children with TBIs are still vulnerable to the effects of poor parenting.

Parenting support and training may prevent the development of antisocial behaviour (Cluver et al., 2018) and/or CU traits, which would both improve the life chances of the individual children, and potentially – given how widespread TBI is – even reduce the national crime rate. The implications of these tentative findings could be that we need to target parents of children with TBI, with the intention of reducing the prevalence of behaviours associated with poor parenting, as these appear to increase the risk of children with TBI engaging in antisocial behaviours. Hospitals, where TBIs are often diagnosed and reported, could be a hotspot for identifying parents of children who have sustained TBIs and encouraging them to enrol in parenting workshops specific to their needs and situation. Furthermore, parents of children who have sustained TBIs could have their parenting style assessed and be provided with support and education regarding the parenting of children who have sustained TBIs.

However, it must also be recognised that reverse causality is a possibility: those with TBI may well be more ‘difficult’ children to parent (more likely to take risks, etc.) who elicit aggressogenic parenting. Longitudinal studies are needed to investigate such effects.

We acknowledge the recognised limitations associated with self-report measures (social desirability bias and lack of insight [the latter could be a consideration where there is a history of TBI]), as well as our limited sample size and representation, which impacts on the statistical power in our analyses and the generalisability of our findings, respectively. We also acknowledge the lower than acceptable alpha found for the ICU for this study sample. We did not have access to medical records of the children and thus had to rely on their recollection of having sustained a TBI. To this end, the severity of TBI was also not objectively assessed. Furthermore, we were not able to administer the parent component of the APQ and thus only had responses of the high school participants, where both would have provided a more reliable score, and the perception of the child may therefore drive our findings.

Conclusion

This study found that children with a TBI are more susceptible to the effects of aggressogenic parenting, in terms of displaying more CU traits, but not to the effects of parental involvement and positive parenting. Further research is needed to establish the lack of effect positive parenting had on those with TBI and to match self-report measures with medical records. The effects of aggressogenic parenting may affect future criminal behaviour and thus it is crucial that interventions be put in place for children with TBIs who are exposed to aggressogenic parenting.

Footnotes

Declaration of conflicting interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was supported by the National Research Foundation (NRF) Thuthuka Grant (TTK170418227316) and the MRC Confidence in Global Mental Health: Trauma and Adverse Childhood Experiences Springboard (TrACES) grant (MC_PC_MR/R019991/1).

ORCID iD

Leigh Schrieff-Brown

References

Andrews

T. K.

Rose

F. D.

Johnson

D. A.

(1998). Social and behavioural effects of traumatic brain injury in children. Brain Injury, 12(2), 133–138. https://doi.org/10.1080/026990598122755

Babor

T. F.

Higgins-Biddle

J. C.

Saunders

J. B.

Monteiro

M. G.

(1992). AUDIT. The Alcohol Use Disorders Identification Test. Guidelines for use in primary health care. Geneva, Switzerland: World Health Organization.

Baumrind

(1966). Effects of authoritative parental control on child behavior. Child Development, 37(4), 887. https://doi.org/10.2307/1126611

Baumrind

(1971). Current patterns of parental authority. Developmental Psychology, 4(1, Pt. 2), 1–103. https://doi.org/10.1037/h0030372

Beck

A. T.

Steer

R. A.

Brown

G. K.

(1996). Beck Depression Inventory manual (2nd ed.). Psychological Corporation. https://doi.org/10.1037/t00742-000

Bhorat

Lilenstein

Monnakgotla

Thornton

van der Zee

(2017). “The SocioEconomic Determinants of Crime in South Africa: an Empirical Assessment”. Development Policy Research Unit Working Paper 201704. DPRU, University of Cape Town.

Cardinale

E. M.

Marsh

A. A.

(2020). The reliability and validity of the inventory of callous unemotional traits: A meta-analytic review. Assessment, 27(1), 57–71. https://doi.org/10.1177/1073191117747392

Chavez Arana

Catroppa

Yáñez-Téllez

Prieto-Corona

de León

M. A.

García

Gómez-Raygoza

Hearps

S. J. C.

Anderson

. (2020). A parenting program to reduce disruptive behavior in Hispanic children with acquired brain injury: A randomized controlled trial conducted in Mexico. Developmental Neurorehabilitation, 23, 218–230. https://doi.org/10.1080/17518423.2019.1645224

Chitsabesan

Lennox

Theodosiou

Law

Bailey

Shaw

(2014). The development of the comprehensive health assessment tool for young offenders within the secure estate. The Journal of Forensic Psychiatry & Psychology, 25(1), 1–25. https://doi.org/10.1080/14789949.2014.882387

10.

Chitsabesan

Lennox

Williams

Tariq

Shaw

(2015). Traumatic brain injury in juvenile offenders: Findings from the comprehensive health assessment tool study and the development of a specialist linkworker service. The Journal of Head Trauma Rehabilitation, 30(2), 106–115. https://doi.org/10.1097/HTR.0000000000000129

11.

Cluver

L. D.

Meinck

Steinert

J. I.

Shenderovich

Doubt

Herrero Romero

Lombard

C. J.

Redfern

Ward

C. L.

Tsoanyane

Nzima

Sibanda

Wittesaele

De Stone

Boyes

M. E.

Catanho

Lachman

J. M.

Salah

Nocuza

Gardner

(2018). Parenting for Lifelong Health: A pragmatic cluster randomised controlled trial of a non-commercialised parenting programme for adolescents and their families in South Africa. BMJ Global Health, 3(1), Article e000539. https://doi.org/10.1136/bmjgh-2017-000539

12.

Dadds

Maujean

Fraser

(2003). Parenting and conduct problems in children: Australian data and psychometric properties of the alabama parenting questionnaire. Australian Psychologist, 38(3), 238–241. https://doi.org/10.1080/00050060310001707267

13.

De Lannoy

Leibbrandt

Frame

(2015). A focus on youth: An opportunity to disrupt the intergenerational transmission of poverty. In: De Lannoy

Swartz

Lake

Smith

(eds) South African Child Gauge 2015. Cape Town, Children’s Institute, UCT.

14.

Dewan

Rattani

Gupta

Baticulon

Hung

Punchak

(2018). Estimating the global incidence of traumatic brain injury. Journal of Neurosurgery, 130(4), 1080–1097. https://doi.org/10.3171/2017.10.jns17352

15.

Docherty

Boxer

Huesmann

L. R

O’Brien

Bushman

(2017). Assessing callous-unemotional traits in adolescents: Determining cutoff scores for the inventory of callous and unemotional traits. Journal of Clinical Psychology, 73(3), 257–278. https://doi.org/10.1002/jclp.22313

16.

du Plessis

Kaminer

Hardy

Benjamin

. (2015). The contribution of different forms of violence exposure to internalizing and externalizing symptoms among young South African adolescents. Child Abuse & Neglect, 45, 80–89. https://doi.org/10.1016/j.chiabu.2015.02.021

17.

Eme

(2016). Life-course-persistent antisocial behavior. Journal of Forensic Psychology, 1(1), 1–4. https://doi.org/10.4172/2475-319x.1000101

18.

Feilhauer

Cima

Arntz

(2012). Assessing callous–unemotional traits across different groups of youths: Further cross-cultural validation of the Inventory of Callous–Unemotional Traits. International Journal of Law and Psychiatry, 35(4), 251–262. https://doi.org/10.1016/j.ijlp.2012.04.002

19.

Fernandez

(2009). Children’s wellbeing in care: Evidence from a longitudinal study of outcomes. Children and Youth Services Review, 31(10), 1092–1100. https://doi.org/10.1016/j.childyouth.2009.07.010

20.

Flouri

Midouhas

(2017). Environmental adversity and children’s early trajectories of problem behavior: The role of harsh parental discipline. Journal of Family Psychology, 31(2), 234–243. https://doi.org/10.1037/fam0000258

21.

Frick

P. J.

(1991). The Alabama Parenting Questionnaire. Unpublished Rating Scale, Tuscaloosa, AL: University of Alabama. https://doi.org/10.1037/t58031-000

22.

Frick

P. J.

(2004). The Inventory of Callous-Unemotional Traits. New Orleans, LA: UNO.

23.

Gardner

Waller

Maughan

Cluver

Boyes

(2015). What are the risk factors for antisocial behavior among low-income youth in Cape Town? Social Development, 24(4), 798–814. https://doi.org/10.1111/sode.12127

24.

Hemphill

S. A.

Heerde

J. A.

Herrenkohl

T. I.

Farrington

D. P.

(2015). Within-individual versus between-individual predictors of antisocial behaviour: A longitudinal study of young people in Victoria, Australia. Australian & New Zealand Journal of Criminology, 48(3), 429–445. https://doi.org/10.1177/0004865815589829

25.

Henry

Moffit

Robins

T. L.

Earls

Silva

(1993). Early family predictors of child and adolescent antisocial behaviour: Who are the mothers of delinquents? Criminal Behaviour and Mental Health, 3(2), 97–118. https://doi.org/10.1002/cbm.1993.3.2.97

26.

Humeniuk

R. E.

Henry-Edwards

Ali

R. L.

Poznyak

Monteiro

(2010). The Alcohol, Smoking and Substance Involvement Screening Test (ASSIST): manual for use in primary care. Geneva, World Health Organization.

27.

Ilie

Mann

R. E.

Boak

Adlaf

E. M.

Hamilton

Asbridge

Cusimano

M. D.

(2014). Suicidality, bullying and other conduct and mental health correlates of traumatic brain injury in adolescents. PloS one, 9(4), e94936. https://doi.org/10.1371/journal.pone.0094936

28.

Khumalo

Plattner

(2019). The relationship between locus of control and depression: A cross-sectional survey with university students in Botswana. South African Journal of Psychiatry, 25. https://doi.org/10.4102/sajpsychiatry.v25i0.1221

29.

Kimonis

E. R.

Fanti

K. A.

Singh

J. P.

(2014). Establishing cut-off scores for the parent-reported inventory of callous-unemotional traits. Archives of Forensic Psychology, 1(1), 27–48.

30.

Kritzas

Grobler

A. A.

(2005). The relationship between perceived parenting styles and resilience during adolescence. Journal of Child & Adolescent Mental Health, 17(1), 1–12. https://doi.org/10.2989/17280580509486586

31.

Lachman

Cluver

Boyes

Kuo

Casale

(2013). Positive parenting for positive parents: HIV/AIDS, poverty, caregiver depression, child behavior, and parenting in South Africa. AIDS Care, 26(3), pp.304–313. https://doi.org/10.1080/09540121.2013.825368

32.

Larsson

Viding

Plomin

(2008). Callous–unemotional traits and antisocial behavior. Criminal Justice and Behavior, 35(2), 197–211. https://doi.org/10.1177/0093854807310225

33.

Leibbrandt

Finn

Woolard

(2012). Describing and decomposing post-apartheid income inequality in South Africa. Development Southern Africa, 29(1), 19–34. https://doi.org/10.1080/0376835x.2012.645639

34.

Latouf

N. C.

(2008). Parenting styles affecting the behavior of five-year olds [Unpublished master’s thesis, University of South Africa].

35.

Maccoby

E. E.

Martin

J. A.

(1983). Socialization in the context of the family: Parent–child interaction. In Mussen

P. H.

(Ed.), Handbook of child psychology: Socialization, personality and social development (Vol. IV, pp. 1–101). Wiley.

36.

Maguin

Nochajski

De Wit

Safyer

(2016). Examining the validity of the adapted Alabama Parenting Questionnaire—Parent Global Report Version. Psychological Assessment, 28(5), pp.613–625. https://doi.org/10.1037/pas0000214

37.

Makwakwa

(2011). Emerging adulthood: Examining the relationship between parenting styles and decision-making of university resident students [Unpublished master thesis, University of the Western Cape].

38.

Mann

F. D.

Briley

D. A.

Tucker-Drob

E. M.

Harden

K. P.

(2015). A behavioral genetic analysis of callous-unemotional traits and big five personality in adolescence. Journal of Abnormal Psychology, 124(4), 982–993. https://doi.org/10.1037/abn0000099

39.

Meneses-Gaya

Zuardi

A.W.

Loureiro

S.R.

Hallak

J.E.

Trzesniak

de Azevedo Marques

J.M.

Machado-de-Sousa

J.P.

Chagas

M.H.

Souza

R.M.

Crippa

J.A.

(2010). Is the Full Version of the AUDIT Really Necessary? Study of the Validity and Internal Construct of Its Abbreviated Versions. Alcoholism: Clinical And Experimental Research. https://doi.org/10.1111/j.1530-0277.2010.01225.x

40.

Moffitt

(2018). Male antisocial behaviour in adolescence and beyond. Nature Human Behaviour, 2(3), 177–186. https://doi.org/10.1038/s41562-018-0309-4

41.

Mooney

N. P.

(2010). Predicting offending within the New Zealand youth justice system: Evaluating measures of risk, need, and psychopathy (Unpublished doctoral dissertation). Massey University, Wellington, New Zealand.

42.

Naidoo

(2013). Traumatic brain injury: The South African landscape. South African Medical Journal, 103(9), 613. https://doi.org/10.7196/samj.7325

43.

Nkoana

Wiiliams

Steenkamp

Clasby

Knowler

Schrieff

(2020). Understanding the educational needs of young offenders: A prevalence study of traumatic brain injury and learning disabilities. International Journal of Educational Development, 78. https://doi.org/10.1016/j.ijedudev.2020.102261

44.

Ockhuizen

H. J.

(2014). The prevalence of traumatic brain injury (TBI) and an investigation of behavioural and executive functioning outcomes (among those who have sustained TBIs) in a sample of male young offenders (Unpublished master’s thesis). University of Cape Town, South Africa.

45.

Park

Lee

Sun

Vazsonyi

Bolland

(2010). Pathways and predictors of antisocial behaviors in African American adolescents from poor neighborhoods. Children and Youth Services Review, 32(3), 409–415. https://doi.org/10.1016/j.childyouth.2009.10.012

46.

Peltzer

Davids

Njuho

(2011). Alcohol use and problem drinking in South Africa: findings from a national population-based survey. African Journal of Psychiatry, 14(1). https://doi.org/10.4314/ajpsy.v14i1.65466

47.

Piotrowska

Stride

Croft

Rowe

(2015). Socioeconomic status and antisocial behaviour among children and adolescents: A systematic review and meta-analysis. Clinical Psychology Review, 35, 47–55. https://doi.org/10.1016/j.cpr.2014.11.003

48.

Power

T. G.

(2013). Parenting dimensions and styles: A brief history and recommendations for future research. Childhood Obesity, 9(Suppl. 1), S14–S21. https://doi.org/10.1089/chi.2013.0034

49.

Roman

N. V.

Makwakwa

Lacante

(2016). Perceptions of parenting styles in South Africa: The effects of gender and ethnicity. Cogent Psychology, 3(1), 1153231. https://doi.org/10.1080/23311908.2016.1153231

50.

Simelane-Mnisi

Mji

(2017). Establishing the reliability and validity of the ASSIST questionnaire: A South African sample perspective. Electronic Journal of Research in Educational Psychology, 15(1), 201–223.

51.

Statistics South Africa. (2018). Victims of crime survey.

52.

Stellenberg

Abrahams

(2015). Prevalence of and factors influencing postnatal depression in a rural community in South Africa. African Journal of Primary Health Care & Family Medicine, 7(1). https://doi.org/10.4102/phcfm.v7i1.874

53.

Tavakol

Dennick

(2011). Making sense of Cronbach’s alpha. International Journal of Medical Education, 2, 53–55. https://doi.org/10.5116/ijme.4dfb.8dfd

54.

Tomaszewski

Buliński

Mirski

Rasmus

Kowalczyk

Bazan

Pąchalska

(2014). An evaluation of antisocial behaviour in children after traumatic brain injury: The prospect of improving the quality of life in rehabilitation. Annals of Agricultural and Environmental Medicine, 21(3), 649–653. https://doi.org/10.5604/12321966.1120620

55.

Viding

Fontaine

N. M.

McCrory

E. J.

(2012). Antisocial behaviour in children with and without callous-unemotional traits. Journal of the Royal Society of Medicine, 105(5), 195–200. https://doi.org/10.1258/jrsm.2011.110223

56.

Wade

Zhang

Yeates

Stancin

Taylor

(2016). Social Environmental Moderators of Long-term Functional Outcomes of Early Childhood Brain Injury. JAMA Pediatrics, 170(4), 343. https://doi.org/10.1001/jamapediatrics.2015.4485

57.

Waller

Gardner

Hyde

L. W.

(2013). What are the associations between parenting, callous-unemotional traits, and antisocial behavior in youth? A systematic review of the evidence. Clinical Psychology Review, 33, 593–608. https://doi.org/10.1016/j.cpr.2013.03.001

58.

Waller

Hyde

L. W.

Klump

K. L.

Burt

S. A.

(2018). Parenting is an environmental predictor of callous-unemotional traits and aggression: A monozygotic twin differences study. Journal of the American Academy of Child and Adolescent Psychiatry, 57(12), 955–963. https://doi.org/10.1016/j.jaac.2018.07.882

59.

Wang

Gorenstein

(2013). Psychometric properties of the Beck Depression Inventory-II: a comprehensive review. Revista Brasileira de Psiquiatria, 35(4), 416–431. https://doi.org/10.1590/1516-4446-2012-1048

60.

Ward

Gould

Kelly

Mauff

(2015). Spare the rod and save the child: Assessing the impact of parenting on child behaviour and mental health. South African Crime Quarterly, 51, 9. https://doi.org/10.4314/sacq.v51i0.2

61.

Ward

C. L.

Artz

Leoschut

Kassanjee

Burton

(2018). Sexual violence against children in South Africa: A nationally representative cross-sectional study of prevalence and correlates. The Lancet Global Health, 6, e460–e468. https://doi.org/10.1016/S2214-109X(18)30060-3

62.

WHO ASSIST Working Group. (2002). The Alcohol, Smoking and Substance Involvement Screening Test (ASSIST): Development, reliability and feasibility. Addiction, 97(9), 1183–1194. https://doi.org/10.1046/j.1360-0443.2002.00185.x

63.

Williams

W. H.

Chitsabesan

Fazel

McMillan

Hughes

Parsonage

Tonks

(2018). Traumatic brain injury: A potential cause of violent crime? The Lancet Psychiatry, 5(10), 836–844. https://doi.org/10.1016/s2215-0366(18)30062-2

64.

Williams

W. H.

Cordan

Mewse

Tonks

Burgess

(2010). Self-reported traumatic brain injury in male young offenders: A risk factor for re-offending, poor mental health and violence? Neuropsychological Rehabilitation, 20(6), 801–812. https://doi.org/10.1080/09602011.2010.519613

65.

Yeates

Taylor

Walz

Stancin

Wade

(2010). The family environment as a moderator of psychosocial outcomes following traumatic brain injury in young children. Neuropsychology, 24(3), 345–356. https://doi.org/10.1037/a001838