Women in Prison With Traumatic Brain Injury: Prevalence,Mechanism,and Impact on Mental Health

Abstract

Relatively little is known about the characteristics of female offenders. Here, we studied the prevalence of traumatic brain injury (TBI) and mental health issues in an exclusively female prison population in New Zealand. Participants (N = 38) were recruited from all security levels at Christchurch Women’s Prison. Measures for depression, anxiety, and stress, sleep, and a history of TBI were administered; 94.7% (36/38) of participants presented with a history of TBI. Younger age at first injury was associated with an increased risk of mental health problems. The study concludes that TBI is highly prevalent among female offenders and may be linked to increased mental health problems. TBI should be considered as an important factor in offender pathways and treatment programs.

Keywords

female offenders brain injury mental health sleep problems

Introduction

Incarcerated offender populations in developed countries are largely male. According to World Prison Brief Data from the Institute for Criminal Policy Research (2017), females comprised 5.7% of incarcerated offenders in Germany (2016), 3.3% in France (2017), 5.8% in Norway (2016), 4.6% in England and Wales (2017), 7.0% in New Zealand (2016), 8.0% in Australia (2016), 5.6% in Canada (2014), and 9.7% in the United States (2014). As a result, the majority of research on offenders has studied male samples. Although this research is clearly important, results and implications for rehabilitation programs will not necessarily generalize to females.

Research with female offenders is particularly important because incarceration rates for women have risen dramatically in recent decades. From 1978 to 2014, these rates increased by 552% in the United States for women, compared with 245% for men over the same period (Bureau of Justice Statistics, 2016a, 2016b). A similar increase was found in New Zealand, where the number of prison sentences started by women rose by 99% from 1984-1985 to 2014-2015 (Department of Corrections, 2015). Unlike male counterparts, increases in female offending are not related to violent offences but more likely nonviolent (e.g., larceny/theft or drug-related; Bloom, Owen, & Covington, 2004). Thus, it is essential that we also have an accurate understanding of why females offend and what their particular treatment needs are, so that optimal interventions can be tailored for them.

Research on gendered pathways has shown that life experiences which lead to offending are different for women than men (Daly, 1994; Steffensmeier & Allan, 1996). Using a quantitative approach (path analysis), Salisbury and Van Voorhis (2009) found that there were three gendered pathways for female incarceration, including childhood victimization, dysfunctional relationships, and challenges in education, family support, and self-efficacy. Similarly, risk factors for offending differ for males and females. A recent review reported that whereas male offending was more closely associated with criminal history, criminal thinking, personality attributes, and criminal peers, female offending was correlated more with factors such as mental health, poverty, trauma, and dysfunctional relationship patterns (Van Voorhis, Wright, Salisbury, & Bauman, 2010). Different offending profiles suggest that it is unlikely that male-specific information can reasonably be generalized to females. For example, the Level of Supervision Inventory–Revised (LSI-R; Andrews & Bonta, 2000), which was developed with largely male samples, does not accurately predict recidivism for female offenders who had followed a gendered pathway to crime (Reisig, Holtfreter, & Morash, 2006).

Moreover, relationships and relatedness is considered to be particularly important and a primary motivator for women across the life span (Covington, 1998). Furthermore, relationship patterns represent a key feature of female offending (Covington, 2002). For example, lack of meaningful relationships and abuse within relationships (sexual, emotional, and physical) are often identifying factors in female offending (Covington & Bloom, 2007). Covington and Bloom (2007) suggested that recognition of relational connections is also an important part of rehabilitation for female offenders in terms of mental health problems, substance abuse, and likely rehabilitation from other adverse events, including traumatic brain injury (TBI).

Incarcerated females also face different challenges compared with their male counterparts. For example, because incarcerated female populations are smaller, there are fewer correctional facilities dedicated to housing them. Therefore, incarcerated females are more likely to be imprisoned far from home, leading to difficulties in maintaining relationships with family and friends (Kingi, 2000). Kingi (2000) also reported that incarcerated females generally had little or no work experience and were welfare-dependent before sentencing. A high proportion of female offenders were single parents who lived with family or in rental accommodation. A multisite study in the United States found that female offenders’ experience of traumatic events related to family dysfunction, interpersonal violence, and external events predicted mental health problems including posttraumatic stress disorder (PTSD), major depression, bipolar disorder, and substance abuse (Green et al., 2016).

One attribute that both imprisoned men and women share is an increased prevalence of self-reported TBI (Shiroma, Ferguson, & Pickelsimer, 2010). Not only is the prevalence of TBI higher among incarcerated populations, TBI can also be a predictor of adverse outcomes in later life. For example, van Vliet-Ruissen, McKinlay, and Taylor (2014) reported that women with a history of TBI had an increased risk of substance abuse and mental health issues. Moreover, TBI history was associated with greater risk of criminal offending, and the risk increased with multiple TBIs (van Vliet-Ruissen et al., 2014). Corrigan and Deutschle (2009) reported that individuals who suffered a TBI in childhood or adolescence were twice as likely to suffer from mental health issues in adulthood when compared with the general population. TBI was also correlated highly with the misuse of drugs and alcohol. Participants with multiple TBI events indicated they started using drugs and alcohol, on average, 5 years earlier than participants with no TBI (Corrigan & Deutschle, 2009). According to cohort data analyzed by McKinlay, Corrigan, Horwood, and Fergusson (2014), preinjury risk factors in young children include gender (being male), a negative maternal parenting style, adverse life events, and depressive symptoms. While more prevalent among males, TBI is also a frequent event for females, particularly among more vulnerable populations (van Vliet-Ruissen et al., 2014).

Development of a mental illness following a TBI is common, with depression reported to occur in 22% to 50% of those with a history of TBI (Underhill et al., 2003). This is extremely high compared with the prevalence of depression in the general adult population of 9.5% (Underhill et al., 2003). Scott et al. (2015) found that females who had experienced a TBI were more likely to report a major depressive disorder than males who had experienced a TBI. This difference was significant in a group with moderate/severe injuries.

It is known from previous research that male offenders have a higher rate of TBI than the general public (Saunders et al., 2009). It is also known that people who suffer from TBI present with higher levels of depression, anxiety, and sleep difficulties (Albicini & McKinlay, 2015). Therefore, research unsurprisingly shows that incarcerated offenders also show a high level of mental health and sleep quality issues (McKinlay & Albicini, 2016). However, most of the existing research focuses almost exclusively on male offenders, and very few studies have investigated the extent to which incarcerated women are affected.

TBI is a high prevalence injury that is associated with deficits in cognition and inhibitory control and increased psychosocial problems and relationship dysfunction. However, there is little information regarding how TBI specifically affects offending pathways for women. Because TBI decreases inhibitory control and increases relationship dysfunction, a history of TBI needs to be considered in the implementation of effective treatment. The goal of the present research was to study the prevalence, association with mental health issues, and effect of age at first TBI among a sample of female inmates from Christchurch Women’s Prison (CWP) in New Zealand. Specifically, we predicted that (a) TBI would be highly prevalent among incarcerated females, (b) mental health problems (such as depression, anxiety, and stress) would correlate strongly with incidence of TBI, and (c) participants who experienced their first TBI at a young age would present with higher levels of mental health problems than those with first injury at a later age.

Method

Participants

All participants were recruited from CWP which is one of three women’s prisons in New Zealand and is the only one located in the South Island. The facility has a capacity for 140 inmates classified minimum through to high security. At the time of the study, 82 women were housed in CWP.

Offenders who were currently incarcerated at CWP in May 2014 were recruited by researchers through a short presentation to each of the security wings. During the presentation, the women were told that both those with and without a known brain injury were required for the study. They were then given the opportunity to sign up with the understanding they would be called individually to speak with a researcher at a later date. Of the 82 who were incarcerated, 38 agreed to participate (46.3%). Table 1 shows the injury characteristics of the women who participated in the study.

Table 1.

Prevalence of Traumatic Brain Injury in Participants.

Participant Characteristic	n (%)
Number of participants with
Multiple injuries	n = 30 (78.9%)
Single injury	n = 6 (15.8%)
No injury	n = 2 (5.3%)
Total number of injuries	n = 94
Age at time of first injury	M = 12 years 8 months (range = 2-34 years)
Highest level of severity
Moderate/severe	n = 8 (22.2%)

Measures

Ohio State University TBI Identification Method–Short Form (OSU-TBI-ID)

The OSU-TBI-ID was used to determine lifetime history of TBI and the severity of the injuries. Test–retest reliability for this scale ranges from .71 to .91 (Bogner & Corrigan, 2009). The OSU-TBI-ID contains five questions in total. Initial questions focus on whether the individual has experienced a TBI, for example, “Have you ever been hospitalized or treated in an emergency room following an injury to your head or neck? Think about any childhood injuries you remember or were told about.” Additional questions ask about potential mode of injury. For example, “Have you ever had a head or neck injury in a car accident or from some other moving vehicle accident?” Each of the five questions is presented in a yes/no format. If the participant answered yes to any of the questions, further details are obtained including length of blackouts and the age of the participant when the injury occurred.

The Achenbach System of Empirically Based Assessment (ASEBA)–Adult Behavior Checklist

The ASEBA–Adult Behavior Checklist (Achenbach, Dumenci, & Rescorla, 2003) is a self-report questionnaire with 126 questions that focus on a range of different mental health issues. Test–retest reliability for this scale ranges from .88 to .94 and internal consistency from .78 to .85 (Achenbach et al., 2003). Questions in the scale are formatted as statements, and the participant is asked to decide how true each statement is using a 3-point scale ranging from 0 to 2, with 0 indicating “not true” and 2 indicating “very true or often true.” Responses to items are summed for different subscales and evaluated as within normal or clinical ranges according to the Diagnostic and Statistical Manual of Mental Disorders (4th ed.; DSM-IV; American Psychiatric Association, 1994) (Achenbach et al., 2003). Subscale scores are then summed and standardized depending on participants’ age to give an overall score that will fall into the normal or clinical range.

Pittsburgh Sleep Quality Index (PSQI)

The PSQI (Buysse, Reynolds, Monk, Berman, & Kupfer, 1989) is a self-report questionnaire used to determine the sleep quality of participants over the last month. Buysse et al. (1989) reported that a global PSQI had test–retest reliability of .87. Buysse et al. stated that a PSQI global score >5 produced a sensitivity of 98.7 and specificity of 84.4 as a marker for sleep disturbances in distinguishing good and poor sleepers. Questions were answered using the following scale: 0 = not during the past month to 3 = 3 or more times a week. The PSQI has subscales for sleep quality and overall enthusiasm throughout the day. Subscale raw scores were converted into a standardized score ranging from 0 to 21. A score of 5 or less is associated with good sleep quality, and scores greater than 5 are associated with poor sleep quality. As shown in Table 2, the mean for our overall sample was 10.52 (SD = 4.85).

Table 2.

Average Scores for the DASS-21 and PSQI, and Level of Severity for Different Subscales.

Scale and subscales	M (SD)	n	%
DASS-21
Depression	5.70 (4.46)
Nonclinical Range		24	65.0
Clinical Range		12	35.0
Anxiety	6.22 (5.02)
Nonclinical Range		19	51.0
Clinical Range		17	49.0
Stress	7.54 (5.51)
Nonclinical Range		24	65.0
Clinical Range		12	35.0
PSQI
Sleep Quality	10.51 (4.85)
Poor		29	78.0
Good		8	22.0

Note. DASS = Depression, Anxiety and Stress Scale; PSQI = Pittsburgh Sleep Quality Index.

Depression, Anxiety and Stress Scale (DASS-21)

The DASS-21 (Grennan & Woodhams, 2007) consists of 21 statements grouped into three subscales of seven questions each. Participants were asked to rate each statement using a 4-point scale with 0 = did not apply to me at all and 3 = applied to me very much or most of the time, depending on their experience of the past week. Scores for each subscale can range from 0 to 21, with higher scores indicating greater levels of depression, anxiety, and stress. The DASS-21 has demonstrated excellent test–retest reliability and consistency in clinical and nonclinical samples (Antony, Bieling, Cox, Enns, & Swinson, 1998; Henry & Crawford, 2005) and an offender group (Grennan & Woodhams, 2007). Internal consistencies for the depression, anxiety, and stress scales in the present sample were .84, .83, and .90, respectively. As shown in Table 2, the mean for our overall sample was as follows: 5.70 (SD = 4.46) for depression, 6.22 (SD = 5.02) for anxiety, and 7.54 (SD = 5.51) for stress.

Wechsler Abbreviated Scale of Intelligence (WASI)–Vocabulary and Matrix Reasoning

Two scales (Vocabulary and Matrix Reasoning) from the WASI were used (The Psychological Corporation, 1999). Participants were first tested on receptive language skills. Answers given by participants were scored from 0 to 2, depending on the level of understanding. The test was discontinued after five consecutive zeros were scored. The score was added up, and the raw score was standardized, so that M = 10 and SD = 3. The matrix-reasoning test required the participants to choose the missing piece of a pattern. Participants were given two practice examples in case the verbal instructions were unclear. Correct answers were worth one point while incorrect answers were worth zero. The puzzles were stopped after a participant received four consecutive zeros or four zeros in the last five puzzles. The standardized score was calculated the same way as the vocabulary test. The scores from these two measures were converted to individual IQ scores for each participant using the process outlined in the manual. The WASI has an average reliability coefficient of .98 to .96, test–retest reliability between .92 and .88, and interrater reliability between .98 and .99 (The Psychological Corporation, 1999). Average IQ for our sample as measured by the WASI was 86 (SD = 13.28, range = 55-115).

To evaluate the impact of age at TBI occurrence on outcomes, data from participants were split into those who experienced first injury 0 to 9 years of age and those who experienced first injury at 10+ years of age. Previous research that has stratified age at first injury suggests that early TBI is associated with more severe outcomes compared with TBI that occurs in middle childhood (McKinlay, Dalrymple-Alford, Horwood, & Fergusson, 2002).

Procedure and Design

Approval was obtained from the University of Canterbury’s Human Ethics Committee, Reference Number HEC 2013/30, and the Department of Corrections. Participants were told at the beginning of the interview session that they were able to stop the session at any time and withdraw their data if they chose to do so; completion of the session was considered informed consent. The session consisted of a semistructured interview with one of two researchers. This interview took place in the interview rooms at CWP. Participants were told that the information collected was confidential, that their name would not be associated in any way, and that the data would not be shared with nonessential researchers and staff members. Each interview took approximately 45 to 55 min. Once the questionnaires and tests were complete, each participant was given a debriefing sheet which explained how their responses would be used and asked if they had any questions or concerns about the study. Participants were also encouraged to speak to the Prison Chaplain if they experienced any problems or distress.

Results

Demographics

Of the 82 incarcerated women, 38 (46%) agreed to participate in the study. The average age of participants was 33 years (SD = 13.24, range = 17-71) and the average IQ as measured by the WASI was 86 (SD = 13.28, range = 55-115), which means that compared with the general population mean (M = 100, SD = 15), the level of cognitive functioning for the participants in this study was in the “low average range.”

TBI events were categorised based on self-report of the participant. Table 1 displays the level of severity for the TBIs reported, and the number of participants who reported more than one TBI. Moderate/severe injuries were classified as those where loss of consciousness occurred for a period of time exceeding 30 min. The mean age of the participants at first injury was 13 years, with the majority of participants reporting a mild TBI (n = 23). However, for five individuals, there was insufficient information to determine either the age at first injury or the injury severity. Overall prevalence rate of TBI in this sample was 94.7% (36 of 38 presented with at least one TBI). The most frequent modes of injury were falls (n = 27), motor crashes (n = 23), and fights (n = 19), which accounted for 74.5% of all injury events. Domestic violence was reported in eight (8.5%) cases and abuse by parent in three (3.2%) cases. Fourteen of the injuries were due to other causes such as unintentionally banging head on an object (14.9%).

Mental Health Issues

Table 2 shows the average scores for the DASS-21 subscales (Depression, Anxiety, and Stress) and the average score of the PSQI for the sample. It also gives the number and percentage of participants who fell into the nonclinical (normal to mild) and clinical (moderate to extremely severe) ranges for each of the DASS-21 subscales, and the number of participants who reported scores of <5 (good sleep) and >5 (bad sleep) on the PSQI.

The mean scores for the current sample fell in different clinical categories depending on the subscale. The mean depression and stress scores (5.70 and 7.54, respectively) were nonclinical (cutoffs = 6 and 9), whereas the mean anxiety score (6.22) was in the clinical range (cutoff = 5). The majority of participants reported poor sleep quality (78%).

Table 3 shows the average score for subscales of the ASEBA. Averages for all subscales except rule-breaking behavior and antisocial behavior fell into the nonclinical range. However, to obtain more information, Table 3 also shows the number and percentage of participants that fell into the clinical and nonclinical range for each subscale. As can be seen, 73.0% of individuals reported rule-breaking behavior in the clinical range, 41.0% of individuals reported antisocial behavior, and 35.0% of individuals reported anxious/depressed, depressive, and/or avoidant behaviors in the clinical range.

Table 3.

Average Scores for the ASEBA Subscales and Number of Participants in Clinical and Nonclinical Range.

Subscale	M (SD)	n	%
Anxiety Problems	7.16 (3.35)
Clinical Range		8	22.0
Nonclinical Range		29	78.0
Depressive Problems	10.81 (6.21)
Clinical Range		13	35.0
Nonclinical Range		24	65.0
Avoidant Behavior	5.11 (3.61)
Clinical Range		13	35.0
Nonclinical Range		24	65.0
Antisocial Behavior	12.89 (8.10)
Clinical Range		15	41.0
Nonclinical Range		22	59.0
Attention Problems	12.19 (6.94)
Clinical Range		11	30.0
Nonclinical Range		26	70.0
Rule-Breaking Behavior	10.86 (5.88)
Clinical Range		27	73.0
Nonclinical Range		10	27.0
Anxious/Depressed	15.08 (8.95)
Clinical Range		13	35.0
Nonclinical Range		24	65.0
Thought Problems	6.46 (4.87)
Clinical Range		15	41.0
Nonclinical Range		22	59.0
Intrusive Thoughts	2.70 (2.78)
Clinical Range		3	8.0
Nonclinical Range		34	92.0

Note. ASEBA = Achenbach System of Empirically Based Assessment.

Table 4 shows outcomes when the participants were split by age of first injury. Five participants were excluded due to missing information. Five variables were significantly different between individuals who experienced their first injury before 9 years (n = 13) and those who experienced a TBI after 9 years (n = 18): anxiety measured in the ASEBA, t(29) = 3.34, p = .002, d = 1.24; anxious/depressed feelings, t(29) = 2.14, p = .041, d = 0.79; thought problems, t(29) = 2.39, p = .024, d = 0.89; anxiety measured by the DASS-21, t(29) = 2.19, p = .037, d = 0.81; and stress, t(29) = 2.32, p = .028, d = 0.86. Of these, only the ASEBA-Anxiety remained significant after correcting for multiple comparisons (Bonferroni).

Table 4.

Outcomes for Participants According to Age of First Injury.

Scale	Group M^d Injury ≤ 9 yearsInjury >9 years	t score^a	p value	Effect size (Cohen’s d)
ASEBA
Anxiety	9.465.78	3.343	.002 ^b	1.24
Depressive	12.859.83	1.322	.196	0.49
Avoidant Behavior	6.385.50	0.690	.496	0.26
Antisocial Behavior	15.1511.89	1.044	.305	0.39
Attention Problems	13.6211.33	0.871	.391	0.32
Rule-Breaking Behavior	11.8510.06	0.776	.444	0.29
Anxious/Depressed	19.2312.56	2.140	.041	0.79
Thought Problems	8.924.89	2.388	.024	0.89
Intrusive Thoughts^c	4.002.06	1.727	.089	0.78
PSQI	10.3811.89	−0.889	.381	0.33
IQ score	82.3187.56	−1.139	.264	0.42
DASS-21
Anxiety	8.624.72	2.189	.037	0.81
Stress	10.315.94	2.315	.028	0.86
Depression	6.155.78	0.226	.823	0.08

Note. ASEBA = Achenbach System of Empirically Based Assessment; PSQI = Pittsburgh Sleep Quality Index; DASS = Depression, Anxiety and Stress Scale.

Boldface t-values indicate p < .05.

Indicates significant after Bonferroni correction.

df = 19.427.

df = 29; group is split into first injury before or after 9 years of age.

Discussion

Given that the large majority of studies with offenders have used male or unspecified populations, there is a need for research with female offenders (Bennett, Farrington, & Huesmann, 2005). A major goal of this study was to determine whether incarcerated women had an increased risk of TBI compared with the general population. The results showed that nearly all participants (94.7%) reported at least one TBI in their lifetime, with only two reporting no such injuries. Multiple injuries were common; 83% of individuals who reported a TBI said they had suffered more than one such injury event, with a total of 96 separate TBI injuries reported by the sample.

The high prevalence of TBI in incarcerated populations is not uncommon; estimates of between 25% and 87% of the jail and prison population in the United States have been reported (Farrer & Hedges, 2011). These figures are generally based on male populations or combined male and female populations. The current sample’s TBI incidence rate is even higher at 94.7%. Using a female population, Brewer-Smyth, Burgess, and Shults (2004) reported a substantially lower TBI prevalence (42.5%). However, Brewer-Smyth et al. studied only individuals who reported TBI with a loss of consciousness, whereas we included all self-reported TBI events. TBI without loss of consciousness occurs at far higher levels than TBI with loss of consciousness. Therefore, the prevalence in this current study is likely to more accurately represent prevalence of TBI in a female prison population.

Domestic violence/abuse accounted for only 11.7% of the total TBI events. This relatively low number must be viewed in relation to the context in which the questions regarding domestic violence/abuse were asked. The women were asked to report all forms of abuse that had resulted in a TBI event. It is likely that participants had experienced physical and emotional abuse that had not been a result of a TBI event. Despite this, 26.3% of women (10 of 38) reported that they had experienced at least one TBI as a direct result of being assaulted by a parent or partner. This is consistent with previous research reporting high levels of physical abuse among incarcerated women (Bloom, Owen, & Covington, 2003), and also points to the importance of a physical abuse history in terms of an increased likelihood of cognitive and mental health deficits associated with a TBI event (Scott et al., 2015).

Most participants from the current study fell into the nonclinical range for both depression and stress. However, there was an increased risk of clinically significant anxiety, and the majority of the women (78%) reported sleep problems. As shown in Tables 5 and 6, the current sample showed significantly higher levels of mood disorders than a nonclinical sample in Antony et al. (1998). When compared with a sample of male offenders (Kavanagh, Rowe, Hersch, Barnett, & Reznik, 2010), participants showed similar levels of anxiety and stress, but significantly greater levels of depression. These results suggest that incarcerated women are similar to male offender populations in terms of higher levels of depression, anxiety, and stress, and that the prevalence of these mental health problems is higher than would be expected in the general population.

Table 5.

Comparison Between Study Participants and Previous Research Using the DASS-21.

Author(s)	Population	n	Subscale	M (SD)	t-value (critical t-value)	Effect size (Cohen’s d)
Antony, Bieling, Cox, Enns, and Swinson (1998)	Nonclinical volunteers	49	Depression	2.12 (3.64)	4.10* (1.989)	−0.89
			Anxiety	1.22 (1.77)	6.47* (1.989)	−1.41
			Stress	3.51 (3.78)	4.02* (1.989)	−0.88
Kavanagh, Rowe, Hersch, Barnett, and Reznik (2010)	Custodial sample	30	Depression	8.48 (5.30)	2.31* (1.997)	−0.57
			Anxiety	7.76 (5.93)	1.14 (−1.997)	−0.28
			Stress	9.72 (5.68)	1.57 (−1.997)	−0.39

Note. DASS = Depression, Anxiety and Stress Scale.

Significant t-values at p < .05. All t tests are two-tailed.

Table 6.

Comparison Between Participants in the Current Study and Previous Research Using the PSQI.

Author(s)	Population	n	M (SD)	t-value (critical t-value)	Effect size (Cohen’s d)
Elger (2009)	Inmate sample
	Complained of insomnia	77	12.50 (4.00)	2.31* (1.981)	0.44
	No complaint	61	3.20 (2.00)	−10.43* (1.985)	−2.13
Knutson, Rathouz, Yan, Liu, and Lauderdale (2006)	General population
	Full sample	610	5.70 (3.10)	8.82* (1.963)	−1.49
	White female subsample	187	5.10 (2.80)	9.37* (1.971)	−1.69

Note. PSQI = Pittsburgh Sleep Quality Index.

Significant t-values at p < .05. All t tests are two-tailed.

Importantly, timing of first TBI had an impact on outcomes. Individuals who reported their first TBI occurring before the age of 9 were significantly more impaired than those who indicated their first injury occurred after the age of 9 in a number of areas, including anxiety, thought problems, and stress. This is consistent with previous research which indicates early injury is associated with more persistent outcomes (Hessen, Nestvold, & Anderson, 2007; McKinlay, 2010; McKinlay et al., 2002) due to the vulnerability of the developing brain (Anderson, Damasio, Tranel, & Damasio, 2000). Females with a history of TBI in the general population have higher rates of internalizing problems, including increased anxiety (Scott et al., 2015). Internalizing problems associated with early TBI may negatively affect the development of effective coping strategies and functional relationships and possibly increase the risk of dysfunctional relationships (Craparo, Gori, Petruccelli, Cannella, & Simonelli, 2014). Furthermore, this prevalence of internalizing problems following TBI has implications for how rehabilitation of female offender populations is targeted.

There are several limitations of the present study that should be acknowledged. The first of these was mentioned earlier, that is, the number of participants from the population willing to participate. Of the 82 offenders who were residing at CWP at the time of data collection, 38 chose to take part which may have biased the results. It is possible that those who chose to be part of the study were those who had a known TBI, while those who chose not to participate were less likely to have had a TBI. Nonetheless, even if all the nonrespondents were negative cases, more than 46% of the population would have experienced a TBI event. However, there was no reason to suspect that the individuals who did not participate differed from those who did. Another limitation was that we relied on self-report to identify injury occurrences rather than objective data such as the Glasgow Coma Scale or medical records. Recent data suggest that only 50% of hospitalized TBI injuries will be recalled (McKinlay, Horwood, & Fergusson, 2016). Our study focused on lifetime prevalence of TBI and mental health among incarcerated women. However, TBI is also associated with deficits in executive function and memory; more detailed information about different types of cognitive deficits would have been useful in identifying gender-specific difficulties for this population. The use of less well-known measures such as the ASEBA limits the ability of the data to be compared with previous literature.

The lack of control group is another limitation to this research. While it is possible to compare the current participants among themselves dependent on age of first injury, it would be just as beneficial to compare the participants with a group with TBI from the community. A control group such as this could help to answer additional questions, such as the degree of mental health problems that are associated with TBI and with incarceration.

Few studies have focused on incarcerated females, but the present study demonstrates why such research is important and has both theoretical and practical implications. There is a definable neurological basis for the deficits in emotion regulation, aggression, and impulse control in individuals with a history of TBI (Bufkin & Luttrell, 2005). Because of impulse control difficulties, TBI has been associated with high incidence of drug and alcohol abuse (McKinlay et al., 2014). A history of TBI among incarcerated females is likely to be associated with increased anxiety and a decreased ability to inhibit impulsive behavior and will likely be associated with difficulties with interpersonal relationships. Perhaps more importantly, TBI, even injuries thought to be relatively mild, has been associated with long-term mental health difficulties. Females have been found to have an increased risk of internalizing problems such as depression and anxiety, whereas males are more likely to report externalizing problems such as aggressive behaviors (Scott et al., 2015; van Vliet-Ruissen et al., 2014). Mood disorders are likely to affect rehabilitation of incarcerated women and result in reduced capacity to engage in treatment or rehabilitative input.

Knowledge of a TBI history may provide a greater understanding regarding pathways to offending and also the steps required to successfully reduce reoffending. This research found that the prevalence of TBI among incarcerated females is high and is associated with other negative outcomes such as mental health and sleep problems, particularly if the injury occurred early in life. Given the high prevalence of TBI within prison populations, it may be that programs aimed at reducing repeat offending need to be tailored for those who present with a TBI. This current study also focused on prevalence and mental health outcomes, but processing speed and executive function deficits are more vulnerable to the effects of TBI. Future research is required to outline more explicitly the cognitive deficits among incarcerated women.

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) received no financial support for the research, authorship, and/or publication of this article.

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