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Utility of the Brain Injury Screening
Index in Identifying Female Prisoners
with a Traumatic Brain Injury and
Associated Cognitive Impairment
Michelle O’ Sullivan
Submitted for the Degree of
Doctor of Psychology(Clinical Psychology)
School of PsychologyFaculty of Arts and Human Sciences
University of SurreyGuildford, SurreyUnited Kingdom
October 2015
1
Abstract
An estimated 60.25% of offenders have a history of traumatic brain injury (TBI).
There is currently no established valid or reliable screening tool for identifying
female prisoners with a TBI and associated cognitive impairment available in the
UK. Using a cross-sectional design, this study aimed to investigate the retest
reliability and construct validity of the Brain Injury Screening Index (BISI).
Convergent validity was explored using self-report measures of mood and
neurodisability, as well as a battery of neuropsychological assessments of
cognitive functioning. Of a planned sample of 73 participants, preliminary data
from 23 participants has been analysed. 69.56% of participants were identified as
having a history of TBI, with a mean of 2.09 TBIs. Intraclass correlation
coefficients reached statistical significance for six of 10 identified key clinical
indicators on the BISI. The BISI variables did not reach statistically significant
convergence with most of the test battery. Two of the four BISI summary
variables demonstrated correlations in the hypothesised directions across the full
assessment battery, however only one BISI variable reached statistical
significance with one subscale in the battery. Analyses provide support for
further investigation into the construct validity and retest reliability of the BISI
with a larger sample. The implications of these findings, particularly in refining
the BISI, and future research and practice are considered.
2
Acknowledgements
Thank you cannot begin to express the gratitude I feel towards the copious amounts of
people who got me to the end of this three years, but it’s probably not a bad place to
start.
Firstly, I would like to thank each person who I have had the pleasure to work with
clinically and took the time to participate in my research. I have witnessed so much
strength and determination in the face of adversity in each of you. I count myself
honoured to have had the chance to learn from you and be part of your stories of
recovery.
I have had the opportunity to learn from some of the most amazing clinical supervisors
over the last three years. A few in particular have shaped my personal and professional
identity so much. Dr Chris Hall taught me patience (albeit a lesson I am still learning!)
and how the most powerful respect is commanded with a quiet confidence. Dr Julie
Nixon taught me the clinical power of personality; how authenticity is one of our most
valuable assets; and how supporting people to be the best they can be extends beyond
our clients, to our team and communities. Dr Oliver Sindall taught me that it is alright to
make mistakes, and that vulnerability is not only not a bad thing, but an asset in the
right context. Dr Manveer Kaur taught me self-compassion and rebuilt my sense of
confidence and competence when my self-belief as a clinical psychologist was at its
lowest. You have all been so much more than supervisors to me and given me so much
to aspire to.
I would like to thank the team at the Disabilities Trust: my field supervisor Prof Mike
Oddy, Dr Sara da Silva Ramos, and Deborah Fortescue, for their unwavering support
throughout my Major Research Project. They enabled me to turn a small idea into a
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rewarding project, that despite three years of hard work and many pitfalls, I remain
passionate about. Ideas are easy to come by, it is the instigators and facilitators that are
invaluable. I would like to thank my University research supervisors Dr Emily Glorney
and Prof Annette Sterr for their support throughout the three years. I am particularly
indebted to Emily who continued to supervise the project after she left the University.
To have such continued support and commitment during the three years meant the
world to me. I would like to thank Dr Laura Simonds, who continued to act as my
research tutor and a link to the clinical team, even when the role no longer existed. Not
only did she provide me with containment and guidance at times of difficulty, but she
modelled for me what I can only hope to provide to future clinical trainees in my career.
I also owe so much thanks to Prof Chris Fife-Schaw who never seemed phased by the
barrage of stats questions I sent his way. I would like to thank all the team at the
participating prison, particularly all the prison officers who made the day to day running
of the project possible – I would still be wandering the corridors looking for a room
right now if it was not for them. I would also like to extend my appreciation to Elaine
Cameron and Sarah Disspain, who took the risk of supporting the project and enabling
its setup, and gave so much time to thinking about how the research design could fit the
prison regime, and balancing the ethics and the practicalities of the procedures.
I would like to thank my clinical tutor, Louise Deacon, and Honorary Clinical Tutor,
Fiona Goodwin. You have been breaths of reflective fresh air amidst administrative
smog.
Without my family I would never have made it this far. You instilled in me core values
of education, compassion for others, and responsibility. The bedtime stories my father
always read me gave me the power of language and knowledge. Witnessing the
4
influence of my mothers’ warmth on others made me believe in the power of kindness.
Finally, Cohort 41, you turned England from just a place I was living, to a home. You
have given me some of the best memories of my life, made my belly ache with laughter,
and brought me back to life with hugs. You are all wonderful clinical psychologists, so
much so I’m expecting to get an awful bill in the post any day now.
5
Contents
MRP Empirical Paper (including Abstract) p7
MRP Empirical Paper Appendices p77
MRP Proposal (without Appendices) p203
MRP Literature Review (with Appendices) p215
Clinical Experience Précis p264
Summary of Assessments Table p268
6
Utility of the Brain Injury Screening Index in Identifying Female
Prisoners with a Traumatic Brain Injury and Associated Cognitive
Impairment
An estimated 60.25% of offenders have a history of traumatic brain injury (TBI).
There is currently no established valid or reliable screening tool for identifying
female prisoners with a TBI and associated cognitive impairment available in the
UK. Using a cross-sectional design, this study aimed to investigate the retest
reliability and construct validity of the Brain Injury Screening Index (BISI).
Convergent validity was explored using self-report measures of mood and
neurodisability, as well as a battery of neuropsychological assessments of
cognitive functioning. Of a planned sample of 73 participants, preliminary data
from 23 participants has been analysed. 69.56% of participants were identified as
having a history of TBI, with a mean of 2.09 TBIs. Intraclass correlation
coefficients reached statistical significance for six of 10 identified key clinical
indicators on the BISI. The BISI variables did not reach statistically significant
convergence with most of the test battery. Two of the four BISI summary
variables demonstrated correlations in the hypothesised directions across the full
assessment battery, however only one BISI variable reached statistical
significance with one subscale in the battery. Analyses provide support for
further investigation into the construct validity and retest reliability of the BISI
with a larger sample. The implications of these findings, particularly in refining
the BISI, and future research and practice are considered.
Keywords: traumatic brain injury; offenders; prisoners; screening; reliability;
validity
Introduction
Traumatic Brain Injury
Traumatic brain injury (TBI) is defined as “an alteration in brain function, or other
evidence of brain pathology, caused by an external force” (Menon et al., 2010),
capturing the range of presentations which fit under the TBI diagnostic umbrella,
including loss of or decreased consciousness, any loss of memory, neurological deficits,
and any alteration in mental state e.g. confusion (Menon et al., 2010). TBI is the most
common form of acquired brain injury (ABI, see Figure 1; Fleminger & Ponsford,
2005), with an estimated prevalence of 8.5% (Silver et al., 2001) across all levels of
severity; however, rates may overlook milder TBI due to reliance on medical records
(Tennant, 2005) and associated diagnostic and selection biases (Feigin et al., 2013).
Figure 1. Types of Brain Injury
TBI severity traditionally has been classified by scores on the Glasgow Coma Scale
(GCS; World Health Organization, 2006). Other commonly used measures include post-
traumatic amnesia (PTA) and length of loss of consciousness (LOC; Sherer et al.,
2008). Table 1 summarises typical cut-offs used for differentiating mild, moderate and
severe TBI. Absence of a uniform classification system makes comparison across
studies difficult (Corrigan et al., 2010).
Most TBIs are mild (Donnelly et al., 2011). Reports of problematic sequelae following
mild TBI (mTBI) range from only 10% (Albicini & McKinlay, 2014) to 42% (Konrad
et al., 2011). Not all blows to the head result in a TBI, and not all TBIs result in
functional difficulties. However, research suggests that multiple mTBIs can have a
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Brain injury
Congenital brain injury
Acquired brain injury
Traumatic Brain Injury
Closed head injury
Open head injury
Non Traumatic
Brain Injury
cumulative effect, with similar cognitive and behavioural profiles to more severe
TBI(Collins, Grindel, Lovell, & et al., 1999; Diamond et al., 2007; Miller et al., 2013).
While moderate to severe TBIs tend to be self-evident, deficits from mTBIs can be
easily overlooked (Donnelly et al., 2011).
Table 1. TBI classifications systems
GCS score (World
Health Organization,
2006)
PTA (Lezak,
2004)
LOC (Greenwald et al.,
2003)
Mild TBI 13-15 < 1 hour <30 minutes
Moderate TBI 9-12 1-24 hours ≥ 30 minutes ≤ 6 hours
Severe TBI 3-8 > 24 hours > 6 hours
Up to twice the rate of TBI has been found in males than females in the general
population (Hillbom & Holm, 1986; Hirtz et al., 2007). The apparent protective effect
of female gender appears attenuated in specific populations, including those with
substance use disorder (Felde et al., 2006) and prisoners (Brain Injury Association of
Wyoming, 2008; Ferguson et al., 2012). TBI risk in females appears more pronounced
with mTBI, e.g. Diamond, Harzke, Magalett, Cummins and Frankowski (2007) found
that 54.7% of females in a prison population self-reported TBI with no LOC in
comparison to 40% of males. This fell to 35.6% of females in comparison to 47.8% of
males with LOC of less than one hour. Differences may be attributable to different
gender-related behavioural patterns, e.g. decreased likelihood of reporting mTBIs. TBI
in females may be underestimated due to unreported domestic violence (Valera &
Berenbaum, 2003). Due to the nature of domestic violence it is difficult to get an
accurate prevalence rate of TBI, with rates varying from 30-74% (Kwako et al., 2011).
Females with a TBI are more likely to report elevated psychological distress, past year
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suicidal ideation, school bullying, drinking, and smoking (Colantonio et al., 2007; Ilie et
al., 2014). Meta-analysis has found that females tend to have worse outcomes after TBI
than males across all TBI types (Farace & Alves, 2000).
TBI in Offenders
A recent meta-analysis (Shiroma et al., 2010a) places TBI prevalence in offender
populations at 60.25% (95% CI: 48-72%), with a male and female prevalence estimate
of 64.41% (95% CI: 53.30-75.53%) and 69.98% (95% CI: 50.18-89.79%) respectively.
Once TBI definition was limited to LOC, excluding milder TBIs, males demonstrated a
higher prevalence than females (59.31% vs. 55.28%). The decrease in prevalence once
limited by LOC supports the prevalence of mTBIs in females. Along with a higher
prevalence than in the general population, prisoners are at higher risk of neurodisability
following TBI, by virtue of reduced cognitive reserve from exposure to factors such
substance use and mental health difficulties (Ropacki & Elias, 2003).
TBI is a complex condition that can result in an array of cognitive, emotional, physical
and behavioural sequelae. The Swedish population registers’ research found that
individuals with TBI have a significantly increased risk of committing a violent crime
(Fazel et al., 2011). Even mTBI in childhood is associated with an array of long-term
negative outcomes, including increased risk of arrest, violent offences, and property
offences (McKinlay, 2014). McKinlay et al. (2014b) found TBI severity and age of
injury to be significant predictors of later offending behaviour; with substance use
mediating the relationship between childhood TBI and later offending (McKinlay,
Corrigan, Horwood, & Fergusson, 2014a). The Repairing Shattered Lives report
emphasised the need for research examining causes and consequences of TBI in female
offenders specifically (Williams, 2012).
10
The field of social neuroscience has begun marrying the previously segregated
understandings of brain development and social behaviour. Damasio’s somatic marker
hypothesis (1994) provides insight into offending behaviour by taking a systems-level
neurological approach with the relationship between motivational and affective
processes, and the coordination of complex reasoning and action. For instance,
individuals with ventromedial prefrontal cortex (vmPFC) injuries demonstrate missing
anticipatory skin conductance responses, which leads to difficulties using the emotional
consequences of past experiences to guide behaviour (Taber-Thomas & Tranel, 2012).
Somatic markers that sit in the vmPFC are essential for normal moral cognition under
conditions of ambiguity, uncertainty and conflict, providing a representation of how the
future self would feel after performing an action (Taber-Thomas & Tranel, 2012). Loss
of somatic markers can manifest itself behaviourally in lack of concern for others,
socially inappropriate behaviour, reduced guilt and shame, and increased aggression
(Anderson et al., 1999; Beer, John, Scabini, & Knight, 2006; Damasio, Tranel, &
Damasio, 1990). The consequences of somatic marker loss may be more pronounced
amongst offenders when contextualised within sociodemographic factors, such as living
in environments with high rates of antisocial behaviour which could increase the
frequency with which individuals are faced with of uncertainty and conflict that are
demanding of moral cognition.
Yeates et al.’s (2012) integrative model of the social outcomes of childhood brain
disorder provides a holistic understanding of the role of social cognition, affect
regulation, factors relating to the neurological insult, and environmental factors, on
social competence. For instance, deficits in social information processing, such as
mentalisation, cue interpretation and outcome evaluation, contribute to poor social
adjustment (Parker, Rubin, Erath, Wojslawowicz, & Buskirk, 2006; Rubin, Bukowski,
11
& Parker, 2006). Consequent antisocial behaviour may arise from choosing
instrumental over prosocial goals; misinterpretation of others’ intent; and generation of
fewer effective responses to social dilemmas (Yeates et al., 2012). Yeates et al. (2012)
emphasise how this can contribute to a negative developmental spiral with social
interactions and relationships, resulting in chronic social problems even if social
information processing improves following TBI, thereby possibly perpetuating
antisocial lifestyles.Without early intervention, individuals with TBI may pose a risk to
others, becoming involved in the criminal justice system (Brower & Price, 2001;
deSouza, 2003; Greve et al., 2001; Kreutzer et al., 1995; Kreutzer et al., 1991; Miller,
1999; Simpson et al., 1999). Once there, they may be more difficult to rehabilitate and
discharge, with services ill-equipped to address their needs. Hawley and Maden’s
(2003) study of TBI in medium secure units indicated that 41.6% of service users had a
history of TBI, and were significantly more difficult to discharge into the community
due to perceived greater risk of violence to others and self-harm. Research
demonstrating increased disciplinary incidents in prisoners with TBI (Merbitz et al.,
1995; Morrell et al., 1998; Shiroma et al., 2010b) suggests they may have increased
difficulty adapting to prison life due to cognitive and behavioural sequelae. For
instance, the somatic marker hypothesis (Damasio, 1994) indicates the vmPFC’s
involvement in the representation and monitoring of reward, highlighting potential
ineffectiveness of traditional behaviour management through contingencies which form
the backbone of the criminal justice system. This has implications for engagement in the
legal process, prison management, and post-discharge and release pathways (Jackson &
Hardy, 2011). Due to inadequate screening and identification of TBI, services are
unable to provide adapted rehabilitation. Under-identification perpetuates inadequate
resources, providing no incentive to fund appropriate interventions. Research in this
12
field is congruent with the Transforming Rehabilitation strategic business priorities
within the UK National Offender Management Service (NOMS; National Offender
Management Service, 2013) and may increase efficiency by informing programs to
reduce recidivism.
Screening for TBI
A valid TBI screen for female offenders is required to facilitate research and clinical
practice, enabling researchers to determine the prevalence of TBI in UK female
offenders, which is currently unknown. Screening is consistent with NOM’s Reducing
Prison Unit Costs strategic business priority by ensuring appropriate services are
commissioned and target the most appropriate offenders (NOMS, 2013), e.g. screening
can provide a cost-effective way of determining who is appropriate for referral to
limited and expensive resources such as neuropsychologists. A valid measure would
enable prisons to add TBI screening to established intake risk assessment procedures.
A clinically useful screen should capture frequency and severity of lifetime TBI, that
can help differentiate uncomplicated head injury from TBI (Diamond et al., 2007). One
difficulty with developing screens is whether the screen purpose is to assess for
exposure to any head injury, which reduces specificity and risks overburdening low
resourced services; or TBI with associated functional sequelae, which is difficult to
capture using self-report. TBI screens in military populations have acknowledged this
conflict, prioritising high sensitivity, compromising on specificity (Donnelly et al.,
2011); however with under-resourced prisons this compromise is less tenable.
There are currently no validated and reliable published screening tools for use with UK
female offenders. Research has begun to support the use of The Brain Injury Screening
Index (BISI; Pitman, Haddlesey, Ramos, Oddy, & Fortescue, 2014) with UK male
13
offenders, but has yet to be extended to females. Much research relies on instruments
developed for individual studies, with little consideration of reliability and validity, or
one to two item methods which underestimate TBI history (Diamond et al., 2007). Two
published screening tools have psychometric data available for use with prisoners,
including females; the Traumatic Brain Injury Questionnaire (TBIQ; Diamond et al.,
2007) and the Ohio State University TBI Identification Method (OSU TBI-ID; Bogner
& Corrigan, 2009). These measures have not been validated within a female UK prison
population. Indices on the OSU TBI-ID which require an estimate of mTBIs, relating to
episodes such as domestic violence, are unreliable (Bogner & Corrigan, 2009).
Therefore, this may be inappropriate for female prison populations. The TBIQ has a
similar layout to the BISI, however includes a symptoms checklist. The TBIQ has only
been validated against short rating scales, with research demonstrating that self-
assessment of cognitive functioning is not representative of cognitive functioning as
measured by objective neuropsychological assessment tools (French, Lange, & Brickell,
2014; Spencer, Drag, Walker, & Bieliauskas, 2010). Reduced insight is well
documented post-TBI (Ham et al., 2013). Self-report neurobehavioural measures
address this using of informant scales to corroborate data (Kreutzer, Marwitz, Seel, &
Devany Serio, 1996), however feasibility of informant scales with offenders is an issue,
e.g. informant scales are usually designed to be completed by family who are not
witness to the daily neurobehavioural presentation of prisoners. Self-report
neuropsychological sequelae tend to correlate highly with psychiatric rather than
cognitive constructs (Spencer et al., 2010). Discriminating between TBI sequelae and
other disorders has proven difficult, e.g., of the 100 symptoms identified in the Brain
Injury Screening Questionnaire, 79 are symptoms of affective or thought disorders
(Walker, Cole, Logan, & Corrigan, 2007). TBI severity and frequency is likely to yield
14
more reliable and valid indicators of TBI sequelae than self-report symptomology
(Donnelly et al., 2011). Screens should have enough questions to facilitate recall of past
TBIs (Diamond et al., 2007), whilst not over-including symptomatic items which have
poor discriminant value. Diamond et al.’s (2007) research indicates that interview
administered screens perform better than self-report checklists.
There is no agreed upon gold standard for the assessment of TBI sequelae by which to
compare screens. Clinical interview is frequently used as the gold standard criterion,
however this is an imperfect method (Albicini & McKinlay, 2014; Donnelly et al.,
2011). Neuropsychological assessments, an objective measure of cognitive functioning,
are valuable additions to post-TBI functioning assessments; however these are rarely
used in assessing the reliability and validity of TBI screens. The gold standard of
clinical interview needs to be bolstered with psychometric measures to evaluate the
most useful screens (Donnelly et al., 2011), particularly when medical records which
would be the strongest criterion measure of TBI, tend to be unavailable in offender
populations.
Aims and Hypotheses
Aims
(1) Explore the reliability and construct validity of the BISI for screening for history
of TBI.
Hypotheses
(1) Presence of TBI; the TBI Severity Index; the TBI Time Index; and the BISI
Global Score will be significantly positively correlated with scores obtained on
the self-report measures of mood and neurodisability.
15
(2) Presence of TBI; the TBI Severity Index; the TBI Time Index; and the BISI
Global Score will be significantly negatively correlated with neuropsychological
measures of cognitive functioning.
(3) The BISI will have statistically significant test-retest reliability intraclass
correlation coefficients (ICC) for all continuous variables examined.
(4) The BISI will have statistically significant test-retest reliability Kappa
coefficients for all binary variables examined.
Methods
Design
A quantitative correlational cross-sectional design using a semi-structured clinical
interview, clinical questionnaires, and neuropsychological measures, was employed.
Participants
The study was conducted at a UK closed women’s training prison, with an operational
capacity of 282. Participants were recruited from new prison receptions. A sample size
calculation for a correlational analysis based on the number of variables being
measured, an anticipated large effect size (Pitman et al., 2014), statistical power of .80
and type I error α of .0004 (Bonferroni correction for multiple comparisons), indicated
that 73 participants were required. Pitman et al.’s (2014) r of -.45 with an N of 189
yielded confidence intervals (CIs) of -.56 to -.33, therefore it was anticipated that for a
similar effect size, an N of 73 would yield CIs of -.62 to -.24. Charter (1999) warns of
such risk of imprecision in the estimation of r in reliability and validity studies with
small Ns, particularly under 400; however due to feasibility related to resource
limitations, and the preliminary nature of this research, a small N was deemed an
appropriate and necessary limitation. Inclusion criteria included prisoners over 18 years
16
of age, with an upper age limit of 80 in line with norms provided in the instruments
used. Exclusion criteria included acute symptoms of physical or mental illness.
Prisoners with a confirmed diagnosis of dyslexia, problems with literacy, inadequate
English fluency, or acquired a TBI in the last six months, were excluded due to measure
validity limitations. Participants with a learning disability (LD) were included unless
queries regarding capacity to consent were raised. Fifty-five prisoners were approached,
eleven of which were ineligible (Figure 2). Twenty-three of the remaining 44
participated, providing a response rate of 52%. Of the 23 participants, 16 self-reported a
TBI.
Participants ranged from 21 to 64 years of age (M = 38.74, SD = 12.73). Premorbid IQ
ranged from 66.50 to 112.30 (M = 88.74, SD = 11.57), while obtained IQ on the
Wechsler Abbreviated Scale of Intelligence-II (WASI-II) ranged from 67 to 126 (M =
95.00, SD = 15.23). The majority of participants identified as White British (69.60%).
Number of years spent in education ranged from 2 to 18 (M = 11.73, SD = 3.57).
Appendix II provides full sample demographics.
No significant correlations were found between the key BISI summary variables and
premorbid IQ, age, educational background, TOMM score, and alcohol use (Table 2).
No participant scored under the cut-off of 45 on the TOMM.
Figure 2. Recruitment flow
17
Table 2. Correlations between sample demographics & BISI summary variables
Correlations (point biserial) with TBI presence (N=23)
Variable Mean (SD) r Sig
Age 38.74 (12.73) -.17a .422
Premorbid IQ
(TOPF raw score)c
33.57 (12.73) .25 a .248
Years in education 11.73 (3.57) .26 a .221
Units of alcohol
consumed daily
26.66 (33.91) -.09 a .680
TOMM Trial 2 49.65 (1.07) .30b .161
Correlation with TBI Global Score (N=23)
Age
Premorbid IQ (TOPF raw score)
Years in education
Units of alcohol consumed daily
.39 a .063
-.11 a .614
-.36 a .083
.24 a .264
-.01 b .956
18
Assessed for eligibility
Ineligibile (n=11)
Acutely unwell (n=3)
Moving prison during assessment
period (n=3)
Insufficient English fluency
(n=4)
Problems with literacy (n=1)
Eligible (n=44)Consented to participating
(n=23)
Self-reported TBI (n=16)
No reported TBI (n=7)
TOMM Trial 2
Correlation with TBI Time Index (n=16)
Age
Premorbid IQ (TOPF raw score)
Years in education
Units of alcohol consumed daily
TOMM Trial 2
.55 b .027
.44 b .084
-.10 b .701
-.10 b .713
.26 b .321
Correlations with TBI Severity Index (n=16)
Age
Premorbid IQ (TOPF raw score)
Years in education
Units of alcohol consumed daily
TOMM Trial 2
.61 a .012
.31 a .234
-.19 a .478
.39 a .126
.26 b .321
aPearson correlation coefficientbSpearman’s rhocFor ease of interpretation M and SD for premorbid IQ once converted to standardised scores are 91.77 (9.21).*Significant at the level of <.0004 based on the Bonferroni correction for multiple comparisons
Measures
The assessment battery used in Pitman et al.’s (2014) study examining TBI in male
offenders was adapted following reflections from the project. Pro formas are only
included for measures freely available due to copyright. Further scale properties are
presented in Appendix III.
Semi-Structured Interview
The semi-structured interview was designed to ascertain history of TBI, offending,
19
mental health, and social history, in prisoners (Appendix IV).
The Brain Injury Screening Inventory (BISI)
The BISI (Appendix V; Pitman et al., 2014) is an eleven item questionnaire designed by
the Disabilities Trust, a UK based charity supporting people with a range of disabilities.
The BISI is designed to enable practitioners of all levels, ranging from health and social
care staff, probation, police, and housing support teams, to screen for TBI using self-
report data. It takes about 10 minutes to complete. Items were constructed on the basis
of items used in previous prevalence studies (Hwang et al., 2008; Williams et al., 2010),
and examines how many times an individual has suffered a serious blow to the head,
and consequent disorientation, PTA and LOC. It includes questions on other potential
ABIs, cognitive sequelae, and neurodevelopmental problems. The BISI provides
qualitative screening data, but efforts have been made to quantify the results using a
TBI Severity Index which is calculated by multiplying the highest rate of
unconsciousness, rated on a 0-3 likert scale, by the number of TBIs (Pitman et al.,
2014). The Disabilities Trust considered use of a TBI Time Index, which is LOC in
minutes multiplied by number of TBIs. The Disabilities Trust also developed a TBI
Global Score based on responses on the first reported TBI, the formula for which is
presented in Appendix V. The BISI Global Score provides an indicator of clinical need,
mapping severity to appropriate treatment pathways. Table 3 summarises the different
scoring systems for the TBI Global Score and TBI Severity Index. There is no
interpretation system developed for the Time Index. There is no published data
comparing these scoring systems. The BISI has been used in research on TBI in a UK
population of homeless people (Oddy et al., 2012) and male prisoners (Pitman et al.,
2014). Pitman et al.’s (2014) research demonstrated preliminary support for the validity
of the BISI with male offenders, with presence of TBI on the BISI and TBI Severity
20
Index correlating with performance on neuropsychological measures. There is no
published data on the reliability of the BISI.
Table 3. Scoring and interpretation of the BISI
The BISI Time Index The BISI Global Score
Severity 1-10: Mild TBI <5: no clinical need
11-30: Moderate TBI 5-8: signposting to healthcare
31-60: severe TBI 9: routine cognitive assessment
61-300: very severe TBI ≥10: routine cognitive assessment
≥300: extremely severe TBI
Beck Depression Inventory-II (BDI-II)
The BDI-II is a 21 item self-report measure of severity of depressive symptoms (Beck
et al., 1996). Items are rated from 0-3. A total score of 0-13 indicates minimal
depression; 14-19 mild; 20-28 moderate; and 29-63 severe depression. The BDI-II has
demonstrated strong validity and reliability across a range of populations, including
offenders (Wang & Gorenstein, 2013). Cronbach’s alpha for the current sample was .91,
indicating excellent internal reliability.
Beck Anxiety Inventory (BAI)
The BAI (Beck et al., 1988) is a 21 item self-report measure of severity of symptoms of
anxiety. Items are rated from 0-3. A total score of 0-7 indicates minimal anxiety; 8-25
mild; 16-25 moderate; and 26-63 severe anxiety. Beck et al. (1988) reported adequate
reliability and validity. Cronbach’s alpha for the current sample was .88, indicating
good internal reliability.
21
The Impact of Events Scale – Revised (IES-R)
The IES-R (Weiss & Marmar, 1997) is a well validated and reliable 22 item self-report
measure of symptoms of PTSD, asking the participant to reference a specific traumatic
event when responding to questions (Appendix VI). Items are rated from 0-4. A total
score over 33 indicates the possible presence of posttraumatic stress disorder (PTSD).
Cronbach’s alpha for the current sample was .91, indicating excellent internal reliability.
The Neurobehavioral Functioning Inventory (NFI)
The NFI (Kreutzer et al., 1999) is a 76 item self-report inventory composed of six
subscales measuring frequency of common difficulties after acquiring a neurodisability,
namely: depression, somatic, memory/attention, communication, aggression, and motor.
Items are rated from 1-5, with higher scores indicating higher levels of neurodisability.
While an informant version of the scale was available, it was only possible to complete
the self-report in this study, as an informant with an appropriate knowledge of the
participants’ functioning would not be available. The NFI has demonstrated adequate
reliability and validity for use in TBI (Kreutzer et al., 1996; Kreutzer et al., 1999).
Cronbach’s alphas for the current sample for the depression, somatic, memory/attention,
communication, aggression and motor subscales are .93, .80, .94, .90, .81, and .82
respectively, indicating good to excellent internal reliability.
The Dysexecutive Questionnaire (DEX)
The DEX (Wilson, Evans, Emslie, Alderman, & Burgess, 1998) is a 20 item self-report
questionnaire assessing frequency of executive-type behavioural problems. Items are
rated from 0-4, with higher scores indicating higher frequency of problems. While an
informant version of the scale was available, it was only possible to complete the self-
report in this study. The DEX has demonstrated adequate reliability and validity for use
22
in TBI (Bennett, Ong, & Ponsford, 2005). Cronbach’s alpha for the current sample
was .95, indicating excellent internal reliability.
The Test of Premorbid Intellectual FunctioningUK (TOPF)
The TOPF (Wechsler, 2009) provides a reliable and valid means of estimating the
premorbid cognitive functioning levels of adults suspected of suffering from intellectual
deterioration. It is designed on the premise that general intelligence is highly correlated
with reading ability, which is relatively resistant to neuropsychological insult (Carlozzi
et al., 2011). It consists of 70 written words which must be read aloud and scored by
pronunciation. The premorbid IQ score can be adjusted for sex and years in education. It
is normed with the Wechsler Adult Intelligence Scale IVUK (WAIS IV; Wechsler, 2008).
The Wechsler Abbreviated Scale of Intelligence II (WASI-II)
The WASI-II (Wechsler & Zhou, 2011) is a reliable and valid abbreviated measure of
cognitive intelligence for individuals aged 6-90 years. It is adapted from the four highest
loading WAIS-IV subtests on g (general intelligence); namely, Vocabulary and
Similarities which constitute the Verbal Comprehension Index (VCI), and Block Design
and Matrix Reasoning which constitute the Perceptual Reasoning Index (PRI). Index
scores are adjusted for age and have a mean of 100 (SD = 15).
The Repeatable Battery for the Assessment of Neuropsychological Status
(RBANS)
The RBANS (Randolph, 1998) is a reliable and valid brief cognitive battery for the
assessment of neuropsychological functioning for individuals aged 12-90 years.
Consisting of twelve subtests (list learning, story memory, figure copy, line orientation,
picture naming, semantic fluency, digit span, coding, list recall, list recognition, story
23
recall, and figure recall), it provides measures of immediate and delayed memory,
visuoconstruction and visuoperception ability, attention, language, as well as a global
summary score. Index scores are adjusted for age and have a mean of 100 (SD = 15).
The Behavioural Assessment of Dysexecutive Syndrome (BADS)
The BADS (Wilson et al., 1996) is designed to be a reliable and valid assessment of
executive functioning for individuals aged 16-87 years. Consisting of six subtests
(temporal judgement, rule shift cards, action program, key search, zoo map, and
modified six elements), the tasks are meant to reflect real life situations. Each task is
scored on a scale of 0-4, which are summed to create a total profile score. Profile scores
can be converted to age adjusted standard scores with a mean of 100 (SD = 15).
The Test of Memory Malingering (TOMM)
The TOMM (Tombaugh, 1996) is a 50 item visual recognition test designed to detect
poor cognitive effort in neuropsychological testing in adults. It consists of two learning
trials and an optional retention trial if a participant scores below the cut-off of 45. In the
learning trials the participants are shown 50 line drawn targets for three seconds. The
test phase is forced choice and each target item is paired with a distractor, requiring the
respondent to indicate the previously shown target. Scores range from 0-50, with five or
more errors on trial two indicating low effort. It has demonstrated its reliability and
validity particularly for use with TBI (Tombaugh, 1997).
Procedure
Participants were recruited through a convenience sample. A list of new receptions from
September 29th 2014 to February 9th 2015 was obtained from the prison. A poster
(Appendix VII) advertising the study was hung in the intake room and reception wing,
24
along with expression of interest slips which could be handed to any prison officer and
returned to the prison psychology office. Recruitment was ongoing during the data
collection period, with one to two participants recruited each week up to three weeks in
advance of assessment. Only two participants returned expression of interest slips. The
remaining participants were recruited in consecutive chronological order by individually
approaching them. Prison officers acted as gatekeepers and were asked if potential
participants met any of the exclusion criteria prior to approaching them. Prisoners in the
healthcare wing were not approached due to exclusion criteria. Copies of the participant
information sheet (Appendix VIII) and consent form (Appendix IX) were dropped into
eligible participants’ cells. A week later prisoners were followed-up face-to-face to
discuss participation and consent. After signing the consent form, a suitable time to
commence assessment was arranged. Participants were allocated a participant number,
which was recorded with their prison number, and stored in a file managed by the
prison psychology team.
Assessment was conducted in a quiet room with a large table, and took place over two
sessions on different days, ideally a week apart unless scheduling conflicts did not
allow. Days between Part One and Part Two of the assessment ranged from three to 42
(M = 12.91, SD = 11.40). During Part One, participants completed the BISI and clinical
interview, taking approximately one hour. They then completed the BDI-II, BAI, and
IES-R. The neuropsychology battery took two to three hours and was administered in
the following order: the TOMM, the TOPF, the RBANS, the WASI-II, the BADS, the
DEX, and the NFI. Participants could choose the Part One end point, to manage fatigue.
Most participants stopped after the RBANS, with a few continuing to the WASI-II.
Participants could request a feedback session at the end of the assessment. Psychometric
data were scored immediately after testing. Feedback was given verbally within one
25
month, at which point they could decide if they wanted clinically significant results to
be passed on to healthcare (see Appendix X for healthcare feedback pro forma). Data
were also extracted from The Offender Assessment System (OASys), a structured
clinical needs assessment tool used throughout NOMS (Home Office, 2006). The
OASys provided brief offence and abuse history (see Appendix XI for list of items
extracted) and was accessed from participant files after the assessment was complete.
Ethics
This study was reviewed and granted favourable ethical opinion by the NOMS National
Research Committee and by the Faculty of Arts & Human Sciences Ethics Committee
at the University of Surrey (see Appendix XII for correspondence with confirmation of
ethical approval). Issues of consent, anonymity and data protection were adhered to
throughout the study according to the requirements set by the above ethical panels.
Data Analysis
While a large dataset was collected, for the purpose of this MRP only data related
directly to these research questions will be discussed. All analyses were done using IBM
SPSS version 20 (IBM, 2011). There were no missing data, as data pertaining to these
research questions came from the interview and neuropsychological assessment. Data
preparation included checking responses, calculating total scores, and assessing
normality of distribution (see Appendix XIII for histograms and z scores). If z scores
were significantly higher than zero (z > 1.96, p <.05) then data were considered to be
abnormally distributed (Field, 2013), in which case non-parametric equivalents of tests
were used where appropriate.
Construct validity of the BISI was explored by examining its convergent validity with a
range of neuropsychological tests. Correlation coefficients were calculated for key BISI
26
summary variables (presence of TBI; the TBI Time Index; the TBI Severity Index; and
the TBI Global Score), the neuropsychological measures, and standardised
questionnaires.
Retest reliability was assessed for key BISI variables, namely: presence of TBI; total
number of TBIs; age of first TBI; presence of any episode of PTA; total number of
episodes of PTA; longest period of reported LOC; TBI Severity Index; TBI Time Index;
and TBI Global Score. For the continuous variables, ICCs using a two-way fixed effect
model for agreement (Rankin & Stokes, 1998), Pearson correlation coefficients, and
Spearman correlation coefficients where appropriate, explored retest-reliability across
the two time points. For the nominal variables, Cohen’s kappa (Cohen, 1960) and Phi
coefficients (Cramer, 1946) assessed retest reliability.
Results
History of TBI
Of the total sample, 69.56% reported a history of any TBI, while 60.86% reported a
history of TBI with LOC. Number of reported TBIs ranged from 0 to 6 (M = 2.09, SD =
1.97). Age of first TBI ranged from 4 to 28 (M = 15.25, SD = 6.85), while age of most
serious TBI ranged from 5 to 33 (M = 19.44, SD = 7.51). Table 4 outlines the reported
causes of the TBIs.
Table 4. Cause of TBIs
27
Time since first TBI ranged from 3 to 50 years (M = 24.94, SD = 18.10), and time since
most recent TBI from 1 to 33 years (M = 8.75, SD = 9.05). While 87.50% of
participants who experienced a TBI reported at least one LOC episode, only 35.41% of
TBIs involved LOC. Most severe LOC reported was over six hours for 18.80% of
participants, between ten minutes and six hours for 35%, and under ten minutes for
43.80%. In 45.65% of cases of TBI, participants did not seek or come to the attention of
medical or professional assistance (Table 5).
A TBI Time Index, consisting of LOC in minutes multiplied by number of TBIs, ranged
between 0 and 11,520 (M = 1,589, SD = 3,522). The TBI Severity Index, consisting of a
likert scale based LOC severity rating multiplied by number of TBIs, ranged from 1 to
12 (M = 4.56, SD = 3.22). The TBI Global Score, which consists of a sum of responses
related to first TBI reported, ranged from 0 to 14 (M = 4.91, SD = 4.36).
28
Cause %
Road traffic accident 17.39
Sporting accident 10.86
Fights 21.73
Intimate partner violence 15.21
Falls (on substances) 13.04
Other (not crime related) 8.69
Falls (sober) 10.86
Childhood abuse 2.17
Table 5. Treatment sought after TBI
Treatment %
Hospital 41.30
Nothing 45.65
Taken to prison 2.17
Paramedic 2.17
Prison/police healthcare 6.52
GP 2.17
Construct Validity
Key summary variables on the BISI were tested for convergence with
neuropsychological measures of cognitive functioning and standardised self-report
questionnaires of mood and neurodisability.
Contrary to hypotheses, the TBI Severity Index demonstrated small to medium
predominantly negative correlations with the self-report mood and cognitive
questionnaires. It was hypothesised that the TBI Severity Index would be negatively
correlated with the neuropsychological measures, however the directions of the
correlations were inconsistent. Across all measures, none of the variables reached
statistical significance (Table 6). Overall, results indicate that as the TBI Severity Index
increased, symptomology on mood and neuropsychological measures did not
consistently increase as expected.
29
Table 6. Correlations between TBI Severity Index (M=4.56 SD=3.22) and variables
from the Neuropsychological Battery (n=16)
Variable Mean (SD) r Sig
Standardised self-report mood and neurodisability questionnaires
BAI 17.56 (11.12) -.15 a .556
BDI-II 24.08 (12.68) -.33 a .211
DEX total score 29.91 (19.05) -.28 a .289
IES-R 45.69 (20.62) -.33 a .208
NFI Depression 40.04 (11.57) -.46 a .067
NFI Somatic 29.73 (8.28) -.39 a .129
NFI Memory 50.30 (17.21) -.09 a .714
NFI Communication 25.95 (8.81) -.14 a .599
NFI Aggression 18.43 (5.78) -.38 a .144
NFI Motor 18.86 (5.45) -.04 a .879
Neuropsychological assessments of cognitive functioning
RBANS immediate memory 90.95 (16.36) .03 a .904
RBANS visuospatial 87.52 (15.03) .11 a .681
RBANS language 95.00 (14.49) .07 a .796
RBANS attention 85.22 (16.66) -.04b .874
RBANS Delayed Memory 93.13 (13.94) .15 b .563
RBANS total score 86.78 (14.54) .02 a .928
BADS Total Score 16.43 (4.13) -.24 b .367
WASI verbal comprehension 99.65 (13.71) .02 a .915
WASI perceptual reasoning 91.13 (15.39) -.17 a .519
WASI full scale 95.00 (15.23) -.08 a .754
WASI-TOPF 6.25 (12.65) -.28 a .292
30
aPearsons’ zero order correlationbSpearman’s rho*Significant at the level of p≤.0004 based on the Bonferroni correction for multiple comparisons
While the TBI Global Score demonstrated small to large correlations in the expected
direction with the self-report mood and neurodisability questionnaires, only the NFI
Motor subscale reached statistical significance (Table 7). The TBI Global Score only
demonstrated small correlations in the expected direction with the neuropsychological
measures of cognitive functioning, and none reached statistical significance (Tables 7).
Overall, results suggest that as the TBI Global Score increased symptomology on mood
and neuropsychological measures increased, however as these were predominantly not
within levels of statistical significance, with such a small sample these results are likely
to be unstable and are interpreted with caution.
Table 7. Correlations between TBI Global Score (M=4.91 SD=4.36) and
Neuropsychological Measures (N=23)
Variable r Sig
Standardised self-report mood and neurodisability questionnaires
BAI .44a .034
BDI-II .29 a .173
DEX total score .37 a .077
IES-R .21 a .328
NFI Depression .25 a .238
NFI Somatic .53 a .009
NFI Memory .58 a .003
NFI Communication .62 a .002
31
NFI Aggression .26 a .220
NFI Motor .68 a <.0004*
Neuropsychological assessments of cognitive functioning
RBANS immediate memory -.27 a .209
RBANS visuospatial -.17 a .417
RBANS language .01 a .933
RBANS attention -.28b .167
RBANS Delayed Memory -.23b .279
RBANS total score -.19 a .382
BADS Total Score -.24 b .255
WASI verbal comprehension -.22 a .300
WASI perceptual reasoning -.25 a .250
WASI full scale -.25 a .240
WASI-TOPF -.07 a .739
aPearson zero order correlationbSpearman’s rho*Significant at the level of p≤.0004 based on the Bonferroni correction for multiple comparisons
Using point biserial correlations, a reported history of TBI on the BISI was correlated
with variables on the neuropsychological test battery. None reached statistical
significance. Similarly to the BISI Global Score, while examination of the correlation
coefficients suggests that the results may be moving in the hypothesised direction, with
some medium and large coefficients (Table 8), lack of statistical significance and a
small sample indicate that these coefficients are likely to be unstable. The strongest
relationships were with the self-report measures.
32
Table 8. Point Biserial Correlations between Presence of TBI and Variables from the
Assessment Battery (N=23)
Variables Sig r
Standardised self-report mood and neurodisability questionnaires
BAI .053 0.40a
BDI-II .284 0.23 a
DEX total score .313 0.21 a
IES-R .172 0.29 a
NFI Depression .228 0.26 a
NFI Somatic .014 0.50 a
NFI Memory .097 0.35 a
NFI Communication .144 0.31 a
NFI Aggression .038 0.43 a
NFI Motor .002 0.70 a
Neuropsychological assessments of cognitive functioning
WASI verbal comprehension .432 -0.17
a
WASI perceptual reasoning .731 -0.07
a
WASI full scale .584 -0.12
a
WASI-TOPF .527 0.13 a
RBANS attention .325 -.21b
RBANS Delayed Memory .474 -.15 b
RBANS immediate memory .496 -0.14
a
RBANS visuospatial .209 -0.27
33
a
RBANS language .231 0.25 a
RBANS total score .661 -0.09
a
BADS Total Score .602 -.11 b
*Significant at the level of p≤.0004 based on the Bonferroni correction for multiple comparisonsaPearson correlation coefficientsbSpearman correlation coefficients
Spearman’s rho was used to assess the correlation between the TBI Time Index and the
neuropsychological battery (Table 9). Contrary to our hypotheses, the TBI Time Index
demonstrated small to medium predominantly negative correlations with the self-report
mood and cognitive questionnaires, as well as neuropsychological measures, none of
which reached statistical significance. Overall, results indicate that as the TBI Time
Index increased, symptomology on mood and neuropsychological measures did not
consistently increase as expected.
Table 9. Correlations between TBI Time Index and Neuropsychological Measures
(n=16)
Variable r Sig
Standardised self-report mood and neurodisability questionnaires
BAI -.018 .947
BDI-II -.187 .487
DEX total score -.294 .269
IES-R -.324 .221
NFI Depression -.496 .051
NFI Somatic -.345 .191
34
NFI Memory -.122 .653
NFI Communication -.170 .528
NFI Aggression -.336 .204
NFI Motor -.038 .888
Neuropsychological assessments of cognitive functioning
RBANS immediate memory -.017 .952
RBANS visuospatial .161 .553
RBANS attention -.037 .892
RBANS delayed memory .271 .310
RBANS language .000 1.000
RBANS total score .058 .830
BADS total score -.218 .418
WASI verbal comprehension -.076 .779
WASI perceptual reasoning -.210 .434
WASI-II full scale -.082 .762
WASI-TOPF -.426 .100
*Significant at the level of p≤.0004 based on the Bonferroni correction for multiple comparisons
Table 10 describes differences between variables tested in this study and Pitman et al.’s
(2014) study, on which our hypotheses were based. Although there was some
consistency in correlation size and direction across studies for Presence of TBI, as
discussed previously these correlations are not statistically significant and likely to be
unstable given the small sample. Table 10 also highlights possible discrepancies in
findings for the TBI Severity Index across the two populations.
35
Table 10. Correlation coefficients and for variables of interest against TBI Presence and TBI Severity Index in the present study and Pitman et
al.’s (2014) study
TBI Presence TBI Severity Index
Correlation coefficients
in this studyc
Correlation coefficients in
Pitman et al.’s sample (2014)c
Correlation
coefficients in this
study
Correlation coefficients in
Pitman et al.’s sample (2014)
NFI Depression .26 .46* -.46 a .49* a
NFI Somatic .50 .46* -.39 a .54* a
NFI Memory .35 .49* -.09 a .51* a
NFI Communication .31 .38* -.14 a .43* a
NFI Aggression .43 .37* -.38 a .40* a
NFI Motor .70 .41* -.04 a .46* a
DEX .21 .40* -.28 a .45* a
BAI .40 .41* -.15 a .47* a
BDI .23 .31* -.33 a .38* a
36
RBANS -.09 -.45* .02 a -.42* a
BADS -.11 -.32* -.24b -.28* a
WASI -.12 -.27* -.08 a -.25* a
WASI-TOPF .13 -.24* -.28 a -.20* a
*Statistically significant at respective p with Bonferroni correctionsaPearson correlation coefficientsbSpearman’s rhocPoint biserial correlation
37
BISI Test-Retest Reliability
Five of the eight continuous variables were consistent with hypothesis three,
demonstrating statistical significance (Table 11). ICC values for six of the eight
continuous variables on the BISI were over .60 (Table 11), meeting minimum criteria
for acceptable retest reliability (Anastasi, 1998; Baumgartner & Chung, 2001; Chinn,
1991), however Total no. of episodes of PTA did not reach statistical significance which
is reflected in its wide confidence intervals. The most reliable variables were Total
Number of TBIs, the TBI Global Score, and the TBI Severity Index, which all had
large positive Pearson coefficients as well as ICCs over .80 (p <.0004), indicating
excellent retest reliability (Landis & Koch, 1977). Total number of episodes of
disorientation, age at first TBI and total number of episodes of PTA had moderate ICC
coefficients and large Pearson coefficients. Longest recorded LOC and the TBI Time
Index did not demonstrate adequate ICC coefficients, despite large Pearson coefficients.
Table 11. Test-Retest Reliability for Key Continuous Variables
Variable Mean (SD) R Sig ICC 95%
CI
Time 1 Time 2
Age at first TBI
(n=16)
15.31 (6.77) 16.94
(7.79)
.814a <.0004
*
.796 .519-.
923
Total no. of episodes
of PTA (n=16)
.69 (.70) .5 (.63) .626b .002 .658 .276-.
864
Total no. of episodes
of disorientation
(n=16)
2.81 (1.37) 2.38 (1.14) .844b <.0004
*
.758 .410-.
910
38
Total no. of TBI
(N=23)
2.04 (1.89) 1.78 (1.56) .989a <.0004
*
.943 .853-.
977
Global TBI Score
(N=23)
4.91 (4.36) 4.65 (4.26) .853a <.0004
*
.857 .693-.
937
Longest LOC (n=16) 479.43
(1003.95)
219.12
(485.48)
.743b .011 .533 .096-.
804
TBI Time Index
Score (n=16)
1589.34
(3522.67)
617.84
(1548.84)
.706b .006 .574 .154-.
824
TBI Severity Index
(n=16)
4.56 (3.22) 4 (2.73) .852b <.0004
*
.830 .588-.
936
aPearson correlation coefficientbSpearman’s rho *Significant at the level of p≤.0004 based on the Bonferroni correction for multiple comparisons
Consistent with hypothesis four, Presence of TBI reached statistical significance (Table
12) and had excellent retest reliability with both Phi and Kappa coefficients of 1
(Landis & Koch, 1977). However, Presence of PTA was inconsistent with our
hypothesis. Although it demonstrated moderate to excellent retest reliability across both
Phi and Kappa (Table 12) it failed to reach statistical significance. Analyses were not
possible for Other ABI as every participant responded negatively to this item.
Table 13 compares reliability coefficients across the BISI, TBIQ and OSU TBI-ID for
variables that were designed to capture the same data. The BISI demonstrated the
highest reliability across three of the four variables.
39
Table 12. Test-Retest Reliability for Key Dichotomous Variables
Variable Consistent
(%)
Inconsistent
(%)
Phi Sig Kappa Sig
Presence of
TBI (N=23)
23 (100%) 0 (0%) 1 <.0004
*
1 <.0004*
Presence of
PTA (n=16)
12 (75%) 4 (25%) .524 .036 .740 <.0004*
Other ABI
(N=23)
23 (100%) 0 (0%) Not
computed
as variable
was
constant
- - -
*Significant at the level of p≤.0004 based on the Bonferroni correction for multiple comparisons
Table 13. Comparison of retest reliability across measures
BISI OSU TBI-ID TBIQ
Presence of TBI 1a N/A 0.56a
No. of TBIs .98b; .94c .87c 0.90b
Age at first TBI .81b; .79c .67c N/A
Longest LOC .74d; .53c .91c N/A
aKappa coefficientbPearson coefficientcICCdSpearman’s rho
Discussion
This study’s results provide some preliminary support for the utility of the BISI in
40
identifying female prisoners with a TBI history and associated cognitive impairment in
the UK, demonstrating the value in further investigation of its use in this population.
History of TBI
The BISI and clinical interview revealed that 69.50% of participants had a history of
any TBI, and 60.86% of TBI with LOC, which is consistent with the female prevalence
of any TBI of 69.98% and 59.31% when restricted to LOC, reported in Shiroma et al.’s
(2010a) TBI in offenders meta-analysis. This female sample experienced slightly fewer
TBIs with LOC than in Pitman et al.’s (2014) UK male sample (87.50% vs 94.20%),
with only 35.41% of TBIs resulting in LOC, and more reporting not seeking help after
the injury (45.65% vs 31.00%). Across both studies, the TBI Severity Index
demonstrated similar means (M=4.06 SD=4.50 in the male sample; M=4.91 SD=4.36 in
the female sample), but with a greater range in the male study (0-18 vs 0-14). The
female sample had a younger mean age of first TBI (15.25 years vs. 17.71 years). These
findings support evidence of gender specific epidemiological pathways in TBI (O'
Sullivan, Glorney, Sterr, Oddy, & Da Silva Ramos, 2015), indicating that while female
offenders have a similar TBI prevalence to males, females experience milder TBIs and
are less likely to seek help. The most frequently reported causes of TBIs were fights,
road traffic accidents, and domestic violence. No studies available studies compare
mechanism of injury across gender (O' Sullivan et al., 2015).
Construct Validity
Results suggest that further investigation of the construct validity of the BISI is
required. Only one of the BISI’s four summary variables demonstrated statistical
significance with one subscale within the assessment battery. Two of the variables
demonstrated correlation coefficients in the hypothesised direction with the battery of
41
neuropsychological measures of cognitive functioning and self-report questionnaires of
mood and neurodisability, however these coefficients are likely to be unstable due to the
small sample. This is the only TBI screening tool in an offender population that has had
its convergent validity investigated against a battery of neuropsychological tests. Our
results emphasise the need to further explore such measures’ convergence with clinical
psychometric assessments.
The TBI Global Score and TBI Presence variables demonstrated correlations in the
expected direction across the measures, however only the NFI Motor subscale reached
statistical significance with the TBI Global Score. There is no prior published research
on the TBI Global Score. Similarly, comparing the scores of those with and without a
self-identified TBI history, the self-report questionnaires demonstrated the strongest
relationship as opposed to the cognitive measures. This mirrors results found in the
male study (Pitman et al., 2014), with the largest effect sizes seen across both studies
being self-report.
Contrary to the hypotheses, both TBI Severity Index and Time Index demonstrated
small to medium correlations predominantly in the opposite direction for the self-report
measures, and in inconsistent directions for the cognitive tests. It is possible that the
TBI Severity Index and Time Index are invalid clinical indicators in this population due
to gender differences in TBI presentation, specifically difficulties in recalling periods of
LOC. Albicini and McKinlay (2014) emphasise the problem with validity that relying
on self-report LOC causes for diagnosis, e.g. individuals confusing PTA with LOC,
which as memory gap is subjectively experienced as the same. Without reliable
corroborating reports, using LOC as an indicator is likely to be misleading. Considering
most women in this study did not seek medical help, corroborating reports are unlikely
42
to exist. Donnelly et al. (2011) found that a binary variable asking whether participants
had experienced LOC in a military population had clinical value, with high specificity
(94%) but lower sensitivity (54%).
Across both studies, the strongest convergence has been with self-report measures of
neurodisability and mood rather than the objective cognitive assessments, highlighting
the complex relationship between mood and subjective, as well as objective, cognitive
functioning (Chamelian & Feinstein, 2006). Chamelian and Feinstein (2006)
demonstrated when mood is controlled for in TBI, subjective cognitive difficulties no
longer predicts most objective cognitive difficulties, with psychological factors
influencing objective recovery. This may be particularly relevant for TBI rehabilitation
considering females report higher levels of somatic depression in particular (Silverstein,
2002). While this may be an artefact of the gender response bias hypothesis (Sigmon et
al., 2005), examining means across self-report measures of mood and cognitive
functioning between this study and Pitman et al.’s (2014) study, the female group did
not consistently report greater pathology across measures, e.g. scores on the BDI-II are
higher across both TBI and non-TBI in the female population, but lower on the NFI
Depression subscale. The only variables which did not demonstrate results in the
hypothesised direction with the TBI Global Score and TBI Presence variables were the
WASI-TOPF and the RBANS Language Index. Premorbid IQ was lower than obtained
IQ across the whole sample, as well as for the TBI and non-TBI groups; with the TOPF
appearing to underestimate premorbid IQ particularly in the TBI group. Although verbal
comprehension was not particularly low in this sample, it is possible that there is lower
literacy proficiency specifically, which would lead to lower scores on the TOPF.
It is notable that on the BISI item which assessed other history of ABI or neurological
43
conditions, no participant provided a positive response. This is unusual, with research
demonstrating frequent comorbidity between TBI and other neurological conditions
(Bazarian, Cernak, Noble-Haeusslein, Potolicchio, & Temkin, 2009), with offenders at
particular risk of hypoxic brain injuries from substance use (Jackson & Hardy, 2011). It
is possible that this item is not a valid indicator of other neurological insults in this
population.
BISI Test-Retest Reliability
These results are the first to provide preliminary support for the retest reliability of the
BISI, with ICCs ranging from .53 to .94 on continuous variables, and Kappa
coefficients ranging from .740 to 1 on binary variables. Six of the 10 variables met
statistical significance as hypothesised. Eight of the 10 variables met minimum criteria
for adequate retest reliability, however two of these did not reach statistical significance
and had wide confidence intervals. Four variables demonstrated excellent retest
reliability. Since the reliability and validity of the OSU TBI-ID has been explored and
refined to its strongest 16 indices, its reliability coefficients range from .63 to .91
(Bogner & Corrigan, 2009). The TBIQ (Diamond et al., 2007) only provides reliability
coefficients for lifetime prevalence of TBI and frequency of TBI. Comparing these
screens, across variables designed to capture the same data, the BISI demonstrated the
highest reliability across three of the four variables. Differences may be attributable to
sample differences: the OSU TBI-ID and TBIQ are American tools; length of retest
period, with the TBIQ reporting approximately 2 to 4 weeks between testing, the OSU
TBI-ID reporting 1 to 2 weeks, while this study had a mean of 12.91 days; or
differences in question phrasing. Phrasing appears to be particularly an issue for the
BISI’s longest LOC item, which asks participants to state length of LOC rather than
providing categories as in the OSU TBI-ID, with poor recall leading to high variability
44
in responses, which is likely to be a factor for those with a TBI history. This is mirrored
in the TBI Time Index which is derived from length of LOC in minutes – this item
could not be reliable if length of LOC was unreliable. In comparison, when LOC was
converted into an ordinal scale for the TBI Severity Index, as in the OSU TBI-ID, the
TBI Severity Index remained reliable. Exploring the reliability of the OSU TBI-ID,
Bogner and Corrigan (2009) also found that items requiring estimation of LOC in
particular had lower reliability.
Comparing types of reliability coefficients both across studies, and within this study,
highlights the variability in statistics used. Pearson coefficients are frequently reported
to demonstrate retest reliability for continuous variables, however as Pearson measures
the strength of linear association rather than agreement, it is possible to have a high
correlation when agreement is low (Rankin & Stokes, 1998). Pearson coefficients do
not take systematic differences into account (Streiner & Norman, 2003). Quality criteria
guidelines specify that because systematic differences are part of measurement error, an
ICC two way models are the most appropriate retest reliability parameter for
continuous measures (Terwee et al., 2007). Pearson coefficients’ overestimation of
reliability is evidenced on a number of variables in this study, e.g. longest LOC, which
has a large Pearson coefficient but only a moderate ICC. The large Pearson coefficient
suggests it is reliable, however the ICC indicates that the frequency of disagreement
would make it unfit for its purpose of providing an estimate of TBI severity. Similarly,
for nominal variables, such as Presence of TBI, Kappa is considered the optimal retest
reliability parameter, as opposed to Phi which is the nominal equivalent of Pearson
(Mokkink et al., 2010; Rankin & Stokes, 1998).
45
Implications for Research and Practice
Providing the first psychometric data on the reliability and validity of a screening tool
for use in UK female offenders, this study has implications for both research and
practice, and is consistent with recommendations of the Repairing Shattered Lives
report (Williams, 2012). Our study demonstrates the value of further investigation into
the utility of the BISI for screening female offenders for TBI and associated cognitive
impairment, which has implications for the provision of specialist services both in
prison and upon release. Although this study was not designed to establish prevalence
specifically, the BISI produced TBI prevalence rates similar to those established in the
literature, for both with and without LOC (Shiroma et al., 2010a), supporting its
sensitivity to TBI in this population. The BISI demonstrated the strongest retest
reliability of comparable screens. However, two of its ten clinical variables, the TBI
Time Index and Longest LOC, which are closely interrelated, did demonstrate
inadequate retest reliability, and a further two did not meet statistical significance which
was reflected in wide confidence intervals. Longest LOC could be rephrased to capture
LOC range, however due to poor validity of self-report LOC, particularly in mTBI,
LOC range may not contribute sufficient clinical value to a screen, and may be best
removed. Similarly, the TBI Time Index demonstrated insufficient retest reliability and
may best be removed.
With regards to data analysis this study demonstrates the value of ICC and Kappa
coefficients over Pearson coefficients; and Phi, Pearson’s binary equivalent, for
establishing retest reliability. Our results highlight how Pearson and Phi coefficients can
substantially overestimate reliability by neglecting to take systematic differences into
account (Streiner & Norman, 2003).
46
Although most of the BISI summary variables did not reach statistically significant
convergence with the assessment battery, results suggest that further data collection is
warranted. No other TBI screen for use with offenders has demonstrated convergent
validity with a battery of neuropsychological measures. Self-report presence of TBI on
the BISI and the TBI Global Score both demonstrated correlations in the hypothesised
directions, although not reaching statistical significance.; Results provide support for
further investigation of the BISI’s utility in identifying those at risk of TBI sequelae,
and extension of Pitman et al.’s (2014) research into the construct validity of the BISI to
a female offender population. This study is the first to explore the new clinical indicator,
the TBI Global Score. As the TBI Global Score is based only on responses to the first
TBI, the BISI instructions should clarify if the first TBI to be reported should be the
first or the most severe; at present it is assumed the first reported will be the most
severe. It could also be considered if obtaining detailed information on other TBIs
makes any further meaningful contribution at a screening level, or if the TBI Global
Score is robust enough to inform clinical pathways.
The relationship between self-identified TBI history and the self-report measures across
both male (Pitman et al., 2014) and female offenders highlights the importance of taking
mood and subjective cognitive functioning into account when researching TBI causes
and consequences. It also demonstrates the difficult negotiation between sensitivity and
specificity when screening for TBI. TBI symptoms and risk factors overlap significantly
with psychiatric constructs. Albicini and McKinlay (2014) highlight the absence of a
gold standard in TBI assessment, emphasising the complex nature and specialist skills
required to diagnose TBI. It is recommended that future TBI research include
neuropsychological cognitive assessments to refine screens and reduce the false
positives, which lead to overburdening and wasting expensive clinical resources. Future
47
research needs to specifically identify the sensitivity and specificity, and diagnostic
odds ratio, for the BISI, whilst taking into account the impact of comorbid mental health
diagnoses on validity.
Both the TBI Severity and Time Indices demonstrated insufficient construct validity,
and the BISI may be strengthened by their removal. Gender differences in TBI
presentation specifically related to LOC, may reduce its validity with female offenders.
The BISI may also be refined by the removal of Question eight, on history of other
neurological insult.
It is advised that these refinements are considered fully once the complete dataset is
available. At present, our study is underpowered, and while some trends have been
detected, no definitive decisions should be made until there is sufficient power to ensure
that non-significant results are statistically sound. Once the BISI is refined it can be
utilised to address under identification of TBI in female prisoners, which has important
implications for allocation of resources, staff training, rehabilitation, and behaviour and
risk management.
Limitations
The study’s primary limitation is its small sample size. As present data are only
preliminary, as discussed, we can see some trends in the data but it cannot be
established whether non-significant hypotheses can be rejected until the full sample size
is reached. The response rate of 52% was also lower than that of the male study, which
had 66% of eligible participants complete the full neuropsychological battery (Pitman et
al., 2014). This difference may be attributable to variation in study design which was
informed by constraints of the prison regime.
Although the proportion of the sample reporting TBI is reported, this is not a prevalence
study, and there is a risk of recruitment bias by virtue of the study’s nature being stated
48
in recruitment materials. It is possible that TBI is overrepresented in our sample,
however difficulties in recruiting participants without a TBI may be a reflection of the
prevalence of TBI in the population. With regards to wider representation of the UK
female prison population, the overall mean age of women in this study was 38 years,
which is consistent with the Ministry of Justice’s (2014) reports that the most common
age range of women in prison is 30-39 years; while 73% of women in prison are
reported to be White British, which is similar to the 69.6% found in this study. Notably,
while the BISI was designed to be administered with minimal training, in this research
the BISI was administered by a trainee clinical psychologist with experience working
with TBI, therefore it is may not be representative of administration in general practice
where staff workloads are high and training in working with TBI is rare. Administration
by a clinician with experience in TBI would likely increase the sensitivity of the BISI,
by virtue of validating mTBI which prisoners are often dismissive of, and which can be
missed when administration is rushed. Furthermore, retesting was always administered
by the same trainee, therefore it was not possible to explore inter-rater reliability of the
BISI, which will need to be investigated in future research.
It is also important to note that as individuals with a diagnosed LD were not excluded
unless they demonstrated difficulties with literacy or were unable to provide informed
consent. Their inclusion could impact some of the results, as individuals with LD tend
to have a different cognitive presentation than those with TBI. Once the full dataset is
gathered this data can be examined separately to assess for any significant impact on the
results.
There are a number of limitations for establishing the retest reliability. Although every
effort was made to ensure a retest interval of seven days, unfortunately due to the
practicalities of prison research this was not always possible, and there was a wide
49
interval range. It could also be argued that knowledge of the BISI results could bias
scoring at the second time point, or scoring of the neuropsychological battery; however
adherence to assessment instructions minimised this risk. Longest LOC, the TBI Index
Score, and the TBI Severity Index, are all not normally distributed, which indicates that
the confidence intervals for these ICCs may be biased. If these variables remain
abnormally distributed once the full sample is collected it is advised that bootstrapping
is used to correct the confidence intervals accordingly. The confidence intervals for the
smaller ICCs are also quite wide. Baumgartner and Chung (2001) advise that a sample
of 50 is necessary to reduce CIs to an acceptable breadth.
Cronbach alphas were not calculated for the established neuropsychological cognitive
assessments as it was beyond the scope of this research; therefore there is a chance that
these measures do not have adequate internal reliability in this specific sample.
However, the internal reliability is well established across a range of populations, and
was considered during the design of this study (Appendix II). Also, the WASI in
particular has had its validity as an assessment tool called into question. Although the
WASI has demonstrated factorial equivalence across standardisation and clinical
samples (Ryan et al., 2003), no studies examining the validity of the WASI-II with TBI
specifically has been conducted, and the Matrix Reasoning subtest has been found to
have no predictive validity for TBI (Ryan et al., 2005).
Conclusions
This study of adult female prisoners in the UK provides support for further
investigation of the retest reliability and construct validity of a short TBI screening tool.
While most results were not statistically significant, two of the four summary variables
demonstrated some correlations in the hypothesised directions with a range of measures
of mood and neurodisability, indicating the value of further research with a larger
50
sample. This is the first data that is available on the Global TBI Score which is a new
summary indicator to help identify level of clinical need and inform appropriate clinical
pathways. Six out of 10 clinical indicators demonstrated statistically significant retest
reliability. These findings have implications for the future refinement of the BISI and
demonstrate value in further investigations with a larger sample. This study is the first
of its kind to explore reliability and validity of a TBI screening tool for female offenders
in the UK, beginning to extend evidence of its utility from male offenders (Pitman et al.,
2014). The development of a reliable and valid screening tool for women with TBI can
enable researchers to address the dearth of research into TBI in female offenders (O'
Sullivan et al., 2015), highlighted by the Repairing Shattered Lives report (Williams,
2012). Adoption of a screening tool by female prisons can inform funding for services,
by ensuring the most efficient use of resources. Identifying this vulnerable population
can help apportion funding into training of prison staff in working with female
offenders with TBI, inform offender rehabilitation plans, promote the populations
engagement with the criminal justice system, and identify who would benefit from
specialist assessment and rehabilitation services. The similar rate of TBI found in this
study with other studies highlights the dangers of the literature’s gender bias.
Differences in presentation such as length of LOC and help seeking behaviours
emphasises the possibility of gender specific epidemiological pathways in TBI, which
require much further research.
51
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List of Appendices
Appendix I: Neuropsychological Rehabilitation Guidelines for Authors …... 130
Appendix II: Demographic Data ……………………………………………. 140
Appendix III: Additional Psychometric Properties of Measures ……………. 144
Appendix IV: Semi-structured Interview …………………………………… 150
Appendix V: The Brain Injury Screening Inventory ……………..………… 164
Appendix VI: The Impact of Events Scale – Revised ………………………. 168
Appendix VII: Recruitment Poster ………………………………………….. 170
Appendix VIII: Participant Information Sheet ……………………………… 172
Appendix IX: Participant Consent Form ……………………………………. 178
Appendix X: Participant Feedback Pro Forma ……………………………… 180
Appendix XI: OASys Items Extracted ……………………………………… 183
Appendix XII: Correspondence Regarding Ethical Approval ………………. 185
Appendix XIII: Normality Data ……………………………………………... 188
77
Appendix I
Neuropsychological Rehabilitation: An International Journal – Guidelines
for Authors
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87
Appendix II
Demographic Data
88
Table 14. Frequency Demographic Data
Ethnicity %
White 69.6%
Black or Black British 17.4%
Mixed race 8.7%
Other ethnic group 4.3%
Marital status
Single 69.6%
Married 8.7%
Divorced 8.7%
Separated (but still married) 8.7%
Widowed 4.3%
Highest qualification
No qualifications 39.1%
GCSE/O level 4.3%
A-level/NVQ/Vocational award 39.1%
Diploma 4.3%
Degree 8.7%
Master’s degree 4.3%
Mental health diagnosis
None 34.8%
Depression 26.1%
Anxiety 4.3%
Bipolar 4.3%
89
Personality disorder 4.3%
Comorbid diagnoses (depression;
anxiety; PTSD; bipolar; OCD;
psychosis; personality disorder)
26.1%
Learning disability diagnosis 13%
History of self-harm 26.1%
Accessed mental health
services
65.2%
Experience of childhood abuse (self-reported on OASys assessment) 42.1%
Experience of domestic violence
Self-reported on OASys assessment 50%
OASys and reports from TBI history
combined
59.1%
Category of index offence
Drug offences 21.7%
Indictable motoring offences 4.3%
Violence against the person 26.1%
Robbery 26.1%
Theft & handling stolen goods 4.3%
Sexual offences 4.3%
Fraud & forgery 4.3%
Criminal damage 8.7%
Table 15. Presence of drug use
TBI (%) Non-TBI (%)
90
Heroin 37.50% 14.30%
Prescription drugs 37.50% 14.30%
Cocaine 56.30% 28.60%
Crack cocaine 31.30% 28.60%
Amphetamines 50.00% 57.10%
Ecstasy 37.50% 42.90%
Cannabis 68.80% 42.90%
Hallucinogens 37.50% 0.00%
Solvents 18.80% 0.00%
Sedatives 31.30% 14.3%
Crystal meth 6.30% 0.00%
Table 16. Descriptive Demographic Data
n Range M (SD)
Age of onset of mental health difficulties 15 9 - 55 21 (12.006)
No. of suicide attempts 23 0 - 10 1.43 (2.53)
91
Appendix III
Additional Psychometric Properties of Measures
92
Questionnaire Details Reliability in Relevant Sample Validity in Relevant Sample
Internal consistency Test-retest reliabilities
The Brain Injury Screening
Index
7 item self-report TBI
screen
N/A Demonstrated preliminary
convergent validity in male
prison sample (Pitman et al.,
2014)
Not known Not known
The Test of Memory
Malingering (Tombaugh,
1996)
50 item recognition test
designed to discriminate
between true memory
impairment and
malingering
Adult sample (Strauss, Sherman, & Spreen, 2006)
0.94 Not known Sensitivity: 0.1
Specificity: 0.9
The Wechsler Abbreviated
Scale of Intelligence
(Wechsler & Zhou, 2011)
Standardised measure of
cognitive function,
consisting of 4 subtests, 2
Adult sample (Wechsler & Zhou, 2011)
0.97 0.90-0.96 Clinical group study on
individuals with TBI conducted
93
verbal and 2 performanceby test authors
The Test of Premorbid
Functioning (Wechsler,
2009)
Provides an estimate of
premorbid intellectual
functioning using atypical
grapheme-phoneme
translation to measure
word knowledge through
reading
Adult sample (Wechsler, 2009)
0.95 0.93 Clinical group study on
individuals with TBI conducted
by test authors
The Behavioural
Assessment of the
Dysexecutive Syndrome
(Wilson et al., 1996)
A battery of 6 subtests to
test executive function
Adult sample – general population & neurological (Wilson et al., 1996)
0.70 -0.08-0.71 Construct validity: differentiated
between neurological and
healthy participants on 74% of
occasions (Norris & Tate, 2000;
Wilson et al., 1996)
The Repeatable Battery for Brief evaluation of Adult sample (Randolph, 1998)
94
the assessment of
Neuropsychological Status
(RBANS; Randolph, 1998)
cognitive function in
adults with neurological
disturbance
0.92-0.94 0.88 Construct validity demonstrated
in TBI population (McKay,
Casey, Wertheimer, &
Fichtenberg, 2007)
Neurobehavioral
Functioning
Inventory(Kreutzer et al.,
1999)
Self-report measure of
behaviours and symptoms
commonly associated
with TBI
Adult sample with TBI (Kreutzer et al., 1996)
0.97 Not known Construct validity: scores on
depression (p<0.002),
memory/attention (p<0.002),
communication (p<0.001),
aggression (p<0.002) and motor
(p<0.002) subscales
distinguished between
individuals with TBI who were
employed and unemployed
(Sander, Kreutzer, & Fernandez,
95
1997)
The Beck Anxiety
Inventory(Beck et al.,
1988)
21 item self-report
inventory of anxiety
severity
Adult psychiatric outpatients (Beck et al., 1988)
0.92 0.75 Construct validity: discriminates
anxious diagnostic groups from
non-anxious diagnostic groups
The Beck Depression
Inventory II (Beck et al.,
1996)
21 item self-report
inventory of anxiety
severity
Adult psychiatric outpatients (Beck et al., 1996)
0.92 0.93 Construct validity: discriminates
depressed individuals from non-
depressed individuals(Arnau,
Meagher, Norris, & Bramson,
2001)
The Impact of Events Scale
– Revised(Weiss &
Marmar, 1997)
Self-report measure
assessing intrusive and
avoidant reactions
associated with a
Adult population (Weiss & Marmar, 1997)
0.79-0.92 0.57-0.94 Construct validity: correlates
well with PTSD Checklist
(Creamer, Bell, & Failla, 2003)
96
particular event
97
Appendix IV
Semi structured Interview
98
Interview Schedule: Head Injury Research
Participant ID no.: ___________________
DOB: ________________________
Informed consent given for study: Yes No
Initial BISI completed: Yes No
Social History
2. How would you describe your ethnicity?
Asian or Asian British Black or Black British Mixed White
Other Ethnic Group I do not wish to disclose this
3. Are you:
Single Married Divorced Separated (but still married)
Widowed
3a. Do you have children?
Yes No
How many
3b
.
Accommodation Type: Before you came to be in prison were you living in:
Your own property Rented accommodation Shared House Hostel
Other
4. Do you have siblings?
Brothers Sisters
Have they been in trouble with police?
Yes No
5. Mother’s Occupation:
Father’s Occupation:
99
Education
6. How many years have you spent in education?
7. What is your highest level qualification?
GCSE/O Level A Level/NVQ/Vocational Award Degree
Masters Degree Doctorate/PHD No Qualifications Diploma
7.a Have you achieved any other qualifications since school/university?
Yes No
Specify (inc. if in prison):
8. What were you like at school?
Academically Good Disengaged/disinterested
Disruptive Truant Left Expelled
9. Did you require any help at school?
Yes No
9a. If yes what was this for?
Dyslexia Learning disability
Learning difficulty Behavioural problems Other
Occupation History
10. What has been your main occupation?
11. What was your job stability?
Stable Left of own accord Dismissed
100
12. Number of jobs had in working life:
Medical History
13. Have you ever had any operations/illnesses?
Yes No
If yes please specify
14. How old were you? – for major illnesses and significant hospitalisation
15. How often have you spent time in hospital?
16. Do you suffer from any long term illness?
Yes No
17. Do you have a physical disability?
Yes No
18. Have you been diagnosed with a mental health problem?
Yes No Age of onset:
19. Have you been diagnosed with a learning disability?
Yes No
20. Have you ever self-harmed
Yes No
If yes, frequency and type
Daily Weekly Monthly Occasionally
Cutting Burning Ingestion Banging head Other
21. Have you ever attempted suicide
101
Yes No
Details (inc. age):
21a
.
Have you ever seen:
Psychologist Psychiatrist Had contact with mental health services
When was this and what was it for (general details)?
Injury
22. How many times have you experienced a blow to the head?
Once Twice Three times Four times Five times >5 times
23. a. How old were you?
If you experienced a loss of consciousness, how long was this for?
Just went dizzy Less than 10 minutes 10 minutes to 6 hours Over 6 hours
What was the cause of your head injury?
RTA Sporting accident Fight Fight with partner Falls
(on substances) Joyriding Falls (sober) Other crimes
Other (non crime related)
Other significant details:___________________________________________________
_________________________________________________________________________
What happened after the injury?
A&E Spent time in hospital Spent time at home recovering
Imprisonment Nothing
102
Other significant details: ____________________________________________________
_________________________________________________________________________
Did you feel different after the injury?
Yes No
If yes, what parts of you were affected?
Physical aspects Emotions Anger Feeling irritable Feeling
anxious Memory Concentration Learning Speech Headaches
Other significant details: ____________________________________________________
_________________________________________________________________________
b. How old were you?
If you experienced a loss of consciousness, how long was this for?
Just went dizzy Less than 10 minutes 10 minutes to 6 hours Over 6 hours
What was the cause of your head injury?
RTA Sporting accident Fight Fight with partner Falls
(on substances) Joyriding Falls (sober) Other crimes
Other (non crime related)
Other significant details:___________________________________________________
_________________________________________________________________________
What happened after the injury?
A&E Spent time in hospital Spent time at home recovering
Imprisonment Nothing
Other significant details: ____________________________________________________
_________________________________________________________________________
103
Did you feel different after the injury?
Yes No
If yes, what parts of you were affected?
Physical aspects Emotions Anger Feeling irritable Feeling
anxious Memory Concentration Learning Speech Headaches
Other significant details: ____________________________________________________
_________________________________________________________________________
c. How old were you?
If you experienced a loss of consciousness, how long was this for?
Just went dizzy Less than 10 minutes 10 minutes to 6 hours Over 6 hours
What was the cause of your head injury?
RTA Sporting accident Fight Fight with partner
Falls (on drugs) Joyriding Falls (sober) Other crimes
Other (non crime related)
Other significant details: ____________________________________________________
_________________________________________________________________________
What happened after the injury?
A&E Spent time in hospital Spent time at home recovering
Imprisonment Nothing
Other significant details: ____________________________________________________
_________________________________________________________________________
Did you feel different after the injury?
Yes No
104
If yes, what parts of you were affected?
Physical aspects Emotions Anger Feeling irritable Feeling
anxious Memory Concentration Learning Speech Headaches
Other significant details: ____________________________________________________
_________________________________________________________________________
d. How old were you?
If you experienced a loss of consciousness, how long was this for?
Just went dizzy Less than 10 minutes 10 minutes to 6 hours Over 6 hours
What was the cause of your head injury?
RTA Sporting accident Fight Fight with partner Falls
(on substances) Joyriding Falls (sober) Other crimes
Other (non crime related)
Other significant details:___________________________________________________
_________________________________________________________________________
What happened after the injury?
A&E Spent time in hospital Spent time at home recovering
Imprisonment Nothing
Other significant details: ____________________________________________________
_________________________________________________________________________
Did you feel different after the injury?
Yes No
If yes, what parts of you were affected?
Physical aspects Emotions Anger Feeling irritable Feeling
105
anxious Memory Concentration Learning Speech Headaches
Other significant details: ____________________________________________________
_________________________________________________________________________
e. How old were you?
If you experienced a loss of consciousness, how long was this for?
Just went dizzy Less than 10 minutes 10 minutes to 6 hours Over 6 hours
What was the cause of your head injury?
RTA Sporting accident Fight Fight with partner Falls
(on substances) Joyriding Falls (sober) Other crimes
Other (non crime related)
Other significant details:___________________________________________________
_________________________________________________________________________
What happened after the injury?
A&E Spent time in hospital Spent time at home recovering
Imprisonment Nothing
Other significant details: ____________________________________________________
_________________________________________________________________________
Did you feel different after the injury?
Yes No
If yes, what parts of you were affected?
Physical aspects Emotions Anger Feeling irritable Feeling anxious
Memory Concentration Learning Speech Headaches
Other significant details: ____________________________________________________
106
_________________________________________________________________________
24. How old were you when you had your first injury?
25. How old were you at the age of your most serious injury?
Offences
26. How many times have you been in prison?
Once Twice Three times Four times Five times More than Five
27. How old were you when you first committed an offence?
28. How many offences (counts) have you had for the following? (0=None, 1= Once, 2 =
Twice, 3 = Three times, or 4= Four or more times)
Burglary Theft & handling Violent offences Driving offences
Fraud & forgery Drug offences Sexual offences Other
Criminal damage Robbery
29. How severe were your violent offences?
None (0) Violent threat (1) Assault without causing injury (2) Minor injury
(3) Serious injury (4) Severe injury (5) Murder (6) Multiple murders (7)
30. How many years in total would you say you have spent in custody in your adult life?
31. Do you attend any education classes?
Yes No Which?
If no, why? ________________________________________________________________
__________________________________________________________________________
107
32. Do you attend any work?
Yes No Which?
If no, why? ________________________________________________________________
__________________________________________________________________________
33. Do you attend any rehabilitation programmes?
Yes No Which?
If no, why? ________________________________________________________________
__________________________________________________________________________
35. How long is your current sentence? (inc. sentenced and to be served)
36. When you were last released from prison, what went wrong?
Return to alcohol/drugs Couldn’t cope Needed money Returned to old habits
other people influencing decisions N/A (1st offence) Nothing
Other, please specify ________________________________________________________
__________________________________________________________________________
What help would have made a difference?
Job Support (to help cope) Family contact/support Drug/alcohol support
Moving away from the area you were living in previously Mental Health
support/intervention Access to education
Other, please specify ________________________________________________________
__________________________________________________________________________
Drug/Alcohol Use
108
37. Have you ever used/taken:
Heroin
Everyday (5) Most days (4) Weekends (3) Once a month (2) Once (1) Never (0)
Drugs prescribed for someone else
Everyday (5) Most days (4) Weekends (3) Once a month (2) Once (1) Never (0)
Cocaine
Everyday (5) Most days (4) Weekends (3) Once a month (2) Once (1) Never (0)
Crack cocaine
Everyday (5) Most days (4) Weekends (3) Once a month (2) Once (1) Never (0)
Amphetamine
Everyday (5) Most days (4) Weekends (3) Once a month (2) Once (1) Never (0)
Ecstasy
Everyday (5) Most days (4) Weekends (3) Once a month (2) Once (1) Never (0)
Cannabis
Everyday (5) Most days (4) Weekends (3) Once a month (2) Once (1) Never (0)
Hallucinogens
Everyday (5) Most days (4) Weekends (3) Once a month (2) Once (1) Never (0)
Solvents
Everyday (5) Most days (4) Weekends (3) Once a month (2) Once (1) Never (0)
Sedatives/tranquilisers
Everyday (5) Most days (4) Weekends (3) Once a month (2) Once (1) Never (0)
Crystal meth
Everyday (5) Most days (4) Weekends (3) Once a month (2) Once (1) Never (0)
Other, please specify _____________________________________________________
_______________________________________________________________________
109
Everyday (5) Most days (4) Weekends (3) Once a month (2) Once (1) Never (0)
38. How often do you/did you drink alcohol?
Everyday (5) Most days (4) Weekends (3) Once a month (2) Once (1) Never (0)
38a How much alcohol would you drink in a day/period?
Other Information
Suitable for study: Yes No
If No, select reason(s) why:
Not interested Other problems more significant e.g. MH or LD? Soon to be
released?
If yes, select TBI or non-TBI:
Non-TBI TBI
Repeat BISI: Yes No
NFI completed: Yes No
BDI-II completed: Yes No
BAI completed: Yes No
IES-R completed: Yes No
110
TOPF completed: Yes No
WASI-II completed: Yes No
TOMM completed: Yes No
RBANS completed: Yes No
BADS completed: Yes No
Assessment feedback session requested: Yes No
Assessment results to be shared with prison/health services: Yes No
To be contacted with research results after study: Yes No
Researcher:_______________________________ Date:___/___/_____
111
Date of Stage 1 __/__/____
Date of Stage 2 __/__/____
Appendix V
The Brain Injury Screening Inventory
112
113
114
BISI Global Score Formula
TBI (Yes = 1; No = 0) + disorientation (Yes = 1; No = 0) + PTA (Yes = 1; No = 0) +
LOC (Yes = 4; No = 0) + other TBI (Yes = 1; No = 0) + ABI (Yes = 10; No = 0) +
memory difficulties (Yes = 1; No = 0) + concentration difficulties (Yes = 1; No = 0) +
speech difficulties (Yes = 1; No = 0) + other difficulties (Yes = 1; No = 0)
115
Appendix VI
Impact of Events Scale – Revised (IES-R)
116
117
Appendix VII
Recruitment Poster
118
119
Appendix VIII
Participant Information Sheet
120
PARTICIPANT INFORMATION SHEET
Traumatic Brain Injury in Adult Female Offenders in the UK
You are being invited to take part in a research study. Before you decide whether or not
to take part, it is important for you to understand why the research is being done and
what it will involve. Please take time to read the following information carefully and
discuss it with others if you wish. Ask the researcher if there is anything that is not clear
or if you would like more information. Take time to decide whether or not you wish to
take part.
This research has been approved by the National Offender Management Service
National Research Committee, reference no.: 2013-266.
Thank you for reading this.
What is the purpose of the study?
We have three aims for this study. Our first aim is to find out how many female
prisoners have a history of traumatic brain injury, and to check that our brief screening
tool is appropriate for use with female prisoners. We would also like to see if
participants who have had a traumatic brain injury have different physical and mental
health needs to those without a traumatic brain injury.
Why have I been invited?
We are asking all new receptions to HMP ____ to take part.
Do I have to take part?
No. Your participation in this research study is completely voluntary and you do not
have to take part if you do not wish to. If you decide to take part you are still free to
withdraw at any time, without giving a reason. This will have no effect on your current
121
or future treatment or medical care and will not be recorded in your record. If you do
decide to take part you will be given this information sheet to keep and be asked to sign
a consent form.
What will happen to me if I take part?
If you decide to take part, you will complete a brief questionnaire and have one
interview with a researcher which will last around an hour. This interview will include
questions about your social history, health, and offending history, but there will be no
compulsory questions. All you have to do is sit down and have a conversation with the
researcher. If there is anything you find uncomfortable you don’t have to talk about it.
This research is independent of the prison and will not affect your sentence in any way.
You can withdraw from the research at any time, without giving a reason.
You will then be invited to complete further questionnaires and for neuropsychological
testing. This can be completed on the same day or arranged for a later date if preferred.
The questionnaires will include measures relating to mental health. The
neuropsychological tests will examine your current and previous cognitive functioning.
After the assessment is completed you will have the option of obtaining feedback on the
findings. You will also have the option of sharing the results with the prison/health
service if you wish. If feedback is requested you will receive a letter saying whether or
not the assessment indicated there was a need for a formal clinical assessment. In the
event that clinically significant results are obtained, e.g. if you seem to be experiencing
significant low mood, you will receive a letter from the researcher suggesting you attend
an arranged feedback session, with an allocated time and date. This can be altered if it
does not suit you. Feedback sessions will occur in a private space designated by the
prison. The researcher will discuss the nature of the significant results with you and try
to answer any questions you may have. We will advise you to allow us to inform prison
122
staff if results suggest you are experiencing difficulties so you can access appropriate
support through the prison healthcare system. In the case of neuropsychological
assessments, with your consent, scores can be forwarded to the psychology staff within
the prison and clinicians can contact the primary researcher with questions if necessary
to support their clinical work.
If you want to, you can also give the researcher your details and they will contact you
after they have the complete results from the study.
Who else will the researchers talk to?
The researchers will access your prison file to collect some background information.
Just like what you tell the researcher yourself in the assessment, this information will be
kept confidential and anonymous.
Only essential background information such as any diagnoses, number and nature of
offences, and behavioural infractions whilst in prison, will be attained through your file.
This background information will be stored anonymously on a secure database that is
only available to the research team.
What are the possible disadvantages and risks of taking part?
There are no health risks to taking part, however if you find the topics of conversation a
bit difficult, you may access support from the prison’s medical unit.
What are the possible benefits of taking part?
The research team hope that you will find the research interesting, but they cannot
promise that the study will help you. As you have the option of sharing results with the
medical unit this may inform your rehabilitation. We hope the information the
researchers get from this study may help inform rehabilitation programs, and how to
support individuals both in prison and on release.
123
Will my taking part in this study be kept confidential?
All information which is collected in the course of this research will be kept strictly
confidential. During the study you will be allocated a participant number. This will
ensure that throughout the study, you will remain anonymous. If you tell the researchers
of behaviour that is against prison rules and can be adjudicated against, illegal acts, and
behaviour which could represent a risk to yourself or others, then this will be reported to
prison staff, who should record this in your notes. The data collected in this study will
be used only for the purpose described in this form. All records related to your
involvement in this research will be stored securely. Data gathered from this study will
be maintained as long as required by regulations.
This research is part of a doctoral project, and will be written up in the thesis, which is
kept at the University of Surrey. Any information which is disseminated will be
completely anonymised so that you cannot be recognised from it.
What if I am unhappy or there is a problem?
If you are unhappy, or if there is a problem, please feel free to let us know by contacting
a member of the research team through the prison, and we will try to help. If you remain
unhappy or have a complaint which you feel you cannot come to us with then you
should the prison staff can put you in contact with the Head of the School of
Psychology at the University.
Who is organising and funding the research?
This research is being organised by the Disabilities Trust.
OK, so what happens now?
If you’d like to take part, you need to sign the form saying that you agree to participate.
Further information and contact details.
124
For any more information, or to answer any questions you may have, please ask a
member of prison staff who can put you in contact with a member of the research team.
Michelle O’ Sullivan & Steven Fitzsimons
School of Psychology, Faculty of Arts & Human Sciences
University of Surrey
You will be given a copy of the information sheet and a signed consent form to keep, in case you wish to refer to it in the future.
125
Appendix IX
Participant Consent Form
126
Participant Consent Form
Traumatic Brain Injury in Adult Female Offenders in the UK
Name of lead researchers: Michelle O’ Sullivan & Steven Fitzsimons
Please initial the relevant boxes
1. I confirm that I have read or the form has been read to me and understand the information sheet for the above study. I have had the opportunity to consider the information, ask questions and have had those answered satisfactorily.
2. I understand that my participation is voluntary and that I am free to withdraw at any time without giving any reason.
3. I understand that data collected during the study may be looked at by individuals from the research team and from regulatory authorities where it is relevant to my taking part in this research. I give permission for these individuals to have access to my data.
4. I understand that my participation is voluntary and that I am free to withdraw at any time, without giving any reason, without my medical care or legal rights being affected.
5. I agree to take part in the above study.
6. I understand that if I tell the researchers of behaviour that is against prison rules and can be adjudicated against, illegal acts, and behaviour which could represent a risk to myself or others, then this will be reported to prison staff, who should record this in my notes.
Name of Participant Date Signature
________________________ __________________ _______________
I have explained the study to the participant and have answered their questions
honestly and fully
Researcher Date Signature
________________________ ________________
_______________
127
Appendix X
Participant Feedback Pro Forma
128
PARTICIPANT FEEDBACK
Date assessment completed:
Prisoner No. _________ participated in a research study which involved an assessment
of her mood and cognition. This is a standardised research protocol and has not been
designed to assess this individuals’ clinical needs. Assessment results suggest that this
participant may be experiencing difficulties in the domains highlighted below. The
assessment results have been explained to the participant and they have consented to
these results being recorded in their notes and highlighted to healthcare. Results that are
of particular concern are highlighted in yellow. These results indicate that the
participant would benefit from a more in-depth assessment of their clinical needs.
This research has been approved by the National Offender Management Service
National Research Committee, reference no.: 2013-266.
Beck Depression Inventory II
Total Score: (mild/moderate/severe depression)
Beck Anxiety Inventory
Total Score: (mild/moderate/severe anxiety)
The Impact of Events Scale
Total Score: (a score above 33 indicates that this participant may be at risk of
posttraumatic stress disorder)
129
Wechsler Abbreviated Scale of Intelligence II
Full Scale IQ: percentile (qualitative descriptor)
Perceptual Reasoning Index: percentile (qualitative descriptor)
Verbal Comprehension Index: percentile (qualitative descriptor)
Repeatable Battery for the Assessment of Neuropsychological Status
Immediate Memory Index: percentile (qualitative descriptor)
Visuospatial/constructional Index: percentile (qualitative descriptor)
Language Index: percentile (qualitative descriptor)
Attention Index: percentile (qualitative descriptor)
Delayed Memory Index: percentile (qualitative descriptor)
Total score: percentile (qualitative descriptor)
Behavioural Assessment of the Dysexecutive Syndrome
Classification:
Risk issues or other researcher observations:
130
Appendix XI
OASys Items Extracted
131
Item 1.1a category of index offence
Item 1.8 Age at first contact with police
Item 1.26 Number of violent previous offences (with current offence added if
also violent)
Item 1.7 Age at first conviction
Item 6.3 Experience of childhood abuse
Item 6.7 Victim of domestic violence
OGP probability of proven non-violent reoffending Year 1%
OVP probability of proven violent-type reoffending Year 1%
Severity of violent offences
Level of violence if robbery is index offence
132
Appendix XII
Correspondence Regarding Ethical Approval
133
134
135
Appendix XIII
Normality Data
136
Table 17. Normality Data for Reliability Variables
Variable Z score Interpretation
Skewness Kurtosis
BISI age at 1st TBI -.079 -.505 Normal
Total number of TBI .627 -.505 Normal
Longest LOC 3.645 2.700 Positive skew & positive kurtosis
TBI Time index 4.026 3.910 Positive skew & positive kurtosis
Repeat BISI Age at 1st TBI -.439 -.891 Normal
Repeat Total number of TBI -.065 -1.448 Normal
Repeat Longest LOC 4.166 3.945 Positive skew & positive kurtosis
Repeat TBI Time index 5.269 8.136 Positive skew & positive kurtosis
TBI Severity Index 1.671 .340 Normal
Repeat TBI Severity Index 2.900 3.840 Positive skew & positive kurtosis
BISI Global Score 1.020 -1.006 Normal
Repeat BISI Global Score 1.488 -.849 Normal
Total no. of episodes of
PTA
.952 -.589 Normal
BISI no. of episodes of
dizziness
.056 -.965 Normal
Repeat BISI total no. of
episodes of PTA
1.602 .024 Normal
Repeat BISI total no. of
dizziness episodes
.620 -1.154 Normal
137
Table 18. Normality Data for Standardised Measures
Variable TBI Group Non-TBI Group
Z score Interpretation Z score Interpretation
Skewness Kurtosis
Normal
Skewnes
s
Kurtosis
Age 0.427 -1.281 .493 -1.569 Normal
Education -.659 .713 Normal .045 -1.305 Normal
TOMM -6.007 11.262 Negative
skew &
positive
kurtosis
- - TOMM
value is
constant in
non-TBI
group
BAI .455 .523 Normal .775 -1.220 Normal
BDI .714 -.098 Normal -.246 -1.514 Normal
TOPF with
Demo
.570 -.436 Normal -.046 .024 Normal
TOPF raw .687 -.503 Normal -0.078 -0.434 Normal
RBANS
immediate
memory
-.083 0.109 Normal -1.682 0.287 Normal
RBANS
visuospatial
1.427 1.026 Normal .906 -.867 Normal
RBANS
language
.374 -.613 Normal 1.633 1.821 Normal
RBANS
attention
-.063 -1.148 Normal 2.392 2.709 Positive
skew &
138
positive
kurtosis
RBANS
delayed
memory
-1.556 .807 Normal -3.190 4.120 Negative
skew &
positive
kurtosis
RBANS total 0.345 .730 Normal -1.693 1.132 Normal
BADS age
corrected
-2.028 1.193 Negatively
skewed
-1.634 1.401 Normal
BADS raw -2.148 1.314 Negatively
skewed
-1.829 1.650 Normal
DEX .356 -.180 Normal .971 .007 Normal
IES -.393 -.230 Normal .675 .304 Normal
NFI Dep % -1.241 .403 Normal -.484 -1.376 Normal
NFI Dep T .097 0.350 Normal -.807 -.654 Normal
NFI Dep Raw .007 .263 Normal -.721 -.752 Normal
NFI Somatic
%
-.420 -1.345 Normal -.049 -.800 Normal
NFI Somatic
Raw
.659 -.870 Normal -.726 -.558 Normal
NFI Somatic T 1.214 -.154 Normal -.686 -.691 Normal
NFI Memory
%
.001 -1.203 Normal .581 -.865 Normal
NFI Memory T .001 -.554 Normal -.118 -.733 Normal
NFI Memory -.132 -.872 Normal -.804 .525 Normal
139
Raw
NFI
communication
%
-.636 -1.006 Normal 1.331 -.016 Normal
NFI
communication
T
.524 .125 Normal .935 -.320 Normal
NFI
communication
raw
.436 -.257 Normal .507 -.272 Normal
NFI aggression
%
.186 -1.114 Normal .437 -1.096 Normal
NFI aggression
T
.537 -.881 Normal .188 -1.086 Normal
NFI aggression
raw
1.232 -.560 Normal .575 -1.446 Normal
NFI motor % .413 -.804 Normal .508 .035 Normal
NFI motor T .395 -.549 Normal -.818 .858 Normal
NFI motor raw .404 -1.144 Normal -1.428 .954 Normal
WASI VC -.125 .490 Normal -.162 -1.437 Normal
WASI PR -1.008 -.299 Normal .104 .213 Normal
WASI FS4 .171 -.410 Normal .216 -.436 Normal
WASI-TOPF .021 -.224 Normal -.376 -.650 Normal
140
Figure 3. Normality Histogram for BISI Age of 1st TBI
141
Figure 4. Normality Histogram for BISI Total No. of TBI
142
Figure. Normality Histogram for BISI TBI Time Index Score
143
Figure 5. Normality Histogram for Repeat BISI Age of 1st TBI
144
Figure 6. Normality Histogram for Repeat BISI Longest LOC
145
Figure 7. Normality Histogram for Repeat BISI Total No. of TBI
146
Figure 8. Normality Histogram for Repeat BISI TBI Time Index Score
147
Figure 9. Normality Histogram for BISI TBI Severity Index Score
148
Figure 10. Normality Histogram for Repeat BISI TBI Severity Index Score
149
Figure 11. Normality Histogram for BISI Global Score
150
Figure 12. Normality Histogram for Repeat BISI Global Score
151
Figure 13. Normality Histogram for BISI Total No. of Episodes of PTA
152
Figure 14. Normality Histogram for BISI Total No. of Episodes of Disorientation
153
Figure 15. Normality Histogram for Repeat BISI Total No. of Episodes of PTA
154
Figure 16. Normality Histogram for Repeat BISI Total No. of Episodes of
Disorientation
155
Figure 17. Normality Histogram for WASI-TOPF with TBI group
156
Figure 18. Normality Histogram for WASI-TOPF with no TBI group
157
Figure 19. Normality Histogram for Age with TBI group
158
Figure 20. Normality Histogram for Age with no TBI group
159
Figure 21. Normality Histogram for Years in Education with TBI group
160
Figure 22. Normality Histogram for Years in Education with no TBI group
161
Figure 23. Normality Histogram for TOMM Trial 2 with TBI group
162
Figure 24. Normality Histogram for BAI with TBI group
163
Figure 25. Normality Histogram for BAI with no TBI group
164
Figure 26. Normality Histogram for BDI-II with TBI group
165
Figure 27. Normality Histogram for BDI-II with no TBI group
166
Figure 28. Normality Histogram for TOPF Raw with TBI group
167
Figure 29. Normality Histogram for TOPF Raw with no TBI group
168
Figure 30. Normality Histogram for RBANS Immediate Memory with TBI group
169
Figure 31. Normality Histogram for RBANS Immediate Memory with no TBI group
170
Figure 32. Normality Histogram for RBANS Visuospatial with TBI group
171
Figure 33. Normality Histogram for RBANS Visuospatial with no TBI group
172
Figure 34. Normality Histogram for RBANS Language with TBI group
173
Figure 35. Normality Histogram for RBANS Language with no TBI group
174
Figure 36. Normality Histogram for RBANS Attention with TBI group
175
Figure 37. Normality Histogram for RBANS Attention with no TBI group
176
Figure 38. Normality Histogram for RBANS Delayed Memory with TBI group
177
Figure 39. Normality Histogram for RBANS Delayed Memory with no TBI group
178
Figure 40. Normality Histogram for RBANS Total Score with TBI group
179
Figure 41. Normality Histogram for RBANS Total Score with no TBI group
180
Figure 42. Normality Histogram for IES-R with TBI group
181
Figure 43. Normality Histogram for IES-R with no TBI group
182
Figure 44. Normality Histogram for WASI Verbal Comprehension with TBI group
183
Figure 45. Normality Histogram for WASI Verbal Comprehension with no TBI group
184
Figure 46. Normality Histogram for WASI Perceptual Reasoning with TBI group
185
Figure 47. Normality Histogram for WASI Perceptual Reasoning with no TBI group
186
Figure 48. Normality Histogram for WASI Full Scale IQ with TBI group
187
Figure 48. Normality Histogram for WASI Full Scale IQ with no TBI group
188
Figure 49. Normality Histogram for NFI Depression Raw with TBI group
189
Figure 50. Normality Histogram for NFI Depression Raw with no TBI group
190
Figure 51. Normality Histogram for NFI Somatic Raw with TBI group
191
Figure 52. Normality Histogram for NFI Somatic Raw with no TBI group
192
Figure 53. Normality Histogram for NFI Memory Raw with TBI group
193
Figure 54. Normality Histogram for NFI Memory Raw with no TBI group
194
Figure 55. Normality Histogram for NFI Communication Raw with TBI group
195
Figure 56. Normality Histogram for NFI Communication Raw with no TBI group
196
Figure 57. Normality Histogram for NFI Aggression Raw with TBI group
197
Figure 58. Normality Histogram for NFI Aggression Raw with no TBI group
198
Figure 59. Normality Histogram for NFI Motor Raw with TBI group
199
Figure 60. Normality Histogram for NFI Motor Raw with no TBI group
200
Figure 61. Normality Histogram for BADS Total Score with TBI group
201
Figure 62. Normality Histogram for BADS Total Score with no TBI group
202
Major Research Project Proposal Form
This form should be completed by the trainee and signed by the University supervisor, and then submitted by the deadline.
Remember to give a draft to your supervisor for comments before submitting the final version.
When preparing this document it would be helpful to consider what you would include when writing the Introduction and Method
sections for your MRP.
* Please append your literature review to this proposal
URN: 6242697
Project Title: Traumatic Brain Injury in Adult Female Offenders in the UK
Introduction
Background and Theoretical Rationale
TBI: Definition and prevalence
Traumatic brain injury (TBI) is “an alteration in brain function, or other evidence of
brain pathology, caused by an external force” (Menon et al., 2010). TBI is the most
common form of acquired brain injury (ABI; Fleminger & Ponsford, 2005), with an
estimated prevalence of 8.5% in the general population (Silver et al., 2001) across all
levels of severity. Incidence ranges from 91-419 per 100,000 in England (Tennant,
2005).
Relationship between TBI and offending
Clinical opinion suggests that violence and impulsive behaviours are both antecedents
and consequences of TBI (Anderson et al., 1999). Violence following TBI has been
characterised as unpredictable, ill-directed, and can occur in the absence of clear
triggers or provocation (Eslinger et al., 1995; Wood & Liossi, 2006). Individuals with
TBI have a significantly increased risk of committing a violent crime (Fazel et al.,
2011). While TBI cannot be assumed to be the sole cause of offending, the cognitive
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and behavioural sequelae of TBI may predispose some individuals (Brower & Price,
2001; deSouza, 2003; Greve et al., 2001; Kreutzer et al., 1995; Kreutzer et al., 1991;
Miller, 1999; Simpson et al., 1999).
Relationship between TBI in females and offending
A recent report commissioned by the Barrow Cadbury Trust emphasised the need for
research examining causes and consequences of TBI in female offenders specifically
(Williams, 2012). Shiroma, Ferguson and Picklesimer’s (2010a) study of TBI in US
prisoners revealed a male and female prevalence estimate of 64.41% (95% CI: 53.3 to
75.53%) and 69.98% (95% CI: 50.18-89.79%) respectively. The prevalence of TBI in
UK female offenders is currently unknown. A valid screen for TBI in female offenders
would facilitate research and support clinical practice. There are currently no validated
published screening tools for use with UK female offenders. The Brain Injury Screening
Index (BISI; Pitman et al., 2013) has been validated in male offenders in the UK, but
has yet to be extended to females.
Without adequate screening in female offenders, TBI is likely to go undetected, and
may impact on engagement in offender rehabilitation programs and the legal process
(Jackson & Hardy, 2011). Individuals with TBI may be more difficult to rehabilitate and
discharge (Hawley & Maden, 2003), with services ill-equipped to address their needs.
Research in this field is congruent with the Transforming Rehabilitation strategic
business priorities within the National Offender Management Service (NOMS; National
Offender Management Service, 2013) and may increase efficiency by informing
programs to reduce recidivism.
Officials within the criminal justice system may misinterpret behaviour of offenders
with TBI (Merbitz et al., 1995; Shiroma et al., 2010b). Research demonstrating
increased disciplinary incidents in prisoners with TBI (Merbitz et al., 1995; Morrell et
204
al., 1998; Shiroma et al., 2010b) suggests that they may have increased difficulty
adapting to prison life due to cognitive and behavioural sequelae. This has implications
for engagement in the legal process, prison management, and post-discharge and release
pathways (Jackson & Hardy, 2011). Under-identification is likely to perpetuate
inadequate resources, providing no incentive to fund appropriate interventions and
inefficient use of available resources. Screening is consistent with NOM’s Reducing
Prison Unit Costs strategic business priority by ensuring appropriate services are
commissioned and targeting the most appropriate offenders (NOMS, 2013), e.g.
screening can provide a cost-effective way of determining who is appropriate for
referral to more limited and expensive resources such as neuropsychologists, or
alternative care pathways.
Risk factors for offending in females with TBI
Females are reportedly less likely to offend than males, yet those who do are more
likely to be experiencing a mental illness (Butler et al., 2005; Fazel & Grann, 2006).
New-onset major depression post-TBI increases the risk of aggression for females
eightfold (Rao et al., 2009). PTSD may also be a significant risk factor (Johansson et
al., 2008). Comorbidities may moderate or mediate the relationship between TBI and
offending in females.
Physical and sexual abuse throughout the lifespan may be a risk factor (Brewer-Smyth
& Burgess, 2008; Brewer-Smyth, Burgess, & Shults, 2004; Shiroma et al., 2010b).
Abuse commences for female prisoners at a young age (Browne et al., 1999). Childhood
victimisation strongly predicts victimisation in adulthood (Browne et al., 1999), and
adult victimisation in turn increases the risk of TBI (Kwako et al., 2011), which may
lead to increased violent behaviour. This is consistent with Brewer-Smyth and Burgess’
205
(2008) findings that female prisoners with more TBIs and violent crime convictions
have increased childhood family sexual abuse.
Post-TBI aggression may be related to being a victim of intimate partner violence
specifically. Shiroma et al. (2010b) found a decreased likelihood of suffering a TBI
whilst incarcerated. Brewer-Smyth et al. (2004) found increased recency of abuse and
hospitalisations for abuse-related injuries in those with violent crime convictions, with
most TBIs occurring in the fronto-temporal region, which has been related to post-TBI
aggression in the literature (Daoust et al., 2006).This lends some tentative support for a
relationship between intimate partner violence and post-TBI aggression.
Brewer-Smyth et al. (2004) examined the cumulative effects of recurrent TBIs on
violence, finding evidence for a dose-response effect between number of TBIs and
violence. These findings are consistent with previous research which has found reported
prevalence rates of multiple TBIs in female offenders ranging from 35-48% (Ferguson
et al., 2012). Multiple mild TBIs can have similar cognitive and behavioural profiles to
individuals with more severe TBI (Diamond et al., 2007).
Research Questions
How prevalent is TBI and how does TBI present itself in the cognitive, psychiatric
and health needs of female prisoners in the UK?
Is self-reported TBI using the BISI associated with cognitive performance in
standardised questionnaires and neuropsychological tests?
Main Hypotheses
Female offenders in the UK demonstrate similar prevalence of TBI as males.
The BISI provides an estimate of prevalence within the confidence intervals of
studies using clinical interviewing.
206
Results of the BISI will be significantly associated with those obtained in the
standardised questionnaires and neuropsychological tests.
The BISI will have a test-retest reliability coefficient of at least 0.60.
Female offenders with self-reported TBI have significantly more cognitive,
psychiatric, and physical health difficulties than female offenders without TBI.
Female offenders with self-reported TBI have higher historical rates of recidivism
and behavioural infarctions that those without TBI.
Method
Participants
Participants will be recruited from prisons for women in southern England, with four
potential prison sites. These prisons have a combined operational capacity of
1,607women from which potential participants can be recruited.
To explore prevalence and severity of TBI in the UK (stage 1), using Daniel and Cross’
(2013) formula for sample size calculation for prevalence studies, on the basis of a level
of confidence of 95%, an expected prevalence of 66% in female offenders using the
gold standard of clinical interviews (Shiroma et al., 2010a), and a precision value of
0.125, a sample of 56 female offenders would be required for stage 1. A large precision
value was chosen due to feasibility related to resource limitations, and the preliminary
nature of this research. The precision value meets the assumption of normal
approximation. To assess the test re-test reliability of the BISI, based on a minimum
reliability of 0.6, an expected reliability of 0.8, α=0.05 and β=.20, an estimated sample
of 39 of the original 56 will be required (Walter, Eliasziw, & Donner, 1998).
To explore the differences in cognitive, psychiatric and health needs of female offenders
with TBI and those without TBI, as well as rates of recidivism and behavioural
infarctions, based on the number of variables being measured, an anticipated large effect
207
size, statistical power of .80 and type I error α of .003 (Bonferroni correction for 14
comparisons), a sub selection of 28 participants with TBI and 28 without TBI will be
required for stage 2.Based on similar research using the BISI with male prisoners
(Pitman et al., 2013) the estimated response rate is 73%, therefore a total of 76 prisoners
will be approached for consent.
Inclusion criteria include prisoners over 18, with an upper age limit of 80 years of age in
line with norms provided in the instruments to be used. Exclusion criteria include acute
symptoms of physical or mental illness or other indication that participants may not be
able to provide informed consent. This will be achieved by excluding participants in the
medical unit. Acute illness and ability to provide consent is also assessed in the clinical
interview, at which point the assessment will be terminated. Prisoners with a confirmed
diagnosis of dyslexia, are not fluent in English, or have reported acquiring a TBI in the
last 6 months, will be excluded from stage 2 due to validity limitations of measures.
Participants with a learning disability will be included unless queries regarding capacity
to consent are raised when are being briefed.
Design
Cross-sectional design using a semi-structured clinical interview, clinical
questionnaires, and neuropsychological measures.
Measures/Interviews/Stimuli/Apparatus
Please see Appendix I for the Participant Information Sheet and Appendix II for the
Participant Consent Form. For psychometric properties of measures please refer to
Table 1 Appendix III. The following assessment tools will be employed:
Semi-structured interview designed for use in male prisoners, which has been adapted to
extend to research to female prisoners (Appendix IV)
Pro forma for collecting data from participant files (Appendix V)
208
The Brain Injury Screening Index (BISI; Appendix VI)
The Wechsler Abbreviated Scale of Intelligence II (WASI-II; Wechsler & Zhou, 2011).
The Test of Premorbid Functioning – UK Version (TOPF; Wechsler, 2009)
The Behavioural Assessment of the Dysexecutive Syndrome (BADS; Wilson,
Alderman, Burgess, Emslie, & Evans, 1996)
The Repeatable Battery for the assessment of Neuropsychological Status (RBANS;
Randolph, 1998)
The Test of Memory Malingering (TOMM; Tombaugh, 1996)
Neurobehavioral Functioning Inventory (NFI; Kreutzer, Seel, & Marwitz, 1999)
The Beck Anxiety Inventory (BAI; Beck, Epstein, Brown, & Steer, 1988)
The Beck Depression Inventory II (BDI; Beck, Steer, & Brown, 1996)
The Impact of Events Scale – Revised (IES-R; Appendix VI; Weiss & Marmar, 1997)
Pro formas are not provided in the appendices for assessments restricted due to
copyright.
Procedure
1. Participants will be recruited through a convenience sample. A list of prisoners who
have been new receptions over a 1-2 month period (depending on average intake
rate- until 76 participants are obtained for sufficient power and response rate
considerations) will be provided by prison staff. Prison staff will act as gatekeepers
and be asked to identify participants under 18, over 80, admitted to the medical unit,
or who cannot provide informed consent.
209
2. Eligible participants will be provided with a copy of the participant information
sheet and consent form, i.e. a copy will be dropped into their cells by a member of
the research team.
3. Within a week of providing the information sheets prisoners will be contacted face-
to-face by a member of the research team to discuss the participation and consent. A
suitable time to commence assessment will be arranged with those who agree to
participate.
4. Participants will be allocated a participant number, which will be recorded with their
prison reference number, and recorded on an encrypted device. This will be separate
from the main data collection file.
5. At assessment, participants will complete the BISI and clinical interview (stage 1).
This will take approximately 1 hour. Participants will be provided with the clinical
questionnaires in the interview and asked to complete them in their own time. These
will then be collected at the end of each day of data collection. Participants will
complete all questionnaires themselves. Data on social history, abuse history,
clinical history, offence history, and behavioural infractions, will be obtained for
these participants from Offender Assessment System (OASys), probation and re-
offending records, and individual history files.
6. Participants will have the option of progressing on to stage 2 straight after stage 1,
or arranging a time to continue with the assessment.
7. Stage 2, consisting of the battery of neuropsychological measures, will occur at an
arranged time, with an expected sample of 28 participants with TBI and 28 without
a history of TBI. This will take 1½-2 hours.
210
8. Participants who progress from stage 1 to stage 2 within 1-2 weeks of completing
the BISI will be asked to complete the BISI again for the purpose of test-retest
validity, until the required sample of 39 is reached.
9. As data is gathered it will be encoded in an SPSS data file stored on an encrypted
device for analysis.
10. Once data collection is completed appointments will be arranged with participants
who request an assessment feedback session. Participants may also request to have
results shared with the prison/health service. A brief report with results will be
provided.
Ethical considerations
1. Great effort will be made to clarify the nature of the relationship between the
researchers conducting assessments and the participant; i.e. it is not an assessment
from a clinical referral, that the primary purpose is research. However, participants
will have the opportunity to have a feedback session after the data collection is
completed and/or to have results shared with the prison/health services. Feedback
will be primarily descriptive and can be used to indicate if support from health
services is required.
2. Feedback on neuropsychological tests may impact on self-esteem, as mean prison
IQ in the UK is 88 (±12.0) (Hayes, Shackell, Mottram, & Lancaster, 2007). It is
hoped that the provision of information and training to staff and the potential for
additional support following the research will enable participants to feel
empowered, with the resources to manage difficulties.
3. Participants may assume that test results can be used for secondary gain, however
when briefing the participants it will be emphasised that tests will not be for clinical
211
use, and only a recommendation for a comprehensive clinical examination can be
made. The TOMM (Tombaugh, 1996) will also be used to assess effort.
4. Due to the time required of participants motivation and fatigue may invalidate
results. To manage this, participants can complete stages on different days if they
wish, or have a brief break during testing if requested.
5. To ensure test validity the participating prisons will be requested to provide a quiet
environment, with adequate space, ventilation, lighting and furniture. We will also
liaise with staff to try to minimise potential interruptions during testing.
6. Information that is related to risk to self or others, including drug use and abuse,
may be disclosed. The research team will liaise with participating prisons to ensure
that the research protocol is congruent with prison policy to manage risk. Potential
limits to confidentiality will be made explicit to participants when obtaining
consent.
Name of Ethics Committee: University of Surrey Ethics Committee: Faculty of Arts and
Human Sciences; National Offender Management Service............................
R&D Considerations
Name of R&D department: R&D approval is not required however a letter of support
from governors of participating prisons will be obtained.
Proposed Data Analysis
All analyses will be done using IBM SPSS version 20 (IBM, 2011). Data will be
checked for normality of distribution and homogeneity of variance.
Descriptive statistics, including age, proportion of participants with a TBI, ethnicity,
education, learning disability, special support at school, diagnosis of mental health
problem, history of self-harm, suicide attempts, frequency of drug and alcohol use, age
212
at first offence, number of offences, number of violent convictions, number of
behavioural infractions, participation in rehabilitation programs, and years spent in
custody, will be provided for those with an identified TBI and those without. This will
include means and standard deviations, and t-tests comparing those with and without a
TBI where appropriate. Further descriptive statistics will be provided for those with a
TBI, namely: number of TBIs, age at earliest TBI, loss of consciousness, cause of
injury, and help-seeking behaviour after TBI.
Concurrent validity of the BISI will be studied by calculating Pearson’s r between the
BISI and clinical interview. Receiver Operating Curve analysis will also be conducted
to assess sensitivity and specificity rates against clinical interview as the gold standard.
Test-retest reliability will be assessed using Pearson’s r.
Between samples t-tests will explore differences participants with TBI and without TBI
on cognitive, psychiatric and physical health measures.
Service User and Carer Consultation / Involvement
Service user and carer consultation was undertaken on 6th August 2013 and informed
this proposal (see Appendix VI for feedback).
Feasibility Issues
As the study is highly dependent on the amenability of the prison involved, there
must be organisational incentive for participation. After the study is complete,
the research team will provide a training and information session with prison
staff to support them in their roles when working with female offenders with
TBI.
Prisons participating must be able to provide adequate support in the event that
participants are distressed after the study. To overcome this we are liaising with
potential prisons and will prioritise the research site accordingly. We are also
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aiming to obtain sensitive data on abuse history from the OASys to reduce the
risk of distress.
Cost of pro formas for the copyrighted measures used is high (totalling
£1418.40), and exceeds the research budget provided by the University of
Surrey. The Disabilities Trust have agreed to cover the cost of pro formas
exceeding the research budget.
Dissemination strategy
Analysed data will be written up in a thesis as part of a doctorate, and disseminated
through research articles (e.g. The Journal of Head Trauma; Brain Injury) and
conferences (The Annual Division of Forensic Psychology conference; International
Association of Forensic Mental Health conference). A briefing can also be provided for
the prison’s newsletter. The Disabilities Trust Foundation will publish results through
reports, presentations, journal articles, and on their website.
Study Timeline
Please see Gantt chart in Appendix VII.
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PSYCHD CLINICAL PSYCHOLOGY
MRP Literature Review
Title: ‘Traumatic brain injury and violent behaviour in females:
A systematic review’
Student URN: 6242697
April 2013
Word count: 7,997
215
Abstract
Research has demonstrated that individuals with traumatic brain injury (TBI) have a
significantly increased risk of committing a violent crime. Whether and how this increased
risk of violent behaviour may present itself in females is not clear. Given the heterogeneity
of study design and sample populations in the literature, a systematic review aiming at
synthesising the literature on the relationship between TBI and violence in females is
presented. Three main psychological and medical databases were searched (PsychINFO,
Scopus, and PubMed). Six studies met the inclusion criteria. Results across these studies were
inconsistent, and due to methodological limitations and scarcity of research, it was concluded
that there is insufficient evidence to determine if there is a relationship between TBI and
violence in females. However, the studies reviewed contributed knowledge of other factors
that may influence this relationship, including psychiatric comorbidities and childhood abuse.
Implications for future research and clinical practice are discussed.
1. Introduction
1.1. Traumatic Brain Injury
Traumatic brain injury (TBI) is defined as “an alteration in brain function, or other evidence
of brain pathology, caused by an external force” (Menon, Schwab, Wright, & Maas, 2010),
capturing the range of presentations which fit under the TBI diagnostic umbrella, including
loss of or decreased consciousness, any loss of memory, neurological deficits, and any
alteration in mental state e.g. confusion (Menon et al., 2010). TBI is the most common form
of acquired brain injury (Fleminger & Ponsford, 2005) (ABI), with an estimated prevalence
of 8.5% (Silver, Kramer, Greenwald, & Weissman, 2001) across all levels of severity.
Annual incidence of TBI ranges from 180-250 per 100,000 in the United States (US; Bruns &
Hauser, 2003), and 91-419 per 100,000 in England (Tennant, 2005); however, rates may
overlook milder TBI due to reliance on medical records (Tennant, 2005) and associated
diagnostic and selection biases (Feigin et al., 2013). TBI severity traditionally has been
classified by scores on the Glasgow Coma Scale (GCS; World Health Organization, 2006).
Other commonly used measures include post-traumatic amnesia (PTA) and length of loss of
consciousness (LOC; Sherer, Struchen, Yablon, Wang, & Nick, 2008). Table 1 Appendix I
summarises typical cut-offs used for differentiating mild, moderate and severe TBI. Many
research studies do not adhere to this definition and classification systems for TBI, making
comparison across studies difficult (Corrigan, Selassie, & Orman, 2010), highlighting the
need for systematic reviews to lend coherence to the literature.
Up to twice the rate of TBI has been found in males than females in the general population
(Hillbom & Holm, 1986; Hirtz et al., 2007). This apparent protective effect of female gender
appears attenuated in specific populations, including those with substance use disorder
(Felde, Westermeyer, & Thuras, 2006) and prisoners (Brain Injury Association of Wyoming,
2008; Ferguson, Pickelsimer, Corrigan, Bogner, & Wald, 2012). Risk of TBI in females
appears to be more pronounced with milder TBI, e.g. Diamond, Harzke, Magalett, Cummins
and Frankowski (Diamond, Harzke, Magaletta, Cummins, & Frankowski, 2007) found that
54.7% of females in a prison population self-reported TBI with no LOC in comparison to
40% of males. This fell to 35.6% of females in comparison to 47.8% of males with LOC of
less than one hour. Differences may be attributable to different gender-related behavioural
patterns, as well as decreased likelihood of reporting mild TBIs. TBI in females may be
underestimated due to unreported experiences of intimate partner violence (Valera &
Berenbaum, 2003). Due to the nature of intimate partner violence it is difficult to get an
accurate prevalence rate of TBI in this population, however reported rates vary from 30-74%
(Kwako et al., 2011). Meta-analysis has found that females tend to have worse outcomes after
TBI than males across all TBI types (Farace & Alves, 2000). Although reviews and meta-
analyses have examined some gender-related factors, e.g. intimate partner violence (Kwako
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et al., 2011) and outcomes (Farace & Alves, 2000), there are an abundance of issues such as
violence in females with TBI which have yet to be explored systematically.
1.2. TBI and violence
For the purpose of this review, the definition of violence is confined to physical acts that
could cause harm to others. This maintains consistency with the forensic mental health
literature (Monahan et al., 2001). For context, this review draws upon the heterogeneous
literature available, examining related concepts such as verbal aggression and general
offending, in the introduction and discussion.
TBI is a complex condition that can result in an array of cognitive, emotional, physical and
behavioural sequelae. Clinical opinion suggests that violence and impulsive behaviours are
both antecedents and consequences of TBI (Anderson, Bechara, Damasio, Tranel, &
Damasio, 1999). TBI has been associated with increased risk of developing comorbid
conditions (Timonen et al., 2002), including substance abuse (Honer et al., 2005), epilepsy
(Ferguson et al., 2010), psychoses (McAllister, 1998), post-traumatic stress disorder (PTSD;
Rogers & Read, 2007) and aggression (Alderman, 2007; Cole et al., 2008; Rao et al., 2009;
Visscher, van Meijel, Stolker, Wiersma, & Nijman, 2011). Females may be particularly at
risk for developing depression (Whelan-Goodinson, Ponsford, Schönberger, & Johnston,
2010) and anxiety (Hibbard, Uysal, Kepler, Bogdany, & Silver, 1998) post-TBI. Aggression
and violence following TBI has been characterised as unpredictable, ill-directed, and can
occur in the absence of clear triggers or provocation (Eslinger, Grattan, & Geder, 1995;
Wood & Liossi, 2006). Research from the Swedish population registers, the only population-
based cohort study of its kind, found that individuals with TBI have a significantly increased
risk of committing a violent crime (Fazel, Lichtenstein, Grann, & Långström, 2011). While
TBI cannot be assumed to be the sole cause of violence, it does suggest that the cognitive and
behavioural sequelae of TBI may predispose some individuals to violence (Miller, 1999).
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Over a decade ago the Aspen Neurobehavioural Conference (Filley et al., 2001) released a
consensus statement that epidemiological research of risk factors needed to be a research
priority. This review aims to further our understanding of the epidemiology and outcomes of
TBI and how it may relate to violence.
Research suggests that aggression is specifically related to the temporal and frontal lobes
(Daoust, Loper, Magaletta, & Diamond, 2006). While clinical profiles of TBI can be
variable, mild and moderate TBI, which victims of intimate partner violence may be more
susceptible to, are often localised in the orbito-frontal and temporal polar zones (Zappalà,
Thiebaut de Schotten, & Eslinger, 2012). Meta-analyses have demonstrated a medium effect
size for the relationship between antisocial behaviour and neuropsychological measures of
executive functioning (Morgan & Lilienfeld, 2000; Ogilvie, Stewart, Chan, & Shum, 2011),
however this area of neuropsychological research is marred by methodological problems,
rendering findings inconclusive (Morgan & Lilienfeld, 2000; Ogilvie et al., 2011). Similarly,
comparing aggressive with non-aggressive individuals with severe TBI, some research has
demonstrated no significant cognitive differences (Greve et al., 2001). However, another
study of severely injured individuals found significant deficits in verbal memory and visuo-
perceptual skills in the aggressive group (Wood & Liossi, 2006).
Without successful early intervention, individuals with TBI may pose a risk to others and
become involved in the criminal justice system (Brower & Price, 2001; deSouza, 2003;
Greve et al., 2001; Kreutzer, Marwitz, & Witol, 1995; Kreutzer, Wehman, Harris, Burns, &
Young, 1991; Miller, 1999; Simpson, Blaszczynski, & Hodgkinson, 1999). Once there,
individuals with TBI may be more difficult to rehabilitate and discharge, with services ill-
equipped to address their needs. Hawley and Maden’s (2003) study of TBI in medium secure
units (MSUs) indicated that 41.6% of service users had a history of TBI, and were
significantly more difficult to discharge into the community due to perceived greater risk of
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violence to others and self-harm. Research demonstrating increased disciplinary incidents in
prisoners with TBI (Merbitz, Jain, Good, & Jain, 1995; Morrell, Merbitz, Jain, & Jain, 1998;
Shiroma et al., 2010b) suggests that they may also have increased difficulty adapting to
prison life due to cognitive and behavioural sequelae. This has implications for engagement
in the legal process, prison management, and post-discharge and release pathways (Jackson &
Hardy, 2011). Due to inadequate screening and identification of TBI, services are unable to
provide adapted rehabilitation for this population. Under-identification is likely to perpetuate
inadequate resources, providing no incentive to fund appropriate interventions. Evidence of
publication bias in studies on TBI and violence has also been found (Fazel, Philipson,
Gardiner, Merritt, & Grann, 2009), highlighting the difficulties of conducting research and
applying evidence-based practice.
Recent research in male populations in this area is leading to increased resources, e.g. the
placement of a prison brain injury linkworker for individuals with TBI (Pitman, Haddlesey,
Ramos, Oddy, & Fortescue, 2013). The next step for research and practice is to extend these
developments to a female population.
1.3. Females and violence
As of December 2012 there were 79,837 males and 3,920 females imprisoned in the UK
(Ministry of Justice, 2013a). In 2011, 34% of females and 31% of males were arrested for
violence against the person, as well as 26.7% and 28.5% of incarcerated females and males
respectively (Ministry of Justice, 2011). The similarity in prevalence across gender
challenges the stereotype that violence in prisoners is a male issue. A total of 9,018 females
were released between July 2011 and July 2012 (Ministry of Justice, 2013a), demonstrating
high turnover. 17.7% of females reoffend within twelve months of release (Ministry of
Justice, 2013b). Despite these figures, female offenders are a relatively understudied
population, with a research gender bias favouring males.
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The literature has recently attempted to generate models and theories to understand female
offending and recidivism. This has ranged from the exploration of the utility of gender
neutral theories of criminal behaviour (Rettinger & Andrews, 2010), to feminist models
which subscribe to the idea that gender is key to female offending (Blanchette & Brown,
2006). While factors such as self-regulation, impulse control; and the role of intimate partner
violence and victimisation in the case of feminist models; are discussed in such theories
(Rettinger & Andrews, 2010), none address the role TBI may play.
1.4. TBI in females and violence
No large community-based epidemiological studies explore the relationship between violence
and TBI in females. Unfortunately, the 35-year Swedish population study only controlled for
gender through matching, rather than including it in the stratified analyses as they did with
age, severity and diagnostic sub-group (Fazel et al., 2011). Services are ill-informed to serve
female populations. This is particularly risky considering the reported gender differences in
the presentation of offenders, such as in psychiatric comorbidity (Zlotnick et al., 2008), as
well as the dominance of socio-economic and child-raising risk factors for females and
parental characteristics for males (Farrington, Painter, & Britain, 2004). A recent report
commissioned by the Barrow Cadbury Trust emphasised this need for research examining the
causes and consequences of TBI in female offenders specifically (Williams, 2012).
Although females have been reported to be less likely to offend than males, those who do, are
more likely to be experiencing a mental illness (Butler, Allnutt, Cain, Owens, & Muller,
2005). Females with a mental illness aged 25-39 demonstrate a population attributable risk-
fraction of 14% in comparison to 6.7% of males (Fazel & Grann, 2006). This increases to
19% over 40 years for females and 7.3% for males (Fazel & Grann, 2006). Rao et al.’s (2009)
study comparing individuals with and without verbal aggression post-TBI found that new-
onset major depression increased the risk of aggression for females with a TBI eightfold. The
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issue of circular causality in the relationship between TBI and violent behaviours has been
raised before (Timonen et al., 2002), in that there are multiple associations between violence
and TBI and an array of other variables such as psychiatric comorbidities, making it difficult
to establish a clear causal pathway.
Prevalence of TBI in general offender populations varies, but a recent meta-analysis places it
at 60.25% (95% CI: 48-72%) (Shiroma, Ferguson, & Pickelsimer, 2010a). Shiroma, Ferguson
and Picklesimer (2010a) revealed a male and female prevalence estimate of 64.41% (95% CI:
53.3 to 75.53%) and 69.98% (95% CI: 50.18-89.79%) respectively. Once TBI definition was
limited to LOC, excluding milder TBIs, males demonstrated a higher prevalence than females
(59.31% vs. 55.28%). This decrease in prevalence once limited by LOC provides further
support for prevalence of mild TBIs in females, which as mentioned previously may result
from intimate partner violence. Prevalence of TBI in service users in secure forensic
psychiatric units is under-researched. Rates vary from 22% in the US (Martell, 1992) and
Canada (Colantonio, Stamenova, Abramowitz, Clarke, & Christensen, 2007), to 41.6% in a
UK MSU (Hawley & Maden, 2003). None of these studies examined females specifically,
most likely due to the small proportion of females. The Canadian study (Colantonio et al.,
2007) found evidence of TBI in 10% of females and 28% in males, while Hawley and Maden
(2003) found 35% in females and 43% in males. Difference in prevalence rates between
prisons and MSUs are surprising in light of the increased risk of comborbidity, particularly
depression in females post-TBI (Whelan-Goodinson et al., 2010). Unfortunately these studies
do not separate violent from non-violent offences, making it impossible to explore the impact
of TBI on violent offending specifically.
Research examining a more heterogeneous population of ABI, as opposed to TBI, suggests
female offenders with cognitive difficulties may require different management strategies
(Jackson & Hardy, 2011). Female prisoners with ABI demonstrate significantly different
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cognitive impairments post-ABI than males, with females performing worse on perceptual
and spatial ability, complex visual memory and spatial working memory (Jackson & Hardy,
2011). In comparison to females without an ABI, they demonstrated cognitive difficulties,
including significantly worse performance on tests of perceptual intellectual and executive
functions, complex processing speed, and working memory (Jackson & Hardy, 2011). As
violent and non-violent offenders were not separated it is not possible to discuss the
neuropsychological relationship to violent behaviour specifically.
As demonstrated in the studies discussed, a plethora of possible mediators and moderators
appear to blur the causal pathway between TBI and violence in females. Research does not
appear to have begun systematically investigating this. This is confounded by differing
definitions of TBI and violence, populations sampled, insufficient investigation of females
specifically, and failure to present gender specific data. The literature needs to be synthesised
in a coherent manner to provide direction for future research. Research is needed to inform
prison services and clinical practice, thereby improving outcomes not only for individuals
with TBI but also reduce risk to others. This systematic review aims to answer the question:
what is the empirical evidence for a relationship between TBI in females and violent
behaviour?
2. Method
2.1. Selection of studies
A literature search of three psychological and medical electronic bibliographic databases was
conducted, namely PsycINFO, PubMed, and Scopus. Date range searched within the
databases was from first available (PsycINFO 1806; PubMed 1948; 1823 Scopus) to
February 2013. Title search terms included those pertaining to TBI (i) “brain injury” OR
“head injury”; violent behaviour (ii) viole* OR offend* OR forensic OR aggress* OR
prison*. Titles, abstracts and key words were searched for terms pertaining to female sex (iii)
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sex OR gender OR female OR women. The database search yielded a total of 77 papers after
duplicates were removed. This was supplemented with searching of article reference lists to
ensure no relevant studies were missed, yielding a further 76 articles. Figure 1 outlines the
flow of studies through the search process.
Abstracts and titles of identified studies were read to determine if they met the following
inclusion criteria:
Original empirical published research presenting data relating to the
association between physical violence, physical aggression, or violent crime
and TBI in female populations.
Verbal threats and aggression were included for inpatient studies only, as these
behaviours may be unreliable and difficult to measure outside inpatient
settings (Monahan et al., 2001). Verbal incidents in inpatient settings may
represent an increased risk of physical violence and demonstrate the same
underlying mechanisms of physical violence due to the restrictive nature of the
environment which prevents verbal incidents from escalating.
The article was written in English
All systematic methodological approaches were included due to the limited
volume of research in this area.
Studies of populations under eighteen years were included but examined
separately from studies of adults.
Mixed-sex studies were included if female data was separated for relevant TBI
and violence variables.
Studies with anger, impulsivity, or verbal aggression specifically as outcomes outside
inpatient settings were excluded to maintain congruency with other research in forensic
mental health (Chambers et al., 2009; Fazel et al., 2009; Monahan et al., 2001; Walsh,
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Buchanan, & Fahy, 2002), maintaining focus on physical violence. Studies investigating
women as victims only, rather than as perpetrators of violence were excluded. Only data
presented in the papers were extracted, as failure to report gender-specific data is evidence of
the gender bias and selective reporting in this area and a limitation of much of the published
studies.
This process yielded 6 empirical papers which are presented in the following sections: cross-
sectional studies investigating the relationship between violence and TBI in females; case-
control studies comparing groups of females with violent behaviours with controls; and
longitudinal studies of violence and TBI in females. To explore how these studies have
contributed to key research questions, sub-sections discussing the strength of the relationship
between violence and TBI in females; and where on the causal pathway variables may lie in
exploring the relationship between violence and TBI in women, are presented.
2.2. Quality assessment
Due to the non-experimental nature of the data, and the absence of a preferred tool for
evaluating such research (Jarde, Losilla, & Vives, 2012), an adaptation of the method
employed by King et al. (2008) for assessing the quality of non-experimental studies, based
on the Cochrane Handbook’s general guidance on non-experimental studies, was used to
determine quality indicators (2 indicating higher quality than 1) was employed (appendix I,
table 2). Factors examined were: sampling (non-random = 1, random = 2); representativeness
(response rates <60% = 1, ≥60% = 2); population definition (selected sample e.g. prison = 1,
general population = 2); and sample size (<100 females with TBI = 1, >100 females with TBI
= 2).
2.3. Data analysis
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Due to the heterogeneity of the available research designs and quality, it was neither feasible
nor appropriate to conduct a formal meta-analysis (The Cochrane Collaboration, 2011).
Therefore, a narrative systematic review was conducted.
Figure 1. Selection of studies using PRISMA guidelines
3. Results
3.1. Sample
As demonstrated in figure 1, 109 titles were retrieved from database searches. In addition, 76
titles were obtained through reference checking. After de-duplication, 153 titles and abstracts
remained and were screened for relevance. This phase demonstrated the poor gender
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reporting amongst studies, with many abstracts failing to report sample sex. Sixty-one studies
were excluded during the title and abstract screening. 84 potentially relevant studies were
selected for further examination. 6 articles could not be retrieved. 78 did not meet the
inclusion criteria. The most common reason for exclusion (n=54) was having male-only
samples, or failing to separate their data by gender for relevant variables, demonstrating the
substantial male gender bias. Other papers did not provide violence specific outcomes, e.g.
they presented variables that did not separate physical violence from other forms, or did not
separate violent offenders from non-violent (n = 17). Inpatient studies that provided gender
separated data did not measure participants consistently as inpatients, e.g. they were
inpatients at the first time point but not the second (n = 2). 5 studies were excluded because
they did not examine TBI specifically, e.g. examining ABI rather than TBI. This process
yielded 6 studies, of which 2 were cross-sectional designs, 1 was a case-control, and 3 were
longitudinal. Quality criteria for the selected studies are presented in table 2 (appendix I),
demonstrating the paucity of research conducted in females with head injury, with no study
obtaining a female TBI sample of over 100.
The following sections will discuss findings for each of the methodological designs regarding
the strength of the relationship between violence and TBI in females; as well as possible
confounders, moderators and mediators that may sit on the causal pathway.
3.2. Cross-sectional studies
3.2.1. Strength of the relationship
Of the two cross-sectional studies, one was conducted with a prison population (Brewer-
Smyth & Burgess, 2008) and the other within a clinical population (Johansson, Jamora, Ruff,
& Pack, 2008) (Table 3, Appendix I). Both studies were conducted within the USA.
Johansson et al. (2008) recruited consecutive male and female patients from an outpatient
neuropsychology service, to explore factors associated with aggression in TBI, including
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gender in their analysis. Aggression included physical aggression, and acted as a surrogate
measure of violence. Generalisability and representativeness is limited. By recruiting from an
outpatient neuropsychology service milder TBIs with less pronounced sequelae are likely to
be excluded. Most participants were also in litigation, which can distort data e.g. by
increasing anxiety or malingering (King, 1997). Johansson et al. (2008) did not address pre-
morbid socioeconomic status of participants. Due to the nature of the healthcare system in the
USA access to outpatient neuropsychology services is likely dictated by expensive private
health insurance, thereby excluding vulnerable (Oddy, Moir, Fortescue, & Chadwick, 2012)
socio-economically deprived demographics. Participants with inadequate English
proficiency, and pre-morbid neurological and/or psychiatric history, were also excluded,
limiting ecological validity. With a sample of 27 females, and no reference to power
calculations for their research questions, it is unclear whether the sample was sufficient to
detect significant results, despite adequate available literature when looking beyond female
specific research (Wood & Liossi, 2006). The study lacked a non-TBI control group. TBI
severity was defined using the American Congress of Rehabilitation Medicine’s (ACRM)
guidelines (American Congress of Rehabilitation Medicine, 1993). They also supplemented
this with neuro-imaging. To measure aggression, Johansson et al. (2008) created ordinal
groups of participants by clinical ratings on a 4-point scale, with level 4 indicating overt
physical aggression. This clinical rating was validated against the anger subscale of the Ruff
Neurobehavioral Inventory (Ruff & Hibbard, 2003) (RNBI). Self-report scales were
corroborated with family reports, but this was only possible in 16% of cases. The authors’
reported clinical impressions were that many participants were under-reporting aggression
due to embarrassment and stigma. Cross-sectional designs which rely on self-report are
limited by recall bias. This has been reported in non-TBI studies (Houtveen & Oei, 2007),
and may be more pronounced in individuals with cognitive impairment. 40% of females and
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32.5% of males reported overt physical aggression, however no statistically significant
relationship was found between gender and physical aggression (r = 0.141, p > 0.05). As
individuals with prior neurological histories were excluded, the impact of multiple TBIs on
aggression could not be examined. Johansson et al.’s (2008) research suggests that females
demonstrate similar levels of post-TBI physical aggression as males.
Brewer-Smyth and Burgess (2008) randomly recruited participants from minimum and
maximum security units of a women’s prison to examine if childhood familial sexual abuse
was related to increased neurological histories, including TBI. Brewer-Smyth and Burgess
(2008) described the study design as cross-sectional in their abstract and as a “modified case-
control design” (p.167) in the methods section. One of the defining characteristics of a case-
control study is that cases and controls are matched on the basis of outcome (Mann, 2003),
whereas Brewer-Smyth and Burgess (2008) matched on exposure to familial childhood
sexual abuse, making their design cross-sectional. Such inconsistent reporting of study
designs in the literature is problematic. Although this study is limited in generalisability due
to the prison sample, it provides a useful overview of a vulnerable population, with reports of
as many as 75% of incarcerated females experiencing severe physical violence by partners
(Browne, Miller, & Maguin, 1999). Although a power calculation was not completed for this
research question as it was a secondary analysis, power analysis for the same variables but
with different variables as exposures indicated that the sample (n= 149) was sufficient to
detect an effect. Brewer-Smyth and Burgess (2008) included non-criminal females in the
analysis, however this group was too small. TBI was dichotomously defined as physical head
trauma resulting in LOC, which risks excluding mild recurrent TBIs and did not examine TBI
severity. As demonstrated by Browne (1999), while 75% of incarcerated females experienced
physical violence, only 22% reported concussions, indicating the risk of missing more subtle
neurological impairment. Brewer-Smyth and Burgess (2008) corroborated reports with
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criminal and medical records where possible, as well as physical examination. Definition of
violence was that of violent crime as defined by the criminal justice system. While this is a
common outcome measure in violence research, it is likely an underestimate of violent
behaviour as it relies on an individual receiving a conviction. It may also be problematic
when comparing across jurisdictions. Brewer-Smyth and Burgess’s (2008) results suggest
that females who experienced familial childhood abuse had more TBIs (OR = 1.49, p = 0.01)
and were convicted of more violent crime (OR = 1.67, p = 0.05) than those who were not
abused. However, it was not reported whether TBI occurred before or after the abuse,
blurring the causal pathway. This will be discussed further in the next section.
Clear conclusions from these two cross-sectional studies on the relationship between TBI in
females and violence cannot be drawn. While Johansson et al.’s (2008) study demonstrated
higher levels of post-TBI physical aggression in females, this was not statistically significant
(r = 0.14, p > 0.05). This may be attributable to methodological flaws and being
underpowered. Brewer-Smyth and Burgess (2008) found a significant relationship between
childhood familial abuse, TBI and violence (OR = 1.67, p = 0.05), however it suggests that
the relationship is more complex than TBI causing violence.
3.2.2. The causal pathway
While it is not possible to determine causality in cross-sectional designs, they can provide
insight into variables that may impact the causal pathway. Johansson et al. (2008) found that
groups with higher aggression demonstrated significantly elevated depression and PTSD on
subscales of the RNBI, which in a larger sample may have contributed to the relationship
between gender and post-TBI violence. In the Brewer-Smyth and Burgess (2008) study it was
unclear whether TBI was independently related to violence, but rather childhood familial
abuse may be a confounder, a moderator or a mediator between TBI and violence. Or that
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TBI may be a confounder, moderator or mediator between childhood abuse and violence.
This was not explored within the study, but lends itself to consideration for future studies.
3.3. Case-control studies
3.3.1. Strength of the relationship
Brewer-Smyth, Burgess and Shults’(2004) study of females from minimum and maximum
security sections of a women’s prison in the USA, was the only case-control study which met
inclusion criteria (table 4, appendix I). Their objective was to examine the relationship
between basal resting salivary cortisol levels, abuse history, neurological history, and violent
crime. This data appears to be from the same project as the Brewer-Smyth and Burgess
(2008) cross-sectional study. Cases and controls were selected on the basis of the outcome of
committing a violent crime. The cross-sectional design (Brewer-Smyth & Burgess, 2008)
stated that participants were randomly recruited, this is unclear from the case-control design,
and it appears to be a convenience sample. The sample (n = 113) had sufficient power to
detect a significant effect. Definition of violence was that of violent crime as defined by
previous research, including murder, non-negligent manslaughter, robbery, assault, sexual
assault, and kidnapping. TBI was dichotomously defined as physical head trauma resulting in
LOC. “Other neurologic history”, consisting of TBI without LOC and sensory abnormalities,
was not significantly different between violent and non-violent offenders (48% and 53%
respectively, p > .05). There was no significant difference between violent (4%) and non-
violent (6%) offenders for severe brain injury, defined as a coma exceeding one day (p > .05).
TBI with LOC was significantly higher in participants convicted of a violent crime (56% vs.
38%), with a dose response effect in that for every additional TBI with LOC the odds of
being convicted of a violent crime in comparison to a non-violent crime increased
significantly (OR = 1.451, p = 0.012). Mean number of TBI with LOC for those with violent
crime conviction was 1.75 (± 2.9) in comparison to .74 (± 1.19) convicted of a non-violent
231
crime (p< .05). Most TBIs were acquired through violence perpetrated against the
participants or through high-risk behaviours such as substance use – the authors do not
provide figures for this. Morning cortisol levels, which the authors posit is related to chronic
stress associated with emotional and physical trauma, were significantly lower for those with
a violent conviction (mean .297 ± .23 vs .446 ± .47, p ≤ .055; OR = 0.036, p = 0.17).
Brewer-Smyth et al. (2004) also compared those with no known violent conviction, with a
current non-violent conviction but known past violent conviction, and those with current
violent convictions. Those with current violent convictions had significantly (1.75 ± 2.96, p <
.05) more TBIs per person, while those with past but not current violent convictions had less
(.61 ± 1.17, p < .05) than those with no known violent convictions (.86 ± 1.23, p < .05). This
was attributed to poor recording of criminal behaviour. It is impossible to ascertain from the
design whether TBIs occurred prior to violent behaviour, or whether those who engage in
violent behaviour are more at risk of TBI. Neurologic examination for evidence of TBI found
them to exist predominantly in the frontal-temporal region. This was limited to physical
examination. Those with violent crime convictions had significantly more hospital treatments
for abuse-related injuries (2.15 ± 3.84 vs .94 ± 2.02, p < .05). Only four participants reported
receiving any neuropsychological interventions post-TBI. In conclusion, while TBI was
prevalent amongst female offenders (42%), those with violent convictions had significantly
more (56% vs 38%), while odds of having a violent conviction increased with each TBI (OR
= 1.45, p = 0.12).
3.3.2. The causal pathway
As mentioned in the previously, the design of past studies has made it impossible to
determine the temporal sequence between violent behaviour and TBI. However, participants
with violent convictions had experienced abuse significantly more recently than those with
non-violent convictions (3.83 ± 4.15 years vs. 9.77 ± 9.96 years, p < .05), suggesting that
232
recency of abuse may be a moderator or mediator of the TBI and violence relationship.
Brewer-Smyth et al. (2004) found that although depression scores were not significantly
different between groups using the Beck Depression Inventory-II (BDI-II; Beck, Steer, &
Brown, 1996), those with violent convictions had significantly increased odds of suicide
attempts (OR = 1.249, p = 0.026) which tended to occur years before the study as opposed to
out of remorse for the violent crime. Brewer-Smyth et al. (2004) do not attempt to explain
this, however it appears that current depression as measured by the BDI-II may not be a
significant variable, but lifetime depression as indicated by suicide attempts may be on the
causal pathway.
3.4. Longitudinal studies
3.4.1. Strength of the relationship
Of the three longitudinal studies, one recruited from a prison, one from a clinical setting, and
one from a high-school population (table 5, appendix I). Two were conducted within the
USA, and one in Australia. Shiroma et al. (2010b) used a prospective cohort design,
retrospectively gathering data on TBI over 11 years (1996-2007), while prospectively
measuring in-prison behavioural infractions. Behavioural infractions were defined as a
violation of prisoner code of conduct, and were deemed violent or non-violent according to
criminal justice system definitions for violent crime. The aim was to compare the in-prison
behavioural infraction rate in prisoners with and without a history of TBI. The study
population included 20,098 males and 1,512 females. This was the largest sample of females
with TBI (n = 94) of the 6 studies. No information on power calculations was provided. TBI
was defined as patients discharged from hospital with a TBI-related International
Classification of Diseases, 9th revision, Clinical Modification (ICD-9-CM) code. Similarly to
Johansson et al. (2008) this is likely to under-report TBI. Those who suffered a TBI outside
the 11 year study period were excluded. Data was extracted from existing databases,
233
including the state-wide hospital discharge and emergency department data sets. In total,
6.22% of females had a history of TBI. Males and females without TBIs had a significantly
higher proportion of current violent convictions (for females 31% vs. 20%, p = .03). Analysis
of the number and/or severity of TBIs and relationship to violence was not conducted. 24% of
females with TBI (n = 94) in comparison to 34% without TBI (n = 1,418) had at least one
behavioural infraction. However, those with TBI had an increased violent infraction rate of
144% (mean with TBI 1.20 ± 1.27, mean without TBI 0.68 ± 0.76; RR = 2.44, 95% CI: 1.45-
4.12) after controlling for age, violent crime conviction, prior criminal history, security level,
sentence length, and race. This significantly increased rate was found between males with
and without a TBI (mean with TBI 1.04 ± 1.50, mean without TBI 0.81 ± 1.18; RR 1.86, 95%
CI: 1.54-2.24), but was lower than in female participants. Shiroma et al. (2010b) did not test
if this difference between males and females was statistically significant. Non-violent
infractions did not have a significant increased likelihood in females with TBI (mean with
TBI 1.09 ± 1.47, mean without TBI 0.91 ± 0.95; RR = 0.62; 95% CI: 0.36-1.08). The
difference between violent behavioural infractions and violent convictions suggests that
although fewer females with a violent conviction had a TBI, those with TBI may have an
increased rate of violent behaviour. Alternatively, the difference between this finding of
lower violent convictions in those with TBIs may be due to methodological limitations. It
suggests, however, that violent crime conviction may not be a reliable surrogate measure for
physical violence. In summary, while prisoners with TBI had significantly less violent
convictions (p = .03) and infractions, those with TBI had an increased rate of infractions, with
this finding more pronounced in females.
Baguley, Cooper and Felmingham’s (2006) retrospective cohort study recruited consecutive
inpatients admitted to an Australian tertiary brain injury rehabilitation hospital, with the aim
of assessing prevalence and predictors of aggressive behaviour. This sampling may over-
234
represent more severe TBIs, with 68% of participants falling into the severe range on the
GCS. Participants were followed up at 6, 24, and 60 months post-discharge. Attrition
occurred during the follow-up period, with the sample commencing at 228, and 67 partaking
in the 60 month follow-up. There was no reference to a power calculation. TBI was defined
using markers on the GCS, Glasgow outcome scale (GOS) and PTA. Aggression was
measured using the Overt Aggression Scale (OAS; Yudofsky, Silver, Jackson, Endicott, &
Williams, 1986), providing a global measure of aggression, which can be broken down into
subscales (verbal, physical toward objects, physical toward self, and physical toward others).
Rather than using the OAS as a continuous variable, Baguley et al. (2006) categorised
participants dichotomously as aggressive or not using a cut-off score of 7. To be classified as
aggressive the participant must have demonstrated aggression in at least one of the physical
subscales. They validated this cut-off against an age-matched control group of individuals
without TBI. The OAS was completed by participants in 66.6% of cases, next of kin in 8.5%
of cases, and by both in 25% of cases. There were no significant differences between scores
with the different methods of completing the scale, demonstrating the scales’ reliability. At
each time point approximately 25% of participants demonstrated substantial aggression
which would include physical violence (scoring >7). Baguley et al. (2006) did not examine
the impact of multiple TBIs on violence. They mention that injury pattern as seen on
computed tomography (CT) was not significant in predicting aggression, however they
provide no information as to how injury pattern was evaluated. Furthermore, mild TBI often
does not demonstrate any abnormalities in CT scans (Haydel et al., 2000). Gender was not
significantly associated with aggression at any of the time points. Data are not provided for
this. The authors attributed the failure to find a gender difference on the underrepresentation
of females in their study. Similarly to Johansson et al. (2008), these findings suggest that
females exhibit comparable prevalence of post-TBI violence as males.
235
Stoddard and Zimmerman’s (2011) retrospective cohort study used data collected to study
youth at risk of high school dropout from 4 public high schools, with the aim of examining
differences in interpersonal violence amongst those with and without a TBI. Participants were
recruited on the basis of a low academic grade point average. The exact age participants were
recruited was not reported, only that they examined mid-adolescence to young adulthood.
Unlike previous studies reported, males and females were equally represented (n=850). They
did not report any power calculations. Data was collected over 8 waves, with waves 1-4
corresponding to consecutive high school years. TBI was assessed at waves 5-7. TBI was
defined as having had a concussion, skull fracture or LOC, with no measure of severity, type
or number of TBIs. Interpersonal violence was assessed using a 4-item scale. Cronbach’s
alpha ranged from 0.62-0.76, suggesting questionable internal consistency (Carmines &
Zeller, 1979; Nunnally, 1978). Multivariate regression analyses demonstrated that TBI in
waves 5 and 6 (childhood TBI occurring during or before high school years) was not
predictive of violent behaviour by the final wave (wave 8) in young adulthood (β = .08, p
> .05) when previous violence was included (β = .36, p < .001), yet gender was a significant
variable in this model (β -.08, p <.05). The role gender plays in this model in not explained,
and as no information was provided on how gender was coded, conclusions cannot be made
from the data provided alone. When TBI is restricted to the last year (i.e. TBI acquired in
young adulthood, wave 7) it predicts violence (β = 1.07, p < .001), but once previous violence
and risk behaviours such as alcohol and marijuana use, delinquency, and violence observation
were added to the model, gender was not significant (β = -.03, p > .05). They did not examine
the role of multiple TBIs and its relationship with violence. Similarly to Johansson et al.
(2008) and Baguley et al. (2006), this research suggests that males and females demonstrate
similar levels of interpersonal violence post-TBI.
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In summary, the longitudinal studies failed to provide sufficient evidence of a relationship
between violence and TBI in females specifically. Shiroma et al. (2010b) had the most
females with TBI, and found that although they had an increased rate of violent behavioural
infractions they did not have significantly more violent convictions. Baguley et al. (2006) did
not find a relationship between gender and aggression in a clinical sample. Stoddard and
Zimmerman’s (2011) high school cohort did not provide support for the role of gender in the
relationship between TBI and violence. Non-significant results may be due to methodological
limitations, or demonstrate that females exhibit similar levels of post-TBI violence as males.
If intimate partner violence is a key risk factor for TBI, which leads to subsequent violence,
participants’ in Stoddard and Zimmerman’s (2011) study may have been too young to
demonstrate a significant relationship.
3.4.2. The causal pathway
An interesting finding by Shiroma et al. (2010b) was that prison reduced the likelihood of
suffering a TBI, with an odds ratio of obtaining a TBI while not incarcerated of 5.88 (95%
CI: 5.26-6.67) in males and 16.67 (95% CI: 5.88-50) in females. This gender difference
suggests that female participants may have been living in a more harmful environment than
males prior to incarceration, and may be evidence of the risk of intimate partner violence.
This supports the idea that intimate partner violence or other environment risk factors
influence the causal pathway between TBI and violence in females. Similarly to Johansson et
al. (2008), using the BDI, Baguley et al.(2006) found depression to be a significant predictor
of aggression across their five year follow-up period, accounting for 24.9% (p < .001) of the
variance in the aggression score at 24 months and 15.9% (p = .002) at 60 months, irrespective
of gender.
4. Discussion
237
Overall, three of the six studies (Brewer-Smyth & Burgess, 2008; Brewer-Smyth et al., 2004;
Shiroma et al., 2010b) provided some evidence of a relationship between TBI and violence in
females. The remaining three (Baguley et al., 2006; Johansson et al., 2008; Stoddard &
Zimmerman, 2011) did not find significant differences between levels of post-TBI violence
in males and females, suggesting that females exhibit similar levels as males. Unfortunately,
all these studies have substantial methodological limitations, and none were designed
specifically to answer the research question at hand. Therefore, the main conclusion
regarding the relationship between TBI and violence in females is that there is insufficient
evidence to answer this question. Brewer-Smyth et al.’s (2004) study was the only one to
examine the cumulative effects of recurrent TBIs on violence, and found some evidence for a
dose-response effect between number of TBIs and violence. This did not include mild TBI.
Brewer-Smyth et al.’s (2004) findings are consistent with previous research which has found
reported prevalence rates of multiple TBIs in female offenders ranging from 35-48%
(Ferguson et al., 2012). Multiple mild TBIs can have similar cognitive and behavioural
profiles to individuals with more severe TBI (Diamond et al., 2007), and has been related to
increased likelihood of post-concussive syndrome (Miller, Ivins, & Schwab, 2013) and
chronic traumatic encephalopathy (Kelly, Amerson, & Barth, 2012). Brewer-Smyth et al.
(2004) found that most TBIs occurred in the fronto-temporal region, which as discussed
previously has been related to post-TBI aggression in the literature (Daoust et al., 2006).
Although none of the studies could provide conclusive results, they did provide some
provoking thoughts about what variables may confound, mediate or moderate the relationship
between TBI and violence in females. Physical and sexual abuse throughout the lifespan may
play a role (Brewer-Smyth & Burgess, 2008; Brewer-Smyth et al., 2004; Shiroma et al.,
2010b). Browne et al.’s (1999) study of victimisation experiences and criminal behaviour
demonstrated that abuse commences for female prisoners at a young age, with 66% of those
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experiencing sexual abuse and 71% of those severely physically assaulted by caretakers
having experienced such abuse by 11 years of age. Childhood victimisation strongly predicts
victimisation in adulthood (Browne et al., 1999), and adult victimisation in turn increases the
risk of TBI (Kwako et al., 2011), which may lead to increased violent behaviour. Therefore,
childhood abuse may be an important confounder of TBI and violence. This is consistent with
Brewer-Smyth and Burgess’ (2008) findings of increased childhood family sexual abuse in
those with more TBIs and violence crime convictions.
Research has demonstrated that increased post-TBI aggression is related to perpetration of
intimate partner violence in males (Rosenbaum et al., 1994), it is unclear if aggression after
TBI is related to being a victim of intimate partner violence. None of the six studies reviewed
provided gender separated data for mechanism of injury. However, Shiroma et al.’s (2010b)
finding of decreased likelihood of suffering a TBI whilst incarcerated lends some tentative
support for this hypothesis, as does Brewer-Smyth et al.’s (2004) findings of increased
recency and hospitalisations for abuse-related injuries in those with violent crime convictions.
Depression appears to be an important factor in violence as an outcome post-TBI (Baguley et
al., 2006; Brewer-Smyth et al., 2004; Johansson et al., 2008), and PTSD may also be
significant (Johansson et al., 2008). It is unclear if there are gender differences in the impact
of psychiatric comorbidities, and a variety of psychiatric comorbidities have been reported in
those with TBI and a history of violence in other literature (Colantonio et al., 2007). Rao et
al. (2009) found verbal aggression was associated with post-TBI depression. This suggests
that comorbidities may moderate or mediate the relationship between TBI and violence in
females. Overall, the studies reviewed suggest that TBI may be one of many factors that
contribute to violence in females.
4.1. Methodological considerations
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The studies reviewed had a number of limitations. With regards to sampling, none of the
studies was generalisable as they were conducted within selected populations, and 5 were
conducted in the USA. No study had a sample with over 100 females with TBI, making it
difficult to have sufficient power to detect significant results. However, the studies that
included mixed-sex samples should be commended for providing gender separated data. Of
the 6 studies, only two, which came from the same original data-set, examined females
specifically (Brewer-Smyth & Burgess, 2008; Brewer-Smyth et al., 2004), demonstrating the
paucity of research in females.
There were limitations regarding the definitions and instruments used to measure TBI and
violence. These limitations are not specific to female studies, and have been reported in
research reviewing the relationship between TBI and violence irrespective of gender (Fazel et
al., 2009). All the studies relied on LOC as an indicator of TBI and only Brewer-Smyth et al.
(2004) attempted to exam the role of injury severity in the relationship. As discussed
previously, females may be at a higher risk of recurrent mild TBIs and have a higher
prevalence of TBI when not limited to LOC (Shiroma et al., 2010a). Milder TBIs should not
be dismissed considering the suggested impact of mild recurrent TBIs (Diamond et al., 2007).
However, Brewer-Smyth et al. (2004) did not find evidence supporting a relationship
between violence and TBI without LOC in females. Two of the three studies that provided
support for a relationship between violence and TBI in females used a combination of
methods for identifying TBI, corroborating self-report with medical and criminal records, as
well as physical examination. Only Stoddard and Zimmerman (2011) relied solely on self-
report, not supporting the hypothesis that there is an increased association between violence
and TBI in females. Aside from Shiroma et al. (2010b), the remaining studies which relied on
medical records only did not support this hypothesis. Reliance on medical records risks
under-identification of TBI, with reports of up to 43% of individuals with a TBI not seeking
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medical attention (Setnik & Bazarian, 2007). This is further compounded by risk of errors
and insufficient recording (Horwitz & Yu, 1984). Reliance on self-report is problematic, with
brief scales and surveys such as that used by Stoddard and Zimmerman (2011) being at risk
for not detecting all but the most recent or severe TBIs (Corrigan et al., 2010). None of the
reported studies used neuropsychological assessment which is considered the gold-standard
of examining the sequelae of TBI (Shiroma et al., 2010a). Furthermore, identifying TBI by
simply using LOC does not assist in determining the prevalence of ongoing sequelae. This is
particularly important in forensic contexts considering research has demonstrated that
females have more ongoing symptoms post-TBI, including difficulties controlling substance
use, temper and emotions (Ferguson et al., 2012).
Three of the 6 studies relied on violent convictions as a measure of violent behaviour
(Brewer-Smyth & Burgess, 2008; Brewer-Smyth et al., 2004; Shiroma et al., 2010b). These
studies that provided the most support for a relationship between violence and TBI in
females. Convictions are limited by how states define violent crime, and may limit
comparison with other jurisdictions. It also does not include crimes that some may perceive
to be violent, and the crime committed may differ from the conviction crime (Shiroma et al.,
2010b). Furthermore, as identified in the mental health literature (Hodgins, 1998), those with
TBI may be at risk of higher convictions due to ease of detection related to cognitive
difficulties. Only Brewer-Smyth et al. (2004) included an analysis of past violent convictions,
alongside current violent convictions, which suggested that current violent crime may not be
a reliable surrogate for violence. The remaining three studies used self-report measures of
violence and physical aggression (Baguley et al., 2006; Johansson et al., 2008; Stoddard &
Zimmerman, 2011). Johansson et al. (2008) supplemented clinical ratings with a valid self-
report scale, however Stoddard and Zimmerman (2011) used a one-item rating scale with
questionable validity. Baguley et al. (2006) attempted to control for bias with the OAS by
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incorporating informant (Yudofsky et al., 1986). Violent behaviour outside of current
convictions needs to be accounted for, as well as managing the bias of self-report measures.
Ideally this could be achieved using resource intensive methodologies such as those used in
the MacArthur study, combining self-report, informant-report, arrest and hospitalisation
records (Monahan et al., 2001).
Other measures of potentially relevant variables used in the studies reviewed also differed.
Overall, across studies there was insufficient investigation and methodological rigour in
examining the association between TBI and violence in females, and the potential
confounders, mediators and moderators of that relationship.
4.2. Future research
Future research can build upon the studies reviewed. A previous meta-analysis has already
identified the scarcity of studies on female populations (Farace & Alves, 2000), yet this
research need appears to have been relatively ignored, with an ongoing gender bias. These
studies suggest that there is a need for quality epidemiological research examining the
relationship between TBI and violence in females using appropriate valid measures. Ideally
this would be achieved by a longitudinal birth cohort study such as the Swedish population
study (Fazel et al., 2011), but examining gender-specific data. Where studies do include
females in their samples, gender separated data and analyses should be provided where
sample size allows. Observational research needs to ensure that reporting standards reach a
high quality, using guidelines such as STROBE (von Elm et al., 2007). This will facilitate a
meta-analysis of this research question when there are sufficient studies. Finally, researchers
and clinicians in both the fields of TBI and forensic mental health would benefit from agreed
measures of both variables to facilitate comparison between studies.
To facilitate future research and support clinical practice, a valid screen for TBI in females
needs to be available. Currently many studies rely on instruments developed for specific
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individual studies, with little consideration of reliability and validity (Diamond et al., 2007).
There are currently 2 published valid screening tools developed for use with prisoners, the
Traumatic Brain Injury Questionnaire (TBIQ; Diamond et al., 2007) and the Ohio State
University TBI Identification Method (OSU TBI-ID; Bogner & Corrigan, 2009). These
measures have not been validated within a female UK prison population. Indices on the OSU
TBI-ID which required an estimate of mild TBIs, relating to episodes such as intimate
partner violence, were unreliable (Bogner & Corrigan, 2009). Therefore, this may not be
inappropriate for female prison populations. Also, the TBIQ has only been validated against
short rating scales. Validation of a TBI screen will enable researchers to determine the
prevalence of TBI in UK female offenders, which is currently unknown. Within the UK, the
Disabilities Trust Foundation are examining the validity of a TBI screen with prison
populations and have already examined its use in a male population (Pitman et al., 2013).
Although data is not yet available, preliminary reports suggest that this will be a useful tool
for clinical practice within the UK, and would benefit from validation in a female prison
population.
As indicated from Brewer-Smyth et al.’s (2004) study, future research needs to explore the
impact of recurrent TBIs and how this compares to the neuropsychological profiles of more
severe injuries. Research on neuropsychological profiles should also examine differences
between those with reported violent behaviour and those without violent behaviour,
particularly in females considering the cognitive differences between male and female
offenders with ABI discussed previously (Jackson & Hardy, 2011).
4.3. Clinical implications
Understanding the relationship between TBI and violence in females has many clinical
implications. Without adequate screening in female offenders, TBI is likely to go undetected,
and may impact on engagement in offender rehabilitation programs and the legal process
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(Jackson & Hardy, 2011). Officials within the criminal justice system may misinterpret
behaviour (Merbitz et al., 1995; Shiroma et al., 2010b). Furthermore, screening can provide a
cost-effective way of determining who is appropriate for referral to more limited and
expensive resources such as neuropsychologists, or alternative care pathways such as MSUs.
As demonstrated by Brewer-Smyth et al. (2004), female offenders with TBI often have had
little if any access to neuropsychological interventions. Such screening can demonstrate
treatment needs and inform policy.
Without an understanding of the impact of TBI on violence in females, offender rehabilitation
programmes are likely to have a limited effect on this population (Jackson & Hardy, 2011).
Further research can inform rehabilitation programmes, facilitate engagement, inform
community placement (Hawley & Maden, 2003) and thereby reduce recidivism (León-
Carrión & Ramos, 2003). This will inform staff training, ensuring staff working with these
individuals understand presentations, are skilled in appropriate behaviour management
techniques, and can make appropriate adaptations to service delivery (Jackson & Hardy,
2011; Merbitz et al., 1995; Morrell et al., 1998).
Given the complex relationship that TBI appears to have with psychiatric comorbidities
(Rogers & Read, 2007; Silver et al., 2001; Timonen et al., 2002), this review highlights the
need for services to address psychiatric comorbidities in individuals with TBI rather than
focusing on the TBI or violent behaviour exclusively, and adopt a multidisciplinary approach
(Jackson & Hardy, 2011). Time spent in prison, away from risky environments (Shiroma et
al., 2010b), may provide offenders and services with a valuable opportunity for
individualised targeted interventions that may decrease victimisation and recidivism (Browne
et al., 1999).
5. Conclusions
244
Although there is some evidence to suggest a relationship between TBI and violence in
females, the inconsistency across studies, methodological limitations, and scarcity of research
in this area does not permit any firm conclusions regarding the nature of this relationship. The
studies reviewed suggest this is a complex relationship, with many variables possibly
impacting on the causal pathway, including psychiatric comorbidities and history of abuse.
These studies can inform future research, and thereby inform clinical practice.
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Appendix I
Tables
246
Table 1. TBI classifications systems
GCS score (World Health Organization, 2006)
PTA (Lezak, 2004) LOC (Greenwald, Burnett, & Miller, 2003)
Mild TBI 13-15 < 1 hour <30 minutesModerate TBI 9-12 1-24 hours ≥ 30 minutes ≤ 6
hoursSevere TBI 3-8 > 24 hours > 6 hours
Table 2. Classification of quality indicators of studies included in the review
Sampling 1= Non-random 2= Random
Participation rate1= <60%2= ≥60%
Population1= Selected2= General
Female sample size1= <1002= ≥100
Brewer-Smyth & Burgess (2008)
2 2 1 1
Shiroma et al. (2010b) 1 2 1 1Johansson et al.(2008) 1 2 1 1Baguley et al .(2006) 1 2 1 1Brewer-Smyth et al.(2004)
1 2 1 1
Stoddard & Zimmerman (2011)
1 2 1 1
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Table 3. Cross-sectional studies of violent behaviour and TBIs in females
Authors & Country
Sampling Gender (M=male; F=female); age (mean years)
Participation rate
Violent behaviour Article quality score
TBI Results
Prison populationBrewer-Smyth & Burgess (2008) USA
Minimum and maximum security units of women’s prisons
89F with no childhood family sexual abuse (34.59 years); 60F with childhood family sexual abuse (34.16 years)
81% Criminal offences defined by criminal justice system
6/8 LOC Females who experienced childhood family sexual abuse experienced more TBIs (OR = 1.49, p = .01) and were convicted of more violent crimes (OR = 1.67, p = .05)
Clinical population
Johansson et al. (2008) USA
Sample of consecutive patients seen at an outpatient neuropsychology office in San Francisco
40M; 27F; Mean age for total sample was 40 years
65% Anger severity rated by clinical interview on a four point ordinal scale. Points 3 and 4 indicate physical aggression; Anger and aggression scores from RNBI (Ruff & Hibbard, 2003) also obtained
5/8 GCS, LOC, PTA, focal neurological deficits, and neuro-imaging results
No significant relationship between gender and anger groups (r = 0.14, p > 0.05) or post-morbid RNBI anger score (t = -1.52, p > 0.05)
Table 4. Case-control studies of violent behaviour and TBIs in females
Author & Country
Sampling Case gender (M=male; F=female); age (mean years)
Control gender (M=male; F=female); age (mean years)
Participation rate
Violent behaviour Article Quality Score
TBI Results
Prison Population
Brewer-Smyth et al. (2004)USA
Convenience sample from minimum and maximum security units of women’s prisons
27F (32.86 years)
86F (33.57 years)
81% Crimes groups as violent or non-violent based on criteria established in previous research (Volavka, 2002)
5/8 LOC TBI was significantly higher in females convicted of a violent in comparison to non-violent crime (OR = 1.45, p = .012).
Table 5. Longitudinal studies of violent behaviour and TBI in females
Country & author
Sampling Gender (M=male; F=female); age (mean years)
Participation rate
Violent behaviour
Article Quality Score
TBI Results
Prison Population
Shiroma et al (2010b) USA
Inmates census sample from SCDS
1,136M (median = 30 years) with TBI, 18,962M without TBI (median = 33 years); 94F (median = 34 years) with TBI; 1,418 without TBI (median = 36 years)
Complete histories available for 87% of sample
South Carolina state statute definition of violent vs. non-violent crime
5/8 Medically attended TBI using ICD-9-CM criteria
Higher proportion of current violent crime convictions (54% vs. 40% [p<.0001] and 31% vs. 20%[p=.03]) in males and females without medically attended TBI respectively; 25% and 18% of males and females with TBI respectively had violent infractions, in comparison to 30% and 18% of males and females without TBI respectively; compared to females without TBI, females with TBI had a significantly increased violent infraction rate (RR=2.44)
Clinical populationBaguley et al. (2006) Australia
Consecutive inpatients admitted to a tertiary hospital over 7 years
179M; 49F; Mean age for male and female combined was 34.3 at time of injury
71.5% OAS (Yudofsky et al., 1986)
5/8 GCS; PTA; GOS
Gender was not significantly associated with aggression at 6, 24 or 60 month follow-up (figures not provided)
High School PopulationStoddard & Cohort of 425M; 425F 68% Four-item 5/8 Concussion, Childhood TBI not predictive of violent
Zimmerman (2011) USA
youth selected by grade point average to study youth at-risk for high school dropout, followed over 8 years from mid-adolescence to young adulthood
scale of inter-personal violence
skull fracture or LOC
behaviour in adulthood (β = .08, p > .05). Gender (β -.08, p <.05) and previous violence (β = .36, p < .001) contribute significantly to model. TBI acquired in young adulthood predicted violence (β = 1.07, p < .001), but gender did not make a significant contribution (β = -.03, p > .05)
251
Major Research Project Proposal Form
This form should be completed by the trainee and signed by the University supervisor, and then submitted by the deadline.
Remember to give a draft to your supervisor for comments before submitting the final version.
When preparing this document it would be helpful to consider what you would include when writing the Introduction and Method
sections for your MRP.
* Please append your literature review to this proposal
URN: 6242697
Project Title: Traumatic Brain Injury in Adult Female Offenders in the UK
Introduction
Background and Theoretical Rationale
TBI: Definition and prevalence
Traumatic brain injury (TBI) is “an alteration in brain function, or other evidence of
brain pathology, caused by an external force” (Menon et al., 2010). TBI is the most
common form of acquired brain injury (ABI; Fleminger & Ponsford, 2005), with an
estimated prevalence of 8.5% in the general population (Silver et al., 2001) across all
levels of severity. Incidence ranges from 91-419 per 100,000 in England (Tennant,
2005).
Relationship between TBI and offending
Clinical opinion suggests that violence and impulsive behaviours are both antecedents
and consequences of TBI (Anderson et al., 1999). Violence following TBI has been
characterised as unpredictable, ill-directed, and can occur in the absence of clear
triggers or provocation (Eslinger et al., 1995; Wood & Liossi, 2006). Individuals with
TBI have a significantly increased risk of committing a violent crime (Fazel et al.,
2011). While TBI cannot be assumed to be the sole cause of offending, the cognitive
and behavioural sequelae of TBI may predispose some individuals (Brower & Price,
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2001; deSouza, 2003; Greve et al., 2001; Kreutzer et al., 1995; Kreutzer et al., 1991;
Miller, 1999; Simpson et al., 1999).
Relationship between TBI in females and offending
A recent report commissioned by the Barrow Cadbury Trust emphasised the need for
research examining causes and consequences of TBI in female offenders specifically
(Williams, 2012). Shiroma, Ferguson and Picklesimer’s (2010a) study of TBI in US
prisoners revealed a male and female prevalence estimate of 64.41% (95% CI: 53.3 to
75.53%) and 69.98% (95% CI: 50.18-89.79%) respectively. The prevalence of TBI in
UK female offenders is currently unknown. A valid screen for TBI in female offenders
would facilitate research and support clinical practice. There are currently no validated
published screening tools for use with UK female offenders. The Brain Injury Screening
Index (BISI; Pitman et al., 2013) has been validated in male offenders in the UK, but
has yet to be extended to females.
Without adequate screening in female offenders, TBI is likely to go undetected, and
may impact on engagement in offender rehabilitation programs and the legal process
(Jackson & Hardy, 2011). Individuals with TBI may be more difficult to rehabilitate and
discharge (Hawley & Maden, 2003), with services ill-equipped to address their needs.
Research in this field is congruent with the Transforming Rehabilitation strategic
business priorities within the National Offender Management Service (NOMS; National
Offender Management Service, 2013) and may increase efficiency by informing
programs to reduce recidivism.
Officials within the criminal justice system may misinterpret behaviour of offenders
with TBI (Merbitz et al., 1995; Shiroma et al., 2010b). Research demonstrating
increased disciplinary incidents in prisoners with TBI (Merbitz et al., 1995; Morrell et
al., 1998; Shiroma et al., 2010b) suggests that they may have increased difficulty
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adapting to prison life due to cognitive and behavioural sequelae. This has implications
for engagement in the legal process, prison management, and post-discharge and release
pathways (Jackson & Hardy, 2011). Under-identification is likely to perpetuate
inadequate resources, providing no incentive to fund appropriate interventions and
inefficient use of available resources. Screening is consistent with NOM’s Reducing
Prison Unit Costs strategic business priority by ensuring appropriate services are
commissioned and targeting the most appropriate offenders (NOMS, 2013), e.g.
screening can provide a cost-effective way of determining who is appropriate for
referral to more limited and expensive resources such as neuropsychologists, or
alternative care pathways.
Risk factors for offending in females with TBI
Females are reportedly less likely to offend than males, yet those who do are more
likely to be experiencing a mental illness (Butler et al., 2005; Fazel & Grann, 2006).
New-onset major depression post-TBI increases the risk of aggression for females
eightfold (Rao et al., 2009). PTSD may also be a significant risk factor (Johansson et
al., 2008). Comorbidities may moderate or mediate the relationship between TBI and
offending in females.
Physical and sexual abuse throughout the lifespan may be a risk factor (Brewer-Smyth
& Burgess, 2008; Brewer-Smyth, Burgess, & Shults, 2004; Shiroma et al., 2010b).
Abuse commences for female prisoners at a young age (Browne et al., 1999). Childhood
victimisation strongly predicts victimisation in adulthood (Browne et al., 1999), and
adult victimisation in turn increases the risk of TBI (Kwako et al., 2011), which may
lead to increased violent behaviour. This is consistent with Brewer-Smyth and Burgess’
(2008) findings that female prisoners with more TBIs and violent crime convictions
have increased childhood family sexual abuse.
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Post-TBI aggression may be related to being a victim of intimate partner violence
specifically. Shiroma et al. (2010b) found a decreased likelihood of suffering a TBI
whilst incarcerated. Brewer-Smyth et al. (2004) found increased recency of abuse and
hospitalisations for abuse-related injuries in those with violent crime convictions, with
most TBIs occurring in the fronto-temporal region, which has been related to post-TBI
aggression in the literature (Daoust et al., 2006).This lends some tentative support for a
relationship between intimate partner violence and post-TBI aggression.
Brewer-Smyth et al. (2004) examined the cumulative effects of recurrent TBIs on
violence, finding evidence for a dose-response effect between number of TBIs and
violence. These findings are consistent with previous research which has found reported
prevalence rates of multiple TBIs in female offenders ranging from 35-48% (Ferguson
et al., 2012). Multiple mild TBIs can have similar cognitive and behavioural profiles to
individuals with more severe TBI (Diamond et al., 2007).
Research Questions
How prevalent is TBI and how does TBI present itself in the cognitive, psychiatric
and health needs of female prisoners in the UK?
Is self-reported TBI using the BISI associated with cognitive performance in
standardised questionnaires and neuropsychological tests?
Main Hypotheses
Female offenders in the UK demonstrate similar prevalence of TBI as males.
The BISI provides an estimate of prevalence within the confidence intervals of
studies using clinical interviewing.
Results of the BISI will be significantly associated with those obtained in the
standardised questionnaires and neuropsychological tests.
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The BISI will have a test-retest reliability coefficient of at least 0.60.
Female offenders with self-reported TBI have significantly more cognitive,
psychiatric, and physical health difficulties than female offenders without TBI.
Female offenders with self-reported TBI have higher historical rates of recidivism
and behavioural infarctions that those without TBI.
Method
Participants
Participants will be recruited from prisons for women in southern England, with four
potential prison sites. These prisons have a combined operational capacity of
1,607women from which potential participants can be recruited.
To explore prevalence and severity of TBI in the UK (stage 1), using Daniel and Cross’
(2013) formula for sample size calculation for prevalence studies, on the basis of a level
of confidence of 95%, an expected prevalence of 66% in female offenders using the
gold standard of clinical interviews (Shiroma et al., 2010a), and a precision value of
0.125, a sample of 56 female offenders would be required for stage 1. A large precision
value was chosen due to feasibility related to resource limitations, and the preliminary
nature of this research. The precision value meets the assumption of normal
approximation. To assess the test re-test reliability of the BISI, based on a minimum
reliability of 0.6, an expected reliability of 0.8, α=0.05 and β=.20, an estimated sample
of 39 of the original 56 will be required (Walter, Eliasziw, & Donner, 1998).
To explore the differences in cognitive, psychiatric and health needs of female offenders
with TBI and those without TBI, as well as rates of recidivism and behavioural
infarctions, based on the number of variables being measured, an anticipated large effect
size, statistical power of .80 and type I error α of .003 (Bonferroni correction for 14
comparisons), a sub selection of 28 participants with TBI and 28 without TBI will be
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required for stage 2.Based on similar research using the BISI with male prisoners
(Pitman et al., 2013) the estimated response rate is 73%, therefore a total of 76 prisoners
will be approached for consent.
Inclusion criteria include prisoners over 18, with an upper age limit of 80 years of age in
line with norms provided in the instruments to be used. Exclusion criteria include acute
symptoms of physical or mental illness or other indication that participants may not be
able to provide informed consent. This will be achieved by excluding participants in the
medical unit. Acute illness and ability to provide consent is also assessed in the clinical
interview, at which point the assessment will be terminated. Prisoners with a confirmed
diagnosis of dyslexia, are not fluent in English, or have reported acquiring a TBI in the
last 6 months, will be excluded from stage 2 due to validity limitations of measures.
Participants with a learning disability will be included unless queries regarding capacity
to consent are raised when are being briefed.
Design
Cross-sectional design using a semi-structured clinical interview, clinical
questionnaires, and neuropsychological measures.
Measures/Interviews/Stimuli/Apparatus
Please see Appendix I for the Participant Information Sheet and Appendix II for the
Participant Consent Form. For psychometric properties of measures please refer to
Table 1 Appendix III. The following assessment tools will be employed:
Semi-structured interview designed for use in male prisoners, which has been adapted to
extend to research to female prisoners (Appendix IV)
Pro forma for collecting data from participant files (Appendix V)
The Brain Injury Screening Index (BISI; Appendix VI)
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The Wechsler Abbreviated Scale of Intelligence II (WASI-II; Wechsler & Zhou, 2011).
The Test of Premorbid Functioning – UK Version (TOPF; Wechsler, 2009)
The Behavioural Assessment of the Dysexecutive Syndrome (BADS; Wilson,
Alderman, Burgess, Emslie, & Evans, 1996)
The Repeatable Battery for the assessment of Neuropsychological Status (RBANS;
Randolph, 1998)
The Test of Memory Malingering (TOMM; Tombaugh, 1996)
Neurobehavioral Functioning Inventory (NFI; Kreutzer, Seel, & Marwitz, 1999)
The Beck Anxiety Inventory (BAI; Beck, Epstein, Brown, & Steer, 1988)
The Beck Depression Inventory II (BDI; Beck, Steer, & Brown, 1996)
The Impact of Events Scale – Revised (IES-R; Appendix VI; Weiss & Marmar, 1997)
Pro formas are not provided in the appendices for assessments restricted due to
copyright.
Procedure
11. Participants will be recruited through a convenience sample. A list of prisoners who
have been new receptions over a 1-2 month period (depending on average intake
rate- until 76 participants are obtained for sufficient power and response rate
considerations) will be provided by prison staff. Prison staff will act as gatekeepers
and be asked to identify participants under 18, over 80, admitted to the medical unit,
or who cannot provide informed consent.
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12. Eligible participants will be provided with a copy of the participant information
sheet and consent form, i.e. a copy will be dropped into their cells by a member of
the research team.
13. Within a week of providing the information sheets prisoners will be contacted face-
to-face by a member of the research team to discuss the participation and consent. A
suitable time to commence assessment will be arranged with those who agree to
participate.
14. Participants will be allocated a participant number, which will be recorded with their
prison reference number, and recorded on an encrypted device. This will be separate
from the main data collection file.
15. At assessment, participants will complete the BISI and clinical interview (stage 1).
This will take approximately 1 hour. Participants will be provided with the clinical
questionnaires in the interview and asked to complete them in their own time. These
will then be collected at the end of each day of data collection. Participants will
complete all questionnaires themselves. Data on social history, abuse history,
clinical history, offence history, and behavioural infractions, will be obtained for
these participants from Offender Assessment System (OASys), probation and re-
offending records, and individual history files.
16. Participants will have the option of progressing on to stage 2 straight after stage 1,
or arranging a time to continue with the assessment.
17. Stage 2, consisting of the battery of neuropsychological measures, will occur at an
arranged time, with an expected sample of 28 participants with TBI and 28 without
a history of TBI. This will take 1½-2 hours.
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18. Participants who progress from stage 1 to stage 2 within 1-2 weeks of completing
the BISI will be asked to complete the BISI again for the purpose of test-retest
validity, until the required sample of 39 is reached.
19. As data is gathered it will be encoded in an SPSS data file stored on an encrypted
device for analysis.
20. Once data collection is completed appointments will be arranged with participants
who request an assessment feedback session. Participants may also request to have
results shared with the prison/health service. A brief report with results will be
provided.
Ethical considerations
7. Great effort will be made to clarify the nature of the relationship between the
researchers conducting assessments and the participant; i.e. it is not an assessment
from a clinical referral, that the primary purpose is research. However, participants
will have the opportunity to have a feedback session after the data collection is
completed and/or to have results shared with the prison/health services. Feedback
will be primarily descriptive and can be used to indicate if support from health
services is required.
8. Feedback on neuropsychological tests may impact on self-esteem, as mean prison
IQ in the UK is 88 (±12.0) (Hayes, Shackell, Mottram, & Lancaster, 2007). It is
hoped that the provision of information and training to staff and the potential for
additional support following the research will enable participants to feel
empowered, with the resources to manage difficulties.
9. Participants may assume that test results can be used for secondary gain, however
when briefing the participants it will be emphasised that tests will not be for clinical
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use, and only a recommendation for a comprehensive clinical examination can be
made. The TOMM (Tombaugh, 1996) will also be used to assess effort.
10. Due to the time required of participants motivation and fatigue may invalidate
results. To manage this, participants can complete stages on different days if they
wish, or have a brief break during testing if requested.
11. To ensure test validity the participating prisons will be requested to provide a quiet
environment, with adequate space, ventilation, lighting and furniture. We will also
liaise with staff to try to minimise potential interruptions during testing.
12. Information that is related to risk to self or others, including drug use and abuse,
may be disclosed. The research team will liaise with participating prisons to ensure
that the research protocol is congruent with prison policy to manage risk. Potential
limits to confidentiality will be made explicit to participants when obtaining
consent.
Name of Ethics Committee: University of Surrey Ethics Committee: Faculty of Arts and
Human Sciences; National Offender Management Service............................
R&D Considerations
Name of R&D department: R&D approval is not required however a letter of support
from governors of participating prisons will be obtained.
Proposed Data Analysis
All analyses will be done using IBM SPSS version 20 (IBM, 2011). Data will be
checked for normality of distribution and homogeneity of variance.
Descriptive statistics, including age, proportion of participants with a TBI, ethnicity,
education, learning disability, special support at school, diagnosis of mental health
problem, history of self-harm, suicide attempts, frequency of drug and alcohol use, age
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at first offence, number of offences, number of violent convictions, number of
behavioural infractions, participation in rehabilitation programs, and years spent in
custody, will be provided for those with an identified TBI and those without. This will
include means and standard deviations, and t-tests comparing those with and without a
TBI where appropriate. Further descriptive statistics will be provided for those with a
TBI, namely: number of TBIs, age at earliest TBI, loss of consciousness, cause of
injury, and help-seeking behaviour after TBI.
Concurrent validity of the BISI will be studied by calculating Pearson’s r between the
BISI and clinical interview. Receiver Operating Curve analysis will also be conducted
to assess sensitivity and specificity rates against clinical interview as the gold standard.
Test-retest reliability will be assessed using Pearson’s r.
Between samples t-tests will explore differences participants with TBI and without TBI
on cognitive, psychiatric and physical health measures.
Service User and Carer Consultation / Involvement
Service user and carer consultation was undertaken on 6th August 2013 and informed
this proposal (see Appendix VI for feedback).
Feasibility Issues
As the study is highly dependent on the amenability of the prison involved, there
must be organisational incentive for participation. After the study is complete,
the research team will provide a training and information session with prison
staff to support them in their roles when working with female offenders with
TBI.
Prisons participating must be able to provide adequate support in the event that
participants are distressed after the study. To overcome this we are liaising with
potential prisons and will prioritise the research site accordingly. We are also
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aiming to obtain sensitive data on abuse history from the OASys to reduce the
risk of distress.
Cost of pro formas for the copyrighted measures used is high (totalling
£1418.40), and exceeds the research budget provided by the University of
Surrey. The Disabilities Trust have agreed to cover the cost of pro formas
exceeding the research budget.
Dissemination strategy
Analysed data will be written up in a thesis as part of a doctorate, and disseminated
through research articles (e.g. The Journal of Head Trauma; Brain Injury) and
conferences (The Annual Division of Forensic Psychology conference; International
Association of Forensic Mental Health conference). A briefing can also be provided for
the prison’s newsletter. The Disabilities Trust Foundation will publish results through
reports, presentations, journal articles, and on their website.
Study Timeline
Please see Gantt chart in Appendix VII.
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Clinical Experience Précis
The following is an overview of the experience gained from clinical placements.
Year One:
Community Mental Health Team - 12 months.
This placement involved offering psychological assessments and interventions
to adults presenting with a range of mental health difficulties in the community at a
secondary care level. The main model utilised was CBT, however I also got to draw on
third wave models such as Acceptance and Commitment Therapy and systemic model.
The multi-disciplinary team consisted of psychiatrists, psychologists, nurses, social
workers, and an occupational therapist. I also got to run relaxation groups in the
affiliated acute ward, which was valuable in obtaining an understanding of the clinical
pathway and progression of the client group. Presenting problems included anxiety,
depression, obsessive-compulsive disorder, psychosis, bipolar affective disorder and
interpersonal issues. During this placement I learned complex formulation skills, and
the importance of perceiving an individual’s life narrative rather a reductionist
diagnostic category.
Year Two:
Community Mental Health and Learning Disabilities Team – 6 months
This placement involved offering assessment, treatment and consultation for
those with a Learning Disability and additional mental health needs, and their families,
carers and staff teams. This placement has involved using CBT, systemic work, and
narrative therapy, as well as neuropsychological assessment and formulation.
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On this placement I have learned the true meaning of a strengths-based approach
and the power of working with families and wider systems. I learnt how to support
individuals in finding their voice, and developed the confidence in being a voice for
those who could not. I learnt how to adapt how I communicate complex ideas, and
synthesise vast amounts of clinical information. I learnt the power of mentalising
everyone in the system, and uniting people in visions they did not realise they shared.
Child and Adolescent Mental Health Service (CAMHS) and Youth Offending Team
(YOT) – 6 months
My CAMHS placement offered assessment and treatment to children and their
families using a range of approaches. During this placement I used CBT, Solution-
focused approaches, and a great deal of systemic thinking. During this placement I
worked with children who were presenting with a range of problems with anxiety,
mood, cognitive, and behavioural difficulties.
As part of the YOT, I worked with two young people whose complex
presentations contributed to involvement in the criminal justice system. This really
taught me about working with complexity, acknowledging the limits of the therapy
room, and the role of the psychologist in providing containment for the system. I had
the opportunity to work with a range of professionals in this placement including those
in mental health services, youth offending officers, and schools.
Year Three:
Older Adults Community Mental Health Team, Memory Assessment Service and
Challenging Behaviour Service – 6 months
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This placement was split between three roles. The Community Mental Health
Team involved offering individual therapeutic intervention to older adults presenting
with a range of low mood, anxiety, and interpersonal problems. A further role was
offering assessment and consultation to care homes which were reporting experiencing
challenging behaviour from residents, specifically with a diagnosis of dementia. The
third role on this placement was assessment and intervention for those experiencing
cognitive problems. Assessment involved a full and comprehensive battery of
neuropsychological tests, designed to profile cognitive strengths and weaknesses and to
compare this to premorbid functioning to aim to assess for dementia or other cognitive
changes in conjunction with colleagues in psychiatry and neurology.
During this placement I particularly learnt how to create safe non-blaming
spaces for care staff to reflect on their clinical practice, and reconnect with their
compassion which can be compromised in such demanding work environments.
Specialist Trauma Service for Veterans – 6 months
This is a service offering psychological support for veterans experiencing mental
health difficulties, particularly post-traumatic stress disorder (PTSD). The service
provides an intensive residential trauma-focussed CBT programme, as well as brief two
week psychoeducational residential programmes. I also had the opportunity to work
with clients on an outpatient basis. During this placement I offered trauma focussed
CBT, and compassion focussed therapy particularly for those experiencing high levels
of guilt and shame. I also ran a range of psychoeducational groups and provided group
nursing supervision.
This placement taught me to understand and work with complex group
dynamics, and to be aware of issues around transference and counter-transference, and
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how to use these therapeutically. Understanding how an individuals’ history before
exposure to a trauma contribute to their responses to trauma has been important
learning. One of the most valuable elements was learning to utilise micro-expressions in
the therapy room, and working within the therapeutic window of distress particularly
when with clients at high risk of disassociation.
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Summary of Assessments
Year I Assessments
PROGRAMME
COMPONENT
TITLE OF ASSIGNMENT
Fundamentals of Theory
and Practice in Clinical
Psychology (FTPCP)
Short report of WAIS-IV data and practice
administration
Practice case report ‘Assessment with a 35 year old man presenting with
depression and multiple sclerosis, employing an
Acceptance and Commitment Therapy based
formulation’
Problem Based Learning
– Reflective Account
Problem Based Learning – Reflective Account. The
Relationship to Change
Research – Literature
Review
‘Traumatic brain injury and violent behaviour in
females: A systematic review’
Adult – case report ‘Assessment and intervention with a 35 year old man
presenting with depression and multiple sclerosis using
an Acceptance and Commitment Therapy approach:
Reflections on treatment challenges
Adult – case report ‘Assessment and intervention with a 36 year old man
presenting with psychosis using a Cognitive
Behavioural Therapy (CBT) approach: Incorporating an
interventionist-causal model with first generation CBT’
Research – Qualitative Experiences of Romantic Relationship Formation Using
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PROGRAMME
COMPONENT
TITLE OF ASSIGNMENT
Research Project Computer-Mediated Communication: A Thematic
Analysis
Research – Major
Research Project
Proposal
Traumatic Brain Injury in Adult Female Offenders in
the UK
Year II Assessments
PROGRAMME
COMPONENT
TITLE OF ASSESSMENT
Research - SRRP An evaluation of the prevalence of poor sleep quality and
provision of treatment amongst service users under a
Community Mental Health Team
Research Research Methods and Statistics test
Professional Issues
Essay
It has been six years since Mencap’s report, Death by
Indifference, highlighted unequal healthcare and
institutional discrimination that people with learning
disabilities can experience within the NHS. What remains
to be done to achieve a more responsive and
compassionate culture of care? What is the role of clinical
psychology in initiating, sustaining and supporting this
culture?
Problem Based Problem Based Learning (PBL) Reflective Account. The
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Learning – Reflective
Account
Stride Family
People with Learning
Disabilities – Case
Report
Extended assessment and formulation with a 22 year old
man presenting with a moderate learning disability and
behaviour that challenged his college
Personal and
Professional Learning
Discussion Groups –
Process Account
Personal and Professional Learning Discussion Group
Process Account
Child and Family –
Oral Presentation of
Clinical Activity
Working with diversity: from individual cognitive
behavioural (CBT) therapy to systemically informed CBT
Year III Assessments
PROGRAMME
COMPONENT
ASSESSMENT TITLE
Research – MRP
Portfolio
Utility of the Brain Injury Screening Index in Identifying
Female Prisoners with a Traumatic Brain Injury and
Associated Cognitive Impairment
Personal and
Professional Learning –
Final Reflective
On becoming a clinical psychologist: A retrospective,
developmental, reflective account of the experience of
training
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Account
Older People – Case
Report
Neuropsychological assessment with a woman in her
early seventies presenting with memory problems and a
diagnosis of mild cognitive impairment
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