An Exploration into the Relationship between Executive Function, Adult Attachment Style and...
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An Exploration into the Relationship between Executive Function, Adult Attachment Style and Addiction Severity in a Treatment Programme for Problematic Substance Users Anne Marie Brown MSc Alcohol and Drug Studies Supervisor: Dougie Marks
Transcript of An Exploration into the Relationship between Executive Function, Adult Attachment Style and...
An Exploration into the Relationship between Executive Function,Adult Attachment Style and Addiction Severity in a Treatment
Programme for Problematic Substance Users
Anne Marie Brown
MSc Alcohol and Drug Studies
Supervisor: Dougie Marks
THIS DISSERTATION IS SUBMITTED IN PARTIAL FULFILMENT OF THE REQUIREMENTS OF THE UNIVERSITY OF THE WEST OF SCOTLAND FOR THEMSc IN ALCOHOL AND DRUG STUDIES
Acknowledgements
I would like to thank my supervisor, Dougie Marks for hisendless patience and help throughout this research project. Iwould also like to thank my husband James and children, Carlaand Sam for their faith, belief and support throughout thistime.
I especially give thanks to the staff and patients at Lothiansand Edinburgh Abstinence programme (LEAP) as without theirparticipation, support and assistance this dissertation wouldnot have been possible.
Table of Contents
Abstract………………………………………………………………………………………………………………………………….1
1. Introduction................................................21.1 Addiction..........................................21.2 Recovery.........................................2-3
2. Literature Review.......................................................................................................................4 2.1 Executive Function………………………………………………………………………………………..……4
2.2 Executive Function and Problematic Substance Use. 4-7 2.3 Treatment Outcomes...............................7-8 2.4 Attachment.......................................8-9 2.5 Adult Attachment Styles and the Relationship with Problematic Substance Use..........................................9-10 2.6 Attachment Related Anxiety....................11-12 2.7 Adult Attachment Measures.....................12-13 2.8 Rationale for Research...........................13
3. Methodology................................................14 3.1 Design...........................................14 3.2 Participants.....................................14 3.3 Measures.........................................14 3.4 Adult Attachment Scale...........................15 3.5 Behavioural Assessment of the Dysexecutive Syndrome………….…………….…..16-17 3.6 Addiction Severity Index (ASI-X)……………………………………………………………………….17 3.7 Procedure.....................................18-19 3.8 Ethical Consideration............................19
4. Results....................................................20 4.1 Power Calculation...............................20 4.2 Descriptive Statistics..........................20 4.3 Independent Samples T-Tests.....................21 4.4 Correlations.................................22-27 4.5 Linear Multiple Regression……………………………………………………………………….. 27-28
5. Discussion.................................................29 5.1 Age..........................................29-31 5.2 Anxiety......................................31-32
5.3 Family, Employment and Education.............32-33 5.4 Strengths and Limitations of the Study.......33-34 5.5 Future Research Implications…………………………………………………………….….. 34-36 5.6 Conclusion………………………………………………………………………………………………….. 36
Table of Contents (Cont’d)
References………………………………….…………………………………………………………………………………. 37-42
List of TablesTable 1: Descriptive Statistics.......................20Table 2: Descriptive Statistics.......................20Table 3: Independent Samples T-Test...................21Table 4 Correlations.................................23Table 5: Relationship between Composite Scores Alcohol and Drugs (ASI-X) and BADS Tests.............................24Table 6: Relationship between Composite Scores Medical, Employment, Family Composite Scores Alcohol and Drugs (ASI-X).....................................................25Table 7: Relationship between Composite Scores Alcohol, Drugs and Years of School and Higher Education (ASI-X) . . .25Table 8-9: Relationship between Age First Use Alcohol (ASI-X) and Total Scores Close and Anxiety (AAS).............26Table 10: Gender, Age, Years of School Education and ASI-X Composite Score Alcohol..............................27Table 11: Gender, Age, AAS Anxiety, Age and ASI-X Composite Score Drugs..................................27Table 12: AAS Close, Depend, Anxiety and Composite Score Drugs .................................................28
Abstract
Background: Problematic use of alcohol and drugs has been
shown to have a negative impact on the individual and society.
As the individual differences that clients bring to treatment
services can impact on outcomes, the aim of this research
project was to explore the relationship between executive
function, adult attachment style and addiction severity. The
researcher’s hypothesis was two-fold (1) that executive
function and (2) adult attachment style would have a
significant relationship with problematic substance use.
Additionally, the composite scores from the Addiction Severity
Index (ASI-X) were used to predict problematic substance use.
Methods: Participants (n=36), males (n=21) and females
(n=15), age range 24-59, mean age 41, were recruited from a
bio-psychosocial treatment programme for problematic substance
use. The Adult Attachment Scale (Collins and Reid, 1990) was
used to measure adult attachment style and the Behavioural
Assessment of the Dysexecutive Syndrome (BADS), which is a
series of six cognitive tests and two questionnaires (DEX) was
used to measure Dysexecutive Syndrome (Wilson et al., 2003).
Results: No significant relationship was found between the
BADS tests and DEX questionnaires and the ASI-X composite
scores, alcohol and drugs. However, significant relationships
were found between age and attachment related anxiety, the
composite scores alcohol and drugs and the cognition component
of the DEX questionnaire. Linear regression analysis showed
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that age and anxiety predicted 23% and 17% consecutively of
problematic substance use.
Conclusions: Future research in this area should focus on
longitudinal studies to assess whether prolonged abstinence
has an impact on executive functions. There is a clinical
need for adult attachment and executive function assessments
to be implemented in the initial stages of treatment planning
and treatment plans tailored to suit the individual needs of
clients who present for problematic substance use.
Keywords: Executive function, Adult Attachment, ProblematicSubstance Use, Recovery, Treatment Outcomes
1. Introduction
1.1 Addiction
Addiction or dependence on drugs or alcohol has been defined
as a “chronic, relapsing, inability to control drug or alcohol
intake or compulsive use, and negative affect in the absence
of the drug or alcohol” (Ketcherside, Matthews and Filbey,
2013, p.1). This definition suggests that an individual has
increased tolerance, experiences loss of control, withdrawal
and craving and has an inability to stop using a particular
substance to the detriment of all other activities. This
definition also suggests that individuals who problematically
use alcohol and drugs are incapable of remaining abstinent for
long periods of time, perhaps due to deficits in the frontal
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lobes of the brain (Wang et al., 2013; Hester, Lubman and
Yucel, 2009). However, Krippner et al., (2012) argue that
addiction is a social construct, the definition of which can
change depending on societal and cultural views and
encompasses many other areas for example, learning, memory,
emotional and environmental influences.
1.2 Recovery
Problematic use of alcohol and drugs has been shown to be
associated with societal and negative health outcomes. Recent
research has suggested that various factors can be involved in
and contribute to problematic substance use (PSU). For
example, individual differences such as early life trauma,
stress, age, gender, social background, educational
opportunities, psychological and neurological issues can all
impact on the health and well-being of individuals who seek or
are referred to treatment services which in turn may affect
treatment outcomes (UK Focal Point on Drugs, 2011; Hammersley
and Dalgarno, 2013; Music. 2014). Recovery from problematic
use of alcohol and drugs is the dominant paradigm in Scotland
at the present time and accordingly, The Scottish Government
publication ‘The Road to Recovery’ (2008) defines recovery as
a ‘process through which an individual is enabled to move on
from their problem drug use, towards a drug free life as an
active and contributing member of society’ (The Scottish
Government, 2008, p.6).
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However, in order to assist individuals with their recovery
journey, health professionals and treatment services would
benefit from research that highlighted the characteristics
that clients bring to treatment. This knowledge would help to
ensure that an individual has the motivation, planning and
problem solving abilities for the successful completion of a
treatment programme. Moreover, research has shown that the
individual differences of clients who attend treatment
settings such as impairments in executive function and adult
attachment styles can have a detrimental relationship with
PSU, in terms of developing the therapeutic process and
treatment outcomes (Aharonovich et al., 2008; Meier et al.,
2005). Therefore, it is beneficial to study these variables
in order to improve client engagement with services and
treatment effectiveness (Urbanoski et al., 2012).
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2. Literature Review
2.1 Executive Function
Executive functioning (EF) is the term used to describe a
variety of related cognitive skills, namely, decision making,
planning, working memory, problem solving, motivation, verbal
reasoning, inhibition of impulsive responses, initiation and
monitoring of action and are carried out in the prefrontal
cortex (PFC) of the brain (Wilson et al., 2003; Verdejo-Garcia
et al., 2006; Crews and Boettiger, 2009). These cognitive
abilities are necessary for individuals to be able to monitor
and change behaviour in order to function independently on a
daily basis (Blume and Marlatt, 2009).
Dysexecutive syndrome is the collective name for impairments
in the frontal lobes of the brain. These impairments have
been found in patients with acquired brain injury, for
example, patients who have suffered head injuries, strokes or
cerebral tumours (Bennett, Ong and Ponsford, 2005; Spikman et
al., 2009). Clinical treatment and rehabilitation of patients
with these lesions has been found to be difficult due to the
patient’s inability to plan, set goals, problem solve or
follow a treatment plan successfully. Therefore, dysexecutive
syndrome is an important area for researchers to study in
terms of recovery and treatment outcomes. Furthermore, Miyake
and Friedman (2012) argue that “EFs are important to study
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because they are a core component of self-control or self-
regulation ability (or “willpower”) which has been shown to
have broad and significant implications for everyday lives”
(Miyake and Friedman, 2012, p.8). However, due to the
difficulties in assessing EF in everyday living, recent
research has suggested a multi-faceted approach to treatment
and rehabilitation which could be tailored to suit each
individual patient’s needs (Spikman et al., 2009).
2.2 Executive Function and Problematic Substance Use
Executive functioning has also been shown to be an area of
interest to researchers in the substance misuse field.
Previous research has demonstrated that individuals who
problematically use drugs and alcohol experience impaired
executive control tasks which rely on different systems within
the PFC: the dorsolateral pre-frontal cortex (DLPC);
orbitofrontal cortex (OFC) and anterior cingulate cortex
(ACC). This dysfunction is associated with different
behavioural, cognitive and emotional deficits and can impact
on working memory, abstract reasoning and cognitive
flexibility (Verdejo-Garcia et al., 2005; 2006).
Additionally, research by Fernandez-Serrano et al., (2010);
George and Koob, (2010) argues that empirical evidence from
human and animal studies show that certain areas of EF namely,
dysfunctional impulsivity and decision-making may have
deficits that pre-dispose PSU, thereby mediating the
transition from recreational drug use to problematic drug use.
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Furthermore, deficits in EF may hinder an individual’s
treatment outcomes in terms of planning, decision-making,
problem solving, abstract thinking and goal-setting. These
skills are all required to facilitate the therapeutic
relationship and for treatment effectiveness (Hester, Lubman
and Yucel, 2009). For example, interventions such as
cognitive behavioural therapy (CBT), motivational interviewing
and relapse prevention would only be effective if a client had
the necessary abilities and coping skills to engage with a
treatment plan (Hill and Colistra, 2014). Aharonvich et al.,
(2008) found that problematic cannabis users (n=20) treated
with combined motivational enhancement therapy and CBT for a
period of 12 weeks and assessed with neuropsychological tests
at treatment entry, exhibited lower scores on cognitive
measures and were more likely to drop out of treatment than
individuals with higher scores at baseline. Although the
sample size in this study was small it reflects the need for
individuals to have the necessary cognitive abilities to
follow an evidence- based treatment plan.
Consequently, EF deficits may be subtle and the lack of
assessment tools to identify specific deficits at the
treatment planning stage may explain poor engagement,
motivation and risk of relapse in PSU individuals (Blume and
Martlatt, 2009; Potenza et al., 2011). Recent research has
indicated that early assessment for EF deficits followed by
specific tailoring of treatment to suit individual need is an
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important concept to consider (Blume and Martlatt, 2009).
Accordingly, these authors argue that “Treatment providers
should assess clients for ECF deficits, which can be difficult
to detect by observation alone and adjust treatment plans
accordingly” (p.123). However, as already stated individuals
would require the skills and abilities to successfully
complete the treatment process.
As discussed earlier in this paper, PSU has been shown to have
a deleterious relationship with EF, negatively impacting on
treatment outcomes. Research has shown that problematic use
of alcohol over a long period can impact on cognitive and
executive functions due to the neurotoxic effects of
intoxication and withdrawal from alcohol (Maharasingam,
Macniven and Mason, 2013). Additionally, nutritional
deficiencies caused by problematic use of alcohol can lead to
Korsakoff Syndrome (KS). Patients with KS will experience
“dense anterograde” and “retrograde amnesia” (Maharasingam et
al., 2013, p1. These authors measured two groups of patients,
KS (n=15) and chronic alcoholics (n=16) with the Behavioural
Assessment of the Dysexecutive Syndrome (BADS) test and found
the KS group to have significantly more deficits in EF than
the chronic alcoholics group.
However, it is also suggested that periods of abstinence from
problematic use of drugs or alcohol may still result in
deficits in EF. For example, research by Zinn et al., (2004)
compared which areas of EF were impaired in early stages of
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abstinence in a group of problematic drinkers (n=27),
attending an out-impatient treatment clinic and an age matched
control group (n=18), recruited from a primary care setting.
They found that the two groups differed on tests of abstract
reasoning, memory discrimination and effectiveness on timed
tasks. The authors concluded that EF was still found to be
impaired early into the recovery process and that this
impacted on treatment effectiveness (Zinn et al., 2004).
However, as only male participants were included in this
study, this gender specific cohort may have had an effect on
the outcome of the research.
Furthermore, it has also been proposed that amphetamine users
(n=12) who had been abstinent for at least a year were shown
to have mild to moderate cognitive deficits in the areas of
attention, memory and executive function (Rapeli et al.,
2005). However, it should be noted that no measures were
taken to confirm abstinence, although participants were
reportedly attending regular mutual aid sessions.
Additionally, the sample size was not large enough to
demonstrate how cognitive functioning may improve with
abstinence from amphetamine use. In addition, a review of the
acute and long-term effects of cannabis use on EF found that
users who had been abstinent for more than three weeks
experienced deficits in decision making, planning and the
forming of new ideas (Crean, Crane and Mason, 2011). On the
other hand, Wang et al., (2013) found that problematic
methamphetamine users who had longer periods of abstinence, in
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this case up to a year, were found to have improved decision-
making capabilities than users with shorter abstinence
periods.
Nevertheless, although the above studies show that EF deficits
can still be present in early to longer-term abstinence,
future research would do well to concentrate on longitudinal
studies and follow up studies of clients who had previously
undergone treatment to ascertain if EF deficits can improve
with prolonged abstinence.
2.3 Treatment Outcomes
Executive functioning has been traditionally measured using
neuropsychological testing and neuro-imaging studies.
However, researchers recognise that EF is a challenging area
to test due to measurement difficulties which do not always
give an accurate picture of EF deficits in day-to-day living
(Spikman et al., 2010; Miyake and Friedman, 2012). However,
research in this area tends to focus solely on cognitive and
EF functions, while important to addiction research, ignore
other factors which can impact on treatment outcomes. For
example, individuals attending treatment settings for PSU can
experience stigma and shame at the micro and macro levels
which has been shown to hamper an individual’s recovery
journey (McPhee, Brown and Martin, 2013; Lloyd, 2010).
Although the notion of stigma is not the focus of this
research paper it merits attention as a barrier to successful
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treatment outcomes. For a fuller review of stigma and shame
experienced by problem drug users (see McPhee et al., 2013).
Age is another factor which is important to consider in terms
of recovery. The ‘maturing out theory’ suggests that
individuals can mature out of problematic drug and alcohol
use. Best et al., (2010) found that problematic users of
heroin had ‘addiction careers’ that were much shorter than
alcohol users. Reasons for sustained abstinence were varied
but were supported by recovery networks.
With this in mind, the notion of recovery capital (Laudet and
White, 2010), recovery communities or mutual aid support
networks could lend support to an individual’s recovery from
PSU and integration back into society. Recovery capital
proposes that individuals utilise resources available to them
in the form of social, physical, human and cultural capital.
For example, self-care, seeking support from their immediate
environment in terms of family or friends or from the wider
environment in terms of community or financial support
(Granfield and Cloud, 1999; 2001, as cited in Marks and Burns,
2013). Studies have shown that positive social support and
networks can help problem users to achieve abstinence and
avoid relapse prevention which can all lead to successful
outcomes for the individuals concerned (Buckman, Bates and
Morgenstern, 2008).
2.4 Attachment
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A further area of research that is often not taken into
consideration when discussing treatment outcome is that of
attachment. Attachment theory refers to the idea that one’s
early interaction with caregivers plays a fundamental role in
the development of the temperament of the individual, by
providing a template for how the individual negotiates the
social world into which they grow up (Ainsworth and Bowlby,
1991). Research by (Ainsworth et al., 1978, cited in Collins
and Read, 1990) explored individual differences in attachment
relationships by observing caregivers and infants, ‘the
Strange Situation’. This research resulted in three styles of
attachment being identified: secure, avoidant/ambivalent and
anxious. The notion being that if the primary care-giver is
responsive to their biological and emotional needs a child
will form a secure attachment to that person, a ‘secure base’
in which to explore their environment, in the knowledge that
the care-giver is in close proximity. However, if the primary
care-giver is unresponsive or ambivalent in their interactions
with the child they will form an avoidant or
anxious/ambivalent attachment style.
It was also proposed that these early interactions with a
primary care-giver result in the infant forming an internal
working model or schema of how they view themselves and others
in close relationships and which it is suggested influence
relationships in later life (Ainsworth and Bowlby, 1991).
Therefore, internal working models can be defined as “mental
representations of the self or others” (Pietromonaco and
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Barrett, 2000, p.155). However, it has also been argued that
attachment styles and internal working models can adapt and
assimilate depending on life circumstances and relationships
formed (Hazen and Shaver, 1987). The concept of ‘earned
attachment security’ postulates that individuals can develop
effective coping mechanisms and emotional regulation despite
an adverse childhood (Moller, McCarthy and Fouladi, 2002 as
cited in Thorberg and Lyvers, 2010; McCarthy and Maughan,
2010).
The concept of attachment styles was applied to adult
relationships by Hazen and Shaver (1987). They proposed that
adult romantic relationships are a biological attachment
process and operate in much the same way as infant-primary
caregiver bonds. Collins and Read (1990) further developed
these attachment dimensions into the Adult Attachment Scale, a
measure of adult attachment, incorporating the sub-scales
close, depend and anxiety, developed from the original
attachment dimensions, secure, avoidant and anxious.
Following on from this, Bartholomew and Horowitz (1991)
developed a four category model of adult attachment using
Bowlby’s notion of internal working models of self and others
and proposed four constructs of adult attachment: (1) a
secure attachment style which suggests a positive model of
self and a positive model of others; (2) a pre-occupied
attachment style which postulates a negative model of self and
a positive model of others; (3) a fearful attachment style
which suggests a negative model of self and a negative model
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of others and (4) a dismissing attachment style suggesting a
positive model of self and a negative model of others. Thus,
it can be proposed that…”Adult attachment style, then, refers
to particular working models, or schemas, of self and others
that are related to both interpersonal and emotional
functioning” (Doumas, Blasey and Mitchell, 2008, p.42).
2.5 Adult Attachment Styles and the Relationship with
Problematic Substance Use
Empirical studies which have investigated adult attachment
have explored numerous psychological variables relating to
attachment styles, for instance, social learning theory,
childhood adversity, personality and depression (Mickelson,
Kessler and Shaver, 1997). However, research which has
explored the relationship between adult attachment styles and
PSU has focussed mainly on insecure or avoidant attachment
styles (Thorberg and Lyvers, 2006). The justification for
this area of research has been that individuals deemed to have
a secure attachment style typically do not use substances
problematically as they are able to manage stress and anxiety
in an effective manner (Cooper, Shaver and Collins, 1998). On
the other hand, research has found that individuals with an
insecure attachment style use drugs and alcohol
problematically which result in maladaptive coping mechanisms
of dealing with trauma, stress, anxiety and low self-esteem
(Schindler et al., 2009; Kassel, Wardle and Roberts, 2007).
Furthermore, insecure attachment can be linked to a host of
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negative outcomes, for example, an inability to bond with
significant others in social or romantic relationships. This
can be as a result of lack of trust or fear of abandonment, or
the belief that the individual will not receive support from
their partner in times of need. This belief system can lead
an individual to use alcohol or drugs problematically to
alleviate stress and anxiety (Davidson and Ireland, 2009).
Another aspect of insecure attachment which has been
previously researched is the self-medication hypothesis which
again proposes that individuals use alcohol and drugs
problematically to alleviate the symptoms of psychological
distress (Thorberg and Lyvers, 2006; Schindler et al., 2005;
Robinson et al., 2011). Hence, it could be argued that an
insecure attachment style places individuals at higher risk of
PSU “that goes beyond recreational or experimental use”
(Schindler et al., 2009, p.308). However, it can also be
argued that it is unclear as to the trajectory between
attachment related anxiety and PSU. In other words, do
individuals with anxiety problematically use alcohol or drugs
to relieve psychological distress or does PSU exacerbate
anxiety and stress (Robinson et al., 2011; Gorka et al.,
2014).
Subsequently, Schindler et al., (2009) compared attachment
styles in three groups of individuals attending PSU treatment:
heroin (n=22); ecstasy (n=31); cannabis (n=19) and a non-
clinical control group (n=22). In terms of attachment styles
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they found that heroin users were mainly fearful-avoidant,
ecstasy users were pre-occupied, fearful avoidant and
dismissing-avoidant and cannabis users were mostly dismissing
and secure. The control group were found to have a secure
attachment style which is thought to be seen as a protective
factor against PSU and is consistent with previous research in
this area (Cooper, et al., 1998; Caspers et al., 2006; Doumas
et al., 2007;). Moreover, Doumas et al., (2007) explored the
relationship between adult attachment, emotional distress and
interpersonal problems in an out-patient treatment programme
for PSU. They found that participants (n=46) with a pre-
occupied or fearful attachment style were shown to have
greater interpersonal issues in terms of anxiety and
depression than participants with a secure or dismissing
attachment style.
However, the authors acknowledge that the sample size in this
study was small and the research was carried out in an out-
patient setting with no control group. Therefore, the findings
may not generalise to other type of treatment settings.
Consequently, Borhani, (2012) found that individuals with an
insecure attachment style were more likely to have misused
substances than those with a secure attachment, which again
confirms previous literature. However, the researcher used a
very small sample (n=19), recruited from a university
population, which is not representative of typical problem
users in terms of levels of substance use, educational
attainment and demographics. Additionally, self-report
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measures of attachment style and substance use do not always
provide an accurate reflection of these variables.
2.6 Attachment Related Anxiety
Attachment related anxiety and fearful avoidant behaviour have
also been shown to have a relationship with PSU (Kelley et
al., 2004; Thorberg and Lyvers 2006). These attachment traits
may interfere with an individual’s ability to interact with
others in romantic relationships or indeed in social settings,
for example, “Mental attachment models are hypothesized to
determine whether individuals avoid or experience anxiety
about close social relationships (Griffin and Bartholomew,
1994b, as cited in Jenkins and Tonigan, 2011, p.855).
Individuals who are deemed to be insecure in terms of
attachment styles “have a reduced capability of experiencing
reliability, trust and safety through relationships” (Wedekind
et al, 2013, p.2). An example of such social interaction can
be found in treatment settings. Research has shown that
mutual aid groups such as Alcohol Anonymous (AA), Narcotics
Anonymous (NA) and Recovery Cafes have been found to aid
recovery from PSU in terms of peer support and community
networks (Campbell et al., 2011).
Jenkins and Tonigan (2011) found that participants (n=235)
recruited from AA 12-step groups and out-patient treatment
services, interviewed at baseline with the Relationship
Questionnaire, (Bartholomew and Horowitz, 1991) and followed
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up at six and 12 months respectively were found at baseline to
have higher anxiety attachment rates than the control group
who were recruited from a college population (n=87).
Interestingly, high attachment avoidance showed a correlation
with lower rates of attendance at 12-step group meetings.
These findings demonstrate that engagement in mutual aids
groups may be hindered by insecure/avoidant attachment styles.
It should be noted however, that the control sample was
relatively small compared to the PSU group and were recruited
from a college population, again this re-iterates the problem
of ecological validity.
Furthermore, Wedekind et al., (2013) explored the relationship
between anxiety attachment style, anxiety coping and
dysfunctional personality styles in a cohort of participants
(n=59) attending in-patient detox treatment for alcohol
dependence. The results of this study found that only 33% of
participants were found to have a secure attachment style.
Insecure attachment style was shown to be significantly
related to higher trait-anxiety which is consistent with other
studies in PSU treatment settings (Thorberg and Lyvers, 2006).
However, as in similar studies the cohort of participants was
comparatively small and there was no control group to compare
results. It is also worthy to point out that the use of self-
report questionnaires in a cohort of individuals who had
recently detoxed from alcohol use is questionable as this may
have confounded the results.
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2.7 Adult Attachment Measures
Adult attachment style has been found to relate to
difficulties in interpersonal functioning and intimacy in
relationships which can predict maladaptive coping strategies
and affect regulation (Thorberg and Lyvers, 2010). Adult
attachment is typically measured using either self-report
questionnaires, which although are not an in-depth assessment
of individual attachment styles, can still nevertheless tap
into unconscious processes and beliefs and are easy to
administer and not time-consuming (Hazan and Shaver, 1987;
Collins and Read, 1990; Bartholomew and Horowitz, 1991).
Alternatively, adult attachment can be measured using the
Adult Attachment Interview (AAI), (George, Kaplan and Main,
1985, as cited in McCarthy and Maughan, 2010). The AAI is a
semi-structured interview and “is designed to measure working
models of early child-parent relationships, not attachment-
related feelings and behaviors in adolescent and adult close
relationships, such as romantic or martial relationships”
(Shaver and Mikulincer, 2010, p.136)
Therefore, the AAI may help to identify unconscious thoughts
and beliefs in relation to childhood attachment dimensions.
Moreover, both instruments are a valid tool for measuring
adult attachment. Prior research has recommended assessing
attachment styles and interpersonal functioning when clients
present for treatment for PSU (Doumas et al., 2008). This
early intervention may help clinicians and health
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professionals to understand the behaviours and characteristics
underlying attachment styles, which could assist treatment
engagement and efficacy (Nanjappa et al., 2014).
2.8 Rationale for Research
This research paper thus far has attempted to demonstrate that
dysexecutive syndrome has been found to effect treatment
outcomes due to deficits in the frontal lobes of the brain
which interfere with a patient’s ability to execute planning,
decision-making and problem solving. Moreover, adult
attachment styles have been linked to PSU in terms of
maladaptive coping mechanisms and psychological distress, all
of which can lead to ineffective treatment outcomes.
Therefore, the aim of this study was to investigate the
relationship between executive functioning, adult attachment
style and addition severity in a treatment programme for PSU.
The researcher’s hypothesis was two-fold (1) that executive
function and (2) adult attachment style would have a
significant relationship with problematic substance use. The
researcher also hypothesised that the composite scores from
the Addiction Severity Index would predict problematic
substance use.
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3. METHODOLOGY
3.1 Design
This research employed a quantitative design, using a self-
report questionnaire to evaluate adult attachment style and a
battery of cognitive tests and two questionnaires to measure
dysexecutive syndrome. The independent variables were adult
attachment style and executive functioning, with addiction
severity being the dependent variable. Participants who took
part in the study were provided with a pack containing: a
participant information sheet (Appendix 1); participant
consent forms (Appendix 2) and the adult attachment style
questionnaire (Appendix 3).
3.2 Participants
Participants for this research (n=36) were recruited from
Lothians and Edinburgh Abstinence Programme (LEAP), which is a
12 week quasi-residential rehabilitation and treatment
programme for problematic substance use. The LEAP programme
is delivered in partnership with NHS Lothian Substance Misuse
Directorate, Edinburgh City Council, Transition/Access to
Industry and the Serenity Café (a community recovery hub). The
treatment programme follows a bio-psychosocial model focussing
on the therapeutic community and incorporates mutual
aid/recovery communities, housing, education, training and
employability and aftercare. The criteria for entry into the
programme are that patients are age 18 or over, be drug or
alcohol dependent and show willingness to achieve abstinence.
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3.3 Measures
Addiction severity was evaluated using data that had been
collected from the Addiction Severity Index (ASI-X; McLellan
et al, 1980) at initial assessment by treatment staff. This
assessment tool is routinely used by LEAP staff to assess a
patient’s suitability for treatment. The following measures
were used to evaluate adult attachment style and dysexecutive
syndrome.
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3.4 Adult Attachment Scale (AAS)
The AAS (Appendix 3) is an 18 item questionnaire which asks
individuals to read a series of statements about how they view
themselves in all close relationships including romantic,
family and friendships. Individuals then rate themselves on a
5 point likert scale (ranging from not at all characteristic
to very characteristic) with some items being reversed scored
(Collins and Read, 1990).
The AAS was adapted from Hazan and Shaver (1987) research into
adult relationships which proposed that romantic love is an
attachment process in much the same way as an infant forms a
bond with primary caregivers. This study incorporated the
original attachment styles: secure, anxious and avoidant as
proposed by (Bowlby and Ainsworth, 1991). Collins and Reid
(1990) in their research found that the way adults interact
and view relationships, romantic or otherwise can be
classified into the following subscales:-
Close – measures how comfortable an individual is with closeness
and intimacy;
Depend - measures how an individual believes others can be
depended on to be available when needed; and
Anxiety - measures the extent to which an individual feels
anxious about being abandoned or unloved by a significant
23
person involved in their life. High scores on close and
depend and low scores on anxiety would indicate a secure
attachment style.
The AAS has demonstrated test-retest reliability and internal
consistency, Cronbach’s alpha for the subscales depend,
anxiety and close were .75, .72 and .69 respectively (Collins
and Reid, 1990). The AAS has also demonstrated construct
validity (Domingo and Chambliss, 1998).
24
3.5 Behavioural Assessment of the Dysexecutive Syndrome
(BADS)
Executive functioning was measured using the Behavioural
Assessment of the Dysexecutive Syndrome (BADS) which
incorporates a battery of six tests and two self-report
questionnaires (DEX) (Wilson et al. 2003). Each of the tests
has a profile score which ranges from 0-4 with an overall
profile score calculated from each of the six tests The aim of
the BADS is to measure participants’ ability to plan,
initiate, monitor and adjust behaviour in response to the
explicit and implicit demands of a series of tasks. The DEX is
a 20 item questionnaire which has two versions (self-rater and
inter-rater) and measures the dimensions of cognition, emotion
and behaviour which are components of dysexecutive syndrome.
The scores from the DEX questionnaires are not included in the
overall profile scores. The BADS has demonstrated concurrent
and construct validity and has been shown to be an effective
measure of executive dysfunction (Norris and Tate, 2000). The
tests assess a variety of cognitive skills which are needed
for independent day-to-day living and are as follows:-
Rule Shift Cards: The purpose of this test is to identify
perseverative tendencies ie it requires participants to change
their behaviour to cope with the demands of a changing
situation and its obverse, mental flexibility. Participants
are required to respond to red or black playing cards
according to one of two rules that are presented
25
consecutively. The participant’s performance is timed and
scored according to how successfully they shift from applying
the first to the second rule.
Action Programme: This is a practical problem solving test and
involves retrieving a cork out of a narrow plastic tube while
not breaking a set of rules. The score is based on the number
of steps completed without assistance and is timed.
Key Search: This test measures a participant’s ability to plan
and form a strategy to find a key that has been lost in a
field. This test is scored on a number of criteria, including
whether the strategy devised to solve the problem is
systematic, efficient and likely to be effective. This test is
timed and points are lost for lack of speed in completing the
task.
Temporal Judgement: This test involves judgement and abstract
thinking which is based on general knowledge. The participant
is required to estimate times for everyday occurrences, for
example how long do dogs live for, or how long does it take to
blow up a party balloon. Participants are not timed in this
test.
Zoo Map: This test measures independent ability to formulate
and implement a plan in a high demand condition and follow a
pre-formulated plan in a low demand condition. It involves
planning or following a route through a map of a zoo to visit
26
attractions that does not break a set of rules. This test is
timed and the score is based on the successful implementation
of the plan.
Modified Six Elements: This test measures time management and
multi-tasking abilities. It involves splitting the specified
time of 10 minutes between a number of simple tasks (ie
picture naming, arithmetic and dictation) while not breaking
the rules. The score is based on the number of tasks
attempted and the number of rules broken.
3.6 Addiction Severity Index (ASI-X)
The ASI-X is an assessment instrument designed to be
administered as a semi-structured interview to patients who
present for problematic substance use treatment (McLellan et
al. 1980). This instrument gathers information about seven
areas of a patient’s life: medical, employment, drug and
alcohol use, legal, family history/social relationships and
psychiatric problems.
Using a scale which ranges from 0 to 9, interviewer severity
ratings indicate the degree of a patient’s problems in each of
the seven areas, based on a client’s history and current
situation. Patients can also rate themselves in each of the
seven areas, these scores range from 0-4. Composite scores
are calculated from each of the areas of the ASI and are
indicators of the patient’s current circumstances. Therefore,
27
they are useful for treatment outcomes studies as successive
composite scores can be used to summarise changes in the
status of a patient. A number of studies have confirmed the
reliability and validity of the ASI (McLellan, et al. 1980;
Franzese, 2005).
3.7 Procedure
The researcher visited the LEAP programme before the
commencement of data collection and presented an outline of
the research project to the Clinical Lead and other treatment
staff, leaving copies of the participant information sheet
which explained the purpose of the study. The Clinical Lead
then provided patients who met the inclusion criteria with a
copy of the participant information sheet to ascertain if they
were interested in taking part in the research. Patients who
had been in the treatment programme for a minimum of two weeks
were included in the study. However, the researcher excluded
patients who had just been admitted to the programme, were in
the first two weeks of treatment or were undergoing a
detoxification process. The researcher did not include a
control group in the study due to the nature of the cohort of
participants. The data was collected over the period July-
December 2013.
Participants who were interested in taking part in the study
gave their initial consent for their details to be passed to
the researcher. The researcher then approached the
28
participants already identified and provided them with a study
pack and an opportunity to ask any questions regarding the
nature of the study before data collection commenced. At this
stage the researcher obtained a participant’s informed
consent, which is in line with ethical guidance that requires
a participant's written informed consent before data
collection can commence. In order to protect the
participant’s identity, the consent form was initialled by the
participant and signed by the researcher, with one copy kept
by the participant. The participant’s identity remained
anonymous at all times and the participant’s name was replaced
by a specially coded number. Participants were also informed
that they could withdraw from the study at any time and that
any data collected would be destroyed, their anonymity would
be protected and their treatment or legal rights would not be
affected. It was also stressed to participants that they
could not be identified in the final research report.
The data collection was conducted using a separate room to
ensure the confidentiality of the participants and that the
day-to-day running of the treatment programme was not
interrupted by the research process. Instructions on the
application of the BADS tests was explained to participants
before the commencement of these tests. The questionnaires and
practical tests were completed in the presence of the
researcher to ensure any queries or concerns about the
research were answered in the first instance. After the data
29
had been collected the researcher thanked participants for
their time and contribution to the research project.
In line with NHS Lothian data protection policy, all data
collected from this research was kept in a locked drawer on
the LEAP premises. The data was then entered into SPSS version
20 on the University of the West of Scotland (UWS) computer
system which is password protected with only the researcher
and academic supervisor having access to this data. This was
to ensure that access to confidential research data was
restricted only to those who require it. In addition, paper
copies of the questionnaires were anonymous in order to ensure
participant confidentiality and were stored in a locked filing
cabinet on the LEAP premises. After the data had been entered
into SPSS, the paper questionnaires were then returned to
LEAP. No patient’s medical notes or any other personal data
which could be used to identify individuals were removed from
the site.
3.8 Ethical Consideration
The researcher applied for ethical approval for this study
using the on-line Integrated Research Application System
(IRAS). Final ethical approval was obtained from the West of
Scotland Research Ethics Committee (Appendix 4) and NHS
Lothian Research and Development Department (Appendix 5). No
financial incentives were offered to participants for taking
part in this study. The researcher executed the research
30
project in line with NHS Lothian ethical procedures and the
research guidelines laid out by the University of the West of
Scotland.
31
4. Results
The researcher’s hypothesis was two-fold:-
(1) executive functioning would have a significant
relationship with problematic substance use;
(2) adult attachment style would have a significant
relationship with problematic substance use.
It was also hypothesised that the composite scores from the
ASI would predict problematic substance use. Using SPSS
version 20, Independent t-tests, Pearson Product Moment
Correlations and Linear Regression were conducted to analyse
the data.
4.1 Power Calculation
G*power was used to calculate the sample size required for
statistical power (Cohen, 1992). As the main outcome variable
is continuous, the sample size was calculated for regression
analysis. As there are no studies which report on the ASI-X
Score as a predictor variable, a medium effect size was
therefore chosen (0.15) at an alpha setting of 0.05, yielding
sample size of 138 participants. However, the researcher was
unable to gather data from this number of participants in the
given time frame, so 36 participants in total were recruited.
32
4.2 Descriptive Statistics
Table 1Gender Frequenc
yPercent
Female 15 41.7Male 21 58.3Total 36 100
Table 2Min Max Mean
(SD)Age 24 59 41.2
(8.9)Table 1 shows a total of (n=36) participants took part in the
research, 21 males (58%) and 15 females (42%). Table 2 shows
participants were aged between 24-59 years, with a mean age of
41, SD 9.
4.3 Independent Samples T-Tests
Independent samples t-tests for male and females were
conducted to compare scores from the ASI-X: Composite Drugs
Score, Emotional Abuse Past 30 days, Physical Abuse Past 30
days, Family Problems Past 30 days, Social Problems Past 30
Days, Composite Score Family and Composite Score Alcohol. The
significant differences for the two groups are shown in Table
3.
Table 3Gender Mean (SD) t(df) Sig (2-
tailed)Composite Score Drugs Female 0.08
(0.10)Male 0.11
(0.12)t(33)=-0.78
p=0.43
33
Emotional Abuse Past 30Days
Female 0.42(0.51)
Male 0.08(0.28)
t21=0.21 p=0.04
Social Problems Past 30Days
Female 2.8 (1.5)
Male 1.7 (1.3) t(28)=2.22
p=0.03
Composite Score Family Female 0.43(0.16)
Male 0.30(0.21)
t(33)=2.20
p=0.03
There was no significant differences in the scores for males
(M=0.083, SD=0.28) and females (M=0.07, SD=0.26); t(24)=-
0.109, p=0.09) for physical abuse in the past 30 days; males
(M=3.1, SD=6.45) and females (M=2.8, SD=1.42); t(-21.4=0.20,
p=0.84) and family problems past 30 days and scores for males
(M=0.51, SD=0.33) and females (M=0.56, SD=0.30); t(31)=0.46,
p=0.64) and composite score alcohol.
34
4.4 Correlations
Correlations between Composite Scores Alcohol, Drugs (ASI-X),
Age, Total Scores Close, Depend, Anxiety (AAS), Age Corrected
Standardised Score, DEX, DEX IR Behaviour, Cognition and
Emotion and Standardised Score (BADS)
Pearsons Product Moment Coefficients Correlations were used to
explore the relationships between the variables: composite
scores alcohol and drugs; age; total scores close, depend,
anxiety (AAS); DEX, DEX IR (behaviour, cognition and emotion);
age corrected standardised scores and standardised scores
(BADS) (Table 4 below). A moderate negative significant
correlation was found between age and total score on anxiety
[r=-.353, p=.038] which suggests that the older an individual
is the less anxiety they experience in relationships. A
strong negative significant correlation was found between age
and DEX cognition, [r=-.728, p=.007] which suggests a
relationship between executive functioning and age. A
moderate significant relationship was found between the
composite score alcohol and age, [r=.465, p=.005] which
suggests that the older an individual is the more alcohol they
consume. A strong negative correlation was also found between
the composite score for drugs and age [r=-.610, p=.000] which
shows that the older an individual is the less drugs they
take.
35
A moderate significant correlation was found between the total
score on anxiety and composite score drugs [r=.435, p=.008]
which suggests that the greater anxiety levels an individual
experiences the more drugs they are likely to consume. There
were no significant relationships found between the composite
score alcohol and the total scores of close, depend and
anxiety. However, a strong negative correlation was found
between the composite score alcohol and composite score drugs
[r=-.521, p=.001] suggesting that the more individuals drink
alcohol the less they take drugs. Additionally, the composite
scores for alcohol and drugs was not found to have any
significant relationship with the age corrected standardised
score and standardised score on the BADS tests and the DEX and
DEX IR components of behaviour, cognition and emotion.
36
Table 4Composite ScoreAlcohol
Composite ScoreDrugs
Age AASCloseTotal
AASDepend
Total
AASAnxiety
Total
AgeCorrecte
dSt’disedScore
DEXBehaviou
r
DEXCogniti
on
DEXEmotion
DEX IRBehaviou
r
DEX IRCogniti
on
DEX IREmotion
St’dised
Score
Composite Score Alcohol
1 -.521**.001
465**.005
.052
.764-.055.749
-.280.098
-.281.205
-.085.783
-.081.793
.136
.675-.421.173
-.421.173
-.257.420
-.214.328
Composite Score Drugs
-.521**.000
1 -.610**
.000
.202
.237.020.910
.435**
.008
.278
.211.327.276
.439
.133.051.868
.261
.412.261.412
.097
.763.337.116
Age .465**.005
-.610**.000
1 -.116.505
-.129.462
-.353.038
.147
.524-.540.070
-.728**.007
-.433.160
-.054.874
-.054.874
-.211.533
-.185.411
AAS Close Total
.052
.764.202.237
-.116.505
1 .643**
.000
.609**
.625
-.110.625
-.074.811
.186
.544.057.853
-.114.725
-.114.725
.058
.857.399.059
AAS Depend Total
-.055.749
.020
.910-.129.462
.643**
.000
1 .492**
.002
-.107.635
-.005.987
.070
.821-.309.304
.292
.357.292.357
.477
.117.436*.037
AAS AnxietyTotal
-.280.098
.435**.008
-.353*
.038
.609**
.000
.492**
.002
1 .046.839
.160
.602.307.308
-.177.563
.214
.503.214.503
.302
.339.378.075
Age Corrected St’dised Score
-.281.205
.278
.211.147.524
-.110.625
-.107.635
.046
.8391 -.452
.140-.218.495
.080
.805-.272.392
-.272.392
-.344.274
.998**
.000
DEX Behaviour
-.085.783
.327
.276-.540.070
-.074.811
-.005.987
.160
.602-.452.140
1 .821**.001
.571*.041
.432
.185.432.185
.331
.320-.469.124
DEX Cogniti
-.081.793
.439
.133-.728**
.186
.544.070.821
.307
.308-.218.495
.821**.001
1 .582*.037
.388
.238.388.238
.309
.356-.219.494
23
on .007DEX Emotion
.136
.657.051.868
-.433.160
-.057.853
-.309.304
-.177.563
.080
.805.571*.041
.582*.037
1 -.293.382
-.293.382
-.546.082
.057
.860
DEX IR Behaviour
-.421.173
.261
.412-.054.874
-.114.725
.292
.503.214.503
-.272.392
.432
.185.388.238
-.293.382
1 1.000**.000
.696*.012
-.290.361
DEX IR Cognition
-.421.173
.261
.412-.054.874
-.114.725
.292
.503.214.503
-.272.392
.432
.185.388.238
-.293.382
1.000**.000
1 .696*.012
-.290.361
DEX IR Emotion
-.257.420
.097
.763-.211.533
.058
.857.477.117
.302
.339-.344.274
.331
.320.309.356
-.546.082
.696**.012
.696**.012
1 -.347.269
St’dised Score
-.214.328
.337-116
-.185.411
.399
.059.436*.037
.378
.075.998**.000
-.468.124
-.219.494
.057
.860-.290.361
-.290.361
-.347.269
1
** Correlation is significant at the 0.01 level (2-tailed)*Correlation is significant at the 0.05 level (2-tailed)
24
Relationship between Composite Scores Alcohol and Drugs (ASI-
X) and the BADS Tests
Table 5Composi
teScoreAlcohol
Composite
ScoreDrugs
ProfileScoreRuleShiftCards
ProfileScoreAction
Programme
ProfileScores KeySearch
Profile
Scores ZooMap
ProfileScores
ModifiedSix
Elements
ProfileScoresTemporalJudgemen
tCompositeScore Alcohol
1 -.521** -.044 -.327 -.387 -.055 -.002 -.199.001 .840 .128 .068 .803 .992 .362
CompositeScore Drugs
-.521** 1 .207 .345 .352 .207 .166 .309.001 .342 .107 .099 .343 .462 .151
Profile ScoreRule Shift Cards
-.044 .207 1 .524* .659** .512* .457* .447*
.840 .342 .010 .001 .013 .032 .033Profile ScoreAction Programme
-.327 .345 .524* 1 .686** .400 .590** .357.128 .107 .010 .000 .059 .004 .094
Profile ScoresKey Search
-.387 .352 .659** .686** 1 .340 .457* .511*
.068 .099 .001 .000 .112 .032 .013Profile ScoresZoo Map
-.055 .207 .512* .400 .340 1 .551** .375.803 .343 .013 .059 .112 .008 .078
Profile Scores Modified Six Elements
-.002 .166 .457* .590** .457* .551** 1 .661**
.992 .462 .032 .004 .032 .008 .001
Profile Scores Temporal Judgement
-.199 .309 .447* .357 .511* .375 .661** 1
.362 .151 .033 .094 .013 .078 .001
** Correlation is significant at the 0.01 level (2-tailed)*Correlation is significant at the 0.05 level (2-tailed)
No significant relationships were found between the profile
scores of rule shift cards, action programme; temporal
judgement; key search; zoo map and modified six elements tests
of the BADS tests and the ASI composite score for alcohol and
drugs (Table 5).
24
Relationship between Composite Scores Medical, Employment,
Family and Composite Scores Alcohol and Drugs (ASI-X)
Table 6Composite ScoreMedical
CompositeScore
Employment
Composite ScoreFamily
Composite ScoreAlcohol
Composite ScoreDrugs
Composite ScoreMedical
1 .211.218
-.114.515
.296
.080-.103.550
Composite Score Employment
.211
.2181 .361*
.033.111.519
.208
.224
Composite Score Family
-.114.515
.361*.033
1 -.113.518
.167
.336
Composite ScoreAlcohol
.296 .111 -.113.518
1 -.521**.001
Composite Score Drugs
-.103.550
.208
.224.167.336
-.521**.001
1
*Correlation is significant at the 0.01 level (2-tailed)**Correlation is significant at the 0.05 level (2-tailed)
A moderate significant correlation was found between the
composite score for family and employment [r=.361, p=.033]
(Table 6). However, no significant relationships were found
between the composite scores for alcohol and drugs and
medical, family and employment.
Relationship between Composite Scores Alcohol, Drugs and Years
of School and Higher Education (ASI-X)Table 7
Composite Composite Years of Years of
25
ScoreAlcohol
Score Drugs HigherEducation
SchoolEducation
CompositeScoreAlcohol
1 -.521**.001
.004
.983.387*.042
CompositeScore Drugs
-.521**.001
1 -.426*.024
-.392*.039
Years ofHigherEducation
.004
.983-.426*.024
1 .132.505
Years ofSchoolEducation
.387*
.042`-.392*.039
1.32.505
1
** Correlation is significant at the 0.01 level (2-tailed)*Correlation is significant at the 0.05 level (2-tailed)A moderate significant correlation was found between the
composite score alcohol and years of school education,
(r=.387, p=.042) and a moderate negative significant
correlation was found between composite score drugs and years
of school education (r=-.392, p=.039). A moderate negative
significant correlation was also found between composite score
drugs and higher education (r=-.426, p=.024). These findings
suggest an impact on education by problematic substance use
(Table 7).
Relationship between Age First Use Alcohol (ASI-X) and Total
Scores Close and Anxiety (AAS)
Table 8AAS Close Total
Age First Use Alcohol
AAS Close Total 1 -.512*.010
Age First Use Alcohol
-.512*.010
1
* Correlation is significant at the 0.05 level (2-tailed)
26
A strong negative significant correlation was found between
age first use alcohol and total score close [r=-.512, p=.010]
which suggests that the earlier in life an individual starts
to drink alcohol will impact on the close bonds they form in
adult relationships (Table 8).
Table 9AAS Anxiety
TotalAge First Use
AlcoholAAS Anxiety Total 1 -.481*
.017Age First Use Alcohol
-.481*.017
1
* Correlation is significant at the 0.05 level (2-tailed)
However, a moderate negative significant correlation between
age first use alcohol and total score on AAS anxiety [r=-.492,
p=.017] was found which suggests that the younger an
individual starts to drink alcohol the less anxiety they
experience in relationships. Additionally there were no
significant relationships between age first use alcohol and
total profile score, standardised score and age corrected
standardised score of the BADS tests (Table 9).
27
4.5 Linear Multiple Regression
Gender, Age, Years of School Education and ASI-X CompositeScore Alcohol
Table 10Coefficientsa
Standardised coefficientsModel 1
(Constant)Adjusted R2
F Change B t Sig.
-1.603 .122Gender -.059 -.340 .737Age .233 3.732 .411 2.293 .031
Years of SchoolEducation .283 1.574 .129
aDependent variable: Composite Score Alcohol
Linear multiple regression analysis was used to test whether
the independent variables, gender, age and years of school
education would predict the ASI composite score alcohol. It
was found that age significantly predicted 23% of the variance
of the composite alcohol score, (R2=..233, F(3.732)=.411,
p=.031) (Table 10).
Gender, Age, AAS Anxiety, Age and ASI-X Composite Score Drugs
Table 11Coefficientsa
Standardised coefficientsModel 1
(Constant)Adjusted R2
F Change B t Sig.
1.769 .087Gender .055 .403 .689
AAS Anxiety .220 1.502 .143Age .364 7.484 -.530 -3.624 .001
aDependent variable: Composite Score Drugs
28
Using the independent variables of gender, AAS anxiety and age
it was found that age significantly predicted 36.4% of the
variance of the ASI-X composite drug score,
(R2=.364, F(7.484)=-.530, p=.001) (Table 11).
29
AAS Close, Depend, Anxiety and Composite Score Drugs
Table 12Coefficientsa
Standardised coefficientsModel 1 Adjust
ed R2F Change B t Sig
(Constant) -.517 .609AAS Close .055 .244 .809AAS Depend -.281 -1.380 .177AAS Anxiety .169 3.374 .540 2.742 .010
aDependent variable: Composite Score Drugs
Using the independent variables of total scores AAS anxiety,
depend and close it was found that anxiety significantly
predicted 17% of the variance of the ASI-X composite drug
score, (R2=.169, F(3.374)=.540, p=.010) (Table 12).
30
5. Discussion
The aim of this research project was to investigate the
relationship between executive function (EF), adult attachment
style (AAS) and addiction severity in a bio-psychosocial
treatment programme for problematic substance use (PSU). The
rationale behind this research project arose from previous
research which had demonstrated that (a) deficits in executive
functioning and (b) adult attachment style can impact on the
therapeutic relationship and treatment outcomes (Blume and
Martlatt, 2009; Nanjappa et al., 2014). The researcher
hypothesised that (1) executive functioning and (2) adult
attachment style would have a significant relationship with
PSU. It was also hypothesised that the composite scores from
the Addiction Severity Index (ASI-X) would predict PSU.
The mean scores from the ASI-X for males and females were
compared using independent samples t-tests. This analysis
showed that males scored higher on the composite score for
drugs. This finding is consistent with previous research which
reports that traditionally more males than females attend
treatment services (UK Focal Report on Drugs, 2011, Best et
al., 2010). Additionally, there were more male participants
than females in the sample which also may account for this
effect. This analysis also found that females had higher
scores for emotional abuse and social problems in the past 30
days prior to entering the treatment programme. Thus
highlighting the validity of using the ASI-X (McLellan et al.
31
1980) as an assessment and outcome tool to alert treatment
providers to the individual differences that clients bring to
treatment as this assessment gathers information from seven
areas of an individual’s life prior to treatment entry. It
was also found that females scored higher on the composite
score for family. This finding concurs with recovery capital
and social support research which proposes that having a
supportive network at the macro and micro level mediates the
recovery process (Laudet and White, 2010). However, there was
no significant differences in the mean ASI-X scores for male
and females for physical abuse and family problems in the past
30 days and the composite score for alcohol.
32
5.1 Age
Correlation analysis of the relationship between age and the
total scores from the AAS sub-scale anxiety demonstrated a
small negative significant correlation. This finding suggests
that the older an individual is the less anxiety they
experience in relationships. This finding is inconsistent
with attachment research which posits that attachment styles
are stable throughout the lifespan. This notion suggests that
the attachment style formed in infancy, in this case, insecure
attachment, would remain with an individual throughout their
adult life (Bowlby, 1991). However the notion of ‘earned felt
security’ confirms the researcher’s finding as recent research
has suggested that an attachment style can be modified in
terms of emotional regulation as an individual matures
(Moller, McCarthy and Fouladi, 2002 as cited in Thorberg and
Lyvers, 2010; McCarthy and Maughan, 2010).
Moreover, a strong negative significant correlation was found
between age and DEX cognition. This finding confirms previous
research which has shown that age can have a negative effect
on EF functions, which could have a detrimental effect on
independent living skills as an individual gets older (Spikman
et al., 2009). A moderate significant relationship was found
between the composite score alcohol and age which suggests
that the older an individual is the more alcohol they consume.
This finding is inconsistent with research that suggests that
individuals mature out of alcohol use (Best et al., 2010;
33
O’Malley, 2005). This finding also has implications from a
public health perspective as increased alcohol use can lead to
conditions such as korsakoff syndrome and alcohol related
brain damage (Maharasingam et al., 2013).
Furthermore, a strong negative correlation was also found
between the composite score for drugs and age which shows that
the older an individual is the less drugs they take.
Furthermore, this finding is in line with the maturing out
theory which suggests that individuals cease taking drugs, or
have shorter ‘addiction careers’ due to various factors. For
example, criminal justice involvement, growing “tired of the
lifestyle” (Best et al., 2010, p.239) or simply to move on
with their lives in terms of social networks and employment.
However, Beynon, McVeigh and Roe (2007) argue that the drug
users attending treatment services were getting considerably
older. In terms of alcohol use, a strong negative significant
correlation was found between age first use alcohol and total
score close. This suggests that the earlier in life an
individual starts to drink alcohol has a negative effect on
the close bonds they form in adult relationships. This is an
interesting result as the attachment style ‘close’ relates to
how comfortable an individual is with closeness and intimacy
in a relationship. However, this finding suggests the
opposite that early alcohol use leaves an individual feeling
insecure in a relationship. This finding is inconsistent with
previous research which states a relationship between alcohol
use and insecure attachment (Thorberg and Lyvers, 2006).
34
Consequently, a moderate negative significant correlation
between age first use alcohol and total score on AAS anxiety
was found which demonstrates that the younger an individual
starts to drink alcohol the less anxiety they experience in a
relationship. Again, this finding is inconsistent with prior
research which proposes the ‘self-medication’ hypothesis,
suggesting that individuals use substances problematically to
ease psychological distress and as a maladaptive coping
mechanism (Schindler et al, 2009).
Linear regression analysis conducted on the independent
variables, age, gender and years of school education found
that age significantly predicted 23% of the variance of the
composite alcohol score. This shows that age is a predicator
for problematic alcohol use which has been discussed above and
which confirms and also rejects previous literature and theory
around the relationship between adult attachment style and
PSU. Furthermore, regression analysis conducted on the
independent variables age, gender and AAS total score anxiety,
again demonstrated that age significantly predicted 36.4% of
the variance of the ASI composite drug score. The above
results in relation to age are interesting and worthy of note
as participants in the study were aged between 24-59 years
with a mean age of 41 and could be described as being more
mature, which may account for these findings. Nevertheless,
research has also shown that there are mixed results in the
literature regarding age and PSU.
35
5.2 Anxiety
A moderate significant correlation was found between the total
score on anxiety and composite score drugs which suggests that
the greater anxiety an individual experiences the more drugs
they will use. This finding is consistent with previous
research which has shown that individuals use drugs
problematically to alleviate emotional stress and as a
maladaptive coping strategy (Schlinder et al., ref, Doumas et
al., 2013). Furthermore, a strong negative correlation was
found between the composite score alcohol and composite score
drugs suggesting that the greater amounts of alcohol consumed
the less drugs are taken. This finding concurs with
literature that suggests ‘addiction careers, or ‘drug use
trajectories’ (Best et al., 2010). Whereby an individual may
achieve abstinence from drugs but still continue to use
alcohol. This finding could also be explained by the notion of
an individual replacing one substance with another. Alcohol
is a legal drug, has social aspects and is embedded in
Scottish culture (Attitudes towards Alcohol in Scotland,
2014).
Regression analysis on the independent variables of total
scores AAS anxiety, depend and close revealed that anxiety
significantly predicted 17% of the variance of the ASI
composite drug score. Again, this finding has been reflected
in previous research which found that individuals with higher
levels of attachment anxiety were found to use substances
36
problematically (Thorberg and Lyvers, 2010; Kassel et al.,
2007). In contrast, no significant relationships were found
between the composite score alcohol and the total scores of
close, depend and anxiety. This finding demonstrates that
alcohol has no significant relationship with adult attachment
styles which does not confirm prior literature, in terms of
anxiety which has been previously discussed in this research
paper.
5.3 Family, Employment and Education
In terms of recovery capital and social support, a moderate
significant correlation was found between the composite score
for family and employment. This finding is in line with
research which posits that a supportive network from either
family or community networks can aid the recovery journey
(Laudet et al., 2010; Campbell et al., 2011). Indeed, Laudet
et al., (2010) in their research found that employment was an
important concept for individuals in recovery to strive for.
However, no significant relationships were found between the
composite scores for alcohol and drugs and family and
employment. A moderate significant correlation was found
between the composite score alcohol and years of school
education which demonstrates that alcohol use has a negative
impact on educational attainment. Conversely, a moderate
negative significant correlation was found between composite
score drugs and years of school education suggesting that
problematic use of drugs has less of an effect on educational
37
attainment. Furthermore, a moderate negative significant
correlation was found between composite score drugs and years
of higher education demonstrating that problematic use of
drugs has less of an effect on higher education.
In terms of EF, no significant relationships were found
between the profile scores of rule shift cards, action
programme, temporal judgement, key search, zoo map and
modified six elements tests of the BADS and the ASI-X
composite score for alcohol and drugs. Additionally, the
composite score for alcohol and drugs was not found to have
any significant relationship with the standardised score on
the BADS tests, total scores on the DEX and DEX IR
questionnaires which measure the dimensions of behaviour,
cognition and emotion. These are very interesting findings and
are considered by the researcher to be significant.
Furthermore, these findings are inconsistent with previous
research in this area as studies have shown there to be a
relationship between scores on neuropsychological tests,
deficits in EF and PSU (Verdejo-Garcia et al., 2005; Verdejo-
Garcia et al., 2006).
5.4 Strengths and Limitations of the Study
It is prudent to discuss the strengths and limitations of this
study. Firstly, the finding of no significant relationships
between the BADS tests, DEX questionnaires and the ASI-X
composite scores for drugs and alcohol is very interesting and
38
could be viewed as a strength of this research as it disagrees
with most of the other research in this area. As participants
were tested at different stages of their treatment this could
perhaps account for the results found. Patients who attend
the LEAP programme are in treatment for a period of 12 weeks.
Therefore, if a patient was tested in week 11 of treatment
does this suggest that abstinence has an effect on EF? This
finding could be an argument for an increase in longitudinal
studies into the effect of prolonged abstinence on EF.
However, it should also be noted that participants in this
study were also tested early in treatment, for example only
two weeks into the programme, which still showed no
significant relationship between EF and the composite scores
of the ASI-X. This is inconsistent with prior research which
has proposed that early abstinence from problematic use of
drugs and alcohol can still show deficits in EF (Rapeli et
al., 2005; Zinn et al., 2005). Another strength of this
research is the significant finding between attachment related
anxiety and drug use. Although this finding was moderate it
confirms previous research that individuals utilise
maladaptive coping mechanisms to deal with anxiety and stress
(Robinson et al.,2011).
Turning now to the limitations of this research. Due to the
nature of the treatment setting the researcher encountered
difficulties in collecting data from patients who were engaged
in treatment. The treatment programme is recovery focussed
and encompasses a bio-psychosocial model which involves group
39
and individual therapy as well as components of 12-step
treatment. This meant that recruiting participants to take
part in the study was difficult as patients attended therapy
groups twice a day and these could not be interrupted.
Additionally, time constraints on the researcher resulted in
data being collected over a period of five months.
Consequently, some participants did not complete all of the
BADS tests, had been discharged or graduated from the
programme, did not attend the aftercare sessions or had left
the programme of their own accord.
Moreover, there was no control group for comparison due to the
nature of the research site. The sample size was small but
again this is due to the number of patients in treatment at
any one time. A power calculation had indicated a sample size
of 138 participants (Cohen, 1992). However, again given the
time constraints placed on the researcher only 36 participants
were recruited which may not be a large enough sample for the
results to be generalised to other treatment settings. In
terms of measures, the researcher utilised the adult
attachment scale which is a self-report measure of adult
attachment. This design of measurement may not reflect true
attachment styles due to participant’s accuracy in reporting
how they viewed themselves in relationships. The present
research could be further enhanced by recruiting a larger
number of participants over a longer time period to ascertain
if this design would produce different results, perhaps with a
control group to compare test scores. However, this
40
researcher acknowledges the difficulties inherent in follow-up
and longitudinal studies of this nature within this client
group.
5.5 Future Research Implications
It has been demonstrated throughout this study that the
individual differences that clients bring to treatment
settings can play a major part in successful treatment
outcomes. As recovery from problematic substance use is the
driver behind current drugs policy in Scotland (Scottish
Government, 2008) and the UK Government (UK Government, 2007)
future research should focus on identifying the factors that
PSU clients bring to treatment settings, in terms of
neurological and psychological differences. To participate
fully in treatment an individual must have the necessary
abilities to engage with and complete treatment, for example,
planning, decision-making, motivation and coping skills to
ensure successful outcomes.
This research also recognises that there is a clinical need
for EF assessment to be included as part of an intervention
programme. Consequently, treatment plans should be tailored
to suit the individual needs of clients as deficits in EF are
not always obvious, which in turn affects client’s engagement
and treatment outcomes and incurs the risk of relapse
prevention. This research also recommends that longitudinal
studies be conducted to measure whether prolonged abstinence
41
(over a year) can improve rates of EF. At the moment research
has shown that there is a lack of longer-term or follow-up
studies to measure whether EF improves with prolonged periods
of abstinence. In terms of adult attachment, health
professionals and treatment services should also include an
assessment as part of recovery planning, which measures
attachment style as issues of anxiety, trust and past trauma
can interfere with the recovery process and the therapeutic
alliance. If these issues were identified at the initial
assessment stage of treatment it could a long way to foster a
successful relationship between service providers and clients.
Currently, testing for deficits in EF are measured by
neuropsychological tests which although are not wholly
conclusive do provide researchers and health professionals
with an idea of an individual’s abilities in relation to
rehabilitation and treatment outcomes. However, in order for
an individual to achieve recovery, treatment providers should
also adopt a person centred approach when engaging with
individuals who may have EF deficits or attachment traits,
taking into account all the other circumstances that accompany
that person to treatment, for instance age, gender, trauma,
stress, stigma, lack of educational opportunities, social
background, social economic status, poverty.
5.6 Conclusion
42
In conclusion this research project set out to test the
hypotheses that (1) executive function and (2) adult
attachment style would have a significant relationship with
problematic substance use; and that the scores from ASI-X
would predict PSU. The hypothesis that adult attachment style
would have a significant relationship with PSU was partly
confirmed as attachment related anxiety was found to predict
17% of the variance of ASI-X composite drug score. However,
the null hypothesis was confirmed as no significant
relationship was found between the scores on the BADS tests
and the ASI-X alcohol and drugs composite scores. This study
has highlighted that the relationship between EF and PSU is
complex and multi-faceted and future research should
concentrate on conducting longitudinal studies into the
effects of prolonged abstinence on EF.
43
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