A Twin Study of Generalized Anxiety
Disorder and Neuroticism
in Middle-aged Adults
He Yinyan
Dissertation presented for the
Msc in the Psychology of Individual Differences
The University of Edinburgh
2008
Acknowledgements
I would like to thank my supervisors Prof. Timothy Bates and Dr. Alexander Weiss,
who provided me an opportunity to access the dataset of MIDUS, and offered their
assistants and supports throughout the process of designing, carrying out and
reporting this study. I am also very grateful to my family, my friends and all other
people who gave me their supports and confidences.
Plagiarism statement
I declare that the work submitted here for this Msc in the psychology of individual
differences dissertation is my own work and contains no section copied in whole, or
in part, from any other source, unless it is explicitly identified and acknowledged by
detailed references to the source material.
He Yinyan
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CONTENTS
1. ABSTRACT
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2. INTRODUCTION
2.1 ANXIETY AND ANXIETY DISORDERS
2.2 THE NATURE OF GENERALIZED ANXIETY DISORDER
2.3 CLASSIFICATION OF GAD
2.3.1 DIFFERENT DIAGNOSTIC CRITERIA
2.3.2 DEVELOPMENT OF DIAGNOSTIC CRITERIA
2.4 FEATURES OF GAD
2.4.1 RESIDUAL DISORDER
2.4.2 WORRY
2.4.3 COMORBIDITY
2.5 PERSONALITY AND GAD
2.5.1 NEUROTICISM
2.5.2 NEUROTICISM AND MOOD DISORDER
2.6 THE RELATIONSHIP BETWEEN DEPRESSION, ANXIETY AND NEUROTICISM
2.6.1 STUDIES OF GAD AND MAJOR DEPRESSION
2.6.2 STUDIES OF NEUROTICISM, ANXIETY AND DEPRESSION
2.7 TWIN STUDIES
2.7.1 TWIN STUDY OF ANXIETY
2.7.2 TWIN STUDY OF COMORBIDITY OF ANXIETY DISORDERS
2.7.3 TWIN STUDY OF GAD AND NEUROTICISM
2.8 THE PRESENT STUDY
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3. METHOD
3.1 PARTICIPANTS
3.2 MEASURES
3.2.1 PERSONALITY TRAITS
3.2.2 GENERALIZED ANXIETY DISORDER
3.3 STATISTICAL ANALYSIS
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4. RESULTS
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5. DISCUSSION
5.1 INTERPRETATION OF THE FINDINGS
5.2 COMPARE TO OTHER STUDIES
5.2.1 TWIN STUDY OF YOUNGER ADULTS
5.2.2 TWIN STUDY OF OLDER ADULTS
5.2.3 TWIN STUDY OF ANXIETY DISORDER
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5.2.4 TWIN STUDY OF MAJOR DEPRESSION
5.2.5 OTHER STUDIES
5.2.6 WHICH IS MORE IMPORTANT: GENES OR THE ENVIRONMENT?
5.3 INFLUENTIAL FACTORS
5.3.1 LOWER GENETIC CORRELATION COEFFICIENT
5.3.2 THE USE OF MEASUREMENT FOR ANXITY DISORDER
5.3.3 AGE EFFECT ON ANXIETY DISORDER
5.4 LIMITATIONS
5.5 FUTURE STUDIES
5.5.1 SEX DIFFERENCES
5.5.2 GENE-ENVIRONMENT INTERPLAY
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6. CONCLUSION
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7. REFERENCE
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APPENDICES
GAD Scale
Personality Scale
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1. Abstract
Objective: Generalized anxiety disorder (GAD) has been show to relate to personality traits,
especially neuroticism. However, to date, a few studies have examined the genetic and
environmental sources of this covariation between GAD and personality traits. The present
study aimed to investigate genetic and environmental influences on GAD and the extent of
shared genetic and environmental linkages with neuroticism in a representative sample of
middle-aged adults.
Method: Current GAD and trait neuroticism were measured in 973 twin pairs (mean age =
44.9) from the National Survey of Midlife Development in the U.S. (MIDUS). Participants
included 365 monozygotic twins of which 171 were male and 194 were female, 259 opposite
sex dizygotic twin pairs and 349 same sex dizygotic twin pairs. All twins provided personality
information as well as GAD in a telephone screening between 1994 and 1995. A bivariate
Cholesky ACE model was used to model the genetic and environmental sources of variance
and covariance in GAD and neuroticism.
Results: Neuroticism was moderately heritable (h2 = 0.40). For GAD, only 12% of the
variance reflected genetic factors with most of the rest attributed to nonshared environmental
factors. Bivariate analyses indicated that no genetic influences on GAD were shared in
common with genetic influences on neuroticism, while most of covariance between GAD and
neuroticism could be attributed to nonshared environmental influences.
Conclusions: There was no overlap between genetic factors influencing individual variation
in neuroticism and those in GAD. In contrast, the life experiences that increase vulnerability
to GAD overlap strongly with those contributing to neuroticism.
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2. Introduction
During the past two decades, anxiety, one of the most prominent and pervasive emotions, has
been introduced to various parts of the world. Anxiety disorder is described as involving
illogical or irrational worry which is not based on fact (Rachman, 2004). As a diagnostic
category, it includes aspects of fears, pathological anxiety and phobias. Research suggests that,
during the life time, approximately 30%-40% population may suffer anxiety with a sufficient
degree of severity to receive a clinical diagnois (Barlow & Wincze, 1998). Considering the
distressing and debilitating nature of the disorder, including impairments in school and work
(Keeley & Storch, 2008), anxiety disorders become one of the most important types of
psychopathology. Among several anxiety disorders, generalized anxiety disorder (GAD) is
relatively common mental disorder with a lifetime prevalence of approximately 3%. It
characterized by feelings of threat, restlessness, irritability, uncontrollable worry, sleep
disturbance, and tension (Tyrer & Baldwin, 2006). Patients who suffered GAD often report
that they spend most of waking hours worrying about minor matters (Mackintosh et al., 2006).
The symptoms of GAD overlap greatly with those of other common mental disorders so that
it is regarded as mood related disorder rather than an independent disorder (Tyrer & Baldwin,
2006).
Personality traits have also been demonstrated to relate to mood disorders including GAD and
depression (Wilson et al., 2007). Most research suggests that extraversion, openness,
agreeableness, and conscientiousness are positively related to health, whereas only
neuroticism shows a negative relationship (Cuijpers et al., 2005; Moutafi et al., 2006). People
with high neuroticism scores tend to be more sensitive, worrying, moody, emotional,
frequently depressed, sleepless, and may suffer from various psychosomatic disorders
(Moutafi et al., 2006), while people with low scores are more likely to be hardy, secure and
relaxed even under stressful conditions. Recently, some studies have investigated the genetic
epidemiology of anxiety disorders and its genetic correlations with neuroticism. The results
show that neuroticism and GAD share many of the same genes whereas environmental
influence has only a weak contribution (Hettema et al., 2004; Mackintosh et al., 2006).
However, no study has examined the genetic correlation between neuroticism and GAD in
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middle-aged adults. Therefore, this study aims to provide an insight into genetic relationship
between neuroticism and GAD in middle-aged adults. The first part will be definitions of
GAD and neuroticism, as well as the background of relevant researches. Then the method part
of the present study will be followed. After analyzing the data, some findings will be
presented and several issues will be discussed.
2.1 Anxiety and anxiety disorders
Prior to 1980s, The Diagnostic and Statistical Manual of Mental Disorders (DSM, now in its
fourth edition), introduced by the American Psychiatric Association committee, firstly created
a separate category for ‘Anxiety Disorders’ and provided clean definitions and criteria for
diagnosing these disorders. This new diagnostic system recognized seven types of anxiety
disorder (see Table 1): panic disorder; agoraphobia; social phobia; specific phobia;
generalized anxiety disorder (GAD); obsessive-compulsive disorder (OCD), post-traumatic
stress disorder (PTSD) and acute stress disorder (ASD).
Table 1
The anxiety disorders
Panic disorder, with or without agoraphobia
Agoraphobia without a history of panics
Social phobia
Specific phobia
Generalized anxiety disorder (GAD)
Obsessive-compulsive disorder (OCD)
Post-traumatic stress disorder (PTSD) and acute stress disorder (ASD)
Source: Rachman,( 2004) p25.
2.2 The nature of generalized anxiety disorder
Among seven anxiety disorders, generalized anxiety disorder (GAD) is a relatively recent
diagnosis. Before 1980, GAD was subsumed under the label of anxiety neurosis which has
first delineated by Freud in 1894. He described anxiety neurosis as ‘free-floating’ anxiety that
was characterized by persistent feelings of unattached fearfulness. It originally included the
symptom of panic, but when panic disorder was identified as a separate illness, the part of
anxiety neurosis that excluded panic became known as GAD (Tyrer & Baldwin, 2006).
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GAD has firstly emerged since the advent of the DSM-III and developed in the DSM-IV. It is
a relatively common mental disorder with a lifetime prevalence of approximately 3%. GAD
often occurs in childhood or adolescence and persists until late life among general population.
People affected with GAD find it is extremely difficult to control their anxiety, so that most of
them are easily tired, irritable and have difficulty in concentrating (Rachman, 1998). As most
of GAD patients are highly affected 6-12 years after diagnosis, it is regarded as a chronic
disorder.
2.3 Classification of GAD
There are two widely used classificatory systems for diagnosing GAD: International
Statistical Classification of Diseases and Related Health Problems, 10th Revision (ICD-10,
1992) and the DSM-IV (1994). Similarly, the main symptoms of GAD described in the
DSM-IV and ICD-10 consist of generalized and persistent excessive anxiety, and various
psychological and somatic complaints (Brown et al., 1994; Tyrer & Baldwin, 2006). However,
there are several differences between the DSM-IV and ICD-10. To distinguish pathological
worry from normal worry, the DSM-IV emphasizes the main feature of GAD is the
uncontrollable nature of worry, whereas ICD-10 focuses on the presence of more anxiety
symptoms. The DSM-IV criteria include the additional symptoms of worry over minor
matters but ICD-10 does not. Although the requirements for the diagnosis of GAD have
changed with time, the DSM-IV still seems to be widely used in various areas of research.
Fisher (2007) points out three probable reasons:
(i) The DSM-IV appears to be more popular among mental health professionals.
(ii) Recent conceptualizations of GAD focus on pathological worry, which has become
the cardinal feature of GAD according to the DSM-IV diagnostic criteria.
(iii) The revised diagnostic criteria in the DSM-IV appear to be more closely tied to
empirical research findings on the nature of GAD and worry. (p171)
2.3.1 Different diagnostic criteria
ICD-10: The diagnostic criteria in ICD-10 incorporate much broader range of symptoms
which significantly differ from that in the DSM-IV. The definition of GAD in ICD-10 is a
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‘generalized and persistent state of ‘free-floating’ anxiety over several months, with key
symptoms of apprehension, motor tension and autonomic over activity’. The diagnosis for
GAD in ICD-10 requires more than two symptoms of autonomic arousal with up to three
other symptoms (see Table 2).
Source: Tyrer & Baldwin, (2006)
Table 2 Criteria for the diagnosis of GAD in ICD-10 and the DSM-IV
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The DSM-IV: According to the DSM-IV (see Table 2), GAD is defined as the ‘excessive
anxiety that occurs more days than not for at least six months’. It is usually accompanied by
physical signs, including notably elevated arousal and muscle tension, and other body
symptoms, e.g., queasy stomach, difficulty swallowing and nausea. When making a diagnosis,
Fisher (2007) suggests at least three out of six tension and stress symptoms must be
accompanied by the anxiety and worry. These six symptoms are restlessness or feeling ‘on
edge’; easily tired; concentration difficulties or mind going blank; irritability; muscle tension;
sleep disturbance (difficulty falling or staying asleep or unsatisfying sleep). It is essential to
notice that these symptoms must be presented with at least moderate severity.
2.3.2 Development of diagnostic criteria
Anxiety is a common complication of substance misuse disorders and none of the individual
symptom is specific to it (Barlow & Wincze, 1998). At the very beginning, most of
individuals with anxiety disorders would have been classified within the rather broadly
defined category. Researchers must to exclude any other anxiety conditions before making the
diagnosis (Tyrer & Baldwin, 2006). However, such exclusion is not always easy when the
patient has more than one disorder. Compared with the DSM-IV, the DSM-III suggests a
diagnostic hierarchy in which excludes the diagnosis if a depressive, phobic, or panic disorder
is present (see Table 3). But it is soon demonstrated to be inappropriate because patients with
anxiety and depressive symptoms always have greater morbidity than those with a mood
disorder alone. In other words, this hierarchical relation described in the DSM-III cannot fully
representative for all patients. Therefore, the criteria for diagnosis are changed (Zimmerman
& Chelminski, 2003). In the DSM-III, the necessary duration of symptoms for GAD is 1
month. However, in later editions of DSM and ICD, the necessary duration of symptoms for a
diagnosis of GAD is raised from 1 to 6 months. Kessler et al. (2005) argue that there is little
difference between patients who qualify for diagnosis when their symptoms last more than 6
months and those who have a duration of symptoms less than 6 months.
Because of its poor reliability, GAD was almost excluded from the DSM-IV classification in
1994. However, supporters of the DSM-IV suggest that, despite its comorbidity, the criterion
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that GAD has a 6-month duration creates a more homogenous disorder so that the diagnosis
of GAD is more advanced than previous categorizations (Tyrer & Baldwin, 2006). On the
other hand, the DSM-IV makes it possible to diagnose any overlapping anxiety symptoms
irrespectively indicating GAD can be separated from other disorders which involve anxiety
symptoms. These disorders include panic disorder (Clark et al., 2004), hypochondriasis
(health anxiety), social anxiety disorder (Chavira et al., 2004), medically unexplained
symptoms (somatisation disorder) (Hamilton et al., 1996), obsessive-compulsive disorder
(Angst et al., 2005) and eating disorders (Kaye et al., 2004). Thus, the diagnosis of GAD in
the DSM-IV should not be abandoned.
2.4 Features of GAD
2.4.1 Residual disorder
For there were no feature that specific to GAD, the original classification people used was
unsatisfactory. As a consequence, GAD became a residual diagnosis that overlapped with
other disorders (Tyrer & Baldwin, 2006). Since it was classified as a residual category in the
DSM-III, several issues have generated and been discussed for a long time. People argue
whether GAD should be viewed as a residual disorder; whether GAD was comorbid with
other anxiety disorders; whether GAD was severe enough to be classified as a disorder.
People suggest these confusions are due to the residual feature of GAD (Barlow & Wincze,
1998). On the one hand, clinical research argues that patients cannot be diagnosed with GAD
unless they meet the criteria for any other anxiety of affective disorder. The researchers
always reported difficulty in setting the duration criterion at 1 month because even temporary
adjustments to life stress often last longer than this (DiNardo et al., 1986). On the other hand,
four major symptom groups of GAD defined by the DSM-III, motor tension, autonomic
hyperactivity, apprehensive expectation and vigilance and scanning, were truly residual
symptoms. All patients with anxiety disorders, such as obsessive-compulsive disorders and
panic disorder, also presented with these four basic features to the same extent as did patients
with GAD (Barlow & Wincze, 1998).
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Later, The DSM-III-R (Diagnostic and Statistical Manual of Mental Disorders, Third Edition,
Revised) introduced a new classification strategy which based classification on the
assumption that cardinal symptom was not necessarily presented in other anxiety disorders.
That is, firstly distinguish a syndrome of GAD from the anticipatory anxiety which is found
in other anxiety disorder categories, and then determine the focus of apprehensive expectation
or worry. After that, only patients characterized as ‘chronic worriers’ with sufficient severity
ratings and accompanying associated symptoms can be considered meet the criteria for GAD
(Barlow & Wincze, 1998). This strategy has removed GAD as a residual category, so that
GAD is no longer a residual disorder since the DSM-III-R.
2.4.2 Worry
As the hallmark of GAD, worry is a common behavior for the whole population. Individuals
who suffered GAD often report that they spend most of waking hours worrying about minor
matters. Unlike other anxiety disorders and non-anxious controls, they have difficulties in
controlling the worry process or stop worrying long enough to carry on with other activities.
It has important consequences and correlates with mental health problems for people.
Generally, people with high levels of worry are more likely to report higher levels of anxiety
symptoms and poorer health compared to people who do not worry as much (Mackintosh et
al., 2006). Studies conducted on GAD and non-anxious subjects indicate that pathological
worry differs from normal worry. Studies comparing the nature of worry in patients with
GAD and non-anxious controls have found that both groups have very similar contents of
worry (Fisher, 2007). The results revealed that worry occurs more frequently and for longer
periods of time in GAD patients. However, people argue that the understanding of the nature
and function of worry in GAD may be constrained by using non-anxious controls. In other
words, the differences between non-anxious group and patients with GAD may be an artefact
of the research design.
Recently, studies on GAD patients and people who worry severely have found that worry
exists along a continuum, and differences that distinguish people with high levels of worry
from GAD patients are quantitative rather than qualitative (Fisher, 2007; Ruscio, 2002;
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Ruscio & Borkovec, 2004). Compared with high worriers, GAD patients reported their
worries more frequently and more distressing. They found more difficult to control their
worries and rated the associated symptoms more severely. Compare to studies that utilized
non-anxious controls, these results provide support to the utility of GAD diagnosis and
indicate that GAD can not be simply viewed as a cognitive disorder characterized by high
levels of worry (Fisher, 2007).
2.4.3 Comorbidity
Another feature of GAD is its comorbidity. According to the DSM-IV, uncontrollable worry
must be unrelated to another Axis I disorder. However, as a form of intrusive thought, worry
is a coexisting feature of many disorders and common to many psychopathologies (Maser,
1998). Therefore, people argue that this comorbid feature of GAD may be due to the nature of
worry as a comorbid feature with other disorders. Except the key symptom of GAD, such as
uncontrolled worry or apprehensive expectation, other symptoms are also included for
diagnosing the GAD, such as restlessness, fatigue, irritability, muscle tension, difficulty in
concentration and sleep disturbance. Compared to the DSM-IV and DSM-III-R, the DSM-III
(see Table 3) consists of a more extensive list of symptoms, which are grouped under four
categories: (i) unrealistic or excessive anxiety or worry; (ii) motor tension; (iii) autonomic
hyperactivity; and (iv) vigilance and scanning. According to the DSM-III-R and the DSM-IV,
many of these symptoms can also be found in patients with other disorders, such as panic
disorder, somatization disorder, post-traumatic stress disorder, depression and dysthymia,
social phobia and specific phobia. For instance, an exaggerated startle response is a prominent
feature in post-traumatic stress disorder, but it has also been found in patients with GAD.
Multiple physical problems associated with GAD are frequently reported by people with
somatization disorder. In addition, prolonged periods of tension and worry has been reported
by people with obsessive-compulsive disorder are also common among people who suffer
from depression (Maser, 1998).
To determine the comorbid features of GAD, some clinical research has experimented with
dropping the hierarchical residual requirement for GAD during the 1980s. More specifically,
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Table 3 DSM-III DSM-III-R and DSM-IV diagnostic Criteria for GAD
Source: Barlow & Wincze, (1998)
clinicians were forced to make attempts to establish whether GAD symptoms defined by the
DSM-III were associated features of the principal diagnosis, or whether they represented a
coexisting independent problems (Barlow & Wincze, 1998). In other words, it required
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clinicians to determine one of the four GAD symptom clusters: the focus of apprehensive
expectation. For example, what were patients worrying about? If they were worrying about
their next encounter with a socially phobic situation or the next panic attack, this would be an
anticipatory anxiety and might be judged by clinicians. Obviously, anticipatory anxiety was
an integral part of a principal diagnosis of panic disorder. Considering multiple life
circumstances, the focus of apprehensive expectation was more easily to be unrelated to the
principal diagnosis, but the patients still presented the other three symptom clusters. Then,
people could judge GAD as a coexisting independent problem. These have been demonstrated
in the later version of DSM-III, the DSM-III-R. The DSM-III-R suggests that GAD is
associated with the highest rates of comorbidity among the anxiety disorders so that it is not
necessary to separate out GAD from other anxiety disorders.
2.5 Personality and GAD
Several studies have demonstrated that GAD and chronic worry are related to other factors,
such as genetic influences and the personality dimension neuroticism. Studies of personality
suggest that personality traits of patients with mental disorder significantly differ from the
traits of other people. Personality traits, on the other hand, have been shown to being
associated with mental disorders such as extraversion and conscientiousness. Neuroticism, in
particular, has been demonstrated to be strongly correlated to the presence of mental disorder.
(Cuijpersa et al., 2005).
2.5.1 Neuroticism
In the past decade, personality traits have been suggested to be important in understanding the
personality-health relationship in theory. For the heuristic value in unifying personality
structure and the robustness across different languages and inventories, the Five-Factor model
of personality structure is the most widely accepted model of personality (Jang et al., 1996).
Among several different labels of the five factors, the most popular labels come from McCrae
and Costa (1987): Agreeableness, Conscientiousness, Extraversion, Openness to Experience,
and Neuroticism. Agreeableness reflects the tendency to be friendly, considerate and helpful;
conscientiousness indicates proneness to be purposeful, self-disciplined and scrupulous;
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extraversion is the tendency to be enthusiastic, sociable, active, and optimistic; openness
refers to intellectual curiosity and independence of judgment; and neuroticism describes a
tendency to experience negative emotions, such as depression and anxiety (Costa & McCrae,
1992; Wilson et al., 2007). Many studies have found that extraversion, conscientiousness,
agreeableness, and openness are positively related to health and well-being, whereas only
neuroticism is negatively related to health and well-being. As mentioned in the beginning,
people with high neuroticism scores tend to be more sensitive, worrying, moody, emotional,
frequently depressed, sleepless, and may suffer from various psychosomatic disorders
(Moutafi et al., 2006). People with low scores are more likely to be hardy, secure and relaxed
even under stressful conditions.
2.5.2 Neuroticism and mood disorder
Neuroticism consists of six facets: anxiety, depression, anger-hostility, self-consciousness,
impulsiveness and vulnerability. As a consistent predictor, neuroticism is found to be crucial
to the onset of depressive symptoms in late life. Depressives and some neurotic people tend to
interpret themselves in a more negative manner when in negative events (Friedman, 2007).
For example, Steunenberg et al. (2006) hypothesized that personality traits were significantly
associated with the onset of depression, and a high neuroticism level strengthened the impact
of health-related variables. Meanwhile, they pointed out that the effect of personality might be
overwhelmed by the effect of health related variables. Their results proved that personality
traits were more strongly related to onset than physical health and social resources. High
neuroticism was strongly related to becoming depressed and this association was not affected
by the influence of other predictors or age. Chien et al. (2007) used a representative sample of
3,246 university students to examine whether personality factors would predict the pattern of
depressive symptom. The findings supported that depressive symptoms were stably related to
depressive personality across one year. Depression measured in the second year could be
predicted by high neuroticism and low agreeableness, extraversion, and conscientiousness.
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2.6 The relationship between depression, anxiety and neuroticism
2.6.1 Studies of GAD and major depression
As mentioned above, GAD patients have difficulty in concentrating, depressed mood, sleep
disturbance and fatigue leading diagnosticians to, at times, suspect depression. Many of these
GAD symptoms are also observed in the whole range of anxiety disorders as well as the
disorder of mood (Maser, 1998). A number of studies have found that GAD is consistently
comorbid with depression. GAD and major depressive disorder are the most common type of
anxiety-mood comorbidity, with up to 80% of patients reporting GAD also reporting a
comorbid mood disorder during their lifetime (Gorwood, 2004). For example, Garvey et al.
(1991) found 34% of 35 affective disorder patients reported comorbid GAD. Massion et al.
(1993) reported 46% of 63 GAD patients of the Harvard-Brown Anxiety Research Project had
comorbid major depression disorder (MDD), 13% had intermittent depression and 10 % had
minor depression. The percentage of GAD patients who attempted suicide was more than
twice that for those with panic disorder. Furthermore, the GAD group was more likely to
exhibit poor emotional health, greater chronicity, an earlier age of onset and the greatest
likelihood of being in an episode at intake. A longitudinal study by Mancuso et al. (1993)
followed up GAD patients who participated in a clinical trial 16 months earlier. Among the
patients with chronic GAD, MDD was present in 9.1%of cases, and 45.5% had dysthymia. All
these studies provide evidence that many of the features of GAD are also diagnostic criteria of
MDD and dysthymia which indicates that GAD might not be an independent disorder in
many cases.
Another important issue is the direction of the association between anxiety and depression.
Bryant et al. (2008) suggest several barriers to testing out the relationship between anxiety
disorders and depressive symptoms. First of all, many researches use hierarchical case
definition in which participants who are cases of depression cannot be deemed cases of
anxiety (Manela et al., 1996). Therefore, these studies cannot inform this issue. Secondly,
when reporting anxiety, the symptoms of older groups are more likely to be under-recognized
by medical practitioners. Thirdly, the majority of studies are cross-sectional which tend to
supporting the association between depression and anxiety. However, most studies cannot
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address the directionality of the association. Lenze et al. (2001) found out that around 85% of
adults with depression endorsed significant symptoms of anxiety, whereas Jeste et al. (2006)
reported that an estimated 42% of their depressed sample have comorbid anxiety. In addition,
higher level of comorbidity was found in participants diagnosed with GAD, of whom 91%
also had a diagnosis of depression. (Manela et al., 1996).
Therefore, longitudinal designs are needed to address the question of comorbidity. de Beurs et
al. (2001) conducted such a study to investigate risk factors for becoming anxious and/or
depressed in the later year. By using the data from participants who were healthy at baseline,
they found similarity of the vulnerability factors between depression and anxiety, but
differential effects on stressful life events, suggesting different pathways leading to
depression and anxiety. However, another study based on a large population sample reported
different results (Schoevers et al., 2003): the severity of depression or anxiety symptoms
increased the likelihood of having mixed depression and anxiety. In summary, although
anxiety often presents with depression, quite significant rates of anxiety are present in the
absence of depression (Bryant et al., 2008).
2.6.2 Studies of neuroticism, anxiety and depression
There is a sizable body of literature demonstrating that high levels of neuroticism are related
to depression and anxiety in a variety of contexts (Weinstock & Whisman, 2006). Kendler et
al. (2006) firstly examined the association between personality and depression from an
epidemiologic perspective. They found that neuroticism was robustly associated with the risk
for lifetime MDD. Extraversion was weakly and negatively related to MDD, indicating that
the relationship between introversion and MDD was marginal. However, when both
neuroticism and extraversion were included in the analysis, the effect of extraversion
disappeared. They suggested this weak association between extraversion and MDD was
mediated through the inverse correlation between neuroticism and extraversion. Then they
followed up that study with a longitudinal study to examine the ability of personality traits to
predict first onset of MDD. Consistent with previous prospective investigations, the results
showed that neuroticism strongly predicted new onsets of depression, whereas extraversion
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was only weakly related to new onsets. When examined together, the predictive power of
neuroticism was stable, whereas that of extraversion became non significant. In addition, they
investigated the genetics between personality and MDD by using twin modeling. For MDD
and neuroticism, the best-fit model only included genes and individual specific environment
and parameter estimates of men differed from women. They reported the genetic correlation
between neuroticism and MDD was 0.46 in women and 0.47 in men (0.45 in both sexes),
which substantially exceeded the environmental correlation (0.05 in women and 0.10 in men).
Trull and Sher (1994) compared the sample of university students who had major depression
or any anxiety disorders to those who did not. They found most students who had major
depression or any anxiety disorders reported significantly higher neuroticism scores than
those who had not. Specifically, higher levels of neuroticism were associated with lifetime
diagnoses of post-traumatic stress disorder, agoraphobia, and social phobia rather than simple
phobia. Another study (Bienvenu et al., 2001) demonstrated that lifetime diagnoses of major
depression, social phobia, agoraphobia, and panic disorder were all significantly related to
high levels of neuroticism. Levels of neuroticism had also been found to reliably and
positively correlate with continuous measures of depressive and anxiety symptomatology.
More recently, research in younger adults found that neuroticism was significantly associated
with a GAD diagnosis and a measure of GAD symptom severity (Gomez & Francis, 2003).
2.7 Twin studies
Twin studies are based on the assumption that identical or monozygotic (MZ) twin pairs share
100% of their genes, whereas dizygotic (DZ) twin pairs only share half their genes. Therefore,
MZ twin pairs have greater genetic similarity than DZ twins. The environmental influences,
on the other hand, also leads to familial resemblance within twin pairs. However, the
environmental influences should be at the same level for both MZ and DZ twins. In addition
to genes and common or shared environment, there are environmental aspects that lead family
members to be different. For instance, individual life events or relationship experiences could
lead to great differences between family members and these are individual specific
environment or described as the nonshared environment (Eley, 2007a).
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2.7.1 Twin study of anxiety
Many anxiety disorders have been examined by using twin data set, such as phobias, GAD,
panic disorder, post-traumatic stress disorder etc. All of these studies show significant genetic
influences as well as the environmental influences (Kendler et al., 1992a; 1992b; 1993). For
example, a large population-based female twin study of Kendler et al (1992b) reported
heritability estimates of around 30-40% for GAD, panic disorder, and agoraphobia, social
phobia, situational phobia and simple phobia. Other studies have found similar heritability
estimates for men in both GAD and panic disorder (Scherrer, et al. 2000). To search for
‘anxiety gene’, Hettema et al. (2001a) compared several measures of twin resemblance by
using a meta-analysis of selected epidemiological studies. They reported that around 32% of
the variance for liability to GAD and 43% for panic disorder were explained by additive
genetic effects in both genders and the same genes predispose men and women to generalized
anxiety disorder. The remaining variance was explained by individual specific environment
and only a small proportion of the variance on GAD was due to common familial
environment in the women had been found. Only few twin studies investigate post-traumatic
stress disorder, and most of those are more likely to focus on symptoms rather than disorder.
However, those available data also indicate a genetic influence of 30% (True et al., 1993).
Interestingly for post-traumatic stress disorder, people argue that a contribution of heritability
comes from a genetic influence on exposure to combat as a term of trauma mediated through
personality aspects (Eley, 2007a). Moreover, literature of child anxiety also shows such
moderate genetic influence and shared environmental influence, although the results from
several studies of childhood anxiety or notably separation anxiety are not consistent (Eley et
al., 2007b). In conclusion, these findings provide evidence for genetic influences in the field
of psychopathology with heritability estimates of 30%-40%. Only a little contribution from
shared environment has been founded in most of studies. Eley (2007a) suggest larger studies
or meta-analyses of genetic studies are required to identify significant influences from shared
environment.
2.7.2 Twin study of comorbidity of anxiety disorders
The high comorbidity has been seen among most anxiety disorders and depressive disorders.
20
One of the most consistent findings with behavioral genetics is that genes play the robust role
in the correlation between anxiety and depression. Studies of childhood symptoms, adult
disorder, and adult symptoms revealed that both anxiety and depression share almost entire of
genetics, and explain majority of their association (Eley & Stevenson, 1999; Kendler et al.,
1992). Put another way, anxiety and depression share many of the same genes, and the effect
of these shared genes lead to large correlation between these phenotypes. More recently,
studies have found a slightly lower level of genetic overlap, but the overall influence of
shared genes on generalized anxiety and depression remains the same. In contrast,
environmental influences are more likely to be specific to either anxiety or depression (Eley,
2007a). Twin studies on both men and women have reported significant genetic overlap as
well as some genetic specificity for the different phobias (Kendler et al., 2001). Kendler et al.
(1995) also examined the genetic factor of six major psychiatric disorders, panic disorder,
phobias, GAD, bulimia, major depression and alcoholism, in women, they found two groups
of genes: one had a large influence on GAD and depression, as well as a small influence on
panic disorder; the other one mainly influencing panic disorder, phobias and bulimia,
indicating a closer genetic relationship between panic disorder and the phobias. Another
analysis of GAD, panic disorder, and other five different phobias also supports two groups of
genes, providing evidence for two genetic factors (Hettema et al., 2005). Additionally, study
on male twin data reported that about 50% of genetic variance in GAD was shared with panic
disorder.
Personality traits, and neuroticism in particular, have been demonstrated to be genetically
correlated with anxiety and depression (Eley, 2007a). There are three relevant studies in the
univariate literature on the association between anxiety types. By using the youngest sample
of pre-school children, Eley et al. (2003) assessed a series of anxiety-related behaviors,
including fears, separation anxiety, general distress (worry and sadness), shyness and
obsessive–compulsive symptoms. The results of all five scales indicated the genetic overlap
which accounted for about 50% of the covaration between each pair of scales. However,
genetic variance for obsessive–compulsive symptoms significantly differed from that on the
other scales. For adolescence, one longitudinal study found strong genetic continuity across
21
time for over-anxious disorder and simple phobia which also shared genetic influence with
late adolescent depression (Silberg et al., 2001). Finally, a multivariate genetic analysis of
DSM-related anxiety (generalized anxiety, obsessions-compulsions, panic, agoraphobia,
separation anxiety, specific fears and social anxiety) and depression symptoms was conducted
on 13- to 21-year-olds people. The results showed that genetic effects accounted for more
than 50% of the overlap between each pair of variables (Eley, 2007a). Therefore, it is clear
that there is significant and substantial genetic overlap among the anxiety disorders and its
related symptoms, as well as with depression. Eley (2007a) suggests that this genetic overlap
implies that ‘when genes are found for one type of anxiety or for depression, they will also
have a potential influence on others’.
2.7.3 Twin study of GAD and neuroticism
Several detailed reviews of the genetic epidemiology of anxiety disorders have examined
whether anxiety disorders are familial and have estimated their heritability. Much knowledge
has been amassed both quantitatively and qualitatively. Behavioral genetic studies have found
that neuroticism is moderately heritable and reasonably stable, with a heritability between
40% to 50% in adults. Additive genetic and nonshared environmental factors explain the
largest amounts of variation, while shared environment effects have consistently been found
to have little influence (Levinson, 2006; Matthews et al, 2003). Behavioral genetic studies of
GAD have yielded similar findings: additive genetic effects and nonshared environmental
effects explain between 14% and 40% of the variation in GAD, whereas common
environment has no significant influence on it (Hettema et al., 2001b; Hettema et al., 2004;
Mackintosh et al., 2006).
More recently, research in younger and older adults has found significant genetic correlations
between neuroticism and several mental health symptoms (Eley, 2007a; Hettema et al., 2001b;
Hettema et al., 2004; Levinson, 2006). However, only a few studies have investigated the
genetic relationship between neuroticism and GAD. One recent study has investigated the
genetic relationship between neuroticism and GAD in younger adults (Hettema et al., 2004).
This study found that the genetic factors underlying neuroticism were indistinguishable from
22
those influencing liability to GAD, and genetic correlations were equal in men and women.
Besides, nonshared environmental influence was only modestly correlated between
neuroticism and GAD. Another study (Mackintosh et al., 2006) conducted on older adults
suggests that neuroticism and GAD share many of the same genes influencing liability with
the genetic correlation of 0.57, which is a little lower compared to the genetic correlation of
0.80 for younger adults (Hettema et al., 2004). The correlation between nonshared
environment and GAD is 0.11, which is similar to the correlation of 0.19 found by Hettema et
al. (2004).
2.8 The present study
According to Erikson’s stages of human development, a person with the age between 19 and
40 is called young adult, whereas a middle adulthood is a person between the ages of 40 and
65. Previous research explored the genetic relationship among the younger adults, with the
mean age of 36.3 (Hettema et al., 2004) and older adults, with a mean age of 62.2
(Mackintosh et al., 2006). However, no study has investigated the genetic relationship
between neuroticism and GAD in middle-aged adults. Thus, the purpose of the present study
is to investigate the genetic influences shared by personality traits, mainly neuroticism, and
GAD in a representative sample of middle-aged adults.
There are three hypotheses of the present study: (1) to investigate whether neuroticism is
strongly correlated with GAD; (2) to examine whether neuroticism and GAD share many of
the same genes; (3) to explore the contribution of environmental influences to the variation
between GAD and neuroticism. It could be predicted that both additive genetic and nonshared
environmental influences may be important sources of variation between GAD and
neuroticism. The genetic influences between GAD and neuroticism would be strongly
correlated, whereas nonshared environmental influences would be less strongly correlated.
Besides, common environment would have no significant influence on it.
23
3. Methods
3.1 Participants
For the present study I will use twin pairs from the National Survey of Midlife Development
in the U.S. (MIDUS) conducted by the John D. and Catherine T. MacArthur Foundation’s
Research Network on Successful Midlife Development. The protocol was reviewed and
approved by the Human Subjects Committee of Harvard University Medical School (Kendler
et al., 2000). The survey was carried out in two parts: a telephone interview followed by a
self-administered mail questionnaire. Before initiation of the telephone interview, informed
consent through oral assent by contact persons was required. Contact persons were informed
that the survey was conducted by Harvard Medical School and was aimed to study health and
well-being during the middle years of life. As participants, they would complete a telephone
interview lasting 45 minutes on average and two mail questionnaire booklets requiring about
1.5 hr on average to complete. All participants were offered $20 and a copy of a final study
monograph as incentives for participation (Keyes et al., 2002). Field procedures lasted
approximately one year, with all data collected during 1994-1995. Approximately 50,000
households were initially screened by telephone and 3032 people had finished survey with
overall response rate 60.8%. Only one-seventh (14.8%) of respondents reported having twins
in the family and of which 60% gave permission to be contacted for the twin study (Kendler
et al., 2000; Kessler et al, 2004; Weiss et al, 2008). Self-report questions which had been
proved more than 90% accuracy in identifying the zygosity were used to determine zygosity
of twin pairs.
All 973 twin pairs (365 monozygotic and 608 dizygotic) were used in analyses. The mean age
was 44.9 (SD =12.1)(Weiss et al., 2008). Specifically, 171 twin pairs of the monozygotic
twins were male, with the mean age of 44.5 (SD = 11.5), and 194 were female with the mean
age of 43.5 (SD = 12.2). Of the dizygotic twin pairs, 259 were opposite sex (mean age = 45.8,
SD = 11.9) and 349 were same sex (136 were male, with the mean age of 44.2, SD = 12.5;
213 were female, with the mean age of 45.9, SD =12.4).
24
3.2 Measures
3.2.1 Personality traits.
Five-Factor personality dimensions were assessed by the Midlife Development Inventory
(MIDI) which consisted of 25 self-descriptive items selected from previous inventories of the
Big Five (Lachman & Weaver, 1997). Participants used 4-point Likert scales to rate the
degree which each adjective on the questionnaire described them most. Scores were the mean
ratings for each dimension so that higher sores reflect higher standing on each dimension
(Keyes et al., 2002). Neuroticism was described to be moody, worrying, nervous, and calm
(Lachman & Weaver, 1997; Weiss et al., 2008). Alpha internal consistency coefficients
obtained in the MIDUS dataset were 0.74 for Neuroticism, 0.78 for Extraversion, 0.77 for
Openness to Experience, 0.80 and 0.58 for Agreeableness and Conscientiousness respectively
(Keyes et al., 2002; Lachman & Weaver, 1997).
3.2.2 Generalized anxiety disorder.
Current studies suggest that it is better to understand anxiety and mood problems as falling on
a continuum rather than as comprising qualitatively distinct categories (Teachman, 2006).
Thus, the GAD score in the present study was calculated as a continuum. GAD was assessed
by 10 items through the telephone interview. The disorder was based on the definitions and
criteria specified in the third edition-revised of the American Psychiatric Association’s (APA)
Diagnostic and Statistical Manual of Mental Disorders (DSM-III-R; 1987). Good retest
reliability and clinical validity were demonstrated by WHO Field Trials and other
methodological studies (Kessler et al., 1999). Respondents rated the degree to which each
item described them on a scale ranging from most days (1) to never (4). All 10 items
described how often people experienced worry emotion over the past 12 months (e.g., ‘how
often you had trouble keeping your mind on what you were doing’). Each score was
calculated by taking the number of “Most days” responses to the items.
3.3 Statistical Analysis
Descriptive statistics were conducted by using SPSS 15.0. Age and gender differences in
mean scores of neuroticism and GAD were tested with the t statistic. Structural equation
25
model was computed via the Mx software package to assess how genetic and environmental
sources of variation on GAD and neuroticism are related (Neale et al., 2003). To test
hypotheses of the present study, the bivariate Cholesky model was applied for the latent
factors to determine the measured phenotypes. There were two sets of factors, one described
the variance influencing neuroticism and GAD (A1, additive genetic; C1, shared
environmental; E1, nonshared environmental). The other one estimated residual influences
which were specific to GAD (A2, C2, E2). According to the prior studies (Hettema et al., 2004;
Mackintosh et al., 2006), the choice of ordering was based on the hypothesis that GAD may
have specific risk factors above those shared with neuroticism. The phenotypic correlation
between GAD and neuroticism was decomposed into three separate components: additive
genetic (rg), shared environmental (rc), and nonshared environmental (re), describing the
relationship between the latent factors.
Neuroticism
eN
EN
cN
CN
aN
AN
re
rc
ra
EG
eG
CG
cG
AG
aG
GAD
Figure 1
The present analysis focused on the MZ twin pairs and same sex DZ twin pairs. In the
beginning, the model was fit to the raw data which included all of the sources of variance
(additive genetic, shared environmental and nonshared environmental, see Figure 1). The fit
of the full model was calculated by the model parameters and indices, and then compared to
reduced models which eliminated parameters in a stepwise fashion. This procedure was
conducted to investigate the deterioration of model fit if sources of variation were dropped.
The viability of reduced models compared to the full model was examined using two statistics
(Mackintosh et al., 2006): (1) The fit of reduced models was assessed by taking the
differences between -2 times the log likelihood (-2LL) for the full model and reduced model.
It was distributed as a chi-square distribution with degrees of freedom equal to the difference
of degrees of freedom of the two models. (2) According to the principle of parsimony, more
parsimonious models with fewer parameters are better unless they provide a significantly
26
worse fit. Differences between models were assessed by using the Akaike’s Information
Criterion (AIC). It was calculated as the model chi-square minus two times the degrees of
freedom and lower values of AIC was providing an improved balance of model fit and
explanatory power (Hettema et al., 2004).
4. Result
Table 4 presents the mean scores and standard deviations for both neuroticism and GAD in
MZ and DZ twin pairs, whereas Table 5 shows average scores and standard deviations in male
and female. In general, MZ twins reported higher scores in both neuroticism and GAD than
DZ twins. The mean score of women (2.29) for neuroticism was significantly higher than that
of men (2.18), t (1722) =3.31, p = 0.001. Similarly, women reported more worry episodes in life
time with the mean score of 0.20, which was significant greater than of men (0.08), t (1723) =
3.30, p = 0.001.
Table 4 Mean scores for neuroticism and GAD
Descriptive statistics
MZ twins
DZ twins
MT1
SDT1
MT2 SDT2
MT1 SDT1
MT2
Neuroticism 2.25 0.72 2.23 0.66
2.21 0.64 2.29
GAD
0.16 0.98 0.18 0.97
0.14
0.88 0.12
Note. MZ= monozygotic; DZ= dizygotic; T1= twin 1; T2= twin 2
SDT2
0.66
0.68
Table 5 Different gender in mean scores for neuroticism and GAD
MZ twins
DZ twins
M
SD
M
SD
Neuroticism Male
2.18 0.75
2.19 0.64
Female
2.29 0.68
2.30 0.66
GAD
Male
0.02 0.31
0.09 0.65
Female
0.27 1.31
0.19 0.95
Note. MZ= monozygotic; DZ= dizygotic
In the present study, GAD and neuroticism were significantly correlate, r = 0.23, p < 0.001.
Table 6 describes intraclass correlation between co-twins for both neuroticism and GAD in
males and females. In general, the correlations for MZ twins were substantially greater than
twice those for the DZ twins, suggesting a genetic influence on neuroticism and GAD.
27
However, the correlation of GAD for both MZ and DZ twins was very low. More specifically,
both males and females from MZ twins were significantly correlated with co-twin in
neuroticism (p < 0.001) while only male twins showed a strong correlation for GAD (p <
0.001). For DZ twins, neuroticism showed significant correlations in both same-sex and
opposite-sex dizygotic twins (p < 0.001) whereas no significant correlations were found in
GAD.
Table 6 intraclass correlations for GAD and neuroticism
rM
rD1
rD2
rD
Neuroticism Male
0.54**
0.24*
0.29**
Female 0.51**
0.26**
0.16
Total
0.52**
0.23**
GAD
Male
0.54** -0.02
-0.17
Female
-0.01
0.00
-0.04
Total
0.07
-0.01
Note: rM = intraclass correlation of monozygotic twins; rD1 = intraclass
correlation of same-sex dizygotic twins; rD2 = correlation of opposite-sex
dizygotic twins; rD = intraclass correlation of all dizygotic twins; *p < 0.05;
**p < 0.001
Additionally, age was significantly negatively correlated with both GAD and neuroticism
although these correlations were weak. The correlation between age and GAD was r = -0.047
(p < 0.05), and r = -0.153 (p < 0.01) for neuroticism. When controlling gender difference,
both neuroticism and GAD still significantly correlated with age.
The results for neuroticism were consistent with prior findings (Hettema et al., 2004;
Mackintosh et al., 2006) with additive genetic influence accounting for 40% of the variance.
For GAD, however, only 12% of the variance reflected genetic factors with most of the rest
attributed to nonshared environmental factors. Results from bivariate analysis indicated that
the E model fits the data best for both neuroticism and GAD. For the Cholesky decomposition
models, full model included estimates for A, C and E. Unexpectedly, Model comparison
indicated that A paths cold be dropped without significant loss of fit (Δχ2 = 0.62, df = 1, AIC =
-1.385, p > 0.05), as the same as C paths (Δχ2 = 1.45, df = 1, AIC = -0.553, p > 0.05). As most
of environmental factors influencing GAD were nonshared environment, E path could not be
dropped (Δχ2 = 10.18, df = 1, AIC = 8.182, p < 0.001). Figure 1 shows the Cholesky model
28
and the parameter estimates from the final model, indicating no genetic variation in GAD was
shared with neuroticism, nonshared environmental factors account for most of variation
between GAD and neuroticism.
Figure 1. Cholesky model and the parameter estimates for additive genetic and nonshared
environmental influences on GAD and neuroticism.
5. Discussion
5.1 Interpretation of the findings
The present study examined the genetic and environmental risk factors shared by GAD and
the personality trait of neuroticism. The result of the present study does not show any genetic
influence on neuroticism and GAD, although the correlations for MZ twins were substantially
greater than twice those for the DZ twins. By using bivariate modeling of twin data, the
results suggested that most of the variation was attributed to individual specific environment
rather than genetic factors, which was not consistent with previous studies conducted among
younger and older adults (Hettema et al., 2004; Mackintosh et al., 2006). Compared with the
previous studies, they reported the genetic correlation of 0.57 between neuroticism and GAD
for older adults (Mackintosh et al., 2006) and the genetic correlation of 0.80 for younger
adults (Hettema et al., 2004). In addition, Jardine et al. (1984) also found genetic risk factors
were highly correlated between anxiety symptoms and neuroticism with the genetic
correlation of 0.80.
29
By using a population-based sample of middle-aged twins, the present study did not find any
genetic correlation between GAD and neuroticism which implicated that most of the genetic
factors underlying neuroticism were not the same genes from those that influence liability to
GAD. In contrast to genetic factors, environmental risk factors were highly correlated
between neuroticism and GAD, suggesting that the types of individual-specific events that
influence GAD were strongly related to those that affect neuroticism scores. Similar to
previous studies, only nonshared environmental factors, not shared environment, influenced
GAD (Kendler et al., 1992c; Roy et al., 1995). So, while there was no significant overlap in
the genes affecting liability for GAD and neuroticism, the environmental factors influencing
GAD were largely as the same as those of neuroticism. However, the magnitude of the
environmental correlation in previous studies is much lower than the present study with the
correlation of 0.19 found by Hettema et al. (2004) between GAD and neuroticism and the
0.40 found by Jardine et al. (1984) between anxiety symptoms and neuroticism.
5.2 Compare to other studies
Previous analyses have investigated the genetic and environmental effects for GAD and
neuroticism separately. For neuroticism, the most detailed findings come from large
population-based studies. In the prior study of Hettema et al. (2001), they reported both
additive and non-additive genetic factors for neuroticism, no significant contribution from
common environment. Gender influenced differently in the magnitude but not the source of
genetic effects for neuroticism, which meant the same genes were expressed differently in
men and women (Hettema et al., 2004). However, previous studies did not detect sex
differences in genetic and environmental factors for GAD. Another large scale twin study
examined the covariation between neuroticism and current depression and anxiety symptoms
(Jardine et al., 1984). They reported genetic correlations of 0.80 between neuroticism and
anxiety scores in both genders. Similarly, Fanous et al. (2002) conducted a study to analysis
neuroticism and major depression disorder by using the same sample as Hettema et al. (2004).
The best model showed the within-sex genetic correlations between neuroticism and major
depression were 0.49 for women and 0.68 for men, which had a slightly better model fitting
than one with a correlation of 0.55 for both genders. Additionally, the correlations between
30
neuroticism and major depression were significantly different from 1.00, indicating some
differences existed in correlation between major depression and GAD with neuroticism
(Kendler et al., 1992c; Hettema et al., 2004).
5.2.1 Twin study of GAD on younger adults
Hettema et al. (2004) firstly examined the underlying factors between neuroticism and GAD
by using structural equation modeling. Their study aimed to investigate the sources of
individual covariation between the semi-quantitative personality trait of neuroticism and the
psychiatric illness of GAD, Like the potential sources of gender differences in those shared
risk factors. As the same as the present study, they applied a bivarate Cholesky model to one
large scale twin data which imposed a stratified structure on the latent factors hypothesized to
determine the measured phenotypes with two sets of factors. Based on the a priori hypothesis
that GAD have specific influences over and above those shared with neuroticism, the first set
of factors included additive genetic influences (A1), common familial environmental
influences (C1) and nonshared environmental influences (E1). The second one (A2, C2, E2)
consisted of residual influences specific to GAD that did not share with neuroticism.
Moreover, Hettema et al. (2004) tested two types of gender differences by choosing a
sex-limitation model. That was (i) differences in the magnitude of effects of the same genetic
and environmental factors and (ii) sex-specific genes.
The results of Hettema et al. (2004) study suggest that the genetic factors underlying
neuroticism and those that influence liability to GAD are nearly indistinguishable. On the
other hand, correlation of environmental risk factors between GAD and neuroticism is not
high but only modest. To determine whether these results were dependent on gender, they
then applied the sex-limitation structure to those models in both same-sex and opposite-sex
twin pairs. The results show that the genetic correlation between GAD and neuroticism is
estimated to be equally to men and women. However, their analysis does not possess the
statistical power to significantly assess sex differences or non-additive genetic factors.
31
Hettema et al. (2004) also suggest several potentially important implications. Firstly, a
significant proportion of genetic influences are shared by neuroticism and GAD in common,
but individual environmental risk factors only account for modest contribution. As GAD has a
high correlation with the genes for neuroticism, they argue that GAD should be characterized
as an anxious personality type that belongs to axis II rather than an axis I syndrome that
developed from the same liability genes as those for neuroticism. In other words, people
should regard GAD’s place in psychiatric nosology. Secondly, their findings do not support
the hypothesis that the greater sharing of genetic risk factors in women may result in higher
genetic correlation between neuroticism and GAD although such higher correlations are
found in men. Finally, they suggest that neuroticism can be viewed as a useful target in
identifying liability genes for GAD.
5.2.2 Twin study of GAD on older adults
Another similar study conducted by Mackintosh et al. (2006) examines the genetic and
environmental influences shared between neuroticism and GAD in older adults. By using a
sample from the Swedish Twin Registry, nearly 10,000 people were investigated including
707 male MZ twins, 911 female MZ twins, 1010 male DZ twins, and 1281 female DZ twin
pairs. To explore the degree of overlap in genetic and environmental influences, they
hypothesized that both additive genetic and nonshared environmental factors were important
sources of variation for both neuroticism and GAD. By applying univariate behavioral genetic
models, they expected a strong correlation of genetic factors between neuroticism and GAD,
and a less strong correlation of nonshared environmental influences. Unlike the present study,
the neuroticism scores of this study were collected 25 year prior to the GAD assessment. The
full univariate model included effects of genetic influences (A), shared environmental
influences (C), and nonshared environmental influences (E) for men and women. It was
applied to estimate the proportion of variation in each variable and assess whether
quantitative sex differences existed. Model fit was tested by dropping the sources of variation
in each subsequent model. In addition, a bivariate Cholesky decomposition procedure was
used to explore how genetic and environmental sources of variation on neuroticism and GAD
were related.
32
The results showed about 2.9% of the population reported GAD during the lifetime, while
14.5% of older adults had a significant worry episode. Consistent with previous studies
(Kendler et al., 1992c, 1995; Roy et al., 1995), Mackintosh et al. (2006) reported around 25%
of the variation in GAD was attributed to genetic influences with the genetic correlation of
0.57. It was especially notable since neuroticism was measured in 1973 and lifetime GAD
was assessed in 1998, indicating that neuroticism and GAD shared many of the same genes
influencing liability. Nonshared environmental factors, on the other hand, were not strongly
related to sources of variation shared between GAD and neuroticism, re = 0.11. No significant
effect was found in common environmental factors, indicating that nonshared environment
effects did not contribution to liability for GAD and neuroticism. Although there was
significant overlap in the genes affecting liability for both neuroticism and GAD, Mackintosh
et al. (2006) argue that most of the environmental factors influencing GAD are different from
those of neuroticism. While study found a significant overlap of genetic effects between
neuroticism and GAD, there was little commonality in environmental influences with
nonshared environmental factors accounting for the majority of the variation in GAD.
Furthermore, their results provided the evidence of sex differences in GAD reflected
differences in prevalence of GAD, rather than contributions of genetic and environmental
factors to liability for the trait.
5.2.3 Twin study of anxiety disorder
The anxiety disorders are comorbid with one another so that understanding the latent factors
of this comborbidity can provide an insight view into the etiology of the anxiety disorder and
its classification and treatment. Such study has been conducted by Hettema et al. (2005) using
more than 5,000 male-male (MM) and female-female (FF) twin pairs from the Virginia Adult
Twin Study of Psychiatric and Substance Use Disorders. Several questions were raised before
examining the latent structure of the genetic and environmental risk factors:
(1) How similar is the pattern of genetic and environmental risk factors across the anxiety disorders
in men and women?
(2) Can one identify shared risk factor domains (genetic, common familial environment, or unique
33
individual environment) that account for the phenotypic correlations (comorbidity) among the
anxiety disorders?
(3) If shared risk factors exist, how are they structured (ie, how many separate factors are necessary
to best describe patterns of comorbidity)?
(4) What are the relative roles of risk factors that are common across the anxiety disorders vs. those
that are disorder specific? (p183)
In analyzing the above questions, Hettema et al., (2005) applied multivariate structure
equation model for the covariation among multiple variables. The whole model included
disorder specific factors, two genetic common (A1, A2), two shared environmental common
(C1, C2) and two unique environmental common (E1, E2) factors. First of all, the model was
fitted to both MM and FF twin data sets. And then six anxiety disorders were assessed to
examine the pattern of genetic and environmental risk factors that underlie their comorbidity.
The result indicated that the full model could be constrained to be equal across male and
female participants. The genetic risk factors on anxiety were best explained by two additive
genetic common factors across the disorders. Shared environmental factors only played a
small role in explaining the total variance for any disorder. In addition, unique environmental
influences could be explained by disorder specific effects and a single common factor
(Hettema et al., 2005). In conclusion, both men and women had the similar latent structure of
the genetic and environmental risk factor for the anxiety disorder. Genetic factor predisposed
to panic generalized agoraphobic anxiety group and the specific phobia group. The remaining
variance for anxiety disorder was largely explained by a unique environmental factor shared
across the all disorders and a common shared environmental factor.
5.2.4 Twin study of major depression
Kendler and Prescott (1999) assessed the genetic and environmental risk factors for major
depression using a large sample of MZ and DZ male twin pairs. The main purposes of their
study were to investigate whether genetic and environmental risk factors played the similar
important role in the etiology of major depression in both men and women, and examined
whether the genetic risk factors for major depression were the same in both genders. The
34
liability–threshold model was used to estimate the genetic and environmental contributions to
twin pair resemblance. When analyzing results from the male-male, female-female, and
male-female twin pairs together, the individual differences in liability were assumed from
additive genes, common or familial environment (C), and individual specific environment (E).
To examine the sex role in the relative importance of genetic or environmental risk factors for
major depression, the study compared estimates for A, C, E in male-male, female-female twin
pairs.
The result from more than 800 twin pairs showed that tetrachoric correlations in MZ and DZ
twin pairs were + 0.37 and + 0.20 and an estimated heritability was 39% (Kendler & Prescott,
1999). Compared to another general population twin study of lifetime major depression,
similar results were reported: tetrachoric correlation for major depression was estimated at
+0.37 in MZ and + 0.13 in DZ pairs, the estimated heritability was around 36% (Lyons et al.,
1998). Both of these studies did not found common or familial environmental contributions to
major depression in men. In addition, there was a positive correlation of genetic factors for
major depression between men and women, indicating that men and women shared some but
not all of their genes for major depression.
5.2.5 Other studies
The role of environmental and genetics factors in the aetiology of GAD was examined by a
meta-analysis. Hettema et al. (2001a) reported that the results from family studies found a
significant association between GAD in the probands and in their first-degree relatives, which
provided strong evidence of familial aggregation in GAD. Compared with the family studies,
results from the twin studies indicate a modest role for genetics in familial aggregation. The
estimated heritability was approximately 30-40% for both genders, and substantially lower
than the 70% heritability for major depression. Fisher (2007) suggests that the largest
proportion of the variance in liability for GAD is due to nonshared environmental factors.
Epidemiological studies have found that childhood sexual or physical abuse are more
common in people with anxiety disorders than in matched controls (Fisher, 2007). This may
35
be due to the linkage between GAD and insecure attachment in childhood. For example, the
experiences of role reversal and enmeshment with caregiver in childhood may lead to serious
consequence in adulthood. Children may be vigilant for possible threats to caregiver or even
themselves. This can develop into beliefs about the world being a dangerous place and worry
being an effective coping strategy in their later life. Traumatic experiences in childhood can
probably have detrimental effects on behavioral and psychological functioning (Fisher, 2007).
Moreover, Safren et al. (2002) argue that early traumatic events and childhood abuse are not
essential and specific risk factors for GAD and any other forms of psychopathology. They
suggest other early environmental factors that may be important in the development of GAD,
including parental separation, lack of opportunity for social interactions, and modelling of a
relative who has an anxiety disorder.
5.2.6 Which is more important: genes or the environment?
As mentioned previously, twin studies are widely used to understanding the genetic and
environmental etiology of psychiatric disorders. It has been demonstrated that genetics,
shared
family environment,
and
individual
experiences
play
different
roles
in
psychopathology of human beings (Eaves et al., 1997; Hewitt et al., 1997; Rutter et al., 1999).
Among the available behavior genetic methods, classical twin designs are commonly applied
to determine the relative contributions of genetic and environmental factors. Their results
indicate that genetic influences explain the most variance of psychiatric disorders whereas
nonshared environmental factors show less influences. Nonshared family environmental
effects have not been found in most of psychiatric disorders (Ehringer et al., 2006).
More recently, some studies have advanced the previous research by simultaneously studying
twins together with their singleton siblings. These studies provided comparable results which
included the role of genes and nonshared environment, and an effect of shared environment
(Eley, 1999; Feigon et al., 2001). They suggest that in addition to genetic influences,
nonshared and shared environmental influences are important in the development of the
anxiety disorder. Ehringer et al. (2006) evaluated six common disorders including GAD and
MDD in a community sample of adolescent twins, and their sibling. They used
36
individually-administered psychiatric interviews avoiding some probably methodological
issues that arose in analyzing, e.g., rating biases. The study tested the relative influence of
genes, and shared and nonshared environments contributing to these disorders. They found
that in GAD and MDD, most of the variance attributed to nonshared environmental factors,
genetic factors only had a moderated contribution. In addition, when fitting the model with
GAD and MDD data, the CE model fitted slightly better than the AE model, suggesting the
potential importance of shared environment (Ehringer et al., 2006). Thus, the role of shared
environmental factors remains an open question. Ehringer et al. (2006) suggest different
symptoms or different levels of symptomatology may result in the different findings.
5.3 Influential factors
5.3.1 Lower genetic correlation coefficient
A number of factors may influence the results of the present study. The extremely lower
correlation estimate in the present study may be due to the strength of the genetic correlation
that constrained by the strength of the correlation between neuroticism and GAD. Compared
with previous studies, Mackintosh et al. (2006) reported the polychoric correlation in older
adults was 0.29 and Hettema et al. (2004) found polychoric correlations of 0.52 for female
twin pairs, 0.32 for male twin pairs, and 0.28 for opposite-sex twin pairs. Besides, a Pearson
correlation of .58 between neuroticism and GAD severity ratings was found in phenotypic
study (Gomez & Francis, 2003). All these studies report higher correlations than the present
study.
5.3.2 The use of measurement for anxiety disorder
Another probable reason may be the measurement used in the present study. The GAD score
in the present study was assessed by 10 items according to the criteria of DSM-III-R (1987)
and calculated as a continuum. Participants rated the degree to which each item described
them on a scale ranging (1) most days; (2) about half the days; (3) less than half the days; (4)
never. Finally, each score was calculated by taking the number of “Most days” responses to
the items. However, when exploring the raw data of GAD, most participants reported their
worries less than half the days. In other words, only a few people had scores greater than zero.
37
Consequently, GAD scores of all twin pairs show a skewed distribution rather than a normal
one (see Figure 2).
In addition, there is a controversy about whether anxiety should be measured dimensionally
or in terms of categorical disorders. However, researchers are more likely to believe the
differences in prevalence reflect differences in how anxiety disorder is defined or measured
rather then real differences in prevalence (Jeste et al., 2005; Bryant et al., 2008). As symptoms
of anxiety are important, what constitutes an anxiety disorder in different age of people, and
how to measure it properly? In other words, is anxiety qualitatively different among younger
adults, middle-aged adults and older adults? A number of researches have addressed this issue.
Take the older population as an example, Fuentes and Cox (1997) argued that much of the
existing assessment on anxiety disorders was premature because the instruments used had not
been validated for older adults. Table 7 lists several epidemiological studies among older
populations. It shows that the checklists or diagnostic criteria used in most studies are not
designed specifically for old population such as The Geriatric Mental Schedule (GMS). GMS
diagnostic classification is a hierarchical system in which anxiety symptoms can be only
diagnosed when excluding the presence of a higher level disorder. As a result, studies
conducted on older population typically report very low rates of anxiety disorder when using
the GMS (Fuentes & Cox, 1997; Bryant et al., 2008). Palmer et al. (1997) argue that the
application of the DSM-IV (APA, 1994) diagnostic criteria developed for younger people
results in the underdiagnosis of anxiety, as well as the criteria for late-life anxiety are
inappropriate.
38
The Source: Bryant et al. (2008)
Additionally, Flint (2005) claimed that the problem is that different age of people may
experience anxiety differently rather than the duration of symptoms. Compared to younger
39
adults, older adults are more likely to report the high level of physical and psychiatric
comorbidity which has been identified as a potential cause of diagnostic confusion (Jeste et al.,
2005). One proper approach to this issue is to develop new instruments specifically designed
for people of ages.
5.3.3 Age effect on anxiety disorders
Prior to 1980s, some studies found that anxiety disorders were less common in older age
groups (Regier et al., 1988). However, other studies reported higher levels of anxiety
disorders among older age groups (Uhlenhuth et al. 1983). More recently, a curvilinear
relationship between anxiety symptoms and age has been found in the research on older
population (Teachman, 2006). It raises the question of whether rates of anxiety symptoms
decrease with age. Schaub and Linden (2000) divided data into two age brackets to examine
the prevalence of anxiety The results supported that rates of anxiety decrease with age.
However, Bryant et al. (2008) argue that sampling method can lead to the lower rates of
anxiety disorder. Later, this sampling issue has been discussed in other studies which reported
consistent findings with previous results that older group was less worried and depressed than
younger group.
5.4 Limitations
Several limitations in the present study need to be identified. Firstly, the generalizability of
the findings from the present study needs to be considered although it based on a large
population sample. This study firstly used a middle-aged population sample to examine the
genetic source of variance between GAD and neuroticism. Compared to previous studies,
however, the number of twin pairs tested in this study is only one forth of the previous one in
which almost 4,000 twin pairs was examined (Mackintosh et al., 2006), allowing for
parameter estimates with smaller standard errors. Secondly, the present study only examined
the genetic and environmental influences between neuroticism and GAD, but did not detect
sex differences in the factors underlying the covariation of neuroticism and GAD and did not
possess the statistical power to confirm it. Third, the analysis of the present study depended
on the assumptions that the equal correlation in monozygotic and dizygotic twins for
40
environmental experiences of relevance to the trait under study. If the equal environment
assumption is violated, monozygotic environmental similarity rather than higher genetic
similarity could potentially result in higher monozygotic similarity. However, such violations
for GAD were not detected in this sample. Thus, differences in heritability estimates of
neuroticism from twin have been attributed to either non-additive genetic effects or violations
of the equal environment assumption. Finally, unlike the study of Mackintosh et al. (2006),
the neuroticism scores and GAD were collected at one time point, which may confound the
effects of individual specific environment and measurement error, reducing the corresponding
estimates of genetic effects (Hettema et al., 2004).
5.5 Future studies
5.5.1 Sex differences
The present study did not examine whether the sex differences in GAD indicated differences
in its prevalence or in contributions of genetic and environmental factors. However, other
behavioral genetic studies have demonstrated that sex differences in GAD reflect differences
in prevalence rather than in contributions of genetic and environmental influences to liability
for the trait (Hettema et al., 2001; Kendler et al., 2003). Future studies can investigate
whether the underlying factors of GAD are more frequently occur in women than men.
5.5.2 Gene-environment interplay
Brostedt and Pedersen (2003) suggest that people with affective illness are more likely to be
re-exposed to stressful environments. The results of previous studies indicate that women are
more likely to experience negative life events and worry episodes. Those who with higher
score of neuroticism are more likely to report worry situations than those with lower score of
neuroticism. Recent researches have found that individuals report more distortions about the
value of worrying that lead to increased worrying (Borkovec et al., 1999; Davey & Levey,
1999), indicating that pathological worry are not only worry about minor matters, but also
their worrying (Wetherell et al., 2003; Mackintosh et al., 2006).
On the other hand, a relatively new area of analysis is the gene-environment interplay on the
41
development of anxiety and other complex phenotypes (Eley, 2007a). Although there are
some studies related to depression, relatively few studies of anxiety have investigated this
kind of interplay. Heath et al. (1998) firstly reported an interaction between marriage-like
status and genetic influence on depression in women. There was a strong role of genetic on
depression scores of women those who over 30 years and were not in a marriage-like situation.
More recently, another adolescent female twin study demonstrated that genetic influences on
anxiety could increase sensitivity to negative life events (Silberg et al., 2001). With increasing
levels of negative life events or maternal punitive discipline, Eley (2007a) suggests a rise in
genetic influence on depressive symptoms. Despite of main effects of genes and environment,
the analyses that allow for gene-environment interplay tend to be common over the next
decade. Therefore, future studies can address the possibility of genetic-environmental
correlation in which high levels of neuroticism are more likely to lead to GAD or worry.
6. Conclusion
This study has attempted to detect the genetic and environmental influences shared by
neuroticism and GAD. By using a large population twin data, the study analyzed the
personality traits neuroticism for both MZ and DZ twin pairs, as well as the GAD symptoms.
The results showed that both neuroticism and GAD score for MZ twin pairs were higher than
DZ twins, indicating the genetic factor on neuroticism and GAD. There were sex differences
in prevalence for GAD and in means for neuroticism. The neuroticism scores of women were
significantly higher than that of men whereas men reported worrying less in life time than
women. This study also found significant correlation between neuroticism and GAD.
However, only neuroticism shows a strong correlation in both MZ and DZ twin, no significant
correlations were found in GAD. When applying the bivariate model to data, it showed
substantial evidence for nonshared environmental influences on the liability between
neuroticism and GAD, and no evidence of genetic influences or common environmental
influences. Although the findings were not consistent with previous studies that genetic
influences accounted for the vast majority of the variation in GAD, it provided evidence of
the role of environmental factors. Thus, whether genetic factors have more important role
than environmental factors in GAD remains an open question for future study.
42
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51
APPENDICES
1. GENERALIZED ANXIETY DISORDER
Scales/Items:
Anxiety Disorder
[GADCON]: (continuous variable based on 10 items)
Items: 10 items - Telephone Questionnaire, Section A, Question A85 (a - j).
(How often - over the past 12 months-, you)
a. “were restless because of your worry”
b. “were keyed up, on edge, or had a lot of nervous energy”
c. “were irritable because of your worry”
d. “had trouble falling asleep”
e. “had trouble staying asleep because of your worry”
f. “had trouble keeping your mind on what you were doing”
g. “had trouble remembering things because of your worry”
h. “were low on energy”
i. “tired easily because of your worry”
j. “had sore or arching muscles because of tension”
(pre-condition)
- A respondent answered s/he
: worries “A lot more” than most people (A80a), AND
: worried “Every day, Just about every day, or Most days” (A81), AND
: worries about “More than one thing” (A82), OR has different worries “At
the same time” (A82a)
Coding: 1 most days; 2 about half the days; 3 less than half the days; 4 never
Scaling: [GADCON] was constructed by taking the number of “Most days” responses to the
items.
[GADDX]: (dummy variable based on [GADCON])
= 1 if [GADCON] greater than or equal to “3.”
= 0 otherwise.
52
Source(s):
Wang, P. S., Berglund, P., & Kessler, R. C. (2000). Recent care of common mental disorder in
the United States: Prevalence and conformance with evidence-based
recommendations. Journal of General Internal Medicine, 15: 284-292.
Studies using the scales:
Kessler, R.C., Mickelson, K.D., & Williams, D.R. (1999). The prevalence, distribution, and
mental health correlates of perceived discrimination in the United States. Journal of
Health and Social Behavior, 40, 208-230.
Additional References:
American Psychiatric Association (1987). Diagnostic and Statistical Manual of Mental
Disorders, 3rd edition. Washington, DC: American Psychiatric Association.
Blazer, D.G., Kessler, R.C., McGonagle, K.A., & Swartz, M.S. (1994). The prevalence and
distribution of major depression in a national community sample: The National
Comorbidity Survey. American Journal of Psychiatry, 151, 979-986.
Kessler, R.C., Andrews, A., Mroczek, D., Ustun, B., & Wittchen, H.U. (1998). The World
Health Organization Composite International Diagnostic Interview Short-Form
(CIDI-SF). International Journal of Methods in Psychiatric Research, 7, 171-185.
Wittchen, H.U. (1994). Reliability and validity studies of the WHO Composite International
Diagnostic Interview (CIDI): A critical review. Psychiatric Research, 28, 57-84.
World Health Organization (1990). Composite International Diagnostic Interview, CIDI,
Version 10. Geneva: World Health Organization.
* The above information is from: Kessler et al. (1999).
Notes:
 The disorder is based on the definitions and criteria specified in the third edition-revised
of the American Psychiatric Association’s (APA) Diagnostic and Statistical Manual of
Mental Disorders (DSM-III-R; 1987). A diagnosis of Major Depression requires of period
of at least two weeks of either depressed mood or anhedonia most of the day, nearly every
day, and a series of at least four other associated symptoms typically found to accompany
depression, including problems with eating, sleeping, energy, concentration, feelings of
self-worth, and suicidal thoughts or actions.
 GAD was operationalized in screening versions of the World Health Organization’s
(WHO) “Composite International Diagnostic Interview”, Version 10 (CIDI) (WHO, 1990;
Kessler et al., 1998).
 WHO Field Trials (Wittchen, 1994) and other methodological studies (Blazer et al., 1994)
have documented good test-retest reliability and clinical validity of these CIDI diagnoses.
53
2. PERSONALITY TRAITS
Scales/Items:
Respondents were asked how much each of 30 self-descriptive adjectives described
them (Section F, Question 4, a - dd). The adjectives measure six personality traits as
follows:
Neuroticism [NEUROT]:
4 items; Self-Administered Questionnaire, Section F, Question 4 (c, h, m, s)
Adjectives: Moody, Worrying, Nervous, Calm
Extraversion [EXTRAV]:
5 items; Self-Administered Questionnaire, Section F, Question 4 (a, f, k, w,
aa)
Adjectives: Outgoing, Friendly, Lively, Active, Talkative
Openness to Experience [OPEN]:
7 items; Self-Administered Questionnaire, Section F, Question 4 (n, q, u, v,
y, bb, cc)
Adjectives:
Creative, Imaginative, Intelligent, Curious, Broad-minded,
Sophisticated, Adventurous
Conscientiousness [CONSC]:
4 items; Self-Administered Questionnaire, Section F, Question 4 (d, i, p, x)
Adjectives: Organized, Responsible, Hardworking, Careless
Agreeableness (communion) [AGREE]:
5 items; Self-Administered Questionnaire, Section F, Question 4 (b, g, l, r, z)
Adjectives: Helpful, Warm, Caring, Softhearted, Sympathetic
Agency [AGENCY]:
5 items; Self-Administered Questionnaire, Section F, Question 4 (e, j, o, t, dd)
Adjectives: Self-confident, Forceful, Assertive, Outspoken, Dominant
Coding:
1 A lot; 2 Some; 3 A little; 4 Not at all.
Scaling: [NEUROT], [EXTRAV], [OPEN], [CONSC], [AGREE] and [AGENCY] were
constructed by calculating the mean across each set of items. Items were recoded so
that high scores reflect higher standings in each dimension.
: Scale scores can be constructed by calculating the sum of the reverse-coded values
of the items in each scale.
Psychometrics: (based on the MIDUS RDD sample)
Neuroticism: alpha = .74
Extraversion: alpha = .78
Openness: alpha = .77
Conscientiousness: alpha = .58
Agreeableness: alpha = .80
Agency: alpha = .79
54
Source(s):
Rossi, A.S. (2001). Caring and doing for others: Social responsibility in the domains of
family, work, and community. Chicago: University of Chicago Press.
: Ch. 7. Developmental Roots of Adult Social Responsibility.
Studies using the scales:
Keyes, C.L.M., Shmotkin, D., & Ryff, C.D. (2002). Optimizing well-being: The empirical
encounter of two traditions. Journal of Personality and Social Psychology, 82,
1007-1022.
Lachman, M.E., & Weaver S.L. (1997). The Midlife Development Inventory (MIDI)
Personality Scales: Scale construction and scoring. Technical report.
Staudinger, U. M., Fleeson W. & Baltes, P. B. (1999). Predictors of subjective physical health
and global well-being: Similarity and differences between the United States and
Germany. Journal of Personality and Social Psychology 76, 305-319.
Additional References:
Bem, S.L. (1981). Bem Sex-Role Inventory Manual. Palo Alto, CA: Consulting Psychologists
Press.
Goldberg, L.R. (1992). The development of markers for the Big-Five factor structure.
Psychological Assessment, 4, 26-42.
John, O.P. (1990). The “Big Five” factor taxonomy: Dimensions of personality in the natural
language and in questionnaires. In L.A. Pervin (Ed.), Handbook of personality theory
and research, (pp. 66-100). New York: Guilford.
Trapnell, P.D., & Wiggins, J.S. (1990). Extension of the Interpersonal Adjective Scales to
include the Big Five dimensions of personality. Journal of Personality and Social
Psychology, 59, 781-790.
Notes:
 Adjectives were selected from existing trait lists and inventories (Bem, 1981; Goldberg,
1992; John, 1990; Trapness & Wiggins, 1990). Also, some items were generated by
Margie Lachman and Alice Rossi.
 A Pilot Study was conducted in 1994 with a probability sample of 1000 men and women,
age 30-70 (574 valid cases were usable for item analysis). Items with the highest item to
total correlations and factor loadings were selected for MIDI. Forward regressions were
also run to determine the smallest number of items needed to account for over 90% of the
total scale variance. Many of the negatively worded items (unemotional, unreliable,
unsophisticated, unsympathetic, shy, unsociable) were dropped due to low variance.
New items were added to increase reliabilities on some scales.
55