This chapter explores childhood mood and anxiety
disorders within a transactional model. Genetic, prenatal, and
postnatal history will be discussed in light of how these factors
interact with neuropsychological, executive, cognitive, perceptual,
and memory functioning. Moreover, the impact these factors have on
the child's functioning (i.e., family, school, and social
interactions) will be discussed within a transactional framework;
that is, social and familial factors play a role in environmentally
induced mood and anxiety disorders which, in turn, interfere with
social interactions and interpersonal well-being.
Mood Disorders
Although some believe that internalizing
disorders in children are more closely related to brain dysfunction
than externalizing disorders (Tramontana & Hooper,
1989), there is a paucity of
published research to support this hypothesis. As with all
taxonomies, the distinction between externalizing and internalizing
disorders becomes blurred in real practice with children and
adolescents who meet criteria for both diagnoses. For example, this
picture is complicated by the finding that mood and anxiety
disorders co-occur with disruptive behavior disorders (Jensen,
Martin, & Cantwell, 1997;
Jensen et al., 2001; Semrud-Clikeman & Hynd, 1991). Approximately 25 to 40 percent of
children with ADHD also experience depression and/or anxiety
disorders (Barkley, 2006). Spencer, Wilens, Biederman, Wozniak, and
Harding-Crawford (2000) found
that 38 percent of children seen in clinics for ADHD had comorbid
major mood disorders (MMD), and these children had a worse outcome
than children with either disorder alone. Moreover, children with
ADHD have a significantly higher tendency to have parents with
diagnoses of anxiety disorder and/or depression than typically
developing children or children with other psychiatric diagnoses.
Thus, it is often difficult to obtain a sample of children with
only mood disorders or internalizing symptomatology, and research
that has done so is rare (Kusche, Cook, & Greenberg,
1993).
Research investigating the neuropsychological
correlates of these disorders has exploded in the past decade. The
following sections are not meant to be exhaustive of all mood
disorders. The disorders that are included in this review are major
depression and bipolar disorders. See Mash and Barkley
(2006) for a more thorough review
of childhood psychopathologies and treatment options.
Childhood Depression
Childhood depression as defined by Diagnostic and
Statistical Manual of Mental Disorders (4th ed. - text revision;
DSM-TR) requires that the child must have experienced the following
symptoms for six months or longer nearly every day: sad or
dysphoric mood (in children, mood can be irritable), loss of
interest in previously enjoyable events, significant weight gain or
loss, sleeping problems (e.g., too little or too much sleep), lack
of energy; excessive guilt or feelings of worthlessness, difficulty
with concentration, and thoughts of death or suicide (APA, 2000, p.
356). In the school setting, children with depression may appear
withdrawn, resist social contact, at times refuse to attend school
and show academic difficulties.
Depression in childhood may last for years and
extend into adulthood (Reinherz, Gianconia, Hauf, Wasserman, &
Paradis, 2000; Weissman et al., 1999); may lead to suicidality, and may be more
widespread than previously recognized (Hammen & Rudolph,
2003). Silver (1988) reported that a diagnosis of depression
was present in 17.9 percent of all children under age 18 admitted
to psychiatric hospitals. Overall prevalence for depression has
been estimated to be 14% in adolescents, with an additional 10
percent with minor depression (Avenenoli, Knight, Kessler, &
Merikangas, 2007; Kessler & Waters, 1998; Lewinson, Hops,
Roberts, Seeley, & Andrews, 1993); while, the full-fledged
diagnosis of major depression among all children ages 9 to 17 has
been estimated at 5 percent (Shaffer et al., 1996). Incidence rates
of depression are lower in younger children (Anderson, Williams,
McGee, & Silva, 1987; Hankin et al., 1998); however, children
who present with depression at early age appear to be at greater
risk for a host of serious problems later in life including more
impaired social and occupational adjustment, a more negative view
of life, increased rates of life-long depression, more medical and
psychiatric comorbidities, increased suicide attempts, and greater
and more severe symptoms with recurring episodes of depression
(Zisook et al., 2007). There are no gender differences in rates of
depression until the middle to late teen years (Hammen &
Rudolph, 2003). In fact gender
ratios are basically equal before adolescence and after age 30
years (Satcher, 1999).
Comorbidity
Depression in childhood has been found to
co-occur with anxiety, other mood disorders and disruptive behavior
disorders. Depression has been found to occur concurrently with
anxiety disorders (Angold, Costello, & Erkanli, 1999; Munir, Biederman, & Knee,
1987; Strauss, Last, Hersen, &
Kazdin, 1988), conduct disorders
(Alessi & Magen, 1988), and
attention-deficit hyperactivity disorder (Biederman, Baldessarini,
Wright, Knee, & Harmatz, 1989;
Jensen et al., 1997; Steingard,
Biederman, Doyle, & Sprich Buckminster, 1992). It has been
hypothesized that children with a dual diagnosis will evidence a
more severe disorder and have a poorer prognosis (Kovacs,
1989).
Although Biederman, Munir, Keenan, and Tsuang
(1991) found that depression
co-occurs with attention-deficit hyperactivity disorder (ADHD) at
approximately an incidence level of 30 percent to 40 percent,
Jensen et al. (2001) reported
lower rates of comorbid affective disorders (between 1% to 7.4%)
for children in a large scale study of ADHD treatments. In a review
of comorbidity in childhood disorders, Pliszka, Carlson, and
Swanson (1999) report that
incidence rates of ADHD and depression vary from 0 percent to 38
percent depending on the study type (epidemiological versus
clinical), with rates of comorbidity highest for the clinic samples
(32% to 38%). Pliszka et al. suggest that children with depression
and ADHD may share some common genetic mechanisms, but more
research is needed to resolve this issue.
It is crucial that the child be evaluated for
other disorders as well as for the presenting symptoms of
depression. There may be a tendency to develop an affective
disorder, and unique environmental and familial factors mediate how
the disorder is expressed in individual children. Although work in
the area of comorbidity is progressing, there are few studies that
have evaluated dual-diagnosed disorders outside of a clinical
sample.
Genetic and Family Factors
Family studies of depression show strong
heritability rates, and clear evidence that adult depression runs
in families (Sullivan, Neale, & Kendler, 2000). The percentage of persons with major
depression who have been found to have family members with
depression is six times greater than those without depression
(Downey & Coyne, 1990). Twin
studies have found a 65 percent concordance rate for affective
disorders for monozygotic twins versus 14 percent for dizygotic
twins. Genome-wide linkage studies investigating affective disorder
susceptibility have found association in numerous chromosomal
regions (Venken et al., 2005).
While these findings suggest a genetic risk factor for depression,
environment and biology may interact in this disorder (Teeter
Ellison et al., 2009). Mothers who are depressed may interact
differently with their children and an insecure attachment may
occur (Quay et al., 1985). Such
insecure attachment is a significant risk factor in the development
of childhood depression (Hammen & Rudolph, 2003).
Dawson, Grofer Klinger, Panagiotides, Hill, and
Spieker (1992) found that infants of mothers with depression had
more activation in the right versus left frontal lobe, even when
placed in neutral conditions. This is considered to be an atypical
pattern of activation, and is also found in subjects who are in
remission for depressive symptoms (Henriques & Davidson,
1990). What is not clear is
whether the patterns of brain activity are the consequence of the
environmental impact of a depressed episode or episodes, or if a
biologically mediated depressive tendency is present (Teeter
Ellison et al., 2009). Thus, depression, as with many other
disorders, appears to have multiple facets that likely interact to
produce the syndrome.
The STAR*D-Child Sequenced Treatment Alternatives
to Relieve Depression, the nation’s largest NIMH-funded study
investigating the treatment of childhood depression, investigated
151 child-mother pairs to determine the effects of maternal
depression on children (Weissman et al., 2006). In the STAR*D-Child study, 11 percent of
children whose mothers were successfully treated for depression no
longer met criteria for depression and one-third of children went
into remission (Weissman et al., 2006). Further, only 12 percent of children
went into remission if their mothers remained depressed. This study
provides insight into the gene by environment interaction in the
transmission of depression, and that successful treatment of
maternal depression serves to protect vulnerable children.
Brain Anatomy and Neurochemistry
Current theories of depression, based on findings
from neuroanatomical as well as functional studies, implicate
prefrontal and striatal systems that regulate limbic and deep brain
structures that ultimately modulate emotions (Drevets,
2001a, 2001b). Drevets (2001a, 2001b)
further suggests that these complex neural networks underlie the
cognitive, motivation, and behavioral features of depression. In a
review of PET and fMRI studies, Phan, Wager, Taylor, and Liberzon
(2002) found that there are
separate brain regions involved in different aspects of emotions
(i.e., emotional responses, processing stimuli that illicit
emotional responses). The basic brain regions implicated in
emotions are: (1) prefrontal cortex processes emotions; (2) the
amgydala processes fear; (3) subcallosal cingulated regions are
involved with feelings of sadness; (4) occipital lobes and amygdala
are involved with emotional response to visual stimuli; (5)
anterior cingulate and insula involved with emotional recall and
imagery, and (6) anterior cingulated and insula involved with
emotional tasks that also have a cognitive component (Phan et al.,
2002).
Much of the research investigating the
neuroanatomical, functional and neurochemical basis of depression
has been conducted on adults, with few studies completed on
children (Hammen & Rudolph, 2003). Structural differences have been found in
the volume of left frontal regions and regions of the basal
ganglia, particularly in the caudate and putamen, and enlarged
lateral ventricles in late onset depression (Pennington,
2002). In a summary of
neuroimaging research, Pennington reports two major findings: (1)
decreased blood flow to frontal lobes and to the cingulate gyrus,
primarily in the left hemisphere, and (2) increased flow in the
amgydala. Frontal lobe blood flow is normalized with antidepressive
medications, so that top-down control (frontal regions) is exerted
over bottom-up (amygdala) components of the emotional regulation
system. See Pennington for more details.
In an effort to better understand the influence
of the frontal circuits, Hasler et al. (2008) investigated PET scans of unmedicated
patients with a history of depression that were in remission. When
given drugs that depleted dopamine and norepinephrine, depression
symptoms reappeared while control subjects with no prior history of
depression had only minor changes in mood. Dopamine inhibits
emotional circuits and, when depleted, this braking system does not
properly exert control over mood. Increased brain activation
patterns showed that the emotional circuit was not actively
inhibited by higher brain regions. The authors suggest that even
when in remission, patients with depression are vulnerable to
symptoms when dopamine and norepinephrine are reduced.
In general, symptoms of psychiatric disorders
affecting mood stability, depression, apathy, obsessive-compulsive
thoughts, and mania are related to various frontal-subcortical
circuits (FSC) including the dorsolateral prefrontal-subcortical
circuit (DLPFC), the superior medial frontal (SMF), the lateral
orbitofrontal-subcortical circuits (OFC), and the medial OFC (Chow
& Cummings, 2007). These large
brain circuits, with complex connections from the frontal lobes and
other brain regions, are rich in neurotransmitters including
dopamine, serotonin, and norepinephrine. Emotional, affective and
social behaviors are affected by dysregulation of these various
frontal-subcortical circuits. Bipolar disorders appear to have
abnormal functions in major FSC systems (DSM-IV TR). fMRI studies
show reduced DLPFC activity during depression, with reduced
superior frontal and OFC during manic states (Haldane &
Frangou, 2004). Mood stabilizers
normalize these activation patters. See Chow and Cummings
(2007) for an in-depth discussion
of the frontal-subcortical circuits.
PET studies also have investigated brain
metabolic changes in frontal-limbic regions in control subjects.
Decreased metabolic activity was found in the “dorsolateral
prefrontal cortex, the dorsal and posterior cingulated gyrus, and
the inferior parietal lobe” and “increases in orbitofrontal
prefrontal cortex, the dorsal and hippocampus” (see Pliszka,
2003, p. 215). These differences
are similar to the metabolic imbalances found in untreated patients
with depression.
Although research on children is limited in
scope, MRI research suggests that the frontal lobes are implicated
in the pathogenesis of early-onset depression (Steingard et al.,
1996). Data from neuroimaging
studies of childhood depression report abnormalities in the
hippocampus and amygdala. Children with depression have
significantly smaller left and right amygdala volumes, compared to
non-affected children (Rosso et al., 2005). White matter hyperintensities, which are
areas of possible increased water density, have been found in the
frontal regions of children with unipolar depression or bipolar
disorders (Lyoo, Lee, Jung, Noam, & Renshaw, 2002).
Current neurological theories suggesting
neurotransmitter imbalances have led researchers to focus on the
hypothalamic-pituitary-adrenal (HPA) axis, as this system appears
to be dysregulated in adults with depression (Hammen & Rudolph,
2003). The HPA system regulates response mechanisms in stress
situations. Adults with depression show three major abnormalities:
“higher basal cortisol, abnormal cortisol regulation as indicated
by the dexa-methasone suppression test (DST) and abnormalities of
corticotrophin-releasing factor” (Hammen & Rudolph, 2006, p
246). Research findings with children and adolescents have been
less consistent, particularly when basal cortisol levels and CRR
infusion are measured; however, non-suppression on the DST is
similar for both children and adults (Birmaher et al,
1996; Kaufman, Martin, King, &
Charney, 2001). See Hammen and
Rudolph (2006) for a detailed discussion of the regulatory role of
the HPA system.
Neuropsychological Correlates: Cognitive, Perceptual, Attention and Memory Functioning
Cognitive impairments, particularly difficulties
in attention, concentration and alertness, have been found in
individuals with depression and are likely related to dysfunction
of the prefrontal cortical and striatal systems that regulate
limbic and brainstem regions (Drevets, 2001a, b; Pliszka,
2003). In addition, Mayberg
(1997) found that positive
medication response increased activity in the anterior cingulate
gyrus (limbic structure) which is important in “executive
attention, recruiting effort for a task” (Pliszka, 2003, p. 215).
In a study comparing internalizing-only,
externalizing-only, and mixed symptoms groups, Kusche et al.
(1993) evaluated found
neuropsychological weaknesses in the clinical groups. Although all
groups performed more poorly than a control group, the mixed
symptom group showed the most severe deficits. The
internalizing-only group was the closest to the control group and
showed the least amount of neuropsychological impairment, while the
externalizing-only group showed moderate amounts of impairment
(Teeter Ellison et al., 2009).
Family and Home Factors
Individuals with major depression are six times
more likely to have family members with depression than those
without depression (Downey & Coyne, 1990; Hammen, 1990). While these findings suggest a genetic
risk for depression, environment and biology interact to express
this disorder. Mothers who are depressed may interact differently
with their children resulting in insecure attachment (Quay et al.,
1985). Such insecure attachment
has been found to be a significant risk factor in the development
of childhood depression (Cummings & Cicchetti, 1990).
A number of family factors influence the
development of depression in children and adolescents, including
dysfunctional parent-child relations, parental psychopathology, and
hostile-rejecting family dynamics (Hammen & Rudolph, 2006). The
mechanisms by which family and contextual factors impact childhood
and adolescent depression are complex and bidirectional; that is,
parental difficulties influence the child’s well-being while the
child’s difficulties have negative influences on parents and family
functioning. The pathways for transmission are multidimensional,
but often persistent, interpersonal difficulties are at the center
of the problem (Hammen & Brennan, 2001). Parenting difficulties and impaired
attachment also seem likely contributors to the development of
childhood depression. Dawson and colleagues further suggest that
impaired mother-child interactions alter the development of brain
circuits in ways that place children at risk for emotional
difficulties and depression (Dawson, Frey, Panagiotides, Osterling,
& Hessl, 1997).
While having a parent with depression is one of
the most predictive factors for childhood and adolescent
depression, adverse psychosocial factors also influence the
development of depression (see Hammen & Rudolph, 2003 for a review). Adverse events include
stressful life events, impaired parent-child relationships, and
marital discord. Furthermore, it is interesting to note that
Silberg et al. (1999) found there
is an increased heritability of depression in adolescent girls,
where genetic vulnerabilities interacted with environmental factors
including stressful life events. The fact that familial and
environmental factors interact has led to a number of cognitive and
psychosocial theories to explain depression (e.g., negative
cognitive schemas, depressive attributional styles,
diathesis-stress models, etc.). See Hammen and Rudolph
(2003) and Hankin and Abela
(2005) for an in-depth review of
depression.
Implications for Assessment
Depression has been found to affect cognition,
memory and concentration which indirectly impact neuropsychological
and psychological performance (Teeter Ellison et al., 2009). Slower
response and completion times, particularly on speeded tasks, may
be problematic. For example, a child or adolescent with major
depression may have decreased attention to detail or lowered
reaction speed which, in turn, reduces scores on performance
subtests of cognitive-intellectual tests as well on timed tasks
such as Trails A and B, the Tactual Performance Test, Stroop, and
others.
In addition to attention problems, depressed
clients experience problems with new learning (Caine,
1986). When the same information
is presented in a very structured format, learning improves
dramatically (Weingartner et al., 1981). For something to be learned it must
first be attended to; thus, if attention is deficient poor
performance follows (Cohen, Weingarten, Smallberg, & Murphy,
1982). Retrieval deficits are also
frequently seen in depressed clients (Firth et al., 1983). Problems in both remote and newly
acquired information are found. These difficulties ameliorate after
recovery from depression (Caine, 1986).
Children with depression may present in much the
same manner as those with medical problems. The astute clinician
will recognize such overlap and seek to differentiate, if at all
possible, between the two types of disorders. Clues for
differentiation may be found in specific areas of the child's
social functioning/ relationships (e.g., isolation, rejection,
withdrawal, etc.) and emotional adjustment/well-being (e.g.,
overwhelming feelings of sadness; prolonged, chronic feelings of
sadness/depression, etc.). In cases where such a distinction is not
possible, retesting should be pursued after a trial of medication
and/or therapy is attempted.
Diagnosing depression involves gathering
information about the client and matching this information to the
DSM-IV criteria for a diagnosis of depression. It is recommended
that the diagnosis be made on the basis of a multi-informant,
multi-method procedure. Although multi-method procedures provide
the best information, it is important to recognize that poor
concordance has been found between raters (Semrud-Clikeman &
Hynd, 1991). Particularly
important is the finding that the child/adolescent is a reliable
source of information about his or her subjective feelings of
depression (Kazdin, 1987).
Therefore, an assessment for suspected depression should include
information gathered directly from the child or adolescent as well
as information from teachers and parents.
Clinical
interviews. Clinical interviews are one of the most
sensitive methods of assessment (Semrud-Clikeman, Bennett, &
Guli, 2003; Teeter Ellison et
al., 2009). Interviews allow information to be gathered from
multiple sources, answer queries about the severity, duration, and
frequency of depressive symptoms more fully, and provides a
comparison of the child or adolescent's feelings with his or her
developmental and mental age.
Self-Report
Scales. The Children's Depression Inventory (CDI; Kovacs,
1992) is the most frequently
utilized rating scale and has had the greatest amount of research.
The CDI consists of 27 items with three alternatives to each
question measuring severity of symptoms (the higher the number, the
more severe). The CDI may be best used as a screening measure,
after which further diagnosis may rest on clinical interviews and
other rating scale measures (Semrud et al., 2003).
Other self-report scales include the Reynolds
Child Depression Scale (Reynolds, 1989), the Children's Depression Rating
Scale-Revised (Pomanski et al., 1984), the Hopelessness Scale (Kazdin, French,
Unis, Esveldt-Dawson, & Sherick, 1983), the Depression
Self-Rating Scale (Birleson, 1981), and the Hamilton Depression Rating Scale
(Hamilton, 1967). Although these
scales may also be used, the results may be redundant with the CDI,
and all of these measures take a longer time to administer. See
Semrud et al. (2003) for an in-depth discussion of the assessment
of childhood depression.
If depression is suspected, use of both the
structured interview and the CDI can most efficiently and reliably
answer the diagnostic questions posed to the examiner. In cases
where difficulty remains in diagnosis due to an unwillingness by
the child or adolescent to discuss his or her feelings, projective
techniques such as the Rorschach, Roberts Apperception Test, or
Thematic Apperception Test should be considered. These measures are
beyond the confines of this book, and the interested reader is
referred to Allen and Hollifield (2003) and DuPree and Prevatt
(2003). If an omnibus rating scale is indicated, clinicians are
advised to use either the Behavioral Assessment Scale for Children
II (BASC-II; Reynolds & Kamphaus, 2004) or the Achenbach System
of Empirically Based Assessment (ASEBA; Achenbach & Rescorla,
2001).
Implications for Intervention
Treatment of depression must be conducted by
professionals with training and sensitivity to the subjectively
felt distress of the child or adolescent. Disturbances in
concentration, feelings of guilt and worry, self-destructive
thoughts, and social withdrawal are extremely painful and have
repercussions for present and future adjustment. Relapses following
treatment or poor progress in the initial stages of treatment may
exacerbate the disorder and prolong the subjective feelings of
hopelessness, helplessness, and sadness (Stark et al.,
2006). Treatment of depression
often combines pharmacotherapy and Cognitive Behavioral Therapy
(CBT).
Pharmacotherapy. Knowledge of the
etiology of depressive disorders has been expanded by examining
neurotransmitter systems affected by antidepressant medications.
Antidepressant medications affect the brain systems in which the
primary neurotransmitters are norepinephrine and for serotonin.
Antidepressants alter these functional systems by increasing or
decreasing the release of neurotransmitters at the presynapse or by
enhancing neurotransmitter reuptake mechanisms at the
postsynapse.
Since the first edition of this book, NIMH funded
a large scale study of treatment for adolescent depression
(Treatment for Adolescents with Depression Study Team [TADS],
2004). In this hallmark study 439 adolescents with depression,
between 12–17 years of age, were randomly assigned to three
treatment groups: medication alone, Cognitive-Behavioral Treatment
(CBT) alone, and medication with CBT. Combined treatments were
superior to both medication and/or CBT alone treatment. Suicidal
ideation was reduced in all treatment groups. It was necessary to
monitor adverse effects (i.e., gastrointestinal track events,
sedation, and insomnia) for medicated youths. NIMH also funded two
other large scale studies of treatment resistant depression. See
Chapter 17 for a more in-depth discussion of results from the
Treatment for Adolescents with
Depression Study (TADS), STAR*D Sequenced Treatment Alternatives to
Relieve Depression, and the Treatment Of Resistant Depression In
Adolescents, TORDIA.
Clinicians suggest that given the long-term
course of depression, the possible morbidity, and the psychic pain
experienced, medication is warranted if the child shows a severe
form of depression, psychosocial treatment has not been successful,
and hospitalization is considered. Frequent communication between
home, school, and physician is recommended, particularly with
regard to assignment completion and rate of social interaction.
Therefore, it is important that the child's progress be closely
monitored, consultation between school, home, and physician be
maintained, and psychosocial interventions be continued.
Cognitive Behavioral Therapy for Depression
Cognitive Behavioral Therapy (CBT) and
interpersonal therapy (IPT) are among the most common forms of
therapy for adolescents with depression (Stark et al.,
2006). These approaches have much
in common and include strategies to improve social interactions,
emotional regulation, and social skills. Cognitive-behavioral
treatments include problem solving therapy, training in
self-monitoring, and self-control training.
While CBT is considered to be a “promising
practice,” more research is needed to determine its efficacy.
Initial research suggests that a number of therapies including CBT
may be helpful for adolescents with depression (Michael &
Crowley, 2002). See Stark et al.
(2006) for an in-depth review of
research on CBT and IPT.
NIMH is currently funding a multi-year study to
determine the efficacy of CBT in girls with depression (ACTION;
Stark et al., 2006). Components
of the study target goal setting, affective education, coping
skills training, problem solving training, cognitive restructuring,
and building a positive sense of self. There is some evidence that
CBT can be an effective treatment for adolescents with depression,
particularly when combined with medication. The TADS study showed
that a combination of Prozac with CBT produced the most favorable
results when weighing both risks and benefits for adolescents with
major depression (March, Silva, & Vitiello, 2006).
In summary, the efficacy of pharmacological
intervention for childhood depression is not clear at this time.
The emergence of studies that utilize psychosocial intervention
indicates improvement when cognitive-behavioral treatment is used.
As controlled studies of pharmacological and therapeutic techniques
appear, the field may well discover the most efficacious methods of
treatment. Major depression may be related to environmental factors
as much as to biological factors. Treatment of familial
difficulties along with multimodal child treatment may be the best
avenue for success.
Pediatric Bipolar Disorder
Mood disorders also include two forms of bipolar
disorder: Bipolar I and Bipolar II (APA, 2000). The essential
features of the bipolar disorders are recurring bouts of mania in
addition to bouts of depression. Approximately 10 percent to 15
percent of adolescents with recurring major depression are later
diagnosed with Bipolar I disorder (APA, 2000). Bipolar disorders
(BPD) are rare in children, with greater frequency of occurrence
found in adolescents. Early onset bipolar disorders appear to have
more severe problems including higher rates of anxiety and
substance abuse disorders, suicide attempts and recurrences (Perlis
et al., 2004).
There is a great deal of controversy concerning
the diagnosis of childhood bipolar disorders (McClellan, Kowatch,
& Findling, 2007). There has
been a 40-fold increase in the diagnosis of BPD in children and
adolescents, and it is unclear whether children display all the
same adult symptoms that are outlined in DSM-IV. Children and
adolescents may have high rates of irritability and impulsivity,
but it is not certain that these are separate from other broader
mood disorders rather than BPD per se. Although 65 percent of
adults with BPD report having symptoms in adolescence, it is
unclear whether children currently diagnosed with BPD will continue
to have the disorder in adulthood. Another of the major diagnostic
issues is the overlap of symptoms of BPD with ADHD, where as many
as 60 percent of children have a dual diagnosis (Dickstein et al.,
2004). Others are concerned that diagnosis is difficult because
children present with a number of symptoms that are difficult to
differentiate from other schizo-affective, schizoid personality and
other mood and anxiety disorders (Gorwood, 2004). Geller and Tillman (2005) have established conservative diagnostic
criteria for childhood BPD in order to improve the validity of the
disorder.
Bipolar and major depressive disorders differ not
only in terms of symptomatology, but also in terms of genetic
contributions (APA, 2000; Hammen & Rudolph, 2006). Bipolar
depression is likely a genetically based disorder, whereas major
depression is related to both genetic and environmental
contributions. Torgesen (1986)
studied 151 same-sex twins for incidence of bipolar and major
depression, and found that 10 had bipolar depression, 92 had major
depression, 35 had dysthymia, and 14 had adjustment disorder with
depressed mood. Torgesen reported a 75 percent concordance rate for
bipolar depression in monozygotic twins and close to 0 percent
concordance in dizygotic twins. Furthermore, data indicated a 27
percent concordance rate for major depression in monozygotic twins
and a 12 percent rate for dizygotic twins, with a 40 percent
concordance rate for psychotic depression in monozygotic twins,
compared to 15 percent in dizygotic twins. Torgesen (1986) concluded that major depression and
bipolar disorders are two different disorders, with bipolar and
severe (i.e., psychotic) depression more likely to be genetically
transmitted.
Dickstein et al. (2004) found that children with bipolar disorder
show deficits in attentional set shifting and visuospatial memory
tasks from the Cambridge Neuropsychological Test Automated Battery.
Children with bipolar depression also experience more difficulty on
performance-based tasks rather than on verbal measures (Dencina et
al., 1983).
Typical first line treatments for BPD include
mood stabilizers and atypical antipsychotic medication (McClellan
et al., 2007). Behavioral
therapies may also be used to address violent outbursts and
violence in some adolescents with juvenile mania. The National
Institute of Mental Health is funding the Systematic Treatment
Enhancement Program for Bipolar Disorder (STEP-BD) study to follow
a cohort of children diagnosed with BPD. Additional studies are
also underway to determine treatment efficacy of early onset mania,
and to examine the effectiveness of family-based treatments and
medications (see NIMH Bipolar Facts, 2008).
Anxiety Disorders
For purposes of this chapter, Generalized Anxiety
Disorder, which includes Overanxious Disorder of Childhood as
defined by DSM-IV-TR (APA, 2000), will be discussed. The essential
features of GAD are excessive anxiety and worry or apprehension
that is difficult to control. Anxiety causes considerable distress
that impairs social, academic and other important daily functions.
One of six symptoms must be present to meet criteria for GAD:
restlessness or feeling keyed up, easily fatigued, difficulty
concentrating, irritability, muscle tension, and sleep disturbance
(APA, 2000, p. 476).
Additional types of anxiety disorders found in
childhood include separation anxiety disorder, social phobia, panic
disorder, obsessive-compulsive disorder and posttraumatic stress
disorder. Obsessive-compulsive disorder (OCD) is diagnosed when
recurrent and distressing thoughts or drive lead to a repetitive or
irrational behavior, which in turn causes anxiety when resisted
(APA, 2000). OCD typically begins in adolescence or early
adulthood, but it can begin in early childhood (APA, 2000; Spence,
Rapee, McDonald, & Ingram, 2001). Early onset of anxiety increases the
risk for comorbidity and, if left untreated, anxiety may persist
into adulthood (Albano, Chorpita, & Barlow, 2006).
Posttraumatic stress disorder (PTSD) is
characterized by anxiety symptoms following an emotionally
distressing event that is unusual in normal human experience. The
child may have been exposed to a variety of traumatic events
including war, natural disaster, actual or threatened death,
serious injury or physical threat to self or others (APA, 2000).
Responses to the trauma may include intense fear or horror,
helplessness, frightening nightmares, acting or feeling that the
event will reoccur (i.e., hallucinations, flashbacks), intense
psychological distress, and physiological reactions to events that
resemble the trauma. Individuals with PTSD seek to avoid stimuli
that are similar to the trauma which may result in a lack of
interest in activities, inability to recall the event, restricted
range of emotions (blunting, inability to feel love), feelings of
detachment, and a sense of hopelessness as it relates to the
future.
Incidence
Prevalence rates for childhood anxiety disorders
estimated from data gathered through the 2003 National Survey of
Children's Health (NSCH) suggest that 2–4 percent of children have
anxiety or depression (Blanchard, Gurka, & Blackman,
2006). In the National Comorbidity
Replication study (NCS-R), Shear, Jin, Ruscio, Walters, and Kessler
(2006), reported prevalence rates
of 4.1 percent of lifetime separation anxiety in children and 6.6
percent in adults, with 1/3 of the children showing persistent
anxiety into adulthood.
Blanchard et al. (2006) found that anxiety and depression maybe
under-diagnosed in children where 36 percent of parents surveyed
indicated concerns over anxiety or depression. The study also
revealed that emotional problems were more frequent in school-aged
versus preschool children. In a longitudinal study of a community
sample of children aged 9–13 years of age participants were
followed until the age of 16 years. Costello, Mustillo, Erkanli,
Keeler, and Angold (2003) found
that anxiety disorders (social anxiety and panic disorders)
increased over the study period.
Comorbidity
Children with generalized anxiety disorders are
at high risk to develop concurrent mood disorders, and other
anxiety disorders (APA, 2000). In a longitudinal study of
individuals living in New Zealand, Moffitt et al. (2007) reported that 72 percent of individuals
with lifetime anxiety had a history of depression. In adulthood, 12
percent had comorbid generalized anxiety disorders with major
depression, which placed them at risk for significant mental health
needs including psychiatric medication (47%), attempted suicide
(11%), sought mental health services (64%), and high recurrence
rates of generalized anxiety (47%) with major depression
(67%).
Externalizing behavioral difficulties have also
co-occurred with anxiety disorders, including ADHD (Jensen et al.,
2001). In addition individuals
with generalized anxiety disorders are at risk for substance abuse
disorders (APA, 2000). Costello et al. (2003) also reported that there was considerable
continuity of having one diagnosis than another over time,
particularly from depression to anxiety, depression to anxiety, and
conduct disorder with anxiety to substance abuse.
The neuropsychological differences between
children with comorbid internalizing and externalizing disorders
(i.e., conduct disorders and anxiety or depression) and those with
co-occurring internalizing disorders (i.e., anxiety and depression)
have not been investigated (Teeter Ellison et al., 2009). Children
with various comorbid psychiatric disorders may well have
underlying weaknesses in neuropsychological functions that
ultimately affect treatment strategies and outcomes. Further
research is needed in this area to more fully determine if there
are unique characteristics for various combinations of comorbid
disorders, and to determine how comorbidity affects treatment
outcome. See the discussion of Implications for Treatment for a
more detailed discussion.
Genetic Factors
Research on the genetic basis of anxiety
disorders has significantly increased over the past 15 years
(Albano et al., 2006). Although
anxiety and other mood disorders typically run in families,
researchers have not isolated any specific gene area or region for
anxiety (Pliszka, 2003). Gratacos
et al. (2001) have found that
chromosome 15 may be involved with several anxiety disorders (i.e.,
panic, agoraphobia, social and simple phobia). Apparently OCD
differs from the other anxiety disorders due to its high
co-occurrence with tic disorders. Pliszka (2003) suggests that tic disorders and OCD have
been found in individuals recovering from encephalitis, and other
autoimmune diseases such as strep throat. “Pediatric autoimmune
neuropsychiatric disorders associated with strep” or (PANDAS) have
been reported. Pliszka suggests that genetic vulnerability may be
to autoimmune weaknesses rather than to OCD.
Twin studies report that heritability estimates
for anxiety disorders range from 30 percent to 40 percent (see
Kendler, Neale, Heath, & Eaves, 1992, 1993).
Studies utilizing twins have found a high concordance rate for
anxiety disorder in identical twins (Torgesen, 1986). There is a tendency for children who are
behaviorally inhibited at an early age to have parents who are
under treatment for panic disorder and agoraphobia (Rosenbaum,
1988). On follow-up these children were at increased risk for
anxiety disorders in late adolescence and early adulthood
(Rosenbaum, 1988).
It appears that biological dispositions may
interact with environmental stressors and result an increase in
anxiety disorders in children born to parents who have been
diagnosed as affectively disordered. A review of twin studies by
Rapoport (1986) found a
concordance of 80 percent for obsessive-compulsive disorder in
monozygotic and dizygotic twins. This high rate of concordance is
suggestive of genetic transmission and needs to be studied further.
This area of study is just beginning, and further information is
needed to determine the relationship that genetics and environment
has on the risk factor of later developing an anxiety
disorder.
Brain and Neurochemistry
Pennington (2002) discusses the brain mechanisms underlying
anxiety and explains the shift from single neurotransmitter
theories (i.e., norepinephrine) to more complex theories involving
the amygdale and the hypothalamic-pituitary-adrenal axis (HPA), and
other neurotransmitters (serotonin, GABA, corticotrophin-releasing
factor, and cholecystokinin). While there are few neuroimaging
studies, Davidson, Abercrombie, Nitschke, and Putman
(1999) report that greater
amygdala and right prefrontal activation patterns were found in
children with anxiety compared to nonanxious controls.
According to Teeter Ellison and Nelson
(2008), negative emotions and
emotional deprivation affect stress-responsive systems,
particularly the sympathetic adrenal medullary (SAM which is the
fight/flight system) and the HPA [counteracts or suppresses acute
stress reactions (Adam, Klimes-Dougan, & Gunnar, 2007)]. While
hormones in the HPA system (cortisol) sustain brain development,
cortisol can also be detrimental to the developing neurons. “More
recently, the link between early experience, brain development, and
both normal and disordered functioning has become increasingly
evident and better understood, due largely to evidence that early
experience (especially deprivation experiences) reduces neural
plasticity to stress experienced later in life (e.g., Mirescu,
Peters, & Gould, 2004) and
even permanently silences genes critical to the regulation of the
stress response (e.g., Weaver et al., 2004)” (Adam et al., 2007, p. 266). Cortisol levels change at
different stages, first when anticipating the stressor, second when
reacting to the stressor, and finally recovering to pre-stress
levels. Cortisol responses can be buffered with secure early
attachment to the primary caregiver, whereby the HPA system becomes
under social regulation (Teeter Ellison & Nelson,
2008).
Positive mother-child interactions, with
responsive care buffer cortisol levels, ultimately reduce the
distress infants feel, while unresponsive, insensitive interactions
have negative affects on the infant’s stress responses (Teeter
Ellison & Nelson, 2008).
“Although parents can clearly serve as buffers on the effects of
social environments on young children’s HPA-axis, they can also
serve as a profound source of social strain if their behavior is
threatening or fails to provide appropriate comfort” (Adam et al.,
2007, p. 274).
Long-term alterations of the HPA system often
occur in children exposed to severe deprivation (institutions) and
those who experience physical and sexual abuse (Teeter Ellison
& Nelson, 2008). Fearful,
anxious children and undercontrolled children also have altered
cortisol levels as a result of negative peer interactions in
childhood and adolescence. Peer rejection, stressful social
interactions, social isolation, and chronic social strain appear to
influence the HPA system.
Differences in HPA-axis activity have been found
in a number of childhood disorders including both internalizing and
externalizing disorders, memory and cognitive deficits, and poor
educational performance (Teeter Ellison & Nelson,
2008). However, positive early
childhood care and school environments may buffer the adverse
affects of high cortisol levels (see Adam et al., 2007).
Elevated blood pressure and heart rate responses
are related to anxiety arousal (Matthews, Manuck, & Saab,
1986). Use of electrophysiology
has found increased arousal in the limbic system of inhibited
children (Kagan, Arcus, Snidman, & Feng-Wang-Yu, 1994). It has been hypothesized that such
arousal contributes to the development of anxiety disorders. It is
also possible that biological dispositions interact with
environmental stressors, subsequently resulting in the
higher-than-expected incidence of anxiety disorder in children of
parents with anxiety and/or depressive disorder. Evidence gained
through PET and CT scans in individuals with OCD has found
increased metabolic rates for glucose, particularly in regions of
the orbital gyrus and caudate nucleus (Baxter et al.,
1987; Luxenberg et al.,
1988).
Academic and School Adjustment
Anxiety disorders have not been found to be
related to low intelligence. In contrast, children with anxiety
disorders tend to have at least average ability (Rachman &
Hodgson, 1991). Anxious children experience significant
psychosocial difficulty, including impaired peer relations,
depression, low self-concept, poor attention span, and deficits in
academic performance (Strauss, Frame, & Forehand,
1987). Children with anxiety
disorder have been found to be as disliked by their peers as those
children with conduct disorder (Strauss et al., 1988). Children with anxiety also have been
found to be socially neglected, isolated, withdrawn, and lonely
(Strauss, 1990). Anxious children
are more likely to experience test anxiety and difficulty in
presenting before their classmates. Children with
obsessive-compulsive disorder are absent from school frequently
because of peer ridicule (Clarizio, 1991) and social isolation (Allsop &
Verduyn, 1990), and are at higher
risk for suicide (Flament et al., 1988, 1990) and substance abuse (Friedman,
Utada, Glickman, & Morrissey, 1987).
It is important to note that anxious children
rarely pose significant overt behavioral difficulties in school,
and often are not referred for assessment by their teacher.
Teachers have frequently described these children as well-behaved
and eager to please (Strauss, 1990). However, such anxiety can impair the
child's social and academic functioning, and teachers need to be
familiar with these difficulties through in-service and direct
training.
Family and Home Factors
There appears to be a relationship between
socioeconomic status and anxiety in children (Strauss,
1990). Separation anxiety
disorder has been found to be more prevalent in families of lower
socioeconomic status (SES; Last, Hersen, Kazdin, Finkelstein, &
Strauss, 1987), while overanxious
children are found in greater concentration in middle to higher SES
families. Moreover, avoidant disorder also has been found to be
more prevalent in middle to higher SES families than in lower SES
families (Francis, Last, & Strauss, 1992). In addition, there is an increased
incidence of psychopathology in close relatives of children and
adolescents with obsessive-compulsive disorders (Templer,
1972). Families of children with
OCD tend to be highly verbal, socially isolated and withdrawn,
emphasize cleanliness and etiquette, and have a tendency to be
extremely frugal with money (Adam et al., 1995). Clark and Bolton
(1985) found that adolescents with
OCD believed their parents held very high expectations for them,
and these expectations were higher than those perceived by
adolescents with anxiety disorders. These authors reported that the
parents of OCD and anxious adolescents did not differ in their
expectations for their children.
Implications for Assessment
It is important to utilize a multi-method
approach to the diagnosis of anxiety disorders. Semi-structured
interviews, rating scales, self-report scales, and observations are
important pieces of an assessment. As discussed in the section on
childhood depression, semi-structured and structured interviews are
helpful in diagnosing anxiety disorders (Loney & Frick,
2003). Last et al. (1987) found good concordance across informants
using a semi-structured clinical interview to diagnose anxiety
disorders. Children reported more anxiety symptoms than parents,
possibly indicating that because of the internal nature of these
signs, children are more aware of these types of difficulties than
their caregivers (Edelbrock, Costello, Dulcan, Kalas, &
Conover, 1986). However, interviews with children under the age of
nine years have low reliability [see (Loney & Frick,
2003) for a review]. The Dominic-R
was developed to address these weaknesses for assessing young
children with anxiety (Valla, Bergerson, & Smolla,
2000). The Dominic-R assesses
DSM-III-R criteria and is presented in a picture format. The
pictorial format, combined with verbal questions, increased the
reliability and validity of the diagnostic interview in young
children (Loney & Frick, 2003).
The neuropsychological underpinnings of anxiety
disorders in childhood have not been as extensively investigated
compared to other disorders of childhood (Teeter Ellison et al.,
2009). Shaffer et al., (1996)
also reported that children with anxiety and withdrawal had a
higher risk of developing long-term problems due to dependent
behavior coupled with signs of motor clumsiness, associated
movements, and/or fine motor delays in childhood (Teeter Ellison et
al., 2009).
Rating Scales
Self-report rating scales are frequently used to
assess general anxiety levels. These scales are not developed to
determine various types of anxiety disorders. One of the most
popular rating scales used is the Revised Children's Manifest
Anxiety Scale (Reynolds & Richmond, 1978), which provides a global score. It is
confounded by symptoms of depression in the scale and may be best
utilized as a general measure of psychic distress. Behavioral
rating scales such as the Achenbach and BASC are useful to screen
for anxiety disorders with children showing elevated scores on more
intensive measures, including a structured clinical interview and
observations. Such a multistage method of evaluation can decrease
false positives and increase the specificity of diagnosis in order
to facilitate selecting the most appropriate treatment.
Implications for Treatment
Treatment of anxiety disorders is typically
multifaceted and may involve behavioral techniques,
cognitive-behavioral therapy, and/or pharmacology (Chorpita &
Southam-Gerow, 2006). Specific
behavioral interventions generally include systematic
desensitization, flooding, modeling, and reinforcement. Systematic
desensitization involves the gradual exposure of fear-evoking
situations paired with a nonanxiety arousing situation. This
technique has been most successful with phobias. Flooding involves
placing the child in the feared situation for an extended period of
time to evoke an intense reaction which gradually diminishes.
Although this technique has been effective with school phobia, it
is not recommended for other types of disorder because of the
aversive nature of the treatment and the availability of less
stressful methods. The use of positive reinforcement, shaping, and
extinction have been most helpful with phobias. One of the most
important components of this technique is to reduce parental
attention when the child becomes fearful, thus removing a very
powerful reinforcement for the anxious behavior.
Modeling is another behavioral technique in which
the child imagines or watches a model successfully interact with
the fear producing stimulus. This technique is helpful in reducing
common childhood fears. Modeling can take a variety of forms: (1)
symbolic where pictures or videos show successful interactions, (2)
covert modeling where the child imagines the model interacting
successfully, and (3) peer or adult models where others confront
the fearful stimulus and model coping strategies (Chorpita &
Southam-Gerow, 2006).
Cognitive behavioral interventions are used to
modify cognitions that underlie the anxiety and emotional distress.
Included in this type of intervention are methods of cognitive
restructuring, self-instruction, and self-monitoring. These
techniques have been successful in treating treatment anxiety
disorders in childhood. Psychopharmacology will be discussed in
Chapter 17.
Effects of Comorbidity on Treatment Outcomes
Children with both anxiety and ADHD respond
differently to ADHD treatments when compared to other groups. The
ADHD + ANX group, regardless of ODD/CD status, tended to be more
responsive to treatment than either children with ADHD + ODD/CD or
ADHD-only groups. In addition, children with ADHD + ANX responded
positively to any of three treatments (behavioral, medication
management, or combined treatment), whereas the ADHD + ANX + ODD/CD
had the greatest benefits from the combined treatment. Finally, the
ADHD + OCC/CD or ADHD-only groups generally only responded to
treatments with medication (Jensen et al., 2001).
Conclusions
Children with internalizing and externalizing
psychiatric disorders appear to present with both functional
(behavioral) and neuropsychological (biogenetic) markers. These
domains are intertwined and difficult to separate out. It seems
safe to conclude that children who have more than one disorder are
more likely to be referred for assessment and are more likely to
demonstrate severe types of psychopathology and neuropsychological
dysfunction.
The next section provides a clinical case study
of a child with Major Depressive Disorder, Generalized Anxiety
Disorder, and Panic Disorder.
Depression Case Study
Learning Characteristics Assessment
Identifying Information:
Name:Mr. L.M.
Age (Date of Birth): 17
Education:12 years
Procedures Administered:
Clinical Interview
Test of Malingering (TOMM)
Wechsler Adult Intelligence Scale – 3rd Edition
(WAIS-III)
Woodcock Johnson Achievement Battery – 3rd
Edition (WJ-III)
Wechsler Individual Achievement Test – 2nd
Edition (WIAT-II; selected tests)
Nelson-Denny Reading Test
Delis-Kaplan Executive Function System (D-KEFS;
Selected tests)
Test of Variables of Attention (TOVA)
Wechsler Memory Scale – 3rd Edition
(WMS-III)
California Verbal Learning Test – 2nd Edition
(CVLT-II)
Rey Complex Figure Test (RCFT)
Beck Depression Inventory (BDI)
State-Trait Anxiety Inventory (STAI)
Minnesota Multiphasic Personality Inventory – 2nd
Edition (MMPI-2)
Referral Question
Mr. M. is a 17-year-old, right-handed male who is
planning to attend the local community college in the fall. He was
referred for evaluation by his parents who are concerned about
possible difficulties that may arise in college in writing and
reading. Mr. M.’s stated goals for the assessment were to determine
if he had a writing disability and to receive recommendations for
improving his writing. During the clinical interview, he reported
that he has problems with academic writing in the social sciences,
especially due to his difficulties sustaining attention while
writing and developing a cohesive argument.
Developmental History
The following information was obtained through
the learning assessment questionnaire completed by Mr. M. and a
clinical interview.
Birth and Developmental Milestones
Mr. M. reported that he was born after a
full-term pregnancy and his mother did not have complications with
his pregnancy or delivery. His mother was 26-years-old when he was
born. Mr. M. reported reaching all developmental milestones
(walking, talking, and crawling) at appropriate times without
difficulty.
Family
Mr. M. described his parents as typical and
conservative. Mr. M. also reported that during his middle school
years, his parents were not very strict and he often argued and
yelled at them. While he does not remember what they argued about,
he indicated that he remembers just wanting to get his way. He
reported that his parents eventually concluded that they “could not
control him and let him go.” His mother has a high school diploma
and his father went on to earn some college credits. They are
employed as managers in a large company. Mr. M.has one younger
brother who is in elementary school and doing well.
Family Medical and Psychiatric History
There is no history of any medical difficulties
or psychiatric problems for Mr. M.’s family. Mr. M. did not report
experiencing any medical problems during his lifetime. He reported
that he has been very healthy.
Academic History
Early Academic Performance
Mr. M. attended a small private elementary school
where he reports performing well academically. In the 7th grade,
however, he began attending a public school and his grades dropped
to mostly Cs and Ds, and deficiency notices were sent home to his
parents. Mr. M. reported that while his parents expected him to do
well in school, they did not help him with schoolwork. In high
school, he continued to do poorly and failed some of his classes,
reportedly because he did not apply himself. He did, however, earn
his high school diploma.
During this time, Mr. M. did not receive any
remedial services or academic tutoring. His favorite subject was
science and his least favorite was history, because he reported
having no connection or interest in the subject. Throughout middle
and high school, Mr. M. reported that he had a good group of
friends and stayed out of trouble.
Behavioral Observations
Mr. M. appeared for each testing session on time
or early, well-groomed, and casually dressed. He indicated that he
is right-handed, does not have any hearing problems, but does wear
glasses to correct his vision problems. English is his native
language.
During the first assessment session, Mr. M. was
very lively and talkative. During the clinical interview, Mr. M.
was candid and open to answering each question to the best of his
ability. He was cooperative and motivated during testing and even
made jokes. For example, during WAIS-III Digit-Symbol Coding, Mr.
M. asked if I had ever tested someone who finished the subtest
incredibly fast “like Rain Man.” He did, however, appear somewhat
nervous. He was frequently observed biting his nails, picking with
his skin, and scratching his head. He took great care in responding
to the items on the BDI-II. He read each item carefully and asked
questions about any items he did not understand.
During the subsequent assessment sessions, Mr. M.
appeared less energetic and somewhat sad and stressed. When given a
self-report anxiety measure on the second day of testing, Mr. M.
said that he had a paper due that day and his responses were
largely influenced by his school concerns. During this testing
session, we completed some of the writing assessment measures. He
did not appear to have trouble during the WJ-III Achievement
Writing Fluency subtest, where he wrote very quickly. During the
WJ-III Achievement Writing Samples subtest, however, he frequently
crossed out what he had written and started again. During the
WIAT-II Written Expression subtest, Mr. M. said that his “mind went
blank,” but it was “not because he was tired.” He began the essay
by creating a short outline of his main points. While writing the
essay for this subtest, Mr. M. frequently erased what he had
written. He also placed a great deal of pressure on the pencil as
he wrote. The table even moved with the force of his writing. After
10 minutes had passed, Mr. M. had only written 4–5 lines of text.
He also held his face very taut, with his lips firmly pressed
together during this and other writing exercises.
Mr. M. was administered a measure of malingering,
which fell within normal limits (TOMM). In sum, the assessment
results are thought to be a valid and reliable representation of
Mr. M.’s psychological, cognitive, and academic functioning.
Test Results
Intellectual Functioning
Mr. M.’s general cognitive abilities were
assessed using the WAIS-III. On the WAIS-III, Mr. M.’s overall
intellectual abilities fell within the high average to
significantly above average range. He obtained a Full Scale IQ of
120, which falls at the 91st percentile when compared to others at
the same education level. The chances that the range of scores from
116 to 124 includes his true IQ are about 95 out of 100. Mr. M.
obtained a Verbal IQ of 115 and a Performance (nonverbal) IQ of
124. The difference between his Verbal IQ and Performance IQ was
not statistically significant. Therefore, Mr. M.’s Full Scale IQ
score is the most appropriate index of his overall intellectual
abilities.
Mr. M.’s performance on tests of verbal
comprehension was in the average range. The verbal comprehension
subtests required him to answer oral questions that measure factual
knowledge, provide meanings of words, exhibit reasoning ability,
and adeptly express his ideas in words. Among these verbal
subtests, Mr. M.’s performance on a test that required him to
describe how two things are similar was a relative weakness.
His performance on tests of perceptual
organization was in the superior range. The perceptual organization
subtests required him to integrate visual stimuli, use nonverbal
reasoning skills, and apply visual-spatial and visual-motor skills
to solve the kinds of problems that are not taught in school. Among
these perceptual subtests, Mr. M.’s very superior performance on a
task that required him to use blocks to create a model in
three-dimensional space based on a two- or three-dimensional
example model was a strength. His superior performance in this
domain suggests that his nonverbal thinking and visual motor
coordination are well developed.
On tests of working memory, he performed in the
superior range. These subtests required him to respond to oral
stimuli that involve handling numbers and letters in a sequential
fashion and displaying a non-distractible attention span. These
results suggest that his sequential processing ability is very well
developed.
Mr. M.’s processing speed was in the high average
range. The processing speed subtests required him to demonstrate
extreme speed in solving an assortment of nonverbal problems. These
tests measured speed of thinking as well as motor speed. His
performance in this domain suggests that his response speed, the
ability to quickly scan, discriminate between, and sequentially
order visual information, is in the high average range.
There was a significant difference between Mr.
M.’s superior performance on perceptual organization and working
memory subtests, and his average verbal comprehension performance.
This indicates that his verbal conceptualization, knowledge, and
expression abilities are a relative weakness.
Overall, Mr. M. exhibited superior intellectual
abilities. His perceptual organization and working memory skills
were strengths, while his verbal comprehension ability was a
relative weakness.
Scholastic Achievement
Mr. M.’s overall performance on the WJ-III
Achievement Battery was in the high average range. Mr. M.’s overall
reading achievement was in the average range.
His reading comprehension and his ability to
recognize words were in the high average range. Mr. M.’s reading
fluency was in the low average range. Mr. M.’s vocabulary,
comprehension, and reading rate were also in the average range when
tested using the Nelson-Denny Reading Test.
Mr. M.’s scores on written achievement were in
the high average range. His ability to produce meaningful written
sentences in response to a variety of tasks was in the average
range (Writing Samples subtest). His spelling was also in the
average range. His writing speed was in the high average range as
measured by the Writing Fluency which required him to write
complete sentences using a given set of words and matching picture.
When writing single sentences in the structured format of the
Writing Fluency subtest, Mr. M.’s performance is in the high
average range. Mr. M.’s written achievement was also tested using
the WIAT-II. On this test, his spelling and written expression were
in the average range.
Mr. M.’s overall math achievement fell in the
high average range. His mathematic calculation skills (Calculation
subtest) and his ability to solve mathematic word problems (Applied
Problems subtest) were both in the average range. His performance
on Math Fluency, a timed task that requires examinees to calculate
addition, subtraction, and multiplication problems quickly, was in
the high average range.
Overall, Mr. M.’s scholastic achievement skills
were in the high average range. Specifically, his overall
mathematics and written language skills were in the high average
range and his reading skills were in the average range. Because his
academic achievement is within cognitive expectations, Mr. M. does
not meet criteria for a learning disorder.
Working Memory and Attention
Mr. M.’s performance on working memory tasks was
in the superior range on both the WAIS-III and the WMS-III. On the
D-KEFS Trail Making Test, a task measuring working memory, visual
scanning, attention, number-letter sequencing, and visual-motor
abilities, Mr. M.’s performance was in the average to high average
range.
The Auditory and Visual T.O.V.A. was used to
assess Mr. M.’s attention and impulse control. The test resembles a
computer game where the examinee is directed to press a switch
whenever a specific stimulus appears. When compared to those of his
same age and gender, Mr. M.’s performance suggested he has a
significant problem with sustained attention.
Executive Functioning
The D-KEFS Color-Word Interference Test was used
to assess Mr. M.’s verbal inhibition and cognitive flexibility.
This test consists of four timed conditions. In the first condition
of this test, Mr. M. was shown a sheet with color patches aligned
in rows and asked to name each of the colors as quickly as
possible. In the second condition, he was shown a list of color
words and asked to read them as quickly as possible. Mr. M.’s
performance in both of these conditions was in the average range.
The third condition required him to inhibit the written color word
and, instead, name the color of ink, and his performance was in the
high average range. He also performed in the high average range
during the fourth condition, which required him to switch back and
forth between naming the dissonant ink color and reading the
conflicting word. His high average performance during these
conditions indicates that he took less time than others of similar
education level to complete the task.
The D-KEFS Verbal Fluency Test was used to assess
Mr. M.’s cognitive flexibility and strategic thinking. This test
required him to generate as many words as possible beginning with a
given letter or belonging to a specific category within a short
period of time. Mr. M.’s performance on this test was in the
average to high average range, indicating that his cognitive
fluency is within normal limits.
The D-KEFS Sorting Test was used to assess Mr.
M.’s executive functioning, concept formation, and problem solving
abilities. This test required him to sort various cards into
groups, describe the concepts he used to generate each sort, and
identify the correct categorization rule or concept used to
generate sorts created by the examiner. Mr. M.’s performance on
these tasks was in the average to high average range suggesting
that his ability to implement and perceive conceptual relationships
in both verbal and nonverbal modalities is within age and education
level expectations.
The D-KEFS Tower Test was used to assess Mr. M.’s
spatial planning and rule learning skills. His performance on this
task was in the average range.
Overall, Mr. M. demonstrated average to high
average executive functioning.
Memory Functioning
Mr. M.’s general memory abilities, as measured by
the WMS-III, were in the high average range. His ability to recall
visual information immediately and after a 25-minute delay were in
the high average and average ranges, respectively. His ability to
recall oral information immediately and after a 25-minute delay
were both in the high average range.
Mr. M.’s auditory learning and memory were also
tested using the CVLT-II. On this test, Mr. M. was given several
oral presentations of a 16-word list and asked to recall the list
after each presentation. Mr. M.’s recall after the initial
presentation of the first word list was in the high average range.
After the fifth trial of oral presentation of the words, Mr. M.’s
performance was significantly above average. His overall ability to
recall words with repeated exposure to the list of words was in the
average range as indicated by his learning slope score. When orally
presented with a second list of words, Mr. M. scored in the
superior range, recalling 14 out of the 16 words. His performance
was significantly above average when he was asked to recall the
first list of words after a short and long delay. An analysis of
his memory performance revealed that across all five trials, Mr. M.
used a less efficient method for learning the words, recalling them
in the order given. While Mr. M.’s performance on this test was in
the high average to superior range, he did not use the most
effective learning strategy, reorganizing the target words into
categorical groups, to pull the words from memory.
In sum, results from both the WMS-III and the
CVLT-II indicate that Mr. M.’s general memory abilities are in the
high average range. His somewhat less developed visual memory
skills and his slower processing speed may be influencing his
overall memory abilities and his current reading
difficulties.
Overall, Mr. M.’s memory abilities were in the
high average range to superior range.
Visual-Motor-Spatial Skills
The Rey-Osterreith Complex Figure test (ROCF) was
used to measure Mr. M.’s visual-motor-spatial memory and
construction skills. This test first required him to make a copy
drawing of a complex figure. The picture of the figure was then
taken away, and Mr. M. was asked to draw the figure immediately and
after a 25-minute delay. Mr. M.’s ability to recall and draw the
figure immediately and after a delay was in the superior and high
average range, respectively. Taken together, Mr. M.’s
visual-spatial memory was very well developed.
Emotional Functioning
Mr. M. provided valid and reliable responses to
the MMPI-2. According to the results of the MMPI-2, Mr. M.’s
profile suggests that he is currently experiencing anxiety and
depression. The profile suggests a tendency to be anxious and
insecure. He also may be experiencing some psychosomatic problems,
such as trouble sleeping and appetite changes.
This profile also suggests that Mr. M. is
introverted and has difficulties meeting other people. He may be
shy, uneasy, and somewhat rigid and overcontrolled in social
situations. He may have high standards and a strong need to
achieve, but feels that he falls short of his expectations and
blames himself harshly. According to the results, he feels insecure
and pessimistic about the future and doubts that he can solve his
problems.
The results also suggest that Mr. M. is passive
and dependent in interpersonal relationships and does not speak up
for himself even when others take advantage of him. He forms deep
emotional attachments and tends to be quite vulnerable to being
hurt. He also tends to blame himself for interpersonal
problems.
On the STAI, a self-report measure of current and
general levels of anxiety, Mr. M. also indicated high levels of
state and trait anxiety (90th and 96th percentiles, respectively).
On the BDI-II, Mr. M. received a score of 28, indicating that he is
reporting moderate depressive symptoms. During the clinical
interview, Mr. M. was assessed for depression, generalized anxiety
disorder, panic disorder, and attention-deficit hyperactivity
disorder.
Major Depressive Disorder
Mr. M. indicated that he has been suffering from
depressed mood, anhedonia, weight loss, sleep disturbances, guilty
feelings, concentration difficulties, and indecisiveness since
middle school. He reported that he often felt down because of
schoolwork and wondered whether he is “cut out for college.” He
became somewhat more introverted this past school year and now
rarely goes out with friends. He felt cut off from the other
students and teachers because guilt surrounding his poor work
performance made him want to avoid seeing them. By the end of the
school year, he had lost 5–7 lbs., due to a decreased appetite. Mr.
M. indicated that he slept fewer hours more than usual. He also
indicated that he felt guilty about not making his paper deadlines.
He found it difficult to concentrate on completing his papers. He
also reported that he usually considers himself an indecisive
person, but that decision making was somewhat more difficult than
usual. Mr. M. did not indicate any thoughts of death or dying.
Based on these responses, Mr. M. meets criteria for a Major
Depressive Disorder.
Mr. M. also reported feeling depressed, hopeless,
and lonely for 2–3 months starting in October when he broke up with
his first serious girlfriend.
Generalized Anxiety Disorder
When assessed for symptoms of generalized anxiety
disorder, Mr. M. indicated that he is often consumed with worry,
has difficulty controlling his worry, and experiences physical
symptoms such as restlessness, fatigue, concentration difficulties,
and body tension when he worries. Mr. M. reported that since his
sophomore year in high school he has frequently worried about the
writing he is required to do at school and work. He finds that
after collecting and reading all of the needed research articles,
it is difficult for him to write a cohesive essay.
Mr. M. reported that he has always worried about
what other people think of him. For example, he often worries about
making mistakes in oral presentations. A few times other people
have told him that he was too sensitive and should not worry about
things so much. He also thinks that he worries too much about what
other people think and that the worry may be excessive. Mr. M.
reported that he spends 5–6 hours each day worrying. He feels like
the worries are on his mind all day, more days than not and are
difficult to control.
Mr. M. reported that when he is worrying he has
trouble sitting still. He gets tired very easily. It is harder for
him to pay attention. He become more introverted and will avoid
talking to his roommate. He feels his chest get tight, as if he can
feel the burden of stress. He also reported feeling tension in his
shoulders and neck. Mr. M. indicated that these physical symptoms
occur 1–2 times per week. This worry has had a significant effect
on Mr. M.’s life. It bothers him that he feels this way and it has
made him question whether he should remain in graduate school. This
worry has also affected his social life. He reported that worrying
has turned him into a hermit, where he hardly ever leaves the
house. Based on these symptoms, Mr. M. meets criteria for
Generalized Anxiety Disorder.
Panic Disorder
When assessed for symptoms of panic disorder, Mr.
M. reported experiencing several panic attacks at the end of the
past school year as he tried to complete his writing assignments.
During these attacks, he felt his heart racing. He began to shake.
He had trouble catching his breath. He had pains in his chest and
feared he was having a heart attack. He also worried whether he
would lose control. He reported that all of these physical symptoms
came on quickly, within 10 minutes after the attack began. Mr. M.
reported having panic attacks three times per week during one month
in the fall and as much as three times per day during one recent
month. Mr. M. indicated that he does not fear having another
attack, but he does believe he will have one again. Based on these
symptoms, Mr. M. meets criteria for Panic Disorder Without
Agoraphobia.
Attention-Deficit Hyperactivity Disorder
When assessed for symptoms of attention-deficit
hyperactivity disorder, Mr. M. reported that has difficulties with
listening, finishing assignments, and organizing. He also reported
that he avoids activities that require him to sustain attention for
long periods and is often forgetful. Mr. M. reported that he has
trouble listening and understanding others. He first noticed this
behavior when he began his junior year of high school. He feels
like it takes him longer to understand things than others,
especially when unfamiliar topics are being discussed. This mainly
happens with teachers, and he does not have this problem with his
parents or peers. Mr. M. also reported that he has more trouble
than others finishing long and tedious tasks. He first noticed that
he had trouble finishing assignments in elementary school, but this
difficulty only causes significant problems for him when he is
writing papers. He also reported difficulties with continuing to
work on one school assignment for an extended period of time. He
indicated that he will start doing one task, get bored, and then
switch to another. This problem, however, is specific to schoolwork
and he does not have trouble completing chores around the
house.
Mr. M. also reported having more difficulties
organizing things than others. He often has trouble keeping papers
and computer files organized. He is also disorganized with his
bills, which are often not paid on time because of this. It is also
difficult for him to organize his schedule, and he will often
forget deadlines and appointments. He reported that he keeps a
calendar, but then will not look at it for a week. When asked how
he was able to arrive on time to each of our assessment sessions,
he indicated that he set a reminder on his phone. Mr. M. reported
that he avoids, dislikes, and is reluctant to engage in activities
requiring sustained attention, especially writing and editing
papers. He does not find himself avoiding reading assignments,
however. Mr. M. also reported that he is somewhat more forgetful
than others. He sometimes forgets to complete school and work
tasks. He reported that this does not occur frequently, however. On
average, he forgets things 1–2 times per month. He does not forget
daily chores. Mr. M. did not indorse any hyperactivity or
impulsivity symptoms. Results from the T.O.V.A. and the clinical
interview indicate that Mr. M. meets criteria for Attention-Deficit
Hyperactivity Disorder Inattentive Type. These findings may
indicate the presence of ADHD, but the presence of a mood disorder
makes this determination problematic and should be more fully
explored psychiatrically. In addition, the difficulties were not
identified until Mr. M was a sophomore in high school. At this time
he does not qualify for a diagnosis of ADHD.
DSM-IV-TR Diagnosis
Axis I:Moderate Major Depressive Disorder,
Recurrent (296.32)
Generalized Anxiety Disorder (300.02)
Panic Disorder Without Agoraphobia
(300.01)
Possible history of Major Depressive Disorder
(311.00; as reported by the client)
Axis II: None
Axis III: None
Axis IV: Academic difficulties
Axis V:Global Assessment of Functioning
54 (current)
Summary and Recommendations
Mr. M. is a 17-year-old, right-handed male who
was referred for an evaluation of learning characteristics and
attention problems. Mr. M.’s stated goals for the assessment were
to determine if he had a writing disability and to receive
recommendations on how to improve his writing. During the clinical
interview, he reported that he has problems with academic writing
in the social sciences especially, due to his difficulties
sustaining attention while writing and developing a cohesive
argument.
An extensive battery of tests was administered to
assess Mr. M.’s current level of intellectual and psychological
functioning. During testing, he was somewhat down and stressed due
to school concerns, but appeared to work to the best of his
abilities on all tasks. Test results are, therefore, believed to be
an accurate reflection of his current level of functioning.
Overall, Mr. M. exhibited superior intellectual
abilities. His perceptual organization and working memory skills
were strengths, while his verbal comprehension was a relative
weakness. Mr. M.’s scholastic achievement skills were in the high
average range. Specifically, his overall mathematics and written
language skills were in the high average range and his reading
skills were in the average range. While Mr. M.’s working memory
abilities were in the average to superior range, his ability to
sustain attention is impaired. Mr. M. demonstrated average to high
average executive functioning and his memory abilities were in the
high average range to superior range.
Mr. M.’s personality profile suggested that he is
introverted, uneasy, and somewhat overcontrolled in social
situations. He also may be feeling insecure and pessimistic about
whether he can solve his problems. Mr. M. is experiencing
significant anxiety and depressive symptoms, and meets criteria for
Major Depressive Disorder, Generalized Anxiety Disorder, and Panic
Disorder. Although results from the tests of attention and the
clinical interview indicate that he meets criteria for
Attention-Deficit Hyperactivity Disorder Inattentive Type, these
symptoms were not reported until his sophomore year in high school
and increased as the writing workload and expectations for academic
performance increased. His attention problems are likely
exacerbated by his significant anxiety symptoms, especially with
regard to writing.
The following recommendations may be useful in
dealing with weaknesses, enhancing strengths, and improving Mr.
M.’s academic performance:
Recommendations
- 1.
Mr. M. shows significant emotional distress that is likely causing him problems in learning and exacerbating his attentional problems. Given that the attention problems were not identified until he was in high school, it is unlikely that he has ADHD.
- 2.
Mr. M.’s anxiety symptoms are likely exacerbating his attention difficulties and may be preventing him from reaching his full academic potential. Therefore, it is recommended that he seek therapeutic counseling and a psychiatric consult. When an appointment is made, this psychological report can be sent to the assigned therapist to aid in the psychological evaluation.
- 3.
Mr. M.’s academic performance may benefit from extra help with his writing skills. He is encouraged to seek assistance from his community college and to ask for additional support prior to beginning the fall semester.
- 4.
It is recommended that Mr. M. take only one writing-heavy course each term in order to give him ample time to develop the skills required for the specific class. Spreading these types of courses out will likely give Mr. M. extra time to complete his writing assignments.
- 5.
Due to his attention problems, Mr. M. may benefit from taking frequent breaks during class. Because his efficiency wanes over time, a short walk outside of the classroom may give him time to regroup.
- 6.
Additionally, Mr. M. may benefit from having larger projects (e.g., paper deadlines) broken into more manageable tasks with individual deadlines. Mr. M. should speak with his advisor about setting discrete deadlines for separate portions of papers.
References
Achenbach, T. M., &
Rescorla, L. (2001). Manual for
the ASEBA school-age forms and profiles . Burlington:
University of Vermont, Research Center for Children, Youth and
Families.
Adam, E., Klimes-Dougan, B.,
& Gunnar, M. R. (2007). Social regulation of the adrenocortical
response to stress in infants, children and adolescents:
Implications for psychopathology and education. In D. Coch, K.
Fischer, & G. Dawson (Eds.), Human behavior, learning, and the developing
brain (pp. 264–304). New York, NY: Guilford Press.
Albano, A. M., Chorpita, B.
F., & Barlow, D. H. (2006). Childhood anxiety disorders. In E.
J. Mash & R. A. Barkley (Eds.), Child psychopathology (2nd ed., pp
279–329). New York: Guilford Press.
Alessi, N. E., & Magen,
J. (1988). Comorbidity of other psychiatric disturbances in
depressed psychiatrically hospitalized children. American Journal of Psychiatry, 145,
1582–1584.PubMed
Allen, J. C., &
Hollifield, J. (2003). Using the Rorschach with children and
adolescents: The Exner Comprehensive System. In C. R. Reynolds
& R. W. Kamphaus (Eds.), Handbook of psychological and educational
assessment of children: Personality, behavior, and context
(2nd ed., pp.182–197). New York: Guilford Press.
Allsop, M., & Verduyn, C.
(1990). Adolescents with obsessive compulsive disorder: A case note
review of consecutive patients referred to a provincial regional
adolescent psychiatry unit. Journal of Adolescence, 13,
157–169.
American Psychiatric
Association. (2000). Diagnostic
and statistical manual of mental disorders (4th ed. text
revision). Washington, DC: Author.
Anderson, J. C., Williams,
S., McGee, R., & Silva, P. A. (1987). DSM-111 disorders in
preadolescent children. Prevalence in a large sample from the
general population. Archives of
General Psychiatry, 44, 6–76.
Angold, A., Costello, E. J.,
& Erkanli, A. (1999). Comorbidity. Journal of Child Psychology and Psychiatry,
40, 57–87.PubMed
Ashman, S. B., Dawson, G.,
Panagiotides, H., Yamada, E., & Wilkinson, C. W. (2002). Stress
hormone levels of children of depressed mothers. Development and Psychopathology, 14, 333–349.
Avenenoli, S., Knight, E.,
Kessler, R. C., & Merikangas, K. R. (2007). Epidemiology of
depression in children and adolescents. In J. R. Z. Abela & B.
L. Hankin (Eds.), Handbook of
depression in children and adolescents (pp. 6–34). NY:
Guilford Press.
Barkley, R. A., (2006).
Attention-deficit hyperactivity
disorder: A handbook for diagnosis and treatment (3
rd ed.). New York: Guildford Press.
Barlow, D. H. (2002).
Anxiety and its disorders (2nd ed.). New York: Guilford
Press.
Baxter, L. R., Thompson, J.
M., Schwartz, J. M., Guze, B. H., Phelps, M. E., Mazziotta, J. C.,
et al. (1987). Trazodone treatment response in obsessive-compulsive
disorder. Psychopathology,
20, 114–422.PubMed
Biederman, J., Baldessarini,
R. J., Wright, V., Knee, D., & Harmatz, J. E. (1989). A
double-blind placebo controlled study of desipramine in the
treatment of ADD: I. Efficacy. Journal of the American Academy of Child and
Adolescent Psychiatry, 28, 777–784.PubMed
Biederman, J., Faraone, S.,
Marrs, A., Moore, P., Garcia, J., Ablon, J. S., Mick, E. Gershon,
J., & Kearns, M. E. (1997). Panic disorder and agoraphobia in
consecutively referred children and adolescents. Journal of the American Academy of Child and
Adolescent Psychiatry, 36, 214–223.PubMed
Biederman, J., Munir, K.,
Keenan, K., & Tsuang, M. T. (1991). Evidence of familial
association between attention deficit and major affective
disorders. Archives of General
Psychiatry, 48, 633–642.PubMed
Birleson, P. (1981). The
validity of depressive disorder in childhood and the development of
self-rating scale: A research report. Journal of Child Psychology and Psychiatry,
22, 73–88.PubMed
Birmaher, B., Ryna, N. D.,
Williamson, D. E., Brent, D. A., Kaufman, J., Dahl, R. E., et al.
(1996). Childhood and adolescent depression: A review of the past
10 years. Part I. Journal of the
American Academy of Child and Adolescent Psychiatry, 35,
1427–1439.PubMed
Blanchard, L. T., Gurka, M.
J., & Blackman, J. A. (2006). Emotional, developmental, and
behavioral health of American children and their families: A report
from the 2003 National Survey of Children's Health. Pediatrics, 117(6),
e1202–e1212.PubMed
Caine, E. D. (1986). The
neuropsychology of depression: The pseudodementia syndrome. In I.
Grant & K. Adams (Eds.), Neuropsychological assessment of
neuro-psychiatric disorders (pp. 221–243). New York: Oxford
University Press.
Checkley, S. (1996). The
neuroendocriniology of depression. International Review of Psychiatry, 8,
373–378.
Chorpita, B. F., &
Southam-Gerow, M. A. (2006). Fears and anxieties. In E. J. Mash
& R. A. Barkley (Eds.), Treatment of childhood disorders , 3rd
ed., (pp. 271–335). New York: Guilford Press.
Chow, T. W., & Cummings,
J. L. (2007). Frontal-subcortical circuits. In B. L. Miller &
J. L. Cummings (Eds.), The human
frontal lobes: Functions and disorders (2nd ed., pp. 25–43).
New York: Guilfrod Press.
Clarizio, H. F. (1991).
Obsessive-compulsive disorder: The secretive syndrome. Psychology in the Schools, 28,
106–115.
Clark, D. A., & Bolton,
D. (1985). Obsessive-compulsive adolescents and their parents.
Journal of Child Psychology and
Psychiatry and Allied Disciplines, 26, 267–276.
Cohen, R. M., Weingarten,
H., Smallberg, S. A., &Murphy, D. L. (1982). Effort and
cognition in depression. Archives
of General Psychiatry, 39, 593–597.PubMed
Costello, E. J., Mustillo,
S., Erkanli, A., Keeler, G., & Angold, A. (2003). Prevalence
and development of psychiatric disorders in childhood and
adolescence. Archives of General
Psychiatry, 60, 837–844.PubMed
Cummings, E. M., &
Cicchetti, D. (1990). Toward a transactional model of relations
between attachment and depression. In M. T. Greenberg, D.
Cicchetti, & E. M. Cicchetti (Eds.), Attachment in preschool years: Theory,
research, and intervention (pp. 339–372). Chicago:
University Press.
Davidson, R. J.,
Abercrombie, H., Nitschke, J. B., & Putman, K. M. (1999).
Regional brain function, emotion, and disorders of emotions.
Current Opinion in Neurobiology,
9 (2), 228–234.PubMed
Dawson, G., Frey, K.,
Panagiotides, H., Osterling, J., & Hessl, D. (1997). Infants of
depressed mothers exhibit atypical frontal brain activity: A
replication and extension of previous findings. Journal of Child Psychology and Psychiatry,
38, 179–186.PubMed
Dawson, G., Grofer Klinger,
L., Pangiotides, H., Hill, D., Spieker, S., & Frey, K. (1992).
Infants of mothers with depressive symptoms: Electrophysiological
and behavioral findings related to attachment status. Development and Psychopathology, 4
,6740.
De Bellis, M. D., Chrousos,
G. P., Dorn, L. D., Burke, L., Helmers, K., Kling, M. A., et al.
(1994). Hypothalamic-pituitary-adrenal axis dysregulation in
sexually abused girls. Journal of
Clinical Endocrinology and Metabolism, 78,
249–255.PubMed
Dencina, P., Kestenbaum, E.
J., Farber, S., Kron, L., et al. (1983). Clinical and psychological
assessment of children of bipolar probands. American Journal ofPsychiatry, 140,
54–558.
Dickstein, D. P., Trelanda,
J. E., Snowa, J., McClurea, E. B., Mehtaa, M. S., Towbina, K. E.,
et al. (2004). Neuropsychological performance in pediatric bipolar
disorder. Biological Psychiatry,
55 (1), 32–39.PubMed
Downey, G., & Coyne, J.
(1990). Children of depressed parents: An integrative view.
Psychological Bulletin,
108, 50–76.PubMed
Drevets, W. (2001a).
Neuroimaging studies of mood disorders. Biological Psychiatry, 48 (8),
813–829.
Drevets, W. C. (2001b).
Neuroimaging and neuropathological studies of depression:
Implications for the cognitive-emotional features of mood
disorders. Current Opinion in
Neurobiology, 119 (2), 240–249.
DuPree, J. L., &
Prevatt, F. (2003). Projective story telling techniques. In C. R.
Reynolds & R. W. Kamphaus (Eds.), Handbook of psychological and educational
assessment of children: Personality, behavior, and context
(2nd ed., pp. 66–90). New York: Guilford Press.
Edelbrock, C., Costello, A.
J., Dulcas, M. K., Kalas, R., & Conover, N. C. (1986).
Parent-child agreement on child psychiatric symptoms assessed via
structured interview. Journal of
Child Psychology and Psychiatry, 27, 181–190.PubMed
Firth, C. D., Stevens, M.,
Johnstone, E. C., Deakin, J. F., Lawler, P., Crow, T. J. (1983).
Effects of ECT and depression on various aspects of memory.
Journal of British Psychiatry,
142, 610–617.
Flament, M. F., Koby, E.,
Rapoport, J. L., Berg, C. J., Zahn, T., Cox, C., et al. (1990).
Childhood obsessive-compulsive disorder: A prospective follow-up
study. Journal of Child Psychology
and Psychiatry, 31, 363–380.PubMed
Flament, M. F., Whitaker,
A., Rapoport, J. L., Davies, M., Berg, C. Z., Kalikow, et al.
(1988). Obsessive compulsive disorder in adolescence: An
epidemiological study. Journal of
the American Academy of Child and Adolescent Psychiatry, 27,
764 – 771.PubMed
Francis, G., Last, C. G.,
& Strauss, C. C. (1992). Avoidant disorder and social phobia in
childhood and adolescence. Journal
of the American Academy of Child and Adolescent Psychiatry,
31, 1086–1089.PubMed
Friedman, A. S., Utada, A.
T., Glickman, N. W., & Morrissey, M. R. (1987). Psychopathology
as an antecedent to, and as a “consequence” of, substance abuse, in
adolescence. Journal of Drug
Education, 17, 233–244.PubMed
Geller, B., & Tillman,
R. (2005). Prepubertal and early adolescent bipolar I disorder:
Review of diagnostic validation by Robins and Guze criteria.
Journal of Clinical Psychiatry,
66 (suppl 7), 21–28.PubMed
Gorwood, P. (2004).
Confusing clinical presentations and differential diagnosis of
bipolar disorder. Encephale,
30 (2), 182–193.PubMed
Gratacos, M., Nadal, M.,
Martin-Santos, R., Pujana, M. A., Gago, J., & Peral, B. (2001).
A polymorphic genome duplication on human chromosome 15 is a
susceptibility factor for panic and phobic disorders. Cell, 106, 367–379.PubMed
Gurley, D., Cohen, P., Pine,
D. S., & Brook, J. (1996). Discriminating anxiety and
depression in youth: A role for diagnostic criteria. Journal of Affective Disorders, 39,
191–190.PubMed
Haldane, M., & Frangou,
S. (2004). New insights help define the pathophysiology of bipolar
affective disorder: Neuroimaging and neuropathology findings.
Progress in Neuropsychopharmacology and Biological
Psychiatry, 28 (6), 943–960.
Hamilton, M. (1967).
Development of a rating scale for primary depressive illness.
British Journal of Social and
Clinical Psychology, 6, 278–296.PubMed
Hammen, C. (1990). Cognitive
approaches to depression in children: Current findings and new
directions. In B. B. Lahey & A. E. Kazdin (Eds.), Advances in clinical child psychology
(Vol. 13, pp. 173–202). New York: Plenum Press.
Hammen, C. D., &
Brennan, P. A. (2001). Depressed adolescents of depressed and
non-depressed mothers: Tests of an interpersonal impairment
hypothesis. Journal of Consulting
and Clinical Psychology, 69, 284–294.PubMed
Hammen, C. D., &
Rudolph, K. D. (2003). Childhood mood disorders. In E. J. Mash
& R. A. Barkley, (Eds.), Child
psychopathology (2nd ed., pp. 233–278). New York: Guilford
Press.
Hankin, J. R., & Abela,
J. R. (2005). Development of
psychopathology: A vulnerability stress perspective. NY:
Sage Publications
Hankin, B. L., Abramson, L.
Y., Moffitt, T. E., Silva, P. A., McGee, R., & Angell, K. E.
(1998). Development of depression from preadolescence to young
adulthood: Emerging gender differences in a 10-year longitudinal
study. Journal of Abnormal
Psychology, 107, 128–140.PubMed
Hasler, G., Fromm, S.,
Carlson, P. J., Luckenbaugh, D. A., Waldeck, T., Geraci, M., et al.
(2008). Neural response to catecholamine depletion in unmedicated
subjects with major depressive disorder in remission and healthy
subjects. Archives of General
Psychiatry, 65 (5), 521–31.PubMedPubMedCentral
Heim, C., & Nemeroff, C.
B. (2001). The role of childhood trauma in the neurobiology of mood
and anxiety disorders: Preclinical and clinical studies.
Biological Psychiatry, 49,
1023–1039.PubMed
Henriques, J., &
Davidson, R. (1990). Regional brain electrical asymmetries
discriminate between previously depressed subjects and healthy
controls. Journal of Abnormal
Psychology, 99, 22–31.PubMed
Jensen, J. P., Martin, D.,
& Cantwell, D. P. (1997). Comorbidity in ADHD: Implications for
research, practice, and DSM-V. Journal of the American Academy of Child and
Adolescent Psychiatry, 36, 1065–1079.PubMed
Jensen, P. S., Hinshaw, S.,
Swanson, J., Greenhill, L., Conners, K., Arnold, E., et al. (2001).
Findings from the NIMH multimodal treatment study of ADHD (MTA):
Implications and applications for primary care providers.
Developmental and Behavioral
Pediatrics, 22, 60–73.
Kagan, J., Arcus, D.,
Snidman, N., & Feng-Wang-Yu (1994). Reactivity in infants.
Developmental Psychology,
30, 342–345.
Kaufman, J., Martin, A.,
King, R. A., & Charney, D. (2001). Are child-, adolescent-, and
adult-onset depression one and the same? Biological Psychiatry, 49,
980–1001.PubMed
Kaufman, J., Yang, B. Z.,
Douglas-Palumberi, H., Grasso, D., Lipschitz, D., Houshyar, S., et
al. (2006). Brain-derived neurotrophic factor-5-HTTLPR gene
interactions and environmental modifiers of depression in children.
Biological Psychiatry, 59,
673–680.PubMed
Kazdin, A. E. (1987).
Conduct disorders in childhood and
adolescence. Beverly Hills, CA: Sage Publications.
Kazdin, A. E., French, N.
H., Unis, A. S., Esveldt-Dawson, & Sherick, R. B. (1983). The
Hopelessness Scale for Children: Psychometric characteristics and
concurrent validity. Journal of
Consulting and Clinical Psychology, 51, 504–510.PubMed
Kendler, K. S., Neale, M.
C., Heath, A. C., & Eaves, L. J. (1992). Major depression and
generalized anxiety disorder: Same genes, (partly) different
environments? Archives of General
Psychiatry, 49, 716–722.PubMed
Kendler, K. S., Neale, M.
C., Heath, A. C., & Eaves, L. J. (1993). A twin study of recent
life events and difficulties. Archives of General Psychiatry, 50,
789–796.PubMed
Kessler, R. C., &
Waters, E. E. (1998). Epidemiology of DSM-III-R major depression
and minor depression among adolescents and young adults in the
National Comorbidity Survey. Depression and Anxiety, 7,
3–14.PubMed
Kovacs, M. (1989). Affective
disorders in children and adolescents. American Psychologist, 44,
201–215.
Kovacs, M. (1992).
Children’s Depression Inventory
(CDI). New York: Multi-Health Systems, Inc.
Kusche, C. A., Cook, E. T.,
& Greenberg, M. T. (1993). Neuropsychological and cognitive
functioning in children with anxiety, externalizing, and comorbid
psychopathology. Journal of
Clinical Child Psychology, 22, 172–195.
Last, C. G., Hersen, M.,
Kazdin, A. E., Finkelstein, R., & Strauss, C. C. (1987).
Comparison of DSM-I11 separation anxiety and overanxious disorders:
Demographic characteristics and patterns of comorbidity.
Journal of the American Academy of
Child Psychiatry, 26, 527–531.
Leech, S. L., Larkby, C. A.,
Day, R., & Day, N. L. (2006). Predictors and correlates of high
levels of depression and anxiety symptoms among children at age 10.
Journal of the American Academy of
Child and Adolescent Psychiatry, 45, 223–230.PubMed
Lenti, C., Giacobbe, A.,
& Pegna, C. (2000). Recognition of emotional facial expressions
in depressed children and adolescents. Perceptual and Motor Skills, 91,
227–236.PubMed
Lewinson, P. M., Hops, H.,
Roberts, R. E., Seeley, J. R., & Andrews, J. A. (1993).
Adolescent psychopathology: I: Prevalence, and incidence of
depression and other DSM-III-R disorders in high school students.
Journal of Abnormal Psychology,
102, 133–144.
Loney, B. R., & Frick,
P. J. (2003). Structured diagnostic interviewing. In C. R. Reynolds
& R. W. Kamphaus (Eds.), Handbook of psychological & educational
assessment of children: Personality, behavior, and context
(2nd ed., pp. 235–247). New York: Guilford Press.
Luxenberg, J. S., Swedo, S.
E., Flament, M. F., Friedland, R. P., Rapoport, J., & Rapoport,
S. I. (1988). Neuroanatomical abnormalities in obsessive-compulsive
disorders detected with quantitative X-ray computed tomography.
American Journal of Psychiatry,
145, 1089–1093.PubMed
Lyoo, I. K., Lee, H. K.,
Jung, J. H., Noam, G. G., & Renshaw, P. F. (2002). White matter
hyperintensities on magnetic resonance imaging of the brain in
children with psychiatric disorders. Comprehensive Psychiatry, 43,
361–368.PubMed
Mash, E. J., & Barkley,
R. A. (2006). Treatment of
childhood disorders (3rd ed.). New York: Guilford
Press.
Matthews, K. A., Manuck, S.
B., & Saab, P. G. (1986). Cardiovascular responses of
adolescents during a naturally occurring stressor and their
behavioral and psychophysiological predictors. Psychophysiology, 23,
198–209.PubMed
Mayberg, H. S. (1997).
Limbic-cortical dysregulation: A proposed model of depression. In
S. Salloway, P. Malloy, & J. L. Cummings (Eds.), The neuropsychiatry of limbic and subcortical
disorders (pp. 167–178). Washington, DC: American
Psychiatric Press.
McClellan, J., Kowatch, R.,
& Findling, R. L. (2007). Work group on quality issues.
Practice parameter for the assessment and treatment of children and
adolescents with bipolar disorder. Journal of the American Academy of Child &
Adolescent Psychiatry, 46 (1), 107–25.
McEwen, B. S. (1998).
Protective and damaging effects of stress mediators. New England Journal of Medicine, 322,
171–179.
Michael, K. D., &
Crowley, S. L. (2002). How effective are treatments for child and
adolescent depression?: A meta-analytic review. Clinical Psychology Review, 22,
247–269.PubMed
Mirescu, C., Peters, J. D.,
& Gould, E. (2004). Early life experience alters response of
adult neurogenesis to stress. Nature Neuroscience, 7 (8),
841–846.PubMed
Moffitt, T. E., Harrington,
H. L., Caspi, A., Kim-Cohen, J., Goldberg, D., Gregory, A. M., et
al. (2007). Depression and generalized anxiety disorder: Cumulative
and sequential comorbidity in a birth cohort followed prospectively
to age 32 years. Archives of
General Psychiatry, 64 (6), 651–660.PubMed
Munir, K., Biederman, J.,
& Knee, D. (1987). Psychiatric comorbidity in patients with
attention deficit disorder: A controlled study. Journal of the American Academy of Child and
Adolescent Psychiatry, 26, 844–848.PubMed
NIMH Bipolar Facts. (2008).
www.nimh.nih.gov/health/topics/bipolar-disorder/index.shtml.
Pennington, B. F. (2002).
The development of
psychopathology: Nature and nurture . New York: Guilford
Press.
Perlis, R. H., Miyahara, S.,
Marangell, L. B., Wisniewski, S. R., Ostacher, M., DelBello, M. P.,
et al. (2004). Long-term implications of early onset in bipolar
disorder: Data from the first 1000 participants in the systematic
treatment enhancement program for bipolar disorder (STEP-BD).
Biological Psychiatry, 55,
875–881.PubMed
Phan, K. L., Wager, T.,
Taylor, S. F., & Liberzon, I. (2002). Functional neuroanatomy
of emotion: A meta-analysis of emotion activation studies in PET
and fMR. Neuroimage, 16
(2), 333–348.
Pine, D. S. (2002). Brain
development and the onset of mood disorders. Seminars in Clinical Neuropsychiatry, 7
, 223–233, 57–67.PubMed
Pliszka, S. R. (2003).
Neuroscience of mental health
clinicians. New York, NY: Guilford Press.
Pliszka, S. R., Carlson, C.
L., & Swanson, J. M. (1999). ADHD with comorbid disorders . New
York, NY: Guilford Press.
Pomanski, E., Grossman, J.
A., Buchsbaum, Y., Banegas, M., Freeman, L., & Gibbons, R.
(1984). Preliminary studies of the reliability and validity of the
children's depression rating scale. Journal of the American Academy of Child
Psychiatry, 23, 191–197.
Quay, H. C., Peterson, D.
R., Radke-Yarrow, M., Cummings, E., Kuczynski, L., & Chapman,
M. (1985). Patterns of attachment in two- and three-year-olds in
normal families and families with parental depression. Child Development, 56, 884–893.
Rachman, S. J., &
Hodgson. (1991). Consequences of panic. Journal of Cognitive Psychotherapy, 5,
187–197.
Rapoport, J. L. (1986).
Childhood obsessive compulsive disorder. Journal of Child and Psychology and Psychiatry
and Allied Disciplines, 27, 289–295.
Recklitis, C. J., Lockwood,
R. A., Rothwell,M. A., & Diller, L. R. (2006). Suicidal
ideation and attempts in adult survivors of childhood cancer.
Journal of Clinical Oncology,
24, 3852–3857.PubMed
Reinherz, Gianconia, Hauf,
Wasserman, & Paradis, 2000
Reynolds, C. R., &
Kamphaus, R. W. (2004). Behavior
assessment system for children second edition. Circle Pines,
MN: American Guidance Service.
Reynolds, C. R., &
Richmond, B. O. (1978). What I think and feel: A revised measure of
children's manifest anxiety. Journal of Abnormal Child Psychology,
6, 27 l–280.
Reynolds, W. M. (1989).
Reynolds child depression
scale. Odessa, FL: Psychological Assessment Resources.
Ronsaville, D. S.,
Municchi, G., Laney, C., Cizza, G., Meyer, S. E., Haim, A., et al.
(2006). Maternal and environmental factors influence the
hypothalamic-pituitary-adrenal axis response to
corticotropin-releasing hormone infusion in offspring of mothers
with or without mood disorders.Development and Psychopathology, 18,
173–194.PubMed
Rosenbaum, J. F. (1988).
Course and treatment of manic depressive illness. Journal of Clinical Psychiatr, 49,
Supplement.
Rosso, I. M., Cintron, C.
M., Steingard, R. J., Renshaw, P. F., Young, A. D., &
Yurgelun-Todd, D. A. (2005). Amygdala and hippocampus volumes in
pediatric major depression. Biological Psychiatry, 57,
21–26.PubMed
Rush, A. J., Trivedi, M.
H., Wisniewski, S. R., Nierenberg, A., Stewart, J. W., Warden, D.,
et al. (2006). Acute and longer-term outcomes in depressed
outpatients who required one or several treatment steps: A STAR.D
Report. American Journal of
Psychiatry, 163 (11), 1905–17.PubMed
Satcher, D. (1999). Mental
health: A report of the surgeon general.
http://www.mentalhealth.org/special/surgeongeneralreport.
Semrud-Clikeman, M.,
Bennett, L., & Guli, L. (2003). Assessment of childhood
depression. In C. R. Reynolds & R. W. Kamphaus (Eds.),
Handbook of psychological and
educational assessment of children: Personality, behavior, and
context (2nd ed., 259–290). New York: Guilford Press.
Semrud-Clikeman, M., &
Hynd, G. W. (1991). Review of issues and measures in childhood
depression. School Psychology
International, 12, 275–298.
Shaffer, D., Gould, M. S.,
Fisher, P., Trautment, P., Moreau, D., Kleinman, M., et al. (1996).
Psychiatric diagnosis in child and adolescent suicide. Archives of General Psychiatry, 53,
339–348.PubMed
Shea, A., Walsh, C.,
MacMillan, H., & Steiner, M. (2004). Child maltreatment and HPA
axis dysregulation: Relationship to major depressive disorder and
post traumatic stress disorder in females. Psychoneuroendocrinology, 30,
162–178.
Shear, K., Jin, R., Ruscio,
A. M., Walters, E. E., & Kessler, R. C. (2006). Prevalence and
correlates of estimated DSM-IV child and adult separation anxiety
disorder in the National Comorbidity Survey Replication.
American Journal of Psychiatry,
163, 1074–1083.PubMedPubMedCentral
Silberg, J. L., Rutter, M.,
& Eaves, L. (2001). Genetic and environmental influences on the
temporal association between earlier anxiety and later depression
in girls. Biological Psychiatry,
49 (12), 1040–1049.PubMed
Silberg, J., Pickles, A.,
Rutter, M., Hewitt, J., Simonoff, E., Maes, H., et al. (1999).The
influence of genetic factors and life stress on depression among
adolescent girls. Archives of
General Psychiatry, 56, 225–232.PubMed
Silver, L. B. (1988). The
scope of the problem in children and adolescents. In J. G. Looney
(Ed.), Chronic mental illness in
children and adolescents (pp. 39–51). Washington, DC:
American Psychiatric Press.
Simon, G. E., Savarino, J.
Operskalski, B., & Wang, P. (2006). Suicide risk during
antidepressant treatment. American
Journal of Psychiatry, 163 (1), 41–47.PubMed
Spence, S. H., Rapee, R.,
McDonald, C., & Ingram, M. (2001). The structure of anxiety
symptoms among preschoolers. Behaviour Research and Therapy, 39,
1293–1316.PubMed
Spencer, T., Wilens, T.,
Biederman, J., Wozniak, J., & Harding-Crawford, M. (2000).
Attention-deficit/hyperactivity disorder with mood disorders. In T.
E. Brown (Ed.), Attention deficit
hyperactivity disorders and comorbidities in children, adolescents,
and adults (pp. 79–124). Washington, DC: American
Psychiatric Press.
Stark, K. D., Snader, J.,
Hauser, M., Simpson, J., Schnoebelen, S., Glenn, R., et al. (2006).
Depressive disorders during childhood and adolescence. In E. J.
Mash & R. A. Barkley (Eds.), Treatment of childhood disorders (3rd
ed., pp. 336–410). New York: Guilford Press.
Steingard, R. J. (2000).
The neuroscience of depression in adolescence. Journal of Affective Disorders, 61,
15–21.PubMed
Steingard, R., Biederman,
J., Doyle, A., & Sprich Buckminster, I. (1992). Psychiatric
comorbidity in attention deficit disorder: Impact on the
interpretation of child behavior checklist results. Journal of American Academy of Child and
Adolescent Psychiatry, 31, 449–454.
Steingard, R., Renshaw, P.,
Yurgelun-Todd, D., Appelmans, K., Lyoo, I. K., Shorrock, K., et al.
(1996). Structural abnormalities in brain magnetic resonance images
of depressed children. Journal of
the American Academy of Child & Adolescent Psychiatry,
35 (3), 307–311.
Strauss, C. C. (1990).
Anxiety disorders of childhood and adolescence. School Psychology Review, 19,
142–157.
Strauss, C. S. (1991).
Anxiety disorders of childhood and adolescence. School Psychology Review, 19,
142–157.
Strauss, C. C., Frame, C.
L., & Forehand, R. L. (1987). Psychosocial impairment
associated with anxiety in children. Journal of Clinical Child Psychology,
1, 235–439.
Strauss, C. C., Last, C.
G., Hersen, M., & Kazdin, A. (1988). Association between
anxiety and depression in children and adolescents with anxiety
disorders. Journal of Abnormal
Child Psychology, 15, 57–68.
Sullivan, P. F., Neale, M.
C., & Kendler, K. S. (2000). Genetic epidemiology of major
depression: review and meta-analysis. American Journal of Psychiatry, 157,
1552–1562.PubMed
Teeter Ellison, P. A.,
Eckert, L., Nelson, A., Platten, P., Semrud-Clikeman, M., &
Kamphaus, R. W. (2009). Assessment of behavior and personality in
the neuropsychological diagnosis of children. In C. R. Reynolds
& Fletcher-Jensen, E. (Eds.), Handbook of clinical child
neuropsychology (2nd ed.). New York: Plenum Press.
Teeter Ellison, P. A.,
& Nelson, A. (2008). Brain development: Evidence of gender
differences. In E. Fletcher-Janzen (Ed.), Introduction to the neuropsychology of
women . New York: Springer
Templer, D. I. (1972). The
obsessive-compulsive neurosis: Review of research findings.
Comprehensive Psychiatry,
13, 375–383.PubMed
Torgesen, J. K. (1986).
Genetic factors in moderately severe and mild affective disorders.
Archives of General Psychiatry,
43, 222–226.
Tramontana, M., &
Hooper, S. (1989). Neuropsychology of child psychopathology. In C.
R. Reynolds & E. Fletcher-Janzen (Eds.), Handbook of clinical child
neuropsychology (pp. 87–106). New York: Plenum Press.
Treatment for Adolescents
with Depression Study Team. (2004). Fluoxetine,
cognitive-behavioral therapy, and their combination for adolescents
with depression: Treatment for Adolescents with Depression Study
(TADS) randomized trial. JAMA,
292, 807–820.
Valla, J., Bergerson, L.,
& Smolla, N. (2000). The dominic-R: A pictorial interview for
6- to 11- year old children. Journal of the American Academy of Child and
Adolescent Psychiatry, 39, 85–93.PubMed
Venken, T., Claes, S.,
Sluijs, S., Paterson, A. D., van Duijn, C., Adolfsson, R., et al.
(2005). Genomewide scan for affective disorder susceptibility loci
in families of a northern Swedish isolated population. American Journal of Human Genetics, 76,
237–248.PubMed
Weaver, I. C., Cervoni, N.,
Champagne, F. A., D’Alessio, A. C., Sharma, S., Seckl, J. R., et
al. (2004). Epigenetic programming of maternal behavior.
Nature Neuroscience, 7 (8),
847–854.PubMed
Weingartner, H., Gold, P.,
Ballenger, J. D., Smallberg, S. A., Summers, R., Rubinow, D. R.
(1981). Effects of vasopressin on human memory functions.
Science, 211,
601–603.PubMed
Weissman, M. M., Pilowsky,
D. J., Wickramaratne, P. J., Talati, A., Wisniewski, S. R., Fava,
M., et al. (2006). Remission in maternal depression and child
psychopathology: A STAR*D-Child report. JAMA, 295, 1389–1398.PubMed
Weissman, M. M., Wolk, S.,
Goldstein, R. B., Moreau, D., Adams, P., Greenwald, S., et al.
(1999). Depressed adolescents grown up. Journal of the American Medical Association,
281, 1707–1713.PubMed
Zisook, S., Lesser, I.,
Stewart, J. W., Wisniewski, S. R., Balasubramani, G. K., Fava, M.,
et al. (2007). Effect of age at onset on the course of major
depressive disorder. American
Journal of Psychiatry 164, 1539–1546.PubMed