Journal of Toxicology and Environmental Health, Part B, 16:127–283, 2013
Published with license by Taylor & Francis
ISSN: 1093-7404 print / 1521-6950 online
PESTICIDE EXPOSURE AND NEURODEVELOPMENTAL OUTCOMES: REVIEW
OF THE EPIDEMIOLOGIC AND ANIMAL STUDIES
Carol J. Burns1, Laura J. McIntosh2, Pamela J. Mink3, Anne M. Jurek3, Abby A. Li4
1The Dow Chemical Company, Midland, Michigan, USA
2SafetyTox, LLC, Santa Clara, California, USA
3Allina Health Center for Healthcare Research & Innovation, Minneapolis, Minnesota, USA
4Exponent, Inc., Menlo Park, California, USA
Assessment of whether pesticide exposure is associated with neurodevelopmental outcomes
in children can best be addressed with a systematic review of both the human and animal
peer-reviewed literature. This review analyzed epidemiologic studies testing the hypothe-
sis that exposure to pesticides during pregnancy and/or early childhood is associated with
neurodevelopmental outcomes in children. Studies that directly queried pesticide exposure
(e.g., via questionnaire or interview) or measured pesticide or metabolite levels in biological
specimens from study participants (e.g., blood, urine, etc.) or their immediate environ-
ment (e.g., personal air monitoring, home dust samples, etc.) were eligible for inclusion.
Consistency, strength of association, and dose response were key elements of the frame-
work utilized for evaluating epidemiologic studies. As a whole, the epidemiologic studies
did not strongly implicate any particular pesticide as being causally related to adverse
neurodevelopmental outcomes in infants and children. A few associations were unique for
a health outcome and specific pesticide, and alternative hypotheses could not be ruled out.
Our survey of the in vivo peer-reviewed published mammalian literature focused on effects
of the specific active ingredient of pesticides on functional neurodevelopmental endpoints
(i.e., behavior, neuropharmacology and neuropathology). In most cases, effects were noted at
dose levels within the same order of magnitude or higher compared to the point of departure
used for chronic risk assessments in the United States. Thus, although the published animal
studies may have characterized potential neurodevelopmental outcomes using endpoints not
required by guideline studies, the effects were generally observed at or above effect levels
measured in repeated-dose toxicology studies submitted to the U.S. Environmental Protection
Agency (EPA). Suggestions for improved exposure assessment in epidemiology studies and
more effective and tiered approaches in animal testing are discussed.
The potential developmental effects of
environmental chemical exposures have been
studied for several decades and remain a
topic of considerable interest (Bjorling-Poulsen
et al., 2008; Bruckner, 2000; Grandjean and
© Carol J. Burns, Laura J. McIntosh, Pamela J. Mink, Anne M. Jurek, and Abby A. Li
The authors are grateful to the European Crop Protection Association (ECPA) for funding this review article. We acknowledge impor-
tant technical and editorial contributions by Dr. Jason Richardson, Dr. Kimberly Lowe, Rebecca Edwards, and Susan Dixon. ECPA is
the trade association for the research and development based crop protection industry in Europe. Dr. Carol Burns is an epidemiologist
employed by The Dow Chemical Company, a producer of several pesticides. Drs. Abby Li, Laura McIntosh, Pamela Mink, and Anne Jurek
are or have previously been employed by Exponent, Inc., a research and scientific consultant firm with clients from industry (including
crop protection) and government. The analyses, conclusions, and opinions expressed in this article are solely those of the authors.
Address correspondence to Abby A. Li, PhD, Attn: Rebecca Edwards, Exponent, Inc., Health Sciences Group, 149 Commonwealth
Drive, Menlo Park, CA 94025-1133, USA. E-mail: firstname.lastname@example.org
Landrigan, 2006; Mendola et al., 2002; Rice,
2005; Wigle et al., 2007, 2008). In particular,
the potential effects of pesticide exposures to
the developing fetus and child are of interest to
society and regulatory agencies. Although the
128 C. J. BURNS ET AL.
neurotoxic associations of high level prenatal
and early childhood exposure to certain
pesticides are well established (Eaton et al.,
2008), the implications of potential effects
observed at low exposures are less straightfor-
ward, particularly in the absence of a clinically
defined adverse outcome. Studies evaluating
potential neurodevelopmental effects associ-
ated with pesticide exposure are challenging
to interpret, in part because of the diversity
of types and classes of chemicals, differences
in exposure measures, and the wide range of
instruments used to assess outcomes (Rice,
2005). Nevertheless, it is important to critically
evaluate the evidence to date, as well as to
identify important research gaps and method-
ological issues that require further attention
in order to advance our understanding of
Neurodevelopmental deficits include a
broad spectrum of disorders and dysfunctions
such as autism spectrum disorder, atten-
tion deficit hyperactivity disorder (ADHD),
decreased intelligence, learning disabilities,
developmental delays, emotional or behavioral
problems, and deficits in gross or fine motor
skills. The exact prevalence of these deficits
is difficult to ascertain; however, it has been
estimated that approximately 3 to 8% of infants
and 12% of children are affected by one or
more of these conditions (National Academy
of Sciences, 1988). This phenomenon provides
sufficient motivation in the scientific and med-
ical communities to identify factors that may
contribute to adverse events in the developing
Findings from human and animal stud-
ies demonstrated that some environmental
contaminants may be toxic to the developing
neurological system (Hass, 2006), and it was
suggested that approximately one quarter of
developmental disorders can be attributed
and Landrigan, 2006; National Academy of
Sciences, 2000). However, the extent to which
these exposures influence the incidence of
developmental deficits and the exact mecha-
nisms for initiation and progression are unclear
(Hass, 2006). The development of the nervous
system extends beyond birth into childhood
and adolescence (Watson et al., 2006); how-
ever, the critical periods of development are
most likely to occur in utero (Rice and Barone,
2000). Neurulation, the process by which
the central nervous system develops during
embryogenesis, begins in the third week of
gestation in humans (DeSesso et al., 1999;
Desesso, 2012). The human brain develops
from a small number of cells located on the
epiblast into the central nervous system that
contains billions of specialized cells (Grandjean
and Landrigan, 2006). Exposure to environ-
during specific periods of development may
impair neurologic development in children.
Numerous studies were conducted in humans
and animals to evaluate the potential effect
of myriad exposures, including environmental
contaminants, on neurologic development.
Research on pesticide exposure has been
increasing, particularly over the past two
decades (Arcury et al., 2006). Billions of pounds
of pesticides (including herbicides, insecticides,
rodenticides, etc.) are used throughout the
world for agricultural purposes and in residen-
tial homes and gardens for crop protection and
pest management. Several studies showed that
agricultural workers have substantially greater
opportunity for pesticide exposure than the
population at large (Curl et al., 2002; Fenske
et al., 2002; McCauley et al., 2001; O’Rourke
et al., 2000; Curwin et al., 2007). In addi-
tion, biomonitoring data indicate that expo-
sures to farm spouses and children are deter-
mined largely by the degree of direct contact
with the application process, and that expo-
sure profiles varied by specific chemical for
each family member (applicator, spouse, chil-
dren) (Thomas et al., 2010; Curl et al., 2002;
Mandel et al., 2005). In the general popu-
lation, there is also evidence to suggest that
contact with pesticides or their residues is
widespread (Barr et al., 2005). Pregnant women
and children may be vulnerable to these
exposures (Berkowitz et al., 2003). Further,
young children are thought to have increased
opportunities for pesticide exposure because
of dietary and physical behaviors (Barr et al.,
PESTICIDES AND NEURODEVELOPMENTAL OUTCOMES 129
There have been relatively few evaluations
of both the animal and human literature on
the effects of pesticides on neurodevelopment.
Previous reviews focused primarily on summa-
rizing significant adverse associations reported
in the epidemiology literature or significant
adverse associations on neurodevelopmental
endpoints in the animal literature (Weselak
et al., 2007; Bjorling-Poulsen et al., 2008;
Julvez and Grandjean, 2009; Wigle et al., 2007,
2008). These reviews have not included a sys-
tematic evaluation of both the absence and
presence of outcomes, or an evaluation of
the evidence for and against a causal inter-
pretation, or integrated the outcomes reported
in analytic epidemiology studies with mecha-
nisms of action determined by animal studies.
In addition, for the most part, the reviews of
the animal literature summarize the findings as
reported by the primary authors of the original
papers and do not include a discussion of how
the reported effect levels compare with no-
observed-adverse-effect levels (NOAELs) deter-
mined by subchronic and chronic toxicity stud-
ies that are used to derive reference doses
(RfDs) and other acceptable levels of exposure
for the general population.
The objective of the current review was to
compile the epidemiologic studies that eval-
uate potential associations between exposure
to specific pesticides in pregnant or nursing
women or in infants or young children and
neurobehavioral outcomes or head circumfer-
ence in infants or young children. Further in
vivo mammalian literature evaluating the effects
of pesticides on functional neurodevelopmental
endpoints was surveyed. The epidemiology and
animal literature was systematically reviewed
with respectto the
(1) What is the evidence of causality between
exposure to specific pesticides (or classes of
pesticides) during critical periods of brain
development and neurobehavioral outcomes
in the epidemiologic literature? (2) What are
the lowest dose levels for adverse functional
neurodevelopmental effects in animals in the
published literature, and how do they com-
pare with effect levels from repeat dose toxicity
studies used to derive the chronic RfD? In
addition, an evaluation of the types of devel-
opmental neurotoxicity (DNT) studies that were
submitted to the U.S. Environmental Protection
Agency (EPA) in comparison with other stud-
ies that contribute toward defining the chronic
RfD was provided based on publically avail-
able information on the U.S. EPA Office of
Pesticide Program’s websites or in the published
APPROACH TO EVALUATION OF
Our review of the epidemiologic studies
began with identification, documentation, and
evaluation of the reported associations in the
peer-reviewed literature. Distinguishing causal
from noncausal effects is particularly challeng-
ing in epidemiology because of observational
study designs and the inevitable role of chance,
bias and confounding. These methodological
challenges, which are inherent to epidemiol-
ogy studies, are critical for causal interpretation.
In addition, comparison of study methodology
(including characteristics of the study popu-
lation, timing of exposure measurement, and
neurobehavioral testing) is essential in order
to interpret similarities and differences in out-
comes observed across studies. Careful atten-
tion to the type and specificity of exposure
metrics and to the validity of methods used in
measuring outcomes is also important in evalu-
ating the evidence for and against causality.
There are several guideposts to consider
when evaluating the evidence from a body of
epidemiologic literature, including strength of
the association (e.g., magnitude of the relative
risk estimate or regression coefficient), consis-
tency, dose response, and biological plausibility
(Hill, 1965). Although these principles are not
criteria per se, the U.S. EPA has recommended
using them to evaluate epidemiology data in
its “Draft Framework for Incorporating Human
Epidemiologic & Incident Data in Health Risk
Assessment” (U.S. Environmental Protection
Agency, 2010a). The “strength” of association is
an arbitrary term for the magnitude of a relative
risk (RR) estimate (e.g., odds ratio, risk ratio, or
130 C. J. BURNS ET AL.
rate ratio). The strength (magnitude) of a regres-
sion coefficient is less straightforward since the
estimate is reflective of statistical transformation
and the unit of measure (e.g., inches or cen-
timeters). In addition to strength of association,
the precision of the confidence interval was also
considered. Poole (2001) recommended com-
puting the confidence interval ratio to consider
the stability of relative risk estimates with wide
intervals, particularly for small studies. Since
“precision” is no better defined than “strong,”
for the purposes of this review, the confidence
intervals and the resulting relative risk estimates
or regression coefficients were considered to
be “imprecise” if the ratio of the upper ver-
sus lower limit was greater than 5. Statistical
significance of a positive or negative associ-
ation was determined if the 95% confidence
interval excluded the null value. Risk estimates
for which the p value was less than .05 were
considered statistically significant and were dis-
cussed in this context. Statistically significant
risk estimates with narrow confidence intervals
were given greater weight than imprecise risk
estimates with large confidence intervals. The
direction of nonstatistically and imprecise sig-
nificant associations was not considered to be
evidence of consistency. Statistical significance
incorporates strength of association and sam-
ple size into its calculations, ruling out the role
of chance, particularly in the direction of the
Consistency was viewed as observing simi-
lar exposure-outcome associations either inter-
nally within the same population or externally
in independent studies. However, the observa-
tional nature of epidemiology permits pesticide
exposure to be analyzed with varying levels
of specificity. Therefore, consistency was evalu-
ated on a continuum of specificity of exposure
both within and across studies. Replications of
associations were of particular interest when
related to a specific pesticide exposure or
biomarker and a specific health outcome. For
example, an adverse association of an outcome
such as lower motor development index and
increased urinary organophosphate would be
considered to be consistent with an adverse
association between motor development index
study. However, the specific organophosphate
metabolite malathion dicarboxylic acid (MDA)
in one study would not provide good corrobo-
ration of specific results of sum of diethylphos-
phate metabolite levels (?DEP) in another
?DEP . Adverse health associations from differ-
not considered to be evidence of consistency
because different tests are designed to mea-
sure different domains. An example would be
a longitudinal study reporting adverse associ-
ations observed with Bayley’s motor develop-
ment index at age 12 mo and with Bayley’s
mental developmental index at age 36 mo.
epidemiologic studies suffer from some degree
of bias (i.e., systematic error) and confounding,
there was a particular emphasis on evidence of
replication of exposure-outcome associations
in independent studies. Several epidemiologic
studies included multiple agents or outcomes;
in this case, “positive” or “significant” results
can be easily generated by chance only. This
emphasizes the importance of consistency of
results among independent studies.
Although dose response is a requirement
for guideline animal studies, the observational
nature of epidemiologic studies and expo-
sure measurement limitations often precludes
a quantitative assessment of dose response.
Typically, “doses” are established based on the
distribution of the data post hoc, for example,
into tertiles or quartiles. It might be efficient to
collapse the groups into high and low expo-
sure levels; however, this essentially eliminates
the ability to determine an exposure-response
trend. If data are continuous, general linear
regression models maintain the ability to test
for a response trend. However, they cannot
test for other forms of monotonic exposure-
response relationships. Where available, cate-
gorical analyses with at least three exposure
levels or continuous modeling were considered
includes the question of whether the findings
from the epidemiologic studies are consistent
urinary organophosphatein another
because malathion does not metabolize to
ent tests conducted in the same cohort were
PESTICIDES AND NEURODEVELOPMENTAL OUTCOMES 131
with data from comparable animal studies.
While simple to describe, this concept is more
difficult in practice. The specific endpoints do
not always match, especially for neurobehavior.
Internal dose for humans must be estimated
for the critical periods based on available data.
This was summarized as the integration of the
epidemiology and animal sections. Since many
of the exposure measures were collected at just
one or two points in time, no evaluation of tim-
ing of exposure during pregnancy was possible.
whether the epidemiologic data indicate a
strong, consistent pattern of causality across
studies from exposures to a specific pesticide
(or class of pesticides) with neurobehavioral
outcomes in infants or young children or with
head circumference at birth.
SCOPE OF THE EPIDEMIOLOGY REVIEW
AND INCLUSION CRITERIA
This review evaluated epidemiologic stud-
ies that reported information regarding expo-
sure to pesticides during critical periods of
brain development (i.e., in utero, infancy, or
early childhood) and neurodevelopmental end-
points measured in infancy or early child-
hood or head circumference measured in new-
borns. Although outcomes in adolescents may
be related to in utero exposures, the cur-
rent review is limited to outcomes in new-
borns and early childhood. Endpoints of interest
included behaviorally defined outcomes (e.g.,
pervasive developmental disorder or PDD as
measured by the Child Behavior Checklist or
CBCL) and subclinical deficits or differences
in performance on neurobehavioral tests (e.g.,
Bayley Scales of Infant Development or BSID).
All epidemiologic studies published in English
and available in print or in electronic form in
MEDLINE by April 30, 2011, were included.
The search did not apply limitations on the geo-
graphic location of the study. Studies that ascer-
tained pesticide exposure data by question-
naires, environmental monitoring (e.g., air, soil,
dust), or biomarkers were eligible for inclusion
provided that exposure to specific pesticides or
classes of pesticides was measured or queried
directly. Publications with inferred exposures
were not included. For example, studies for
which exposure data were limited to questions
such as “Have you ever lived on a farm?” did
not meet the inclusion criteria because determi-
nation of exposure to pesticide per se could not
be identified. In contrast, exposure data from
questions such as “Have you ever applied pes-
ticides?” were considered. Studies that reported
pesticide poisoning or exposures at acute or
toxic levels beyond the directed or approved
level of use were also excluded, as were pes-
ticide biomonitoring studies that reported pes-
ticide levels in biologic specimens but did not
evaluate health outcomes.
Exposure Measurements: Specific and
Nonspecific Biomarkers of Pesticide
Most of the epidemiologic studies included
in this review were studies in which biomarkers
of pesticide exposure were measured directly
from maternal blood during pregnancy, mater-
nal urine during pregnancy, cord or placental
blood of the infant directly after birth, infant or
child urine, or breast milk during pregnancy.
Where possible, this review summarized
results for specific pesticides. Some studies
reported associations between the outcomes of
interest and the parent compound or a specific
biomarker, while others reported biomarkers
of exposure to the class of pesticide. The fol-
lowing broad categories were used to group
pesticides and address similar mechanisms of
action: organophosphate (OP), organochlorine
(OC), N-methyl carbamate, pyrethroid, and
other pesticides. In order to provide a summary
of the existing data, results were provided and
discussed for the specific pesticides, as well as
broad classes where available.
A brief description of the main biomarkers
for OP and OC pesticides evaluated in the
studies that met the inclusion criteria follows.
Limited space did not permit a description of
every biomarker that was evaluated. Readers
are referred to the original papers for further
details and information.
132 C. J. BURNS ET AL.
Many of the OP insecticides metabolize to
the broad class of dialkyl phosphates (DAP)
that can be measured in urine, and repre-
sent the sum of diethylphosphates (?DEP)
and Stone, 2011). Urinary
10 OP insecticides
(CPF) and diazinon. The?DMP are a broad
17 methyl OP insecticides including malathion
and chlorpyrifos methyl (a pesticide registered
separately from CPF because of structural and
metabolic differences from CPF). (Barr et al.,
2004)In urine, 3,5,6-trichloro-2-pyridinol
(TCPy) is the more specific biomarker of
CPF exposure, as well as TCPy residues in
the environment or diet (Barr and Angerer,
2006). Malathion exposure is estimated by
the metabolite malathion dicarboxylic acid
(MDA), and parathion and methylparathion
are estimated by the metabolite 4-nitrophenol
(PNP) (Eskenazi et al., 2004). CPF and diazinon
can be measured directly in blood. In general,
the biological half-life of all OP pesticides is
relatively short; for example, the half-life of
CPF in blood and urine ranges from 15–24 h
and the half-life of malathion in blood is less
than 1 h (Barr and Angerer, 2006).
Organochlorine (OC) insecticides
OC include insecticides such as aldrin, chlor-
dane, dichlorodiphenyl-trichloroethane (DDT),
and mirex. In contrast to the OP insecticides,
which are rapidly cleared in hours, the OC
pesticides have a half-life of several years.
(Longnecker et al., 1997). The long half-life
has implications for exposure measurement
in epidemiologic studies. Since the chemi-
cals are persistent in the body tissue, there
is less day-to-day variability in internal expo-
sure levels as compared to an OP that is
rapidly cleared from the body. The commer-
cial grade DDT that was once applied to
crops was a mixture of p,p’–DDT (approxi-
mately 85%), o,p’-DDT (approximately 15%),
and trace amounts of o,o’-DDT (Agency for
Toxic Substances and Disease Registry, 2002).
Dichlorodiphenyl-dichloroethylene (DDE) and
and dimethylphosphates (?DMP) (Sudakin
class of dimethylphosphate metabolites of
the metabolites and breakdown products of
DDT in the environment. DDT, DDE, and DDD
can be measured in fat, blood, urine, and
breast milk. The half-life of DDT is about 7 yr,
and that of DDE is longer (Longnecker et al.,
1997). Because the relation of biological half-
lives of DDT compounds is DDE > DDT >
DDD, detection of higher ratios of DDD or
DDT to DDE is postulated to indicate more
recent exposure while lower ratios are pre-
sumed to indicate longer term exposure and
storage capacity. Notably, decades after DDT
use was banned in most countries, virtually all
of the general population is exposed to the
metabolite DDE through the diet.
Paraoxonase (PON1) Activity and
Included were studies evaluating the inter-
action between PON1 enzyme activity or
genotype and pesticide exposure. Reports of
main effects of PON1 enzyme activity or
genotype were not the focus of this review and
were only considered in relationship to pes-
ticide exposure. Briefly, PON1 is an enzyme
that is capable of metabolizing the active
metabolites (oxons) of certain OP insecticides.
Variation in PON1 polymorphism influences
the speed with which individuals detoxify oxon
metabolites of OP . Reduced PON1 activity may
be related to higher toxicity as a result of
reduced detoxification of the oxon (Furlong
et al., 1988). Animal experiments indicated
that PON1 exerts protection against OP tox-
icity, depending on the specific OP com-
pound (Costa et al., 2012). Based on physio-
logically based pharmacokinetic and pharma-
codynamic modeling, Timchalk et al. (2002)
predicted that at low, environmentally rele-
vant exposures to CPF other metabolic sys-
tems redundant to PON1 will compensate for
slower PON1 activity. Thus, the significance of
the role of PON1 status in modulating toxic-
ity at lower levels of exposure to the parent
OP insecticides is uncertain (Timchalk et al.,
2002; Cole et al., 2005; Costa et al., 2012).
PON1 enzyme activity is considered to be
PESTICIDES AND NEURODEVELOPMENTAL OUTCOMES133
a more reliable measure of PON1 functional
activity than PON1 genotype (Furlong et al.,
2005; Cole et al., 2005). As will be dis-
cussed in greater detail in the results section,
two cohort studies (Mt. Sinai and University
of Berkeley Center for the Health Assessment
of Mothers and Children of Salinas) evaluated
PON 1 activity and/or polymorphisms in DNA
(Berkowitz et al., 2004; Engel et al., 2007;
Eskenazi et al. 2010). Both epidemiology stud-
ies focused on the PON1Q192Rpolymorphism
in DNA, which is based on whether the amino
acid present at position 192 is glutamine (Q)
or arginine (R). Some studies estimate that the
R form has eight- to ninefold higher catalytic
activity than the Q form and hence provides
more resistance to the acute toxicity of OP at
higher doses (Furlong et al., 2005; Cole et al.,
2005). Therefore, mothers homozygous for the
Q192 alloform (QQ) would be predicted to
have increased sensitivity to certain OP com-
pared to those homozygous for the R192
Head circumference and neurobehavioral
outcomes were evaluated. All studies of head
circumference measurements were based on
data obtained directly after birth and were often
abstracted from hospital or patient records.
Head circumference was included because
some investigators have related newborn head
circumference with neurodevelopmental out-
comes such as reduced intelligence in children
(Ivanovic et al., 2004). The other outcomes
included measures of psychomotor develop-
ment, behavior, attention, and intelligence
using standard tests and indices. Following is
a brief description of the main assessment
tools used in the papers in this review, pre-
sented in alphabetical order. Space does not
permit a summary of every instrument used.
Readers are referred to the original papers
and their reference sections for additional
• Brazelton Neonatal Behavioral Assessment
Scale (BNBAS): The BNBAS groups the
measurement of behavioral abilities and
reflexes into the following seven domains:
habituation, orientation, motor performance,
range of state, regulation of state, autonomic
stability, and number and type of abnormal
reflexes (Brazelton and Nugent, 1995). This
test is used by physicians, psychologists, and
other health professionals to describe indi-
vidual differences in information processing
and regulation observed in newborns up to
2 mo of age. This test is also referred to
as the Neonatal Behavioral Assessment Scale
• Bayley Scales of Infant Development II (BSID).
The BSID was developed to assess motor
and mental development in infants, age 1 to
42 mo. The Mental Development Index
(BSID:MDI) assesses general cognitive devel-
opment and higher order mental process-
ing, with 178 individual items that measure
memory, habituation, generalization, classifi-
cation, vocalizations, visual preference, visual
acuity skills, problem solving, early num-
ber concepts, language, and social skills
and development (Black and Matula, 2000;
Sattler, 2001; Strauss et al., 2006). The
Psychomotor Development Index (BSID:PDI)
assesses overall motor development and con-
tains 111 items that measure quality of move-
ment, sensory integration, motor planning,
fine and gross motor skills, and perceptual-
motor integration (Black and Matula, 2000;
Strauss et al., 2006). Standardized scores for
the BSID:MDI and BSID:PDI have a mean
of 100 and a standard deviation of 15, and
range from 50 to 150.
• Child Behavior Checklist (CBCL): The CBCL is
administered to parents of children 1.5 to 5 yr
of age to measure emotional and behavioral
problems that have occurred in the previ-
ous two mo (Achenbach and Rescorla, 2000).
The CBCL generates results for nine scales
that are completed by the parent: adapt-
ability, aggression, anxiety, attention prob-
lem, atypicality, conduct problems, depres-
sion, hyperactivity, leadership, social skills,
somatization, and withdrawal. The results of
the CBCL are consistent with the Diagnostic
and Statistical Manual of Mental Disorders,
134 C. J. BURNS ET AL.
4th edition (DMS–IV), diagnoses (American
Psychiatric Association, 2000). The CBCL
uses the parent’s ratings of 99 problem items
as: 0 = not true, 1 = somewhat or sometimes
true, 2 = very true or often true, within the
past 2 mo (Rescorla, 2005). The scores are
obtained by summing the subtotal items for
each child and then the total problem score is
summed for all of the items combined. Each
subscale may be scored continuously or cat-
egorically as normal, borderline, or clinical
range (Rescorla, 2005).
• Continuous Performance Test (CPT): The stud-
ies that implemented the CPTs in our review
used a version of the test referred to as
the Michigan Catch-the-Cat Test (version
1.2) (Jacobson et al., 1992), CPT with pic-
tures from the Neurobehavioral Evaluation
System 2 (NES2), and the Conners’ Kiddie
Performance Test (K-CPT) (Marks et al.,
2010). These tests measure sustained atten-
tion or impulsivity to children preschool ages
(4–5 yr) and older. Most of the tests involve
presenting a visual stimulus on a computer
screen to the child at variable intervals. The
child’s task is to indicate (e.g., by pressing
a button) when the target stimulus (e.g., a
ball) is presented. A record is kept of the
number of correct responses, the number of
misses, and the number of times the child
responds to an incorrect stimulus. Separate
scores are derived for attention, reaction
time, and impulsivity. Scores may be influ-
enced by anxiety, fatigue, boredom with the
task, use of cold medication, and other prob-
lems that may interfere with concentration
(Sattler and Hoge, 2006). It is recommended
that CPT scores “never be used indepen-
dently to make a diagnosis about ADHD”
(Sattler and Hoge, 2006, p. 380).
• NEPSY-A Developmental Neuropsychological
Assessment; Visual Attention Subtest: The
NEPSY is a neuropsychological test for chil-
dren ages 3–12 yr, consisting of 27 subtests,
which are divided into a core battery and
a full battery. The visual attention subtest
instructs children to scan an array of pictures
and circle the “target” picture as quickly and
accurately as possible. Speed and accuracy
are measured. This subtest is part of the
Attention/Executive Functions domain of the
• Fagan Test of Infant Intelligence (FTII): The FTII
is a test of visual recognition memory, uti-
lizing a “novelty problem” paradigm (Fagan
and Detterman, 1992; Benasich and Bejar,
1992). First, infants are presented with one
picture or two identical pictures to study for
a preset accumulated looking time. Then, the
now-familiar picture is paired with a new or
novel picture. A novelty preference score is
computed for each test item by dividing the
time spent looking at the novel picture during
the test trial by the total amount of look-
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