Bibliography
American Psychiatric Association. (2013). Diagnostic and statistical manual of mental disorders (5th
ed.). Arlington, VA: American Psychiatric Publishing.
The DSM-5, as this edition of The Diagnostic and Statistical Manual of Mental Disorders (5th
ed.; DSM–5; American Psychiatric Association, 2013) is referred to in brief, is used for the
diagnosis of psychiatric disorders in the United States and worldwide. It is considered the
authoritative reference, presenting diagnostic criteria in terms of symptom qualifiers, as well as
symptom frequency and severity. It also presents known overview-level information about
etiology, comorbidity, and prognosis of each disorder. Before the DSM came into being in the
1950s, the US Census Bureau collected statistical data on “manias” and other specific
psychiatric and medical conditions and published a statistical manual for the use of institutions
for the insane. The DSM filled a need for a system of classification that could be used for
systematic diagnosis. Each edition has incorporated the growing understanding of
neuropsychiatric phenomena and improved organization and specificity for diagnostic criteria, as
well as an increasing list of disorders described.
Center for Disease Control. (2018, September 21). Attention-Deficit / Hyperactivity Disorder (ADHD).
Retrieved from https://www.cdc.gov/ncbddd/adhd/data.html
This website from the CDC presents statistical information about ADHD prevalence, comorbidities, treatment methodologies, diagnostic criteria and methodologies, and epidemiology
both nationally and state-based.
Chang, L., Wang, M., & Tsai, P. (2016). Diagnostic accuracy of rating scales for attentiondeficit/hyperactivity disorder: A meta-analysis. Pediatrics, 137(3), e20152749.
doi:10.1542/peds.2015-2749
Chang et al. present an evaluation and comparison of the sensitivity and specificity of 2 ADHD
rating scales, the Child Behavior Checklist (CBCL) and Conners Rating Scale-Revised (CRS-R).
They used standardized statistical methods designed for diagnostic testing accuracy evaluations.
The data were derived from a review of the literature in which study populations were children
ages 3-18. This meta-analysis determined that CBCL and CRS-R have comparable and
satisfactory sensitivity and accuracy, as well as comparable diagnostic performance. The study
was unable to determine, however, the quality of overall diagnostic performance.
Fair DA, Posner J, Nagel BJ, Bathula D, Dias TG, Mills KL, Blythe MS, Giwa A, Schmitt CF, Nigg J.T.
(2010). Atypical default network connectivity in youth with attention-deficit/hyperactivity disorder.
Biol Psychiatry. 2010 Dec 15;68(12):1084-91.
The researchers identify ADHD as a “major public health concern” with significant impacts to
health and education and are the first I have seen to refer to this disorder as a gateway condition
for other psychiatric problems such as depression, conduct disorder, substance abuse and
personality disorders (known co-existing conditions). They discuss the progression of
understanding of the default mode network, presumably from its former supposed role in resting
brain state, to current thinking about its relationship to executive function and reward
processing. Prior studies have established a link between default network connectivity
impairment and ADHD. The purpose of this study was to investigate developmental changes in
default mode network functionality in children with and without ADHD, using functional
connectivity magnetic resonance imaging (fcMRI). The process of participant recruitment and
exclusion criteria are discussed, resulting in a sample size of 46 children. Rigorous data analysis
methods were used to examine group differences in DMN connectivity, and confirmed through
analysis of potential outlier effects (gender), threshold variability, and outlier effects (through
bootstrapping), and each analysis confirmed the original finding: functional connections in the
DMN in children with ADHD were weaker than children without ADHD – though these
findings did not end up being statistically significant after correction – and ‘spontaneous
correlated activity’ within the network is reduced in these children compared to typicallydeveloping children. Predictions related to maturation were well-supported and it seems that the
authors will continue to follow these children over time. Possible causal factors related to
ADHD may be altered myelination which affects network connectivity, or delayed or disrupted
maturation of the network, both of which are suggested by the data as future avenues for
research. The authors did not distinguish subtypes of ADHD in this study, partly because of the
loss of power associated with stratifying the data and partly because of growing disagreement
about the validity of these subtypes based on neurobiological research.
Fair, D. A., Nigg, J. T., Iyer, S., Bathula, D., Mills, K. L., Dosenbach, N. U., Schlaggar, B. L., Mennes,
M., Gutman, D., Bangaru, S., Buitelaar, J. K., Dickstein, D. P., Di Martino, A., Kennedy, D. N.,
Kelly, C., Luna, B., Schweitzer, J. B., Velanova, K., Wang, Y. F., Mostofsky, S., Castellanos, F. X.,
Milham, M. P. (2013). Distinct neural signatures detected for ADHD subtypes after controlling for
micro-movements in resting state functional connectivity MRI data. Frontiers in systems
neuroscience, 6, 80. doi:10.3389/fnsys.2012.00080
The authors make the argument that while magnetic resonance imaging (MRI) holds great
promise for understanding neural processes involved in psychiatric disorders, there is a need for
large data sets and methods to separate noise from the phenomenon under study in these images.
They propose some data-processing methods to reduce artifacts due to motion which allow them
to study a large pooled dataset including 455 typically-developing children and 193 children
with ADHD. The data, corrected for artifacts imposed by micro-movements in the imaging
process, show support for current hypotheses which view ADHD as an abnormality in brain
connectivity rather than a regional brain deficit. The most interesting finding of this study
showed distinct patterns of atypical connectivity relative to diagnosed ADHD subtype. The
Inattentive subtype was associated with atypical connectivity in the frontoparietal network,
which is responsible for task control, which may account for inattentive behaviors. Conversely,
the Combined Subtype was associated with connectivity abnormalities in the Default Mode
Network, the brain network responsible for remembering past events and connecting those to
planning for/anticipating events in the future, a known deficit in children with ADHD with
respect to consequence anticipation and reward delay. The authors discuss the strengths and
weaknesses of the image manipulation algorithms they use and the future implications of MRIbased diagnostic tools to improve and possibly revise current understanding of ADHD subtypes.
George Washington University Milken Institute School of Public Health. (2015, December 8). New report
finds 43 percent increase in ADHD diagnosis for US schoolchildren: Girls showed a sharp rise in
ADHD diagnosis during eight-year study period. ScienceDaily. Retrieved November 20, 2018 from
www.sciencedaily.com/releases/2015/12/151208150630.htm
This news article reports findings from the George Washington University Milken Institute
School of Public Health study on rates of ADHD diagnosis in children in the USA. The study
found that rates of diagnosis of ADHD have jumped 43% between 2003 and 2012. The study
was not designed to uncover reasons for the change in prevalence, and the researchers note that
this could be a true increase or a result of overdiagnosis. Perhaps most interesting were large
increases in diagnosis rates in certain subgroups, such as girls (increased 55% in 8 years) and
Hispanic youth (increased 83%). Data were taken from the 2012 National Survey of Children’s
Health.
Henderson, K., American Institutes for Research, & Special Education Programs, (U. S.).
(2008). Teaching children with attention deficit hyperactivity disorder : Instructional strategies and
practices Retrieved from http://hdl.handle.net/2027/pur1.32754073526950
This report was produced under contract to the US Department of Education. It contains brief
background information about ADHD and primarily concentrates on strategies and a systematic
approach to analyzing and planning for the individual needs of children with ADHD in the
classroom. The bulk of the report is devoted to instructional strategies, interventions and
classroom accommodations, and this is the organization I adopted for Table 1 in my paper, as
well as the source for many of the strategies I listed there. It covers instructional practices and
strategies by content area as well as practices which support specific desirable skills.
Lange, K. W., Reichl, S., Lange, K. M., Tucha, L., & Tucha, O. (2010). The history of attention deficit
hyperactivity disorder. Attention deficit and hyperactivity disorders, 2(4), 241-55.
Much of the historical perspective on ADHD in this paper was distilled from this review article
by Lange et al. The article traces the description of ADHD symptoms in children in medical
and psychological literature over the last 200 years, adjusting for the terminology of each time.
Significant attention is given to the development of treatments/therapies, especially stimulant
medications and most especially Methylphenidate, named Ritalin for the wife of chemist
Leandro Panizzon, who first synthesized it in 1944. The critical purpose of the article seems to
be to establish he understanding that ADHD is not a new condition, and that its validity as a
clinical entity could be considered questionable, due to the degree of comorbidity and lack of a
unique set of cardinal symptoms.
Morgan, P. L., Staff, J., Hillemeier, M. M., Farkas, G., & Maczuga, S. (2013). Racial and ethnic
disparities in ADHD diagnosis from kindergarten to eighth grade. Pediatrics, 132(1), 85-93.
Despite being more likely to be exposed to many socioeconomic and health risk factors
associated with ADHD diagnosis, several studies have reported that children of racial/ethnic
minorities are diagnosed with ADHD at lower rates than white children. The authors of this
study state that African American and Hispanic American children are likely underdiagnosed,
that is, diagnosed with ADHD at a fraction of the rate of white children despite what seems to be
greater symptomatology. They studied 17,100 kindergarten students from across the United
States, and followed them to their 8th grade year (15,100 students were included in the final
sample; some were removed from the study due to incomplete data or moving out of the sample
population). In the first model derived from initial data, race/ethnicity and time were used as
predictors of ADHD diagnosis. The second model included child and family-level predictors,
including the child’s behavioral and academic functioning. The data clearly show that
racial/ethnic minority children are much less likely than otherwise comparable white children to
receive an ADHD diagnosis, though parent responses suggest ADHD symptoms are similar to
prevalent. The probability of diagnosis was greatly increased for boys, children who frequently
engage in externalized problem behaviors, children being raised in homes where English is
spoken by at least one parent, and children being raised by an older mother (>38 yoa). There
was a significant though less-strong association between ADHD diagnosis and the health
insurance status of the child. When the authors examined adjusted data, among children
diagnosed with ADHD by a medical or mental health professional, racial/ethnic minority
children were much less likely than their white peers to be using medication to offset their
ADHD symptoms. This is a more fine-scale and comprehensive study than previous research
which has noted this pattern.
Mueller, K. L., & Tomblin, J. B. (2012). Examining the comorbidity of language disorders and
ADHD. Topics in language disorders, 32(3), 228-246.
The authors advocate more research in general on comorbidity in developmental disorders, and
there they examine the co-occurrence of Specific Language Impairment (SLI) and ADHD, in a
review of clinical and population-level studies. They propose a model in which SLI is
considered a risk condition for ADHD, and calculate the relative risk-ratio to determine strength
of this comorbidity association (not a population rate). The shortcoming to this approach is that
evidence of comorbidity comes mostly from studies of children with ADHD, in which rates of
SLI are very high. Their review-based findings support the conclusion of earlier individual
studies that many more children with ADHD have SLI than vice-versa (about 20% of children
with SLI are estimated to have ADHD). As yet, insufficient evidence exists to determine a
causal link from SLI to ADHD as has been proposed.
Parens, E., & Johnston, J. (2009). Facts, values, and attention-deficit hyperactivity disorder (ADHD): An
update on the controversies. Child and Adolescent Psychiatry and Mental Health, 3(1), 1.
doi:10.1186/1753-2000-3-1.
This article represents the summary findings of the 2nd of a series of workshops examining
controversies around use of medication to treat emotional and behavioral disturbances in
children; this session focused on ADHD diagnosis and treatment. The authors identified a “zone
of ambiguity” around diagnosis based on differences in reasonable interpretations of symptoms.
According to the authors, the USA leads the world in per-capita stimulant (methyphenidate)
consumption, including in preschool children. Genetic correlates have been identified, including
a gene variant which codes for a dopamine receptor (DRD4 7-repeat allele) and is also
associated with cortex thinning in the region of the brain associated with attention – but gene
variants are not as useful in explaining the complex phenotypes of ADHD as they initially
promised to be. The authors explain the dimensionality of ADHD symptoms, and the factors
affecting the rates and accuracy of diagnoses, but emphasize that the suffering and costs
associate with ADHD are real, though not a “unitary, simple thing”. They caution against
enshrining DSM categories while so much is yet unknown. Diagnostic criteria threshholds may
be too low and result in overmedication, or the “medicalization of underperformance” in the
USA, accounting for differences in rates of ADHD worldwide.
Quinn, P. O., & Madhoo, M. (2014). A review of attention-deficit/hyperactivity disorder in women and
girls: uncovering this hidden diagnosis. The primary care companion for CNS disorders, 16(3),
PCC.13r01596.
The authors reviewed 41 articles from PubMed on 9 April 2012, plus ancestral searches and
other incidental articles, using a keyword list to find relevant empirical information about
clinical presentation of ADHD in females, to build a more comprehensive picture of the way in
which girls and boys differ in their expression of ADHD symptoms, and the implications for
education and treatment of girls with ADHD. They stress the need for more awareness of these
differences based on trends found in the reviewed literature. One, that adults in the childrens’
lives tend to view diagnostic descriptors of ADHD as being more applicable to boys than to
girls. Attitudes about ADHD vary by gender of the diagnosed person overall. Girls tend to have
a distinct symptom presentation, clustered around internalized symptoms such as inattention,
rather than the externalized hyperactivity also associated with ADHD subtypes, which is less
disruptive to the classroom setting. Girls also been found to have better coping strategies, up to
a point in their lives. ADHD diagnosis is often missed in females when the disorder is comorbid
with anxiety and/or depression, a common co-occurrence. Girls tend to have a greater degree of
impaired social functioning and low self-esteem than boys with ADHD.
Saad, J. F., Griffiths, K. R., Kohn, M. R., Clarke, S., Williams, L. M., & Korgaonkar, M. S. (2017).
Regional brain network organization distinguishes the combined and inattentive subtypes of Attention
Deficit Hyperactivity Disorder. NeuroImage. Clinical, 15, 383-390. doi:10.1016/j.nicl.2017.05.016
The authors studied 34 minors ranging in age from 8-17 and 28 age- and gender-matched
typically developing controls. The participants with ADHD had either the inattentive subtype
(n=18) or the combined subtype (n=16). ADHD diagnosis was confirmed through a battery of
validated assessment scales; likewise, severity was assessed. Brain imaging was carried out
through high-resolution MRI to examine regional connectivity (rather than connectivity within
regions), after a period of medication wash-out. Significant differences were found in the degree
to which brain regions were connected to other regions, measured by nodal degree. ADHDinattentive type showed significantly greater nodal degree in the hippocampus compared with
ADHD-combined or healthy controls. There were also significant variations between the two
ADHD subtypes. ADHD-combined had greater nodal degree in the cerebellum than ADHDinattentive. There was no difference observed in global network organization or gray matter
volume. These and other differences in nodal degree identified suggest there may be distinct
differences in regional brain organization underlying the symptoms of ADHD subtypes. The
authors posit this may be used to better understand the neurobiology of ADHD subtypes and
factors leading to the functional deficits observed in children with ADHD, and develop more
accurate, brain-based diagnostic tools and future treatments for ADHD.
Singh, A., Yeh, C. J., Verma, N., & Das, A. K. (2015). Overview of Attention Deficit Hyperactivity
Disorder in Young Children. Health psychology research, 3(2), 2115. doi:10.4081/hpr.2015.2115
This article summarizes the etiology, symptomatology and neuropsychology of ADHD,
including the roles of diet and other interventions and treatments. The purpose of this review is
to provide information to teachers and clinicians for their use in conversation with parents about
current knowledge regarding ADHD, as misconceptions and controversies concerning this
disorder are common. The article was useful for this paper in that traditional hypothetical causal
mechanisms as well as current neurobiological understanding of brain network activity in
ADHD are presented side-by-side.
Visser, S. N., Zablotsky, B., Holbrook, J. R., Danielson, M. L., & Bitsko, R. H. (2015). Diagnostic
experiences of children with attention-deficit/hyperactivity disorder. National Health Statistics
Reports, (81), 1. Retrieved from https://www.ncbi.nlm.nih.gov/pubmed/26375578
The Center for Disease Control (CDC) website presents epidemiological data about ADHD, as
well as essential features for diagnosis. An interesting page on this site explains specifically the
process and features of diagnosis of children in the United States of America. The CDC has
found that about 50% of children in the US with ADHD were diagnosed by a physician, using
validated rating scales and parent/teacher feedback. Psychiatrists, psychologists and
neurologists comprised the remaining proportion of professionals making the diagnosis. In the
CDC’s data, which was obtained from parents included in the 2014 National Survey of the
Diagnosis and Treatment of Attention Deficit/Hyperactivity Disorder and Tourette Syndrome, a
follow-up to the 2011–2012 National Survey of Children’s Health, the primary locus of concern
about a child’s behavior was typically a family member, though other studies have reported that
teachers most often prompt diagnosis.
Wilson, V., Mitchell, S., Musser, E., Schmitt, C.F., & Nigg, J.T. (2011). Delay discounting of reward in
ADHD: Application in young children. Journal of Child Psychology and Psychiatry, 52, 256-264.
The authors discuss prior research which examined the processes related to reward, motivation
and learning in children with ADHD. Previous studies have identified a steeper gradient of
delay discounting of rewards in ADHD-affected children – they are less motivated by a reward
that is far out in the future, and will opt for lesser rewards that are available immediately vs. a
greater reward that is available after a delay. The same pattern was found here, but when the
data were corrected for IQ as a co-variant, the conclusion did not hold. IQ plays a significant
role in delay discounting decisions, with lower IQ associated with steeper discounting gradients,
which might reflect lower understanding of valuation. ADHD has been associated with lower-
than-average-for-development IQs, but it is well-documented that there is a wide variation in IQ
among children with ADHD, including test performances which qualify children as gifted. The
children with ADHD in this study had faster decision times which may have influenced their
ability to think through reward delay decisions, but when the data were examined with attentionto-task controlled, the difference between the ADHD group and the control group did not
appear, suggesting it’s not an effect of fully processing the consequences of decisions but
possibly due to other cognitive deficits associated with ADHD.
Wolraich, M. L., Lambert, W., Doffing, M. A., Bickman, L., Simmons, T., & Worley, K. (2003).
Psychometric properties of the Vanderbilt ADHD diagnostic parent rating scale in a referred
population. Journal of Pediatric Psychology, 28(8), 559-568. doi:10.1093/jpepsy/jsg046
This study determined the validity of the Vanderbilt ADHD diagnostic parent rating scale, based on
internal consistency, reliability, factor structure and concurrent validity. As Vanderbilt is based
closely on DSM-IV and DSM-5, it is expected that it would provide information that would lead
reliably to diagnosis using those criteria. In this 2-year blinded study with 243 participants, it was
found to be reliable in both clinical and research settings, and cost-effective to use. It was also
manageable for parent respondents, even those with low reading levels.
Xu, C., Reid, R., & Steckelberg, A. (2002). Technology Applications for Children with ADHD:
Assessing the Empirical Support. Education and Treatment of Children, 25(2), 224-248. Retrieved
from http://www.jstor.org/stable/42900528
This is a review of research into the value of assistive technology in meeting the educational
needs of students with ADHD. The authors define five applications of assistive technology in
this article: behavioral modification, computer-aided instruction, cognitive training, biofeedback
and computerized assessment. This is a simple review article with no criteria for exclusion
discussed; inclusion was based on keyword search of academic databases and ancestral search of
citations in the articles arising from the keyword search. Findings and limitations of the studies
in each category are discussed; methodological shortcomings of the studies reviewed, some of
which are case studies, are examined in some detail. It’s not clear whether the limited number of
studies included in this review represent a lack of strong empirical research in this area, as the
authors suggest, or a limitation of the selection method. They recommend caution in relying on
assistive technology to make up for social, behavioral or learning deficits experienced by
children with ADHD. Their chief recommendation is that more study is needed, and practical
concerns with introduction of assistive technology in the classroom must be addressed. They
state four questions that need to be answered through empirical research – how can computers
and other assistive technology be integrated with other forms of instruction to maximize
effectiveness; how can teachers and students use assistive technology efficiently to produce
optimal results; how can teachers select the appropriate technology for use with their students
with ADHD; what are the short- and long-term effects of assistive technology use in learning;
how can a computer program be best designed to help ADHD students with behavioral and
social skills? I would add to this, how do we know that mastery of learning using the assistive
technology can be transferred to other forms of expression or analogous situations, including
Bloom’s higher-order thinking?