research

Topic Specific Learning Disorder

· Your Instructor will assign a specific disorder for you to research for this Assignment.

· Use the Walden library to research evidence-based treatments for your assigned disorder in children and adolescents. You will need to recommend one FDA-approved drug, one off-label drug, and one nonpharmacological intervention for treating this disorder in children and adolescents.

Recommend one FDA-approved drug, one off-label drug, and one nonpharmacological intervention for treating your assigned disorder in children and adolescents.
Explain the risk assessment you would use to inform your treatment decision making. What are the risks and benefits of the FDA-approved medicine? What are the risks and benefits of the off-label drug?
Explain whether clinical practice guidelines exist for this disorder and, if so, use them to justify your recommendations. If not, explain what information you would need to take into consideration.
Support your reasoning with at least three scholarly resources, one each on the FDA-approved drug, the off-label, and a non-medication intervention for the disorder. Attach the PDFs of your sources.

Learning Disorder Confers Setting-Specific Treatment
Resistance for Children with ADHD, Predominantly

Inattentive Presentation

Lauren M. Friedman, Keith McBurnett, and Melissa R. Dvorsky
Department of Psychiatry, University of California, San Francisco

Stephen P. Hinshaw
Department of Psychiatry, University of California, San Francisco and Department of Psychology,

University of California, Berkeley

Linda J. Pfiffner
Department of Psychiatry, University of California, San Francisco

Attention deficit/hyperactivity disorder–predominantly inattentive presentation (ADHD-I)
and specific learning disorder (SLD) are commonly co-occurring conditions. Despite the
considerable diagnostic overlap, the effect of SLD comorbidity on outcomes of behavioral
interventions for ADHD-I remains critically understudied. The current study examines the
effect of reading or math SLD comorbidity in 35 children with comorbid ADHD-I+SLD and
39 children with ADHD-I only following a behavioral treatment integrated across home and
school (Child Life and Attention Skills [CLAS]). Pre- and posttreatment outcome measures
included teacher-rated inattention, organizational deficits, and study skills and parent-rated
inattention, organizational deficits, and homework problems. A similar pattern emerged
across all teacher-rated measures: Children with ADHD-I and comorbid ADHD-I+SLD
did not differ significantly at baseline, but between-group differences were evident following
the CLAS intervention. Specifically, children with ADHD-I and comorbid ADHD-I+SLD
improved on teacher-rated measures following the CLAS intervention, but children with
ADHD-I only experienced greater improvement relative to those with a comorbid SLD. No
significant interactions were observed on parent-rated measures—all children improved
following the CLAS intervention on parent-rated measures, regardless of SLD status. The
current results reveal that children with ADHD-I+SLD comorbidity benefit significantly
from multimodal behavioral interventions, although improvements in the school setting are
attenuated significantly. A treatment-resistant fraction of inattention was identified only in
the SLD group, implying that this fraction is related to SLD and becomes apparent only
when behavioral intervention for ADHD is administered.

Attention deficit/hyperactivity disorder (ADHD) and speci-
fic learning disorders (SLDs) are two of the most prevalent
disorders in childhood, affecting approximately 7% and 9%
of children worldwide, respectively (Altarac & Saroha,

2007; Thomas, Sanders, Doust, Beller, & Glasziou, 2015).
ADHD and SLD are also commonly co-occurring—chil-
dren with ADHD are almost 5 times more likely to be
diagnosed with an SLD relative to their typically develop-
ing peers (DuPaul, Gormley, & Laracy, 2013), and recent
estimates suggest that approximately 45% of children with
ADHD meet criteria for an SLD (DuPaul et al., 2013).

Comorbidity of any two disorders may be worse than the
sum of its parts. For example, children with ADHD and

Correspondence should be addressed to Lauren M. Friedman, Linda
J. Pfiffner, Department of Psychiatry, University of California, San
Francisco 401 Parnassus Avenue, San Francisco, CA 94143. E-mail:
Lauren.Friedman2@ucsf.edu; Linda.Pfiffner@ucsf.edu

Journal of Clinical Child & Adolescent Psychology, 49(6), 854–867, 2020
Copyright © Society of Clinical Child & Adolescent Psychology
ISSN: 1537-4416 print/1537-4424 online
DOI: https://doi.org/10.1080/15374416.2019.1644647

http://orcid.org/0000-0002-3790-1334

https://crossmark.crossref.org/dialog/?doi=10.1080/15374416.2019.1644647&domain=pdf&date_stamp=2020-12-09

conduct disorder, compared to children with only one of these
disorders, have been found to have an earlier age of symptom
onset, greater persistence of problem behaviors, worse aca-
demic problems, and increased severity of ADHD and con-
duct symptoms (Loeber & Keenan, 1994). An additive effect
may explain some findings, but simple addition cannot
explain the synergistic effect that comorbid ADHD has on
the severity of conduct disorder symptomatology, and vice
versa. In a related vein, both inattention and learning difficul-
ties are often more severe for children with ADHD and SLD
than for children diagnosed with only one disorder
(McNamara, Willoughby, & Chalmers, 2005; Purvis &
Tannock, 2000; Wei, Yu, & Shaver, 2014). Comorbid
ADHD/SLD is also associated with greater educational, neu-
rocognitive, and social impairments relative to children with
only ADHD, including more severe executive functioning
deficits, higher rates of grade-retention, increased likelihood
of placement in special education classes, greater use of in-
school tutoring services, and poorer social skills (Bental &
Tirosh, 2007; Seidman, Biederman, Monuteaux, Doyle, &
Faraone, 2001; Wei et al., 2014; Willcutt et al., 2007, 2010;
Willcutt, Pennington, Olson, Chhabildas, & Hulslander,
2005). The greater symptom load associated with comorbidity
is difficult to explain solely on the basis of additive effects of
ADHD and SLD.

The question thus arises: If having an accompanying condi-
tion such as SLD confers more impairment than ADHD alone,
will ADHD interventions prove less effective for children with
ADHD/SLD comorbidity as a result of the inattentive sequela
related to SLD? This question must be framed in the context of
specific effects of treatment, because the best information will
come from using a treatment that is known to preferentially
reduce ADHD rather than SLD. If treatment targeted at one
domain reduced impairments related to ADHD and SLD, we
would not be able to distinguish the improvement of ADHD
proper from the improvement in inattention that overflows from
SLD. Recent evidence, however, suggests that treatments tar-
geted toward one disorder do not substantially affect the other.
Tamm et al. (2017) examined the effectiveness of intensive
reading instruction, ADHD treatment (behavioral parent train-
ing and medication management administered concomitantly),
and combined treatment (reading instruction, parent training,
andmedication) for childrenwith comorbidADHDand reading
disorder. Children assigned to the ADHD and combined treat-
ment conditions improved in parent- and teacher-reported
ADHD symptoms, whereas those receiving reading instruction
did not. In addition, children assigned to the reading instruction
and combined conditions showed improvement on standardized
reading measures, whereas children receiving Behavioral
Parent Training (BPT)/medication therapy only did not show
significant reading gains. Furthermore, there was no added
benefit to combined versus mono-domain therapy. Thus,
Tamm et al. demonstrated specific effects of treatments
designed for each diagnosis.

One of the most difficult differential decisions in child
psychopathology, for children with weaknesses in both atten-
tion and learning, is ascertaining how symptoms and impair-
ment might be attributable to each disorder. On the continuum
of learning problems, even mild difficulty with reading or math
may manifest as inattention, particularly when the child is
engaged in academic endeavors and when the effort demanded
requires additional attentional resources for those with already-
reduced attention spans, sapping energy and motivation.
Therefore, during academic tasks children with ADHD/SLD
comorbidity may appear inattentive phenotypically partially
because they lose focus, engage in off-task behaviors, and
become frustrated because of the arduous nature of learning-
related tasks (Pennington, Groisser, &Welsh, 1993). This frac-
tion of the total inattention symptomatology (the part emanating
from SLD) may be relatively intractable; that is, treatments that
are effective for primary inattention may be considerably less
effective for inattention that is secondary to learning difficulties,
particularly in settings requiring increased learning demands
(e.g., school, homework completion). Such an interpretation is
consistent with evidence that childrenwithADHDand SLDare
poorer responders to psychostimulant medications than those
with ADHD alone (Grizenko, Bhat, Schwartz, Ter-Stepanian,
& Joober, 2006).

Indeed, recent evidence suggests that deficits in learning
adversely affect response to behavioral interventions.
Breaux et al. (2019) examined predictors of treatment
response among middle school adolescents with ADHD
who received either a contingency-management or skill-
based intervention for homework problems. Across
a range of predictors examined, baseline math and reading
achievement scores were the most consistent predictors of
parent- and teacher-rated treatment response. Those with
low to below-average academic achievement (i.e., reading
or math achievement standard scores less than 95) were
less likely to have reductions in homework problems and
improved homework completion following treatment.
However, findings from the multimodal treatment study
for ADHD (MTA) did not support these results, as youth
with a comorbid SLD did not differ on treatment-related
improvement in homework problems (Langberg et al.,
2010). It is important to note that whether comorbid SLD
moderates or predicts treatment-related improvements in
inattention and other related impairments (e.g., organiza-
tional and study skills) has not been examined but warrants
scrutiny given the potential synergistic effect of SLD
comorbidity on ADHD-related sequelae.

No study to date has examined varying responses to
behavioral intervention outcomes among children with
ADHD–predominantly inattentive presentation (ADHD-I).
Extrapolating conclusions regarding treatment response
from children with clear hyperactivity and impulsivity to
children with ADHD-I is questionable, given that ADHD-I
is uniquely associated with different attention and

LEARNING DISORDER CONFERS SETTING-SPECIFIC TREATMENT RESISTANCE FOR CHILDREN 855

neurocognitive profiles, psychopathological correlates (e.g.,
less oppositionality, greater sluggish cognitive tempo and
substance use), and social skills deficits than is the com-
bined presentation (Bauermeister et al., 2005; Huang-
Pollock, Mikami, Pfiffner, & McBurnett, 2007;
McBurnett, Pfiffner, & Frick, 2001; Milich, Balentine, &
Lynam, 2001; Sobanski et al., 2008). Furthermore, at least
one longitudinal study indicates that academic impairments
for youth with ADHD-I presentation are more profound
and persistent than those found in other presentations of
the disorder (Massetti et al., 2008). Given the unique
impairments and academic difficulties faced by children
with ADHD-I, it is especially important to examine the
impact of SLD in this presentation of ADHD.

Most behavioral interventions for ADHD target proble-
matic behaviors typically associated with ADHD–com-
bined presentation. That is, most behavioral interventions
emphasize reducing hyperactivity, impulsivity, and defiance
that are either absent in or less relevant to children with
ADHD-I. To our knowledge, only one validated behavioral
treatment exists currently for children with ADHD-I: The
Child Life and Attention Skills program (CLAS; Pfiffner
et al., 2014). CLAS is a multicomponent intervention that
combines behavioral parent training, child skills training,
and classroom consultation strategies tailored to address the
cross-setting challenges specific to children with ADHD-I.
In a randomized, controlled trial, our team (Pfiffner et al.,
2014) found that CLAS was associated with significant
improvements in teacher-rated attention, social skills, orga-
nization, and global functioning, as well as parent-rated
organizational skills, relative to parent training alone and
to treatment as usual. CLAS also demonstrated superior
results relative to treatment as usual on parent-rated atten-
tion, social skills, and global functioning. Whether SLD
comorbidity affects response to CLAS among children
with ADHD-I, however, remains unknown.

In sum, no study to date has examined whether the
presence of SLD predicts differential response to beha-
vioral intervention for treatments designed specifically for
ADHD-I. Herein, the effect of SLD comorbidity was
assessed across several outcome domains (e.g., ADHD
symptoms, organizational deficits, study skills, and home-
work problems) using both parent and teacher informants.
We hypothesized a significant interaction between treat-
ment and comorbid SLD status, such that children with
ADHD-I (without SLD) would exhibit greater treatment-
related improvements on multiple domains, including inat-
tention severity, relative to those with ADHD-I/SLD. The
hypothesized interaction is based on the greater symptom
severity, educational impairments, and cognitive challenges
among children with comorbid ADHD/SLD, compared to
those with only ADHD (whose inattention is less likely to
be secondary to learning-related difficulties; Bental &
Tirosh, 2007; Seidman et al., 2001; Willcutt et al., 2010,

2005). This fraction of the symptom profile emanating from
learning difficulties is hypothesized to be less responsive
when treated with interventions targeting ADHD singly,
such as CLAS. It is also based on contemporary etiological
models of ADHD/SLD comorbidity suggesting that chil-
dren with comorbid ADHD/SLD evince more severe and/or
numerous neurocognitive (DuPaul et al., 2013; Purvis &
Tannock, 2000; Willcutt et al., 2005, 2007) and neural
morphology (Hynd, Semrud-Clikeman, Lorys, Novey, &
Eliopulos, 1990; Jagger-Rickels, Kibby, & Constance,
2018; Kibby, Kroese, Krebbs, Hill, & Hynd, 2009) deficits
than those with an ADHD monodiagnosis, features that are
not directly addressed through the CLAS (ADHD-focused)
intervention.

METHOD

Participants

The current study comprises a secondary analysis of
a larger, randomized, controlled clinical trial (Pfiffner
et al., 2014). Briefly, participants ages 7 to 11 with
a diagnosis of ADHD-I were randomly assigned to one of
three treatment conditions: CLAS program, behavioral par-
ent training only, and treatment as usual. We examine the
CLAS group (n = 74; age M = 9.21, SD = 1.10) exclusively
herein. First, CLAS demonstrated superior results relative
to parent training alone and treatment as usual in previous
studies (Pfiffner et al., 2014). Second, it was the only
intervention associated with improvements across all of
the outcome domains assessed (e.g., inattention, organiza-
tional skills, social skills, and overall functioning)—and it
is unlikely to find moderation effects in the absence of
treatment effects barring any suppression effects (Hayes,
2017). Third, it was the only intervention that improved
performance in the school setting, which is particularly
relevant for children with learning disabilities.

Participants were recruited at two treatment sites:
University of California, San Francisco and University of
California, Berkeley. Children were recruited or referred
from school personnel including principals, school mental
health professionals, and learning specialists; pediatricians;
and child psychiatrists and psychologists. In addition,
recruitment flyers were posted in online parent networks
and professional organizations. Across 4 years (2009–
2012), six cohorts of children participated, with a mean
number of 12 children in each cohort (range = 10–15).

To be considered for inclusion, children met the follow-
ing criteria: (a) primary Diagnostic and Statistical Manual
of Mental Disorders (4th ed.; DSM-IV; American
Psychiatric Association, 1994) diagnosis of ADHD-I, as
confirmed by the Kiddie Schedule for Affective Disorders
and Schizophrenia (KSADS-PL) clinical interview (see
next); (b) ages 7–11 (Grades 2–5); (c) attending school

856 FRIEDMAN ET AL.

full time in a regular classroom; (d) Full Scale IQ greater
than 80, as confirmed on the Wechsler Intelligence Scale
for Children, Fourth Edition (Wechsler, 2003); (e) living
with at least one parent for 1 year prior to study recruit-
ment; (f) family schedule that permitted participation in
CLAS groups; and (g) school proximity within 45 min of
either treatment site to allow study personnel to conduct
teacher consultation meetings. Children were excluded if
they were planning to initiate or change medication (stimu-
lant or otherwise) in the near-term. Children taking non-
stimulant psychoactive medications were also excluded
because of the difficulties of withholding medication to
confirm ADHD-I symptoms among raters potentially unfa-
miliar with children’s behavior while not taking medica-
tions (i.e., classroom teachers), as required to confirm
cross-setting impairment required for diagnosis. Children
with pervasive developmental disorders or other neurologi-
cal illnesses were also excluded.

Demographic data for the participants in this study (i.e.,
children receiving CLAS, n = 74) are as follows: Mean
child age was 9.21 years (range 7–11) with 18% in
the second grade, 21% in third grade, 21% in fourth
grade, and 14% in fifth grade. Boys comprised 51.4% of
the sample. 55.4% were Caucasian, 12.2% were Latinx,
9.5% were Asian American, 5.4% were African
American, and 17.6% identified as mixed-race. Total
household income was below $50,000 for 12.2% of
families, $50,000-$100,000 for 31.1%; $100,000-$150,000
for 24.3%, and more than $150,000 for 27.0% of families.
Income data was missing from 5.4% of families. 84.9% of
parents reported graduating from college and 9.5% of chil-
dren were living in single-parent homes. Note that only
6.8% of children were taking medication for ADHD.

Procedure

A detailed description of participant screening, flow, attri-
tion, diagnostic procedures, treatment fidelity, and therapist
qualifications are provided elsewhere (Pfiffner et al., 2014).
In short, participant screening was conducted using
a successive, three-wave approach. First, telephone screen-
ing calls were conducted with parents and teachers to assess
initial eligibility regarding demographics and medication
status. Next, those meeting initial screening criteria were
invited to complete rating scale packets containing the par-
ent- and teacher- versions of the Child Symptom Inventory
(CSI-IV, Gadow & Sprafkin, 2002) and the Impairment
Rating Scale (IRS, Fabiano et al., 2006). Third, children
who met the following criteria were invited for a full diag-
nostic assessment: (a) at least five symptoms rated as occur-
ring “often” or “very often” by parents or teachers on the
CSI, with each informant endorsing at least two symptoms;
(b) five or fewer hyperactive/impulsive symptoms endorsed
as occurring “often” or “very often” by parents and teachers

on the CSI; and (c), at least one area of functioning rated as
� 3 on the IRS by both parent and teacher, thereby indicat-
ing evidence of impairment across settings. Diagnostic status
was ascertained using clinical interviews that consisted of
detailed questions regarding children’s developmental, med-
ical, clinical, and school history, as well as the Kiddie
Schedule for Affective Disorders and Schizophrenia
(K-SADS-PL; Kaufman, Birmaher, Brent, Rao, & Ryan,
1997). The K-SADS is a semi-structured interview that
assesses the presence and impairment of psychopathology
including ADHD, oppositional defiant disorder, conduct dis-
order, anxiety disorders, mood disorders, and psychosis
based on DSM-IV criteria. Its psychometric properties are
well-established (cf., Kaufman et al., 1997).

To be considered for study entry, children were required
to meet full DSM-IV criteria for ADHD-I based on
K-SADS interview—viz., six or more inattention symp-
toms and fewer than six hyperactive/impulsive symptoms.
Parents also completed a battery of questionnaires, and
children were administered the Wechsler Intelligence
Scale for Children, Fourth Edition (Wechsler, 2003), select
subtests from the Woodcock–Johnson Test of Achievement,
Third Edition (Woodcock, Mather, McGrew, & Schrank,
2001), and a questionnaire battery.

Study procedures were approved by the Committee on
Human Research at University of California, San Francisco
and University of California, Berkeley. All participating
parents and children provided their informed written con-
sent and assent, respectively. Families were compensated
for measure completion at posttreatment ($50). Teachers
were also compensated for competing measures at baseline
($50) and posttreatment ($75) and provided a total of $100
for their participation in teacher consultation meetings.
Treatment was provided to participants at no cost.
Immediately following treatment, laboratory visits were
scheduled with families and rating scales were sent to
teachers to collect posttreatment ratings.

Intervention

CLAS consists of three empirically supported behavioral
interventions adapted for children with ADHD-I: beha-
vioral parent training, child skills training, and daily report
card with teacher consultation. For a detailed description of
CLAS intervention skills and modules, see Pfiffner et al.
(2014). The size of each CLAS group ranged between six
and eight families.

Parent component

The parent training consisted of ten 90-min weekday
groups, along with up to six 30-min individual family
meetings (parent, child, and therapist). The curriculum
was adapted from extant parent training programs
(Barkley, 1997b; Forehand & McMahon, 1981) and

LEARNING DISORDER CONFERS SETTING-SPECIFIC TREATMENT RESISTANCE FOR CHILDREN 857

modified to include modules targeting challenges specific to
ADHD-I. Parent stress management skills were also
included.

Child component

The child skill component consisted of ten 90-min
weekday groups that ran concurrently with the parent
group sessions. Modules were adapted from a social skills
program for children with ADHD (Pfiffner & McBurnett,
1997) and focused on building independence, organization,
emotion regulation, assertiveness, and social skills. Parents
reinforced skills using a token economy outside of the child
group to encourage generalization of the skills across
contexts.

Teacher component

Teachers were taught evidence-based classroom man-
agement strategies to scaffold and support attention and
use of the child skills in the classroom (DuPaul, Weyandt,
& Janusis, 2011; Fabiano et al., 2010; Pfiffner et al., 2011).
Teachers also implemented a customized school–home
daily report card whereby teachers rated students three
times daily on up to four personalized treatment goals. Up
to five meetings were conducted with teachers, parents,
children, and study personnel to discuss daily report card
goals, classroom accommodations, and the skills taught
within the child component to encourage generalization of
group skills across contexts.

Measures

Specific learning disorder

SLD Status was assessed a posteriori and did not affect
participant inclusion or exclusion. Children were consid-
ered to have a suspected SLD if they received a standard
score of 85 or lower (i.e., 16th percentile) on any of the
following subtests of the Woodcock–Johnson Test of
Educational Achievement–III (Woodcock et al., 2001):
Passage Comprehension, Reading Fluency, Calculation, or
Math Fluency. The psychometric properties of this test are
well-established, including concurrent validity with other
measures of academic achievement (Woodcock et al.,
2001).1

Although SLD definitions vary widely in the literature
wherein delineation scores range from 80 to 90 (cf.
Brueggemann, Kamphaus, & Dombrowski, 2008, for
a review), a cutoff score of 85 was chosen, as it indicates
the presence of a basic skill deficit that may require

intervention, reliably identifies children with poor school
performance and functional impairments (Brueggemann
et al., 2008), and is associated with the lowest rates of
reading growth following intervention (Vellutino, Scanlon,
& Reid Lyon, 2000). In addition, the “low achievement
model” (i.e., below-average academic achievement) was
chosen over alternative models of SLD definition, such as
the “IQ-achievement discrepancy model,” as the latter is
associated with limited reliability, questionable validity,
poor sensitivity and positive predictive power, and limited
incremental validity over the low-achievement definition
(Brueggemann et al., 2008; Dombrowski, Kamphaus, &
Reynolds, 2004; DuPaul et al., 2013). Both fluency and
ability subtests were considered, consistent with the current
conceptualization of SLD within the DSM-5 (American
Psychiatric Association, 2013), which recognizes an
uneven profile of abilities wherein deficits can be observed
in accurate and fluent calculation/reading, either indepen-
dently or concomitantly. Based on this definition, 47.3%
(n = 35) met criteria for an SLD. Specifically, 41.9%
(n = 31) met criteria for a disability in math, 13.5%
(n = 10) met criteria for a disability in reading, and 8.1%
(n = 6) met criteria for a learning disability in both reading
and math.

Outcome Measures

Inattention

Parent- and teacher-rated symptom count2 from the
Inattention scale of Child Symptom Inventory (CSI;
Gadow & Sprafkin, 2002) was used to assess ADHD-
related inattention symptomatology and had good internal
consistency in the present sample (αs = .77–.82). The CSI
measures inattention consistent with ADHD DSM-IV cri-
teria on a 4-point scale from 0 (never) to 3 (very often).
Inattention symptoms were considered present if they were
rated as occurring often or very often. The Inattention scale
of the CSI has normative data, acceptable test–retest relia-
bility, and predictive validity for a categorical diagnosis of
ADHD (Gadow & Sprafkin, 2002).

Organizational deficits

Parents and teachers completed respective versions of
the Children’s Organizational Skills Scale (COSS; Abikoff
& Gallagher, 2003). Age-corrected T-scores of the COSS
Total composite score served as the dependent variable to
assess children’s deficits in organization, planning, and time
management skills and had good internal consistency in the
present sample (α = .91–.97). The parent and teacher ver-
sions have adequate psychometric properties including high

1 It is important to recognize that SLD diagnosis is usually conferred
following full psychoeducational or neuropsychological evaluation and
that the presence of significant academic achievement deficits indicates
a suspected but not confirmed SLD diagnosis.

2 Alternative summary scores, such as symptom severity scores, were
also analyzed but did not change the pattern or interpretation of results.

858 FRIEDMAN ET AL.

test–retest reliability (rs = .94–.99 and .88–.93, respec-
tively), and evidence of structural, convergent, and discri-
minant validity (Abikoff & Gallagher, 2003). Items are
rated on a 4-point scale from 1 (hardly ever/never) to 4
(just about all the time) and assess the extent to which
children have difficulties with planning tasks effectively;
engaging in organizational behaviors such as list creation,
routines, and reminders; and managing materials and sup-
plies necessary for task completion.

Study skills

Teacher-rated age-corrected decile scores on the Study
Skills subscale of the Academic Competence Evaluation
Scale (DiPerna & Elliott, 2001) served as the dependent
variable to measure children’s study skills and had adequate
internal consistency in the present sample (α = .88–.90).
The Academic Competence Evaluation Scale has excellent
psychometric properties including test–retest reliability (r =
.96) and evidence of predictive and concurrent validity
(DiPerna & Elliott, 2001). Items are rated on a 5-point
scale ranging from 1 (never) to 5 (almost always); they
assess the extent to which children are able to prepare for
and manage tests and class assignments, with higher scores
indicating greater functioning in study skills.

Homework problems

Average parent-rated scores on the

Homework Problems

Checklist (Anesko, Schoiock, Ramirez, & Levine, 1987)
served as the dependent variable to measure children’s
challenges with managing and completing homework and
showed high internal consistency in the present sample (α =
.89–.91). The Homework Problems Checklist has adequate
psychometric properties, including test–retest reliability
and predictive validity with children’s academic perfor-
mance (Anesko et al., 1987). Items are rated on a 4-point
scale ranging from 1 (never) to 4 (very often) and assess
difficulties with the management of homework materials,
knowledge and organization of homework tasks, homework
completion, and homework independence.

Data Analytic Plan

All statistical analyses were performed using SPSS (Version
25; IBM Corp, 2017). Preliminary analyses involved inves-
tigation of missing data and assessment of baseline charac-
teristics by SLD status (see Table 1). We analyzed outcomes
in the four domains that were the primary focus of our
investigation: inattention, organizational deficits, study
skills, and homework problems. For measures that included
both parent and teacher ratings (i.e., inattention and organi-
zation deficits), separate analyses were performed for each
rater. Primary analyses involved mixed model analyses of
variance (ANOVAs) examining within (pretreatment,

posttreatment) and between (ADHD-I, ADHD-I+SLD)
group comparisons. Analyses were initially completed with-
out covariates. We then performed follow-up ANCOVAs
adjusting for the following pretreatment variables: child’s
age, gender, race, medication status, and oppositional defi-
ant disorder symptoms, as well as education level of the
primary parent. However, each of these covariates were
either nonsignificant or did not change the pattern of inter-
pretation of results when included within the analyses.
Simple mixed model ANOVAs without covariates are there-
fore presented. Consistent with recommendations (Dennis
et al., 2009; Miller & Chapman, 2001), participant’s Full
Scale IQ score was not examined as a covariate. That is,
current etiological models of ADHD (Barkley, 1997a;
Castellanos & Tannock, 2002; Rapport et al., 2008;
Sagvolden, Johansen, Aase, & Russell, 2005; Sonuga-
Barke, Bitsakou, & Thompson, 2010; Willcutt, Doyle,
Nigg, Faraone, & Pennington, 2005), as indicated in the
most recent version of the DSM (American Psychiatric
Association, 2013), conceptualize the core symptoms and
related impairments of the disorder as secondary to under-
lying neurocognitive deficits. Therefore, cognitive deficits
(e.g., working memory, processing speed) that contribute to
Full Scale IQ (a) are considered inherent to ADHD, (b) do
not represent systematic error, and (c) violate the assump-
tions of a covariate (cf. Dennis et al., 2009; Miller &
Chapman, 2001, for a review)

To control for Type 1 error, a Benjamini-Hochberg false
discovery rate (FDR; Benjamini & Hochberg, 1995) was
applied within domain. The FDR exerts more powerful con-
trol over wrongly rejecting the null compared to procedures
that control the familywise error rate (e.g., the Bonferroni
correction). Specifically, using this method, each p value
below the a priori family-wise alpha level of .05 (i) is ranked
in ascending order, i through M, where M is the rank of the
largest (least significant) p value. These p values are then
compared to an adjusted alpha level of i(α)/M, until one of
the p values (k) is larger than the adjusted alpha level. In this
case, k and all p values ranked after k are considered non-
significant. For all pairwise comparisons, Hedges’s g effect
size metrics are provided. Hedges’s g estimates are Cohen’s
d estimates corrected for the upward bias associated with
smaller sample sizes. Interpretation of Hedges’s g estimates
are consistent with traditional effect size conventions (i.e.,
0.2 = small; 0.5 = moderate; 0.8 = large)

RESULTS

Preliminary Analyses

Very few data were missing at pretreatment (five data
points, 0.4%) or posttreatment (seven data points, 0.9%),
so none were imputed. Most of the missing data at post-
treatment were related to attrition (Pfiffner et al., 2014), as

LEARNING DISORDER CONFERS SETTING-SPECIFIC TREATMENT RESISTANCE FOR CHILDREN 859

one family dropped from treatment prior to the posttreat-
ment assessment. All outcome variables were screened for
univariate outliers as reflected by scores exceeding 3.5
standard deviations from the mean in either direction
(Tabachnick & Fidell, 2007). None were identified. As
seen in Table 1, participants did not differ significantly on
pretreatment variables based on SLD Status.

Inattention

Treatment-related effects on teacher-rated inattention symp-
toms were analyzed in a 2 (SLD Status: ADHD-I, ADHD-I
+SLD) × 2 (Time: baseline, posttreatment) mixed model
ANOVA; see Figure 1a. Means comparisons are shown
in Table 2. As expected, a significant main effect of time,
F(1, 72) = 99.81, p < .001, was observed, indicating

significant, large magnitude improvement on teacher-rated
inattention following CLAS (g = 1.33). A significant main
effect of SLD Status, F(1, 72) = 4.58, p = .036, and an SLD
Status × Time interaction, F(1, 72) = 13.05, p = .001, were
also observed. Follow-up pairwise comparisons using the
Benjamini-Hochberg FDR correction indicate that children
with ADHD-I and comorbid ADHD-I+SLD did not differ
significantly at baseline, but large-magnitude between-group
differences were evident following the CLAS intervention
(g = 0.80). Further inspection indicates that children with
ADHD-I and comorbid ADHD-I+SLD improved on teacher-
rated inattention following the CLAS intervention;
however, children with only ADHD-I experienced greater
improvement in teacher-rated inattention following interven-
tion (g= 2.08) relative to those with a comorbid SLD
(g = .80).

A similar mixed model ANOVAwas analyzed to assess
CLAS treatment-related effects on parent-rated inatten-
tion. As expected, there was a significant main effect of
time, F(1, 73) = 112.57, p < .001, indicating significant, large-magnitude improvement in parent-rated inattention following CLAS (g = 1.52). Neither the main effect of SLD Status, F(1, 73) = 0.27, p = .60, nor the SLD Status × Time interaction, F(1, 73) = 0.24, p = .63, was significant.

Organizational Deficits

A mixed model ANOVA was analyzed to assess CLAS
treatment-related effects on teacher-rated organizational
deficits, as depicted in Figure 1b. As expected,
a significant main effect of time, F(1, 72) = 72.82, p < .001, was observed, indicating significant, large-magnitude improvement on teacher-rated organizational deficits fol- lowing CLAS (g = 0.83). A significant SLD Status × Time interaction, F(1, 72) = 3.95, p = .05, was also observed. However, the main effect of SLD Status, F(1, 72) = 3.24, p = .076, was not significant. Follow-up pair- wise comparisons using the Benjamini–Hochberg FDR cor- rection indicate that children with ADHD-I and comorbid ADHD-I+SLD did not differ significantly on teacher-rated organizational deficits at baseline, but moderate-magnitude between-group differences were evident following the CLAS intervention (g = 0.59). Further inspection indicates that children with ADHD-I and comorbid ADHD-I+SLD improved on teacher-rated organizational deficits following the CLAS intervention, but children with only ADHD-I experienced greater improvement in teacher-rated organiza- tional deficits following intervention (g = 1.19) relative to those with a comorbid SLD (g = 0.62).

For parent-rated organizational deficits, the mixed
model ANOVA was significant for a main effect of time,
F(1, 72) = 94.14, p < .001, indicating significant, large

TABLE 1
Sample and Demographic Variables of Children Receiving Child Life

and Attention Skills

ADHD-Ia ADHD-I+SLDb

Variable M SD M SD

Child Age (Years) 8.98 1.09 9.47 1.07
Gender (% Boys) 53.8% 48.6%
KSADS IN Symptoms, Parent 7.56 1.10 7.42 1.04
KSADS HI Symptoms Parent 1.25 1.18 1.17 1.50
IRS–Parent 3.20 1.12 3.07 0.73
IRS–Teacher 3.02 1.06 3.17 0.97
On Medication at Randomization 7.7% 5.7%
KSADS Comorbid ODD* 0.0% 6.8%
KSADS Comorbid Mood Disorder 2.6% 1.4%
KSADS Comorbid Anxiety Disorder 2.6% 5.4%
FSIQ 104.92 9.98 102.26 12.06
WJ-III Passage Comprehension 100.38 8.07 96.29 10.96
WJ-III Reading Fluency* 105.95 14.94 93.71 13.03
WJ-III Math Fluency* 98.35 12.01 88.02 6.85
WJ-III Calculation* 106.62 11.47 98.51 11.09
Child Ethnicity
Caucasian 56.4% 54.3%
African American 2.6% 8.6%
Hispanic/Latinx 10.3% 14.3%
Asian/Pacific Islander 12.8% 5.7%
Mixed/Other 17.9% 17.1%

Note: ADHD-I = attention deficit/hyperactivity disorder–predomi-
nantly inattentive presentation; SLD = specific learning disorder;
KSADS = Kiddie Schedule for Affective Disorders and Schizophrenia
(Kaufman et al., 1997); IN = inattention; HI = hyperactivity and impul-
sivity; IRS = Impairment Rating Scale (Fabiano et al., 2006);
ODD = oppositional defiant disorder; FSIQ = Full-Scale IQ; WJ-III
= Woodcock–Johnson Test of Educational Achievement–III (Woodcock
et al., 2001).

an = 39.
bn = 35.

*p < .05.

860 FRIEDMAN ET AL.

magnitude improvement in parent-rated organizational
deficits following CLAS (g = 1.14). Neither the main
effect of SLD Status, F(1, 72) = 1.48, p = .23, nor the
SLD Status × Time interaction, F(1, 72) = .56, p = .46,
was significant.

Study Skills

As shown in Figure 1c, a significant main effect of time, F(1,
71) = 32.64, p < .001, was observed, indicating significant, moderate to large-magnitude improvement on teacher-rated study skills following CLAS (g = 0.61). A significant SLD Status × Time interaction, F(1, 71) = 4.12, p = .046, was also observed. However, the main effect of SLD Status, F(1, 71) = 3.43, p = .07, was not significant. Follow-up pairwise comparisons using the Benjamini–Hochberg FDR correction indicate that children with ADHD-I and comorbid ADHD-I +SLD did not differ significantly on teacher-rated study skills at baseline, but medium-magnitude between-group differ- ences were evident following the CLAS intervention (g = 0.56). Further inspection indicates that children with ADHD-I and comorbid ADHD-I+SLD improved on teacher- rated study skills following the CLAS intervention; however, children with only ADHD-I experienced greater improvement

in teacher-rated study skills following intervention (g = 0.89)
relative to those with a comorbid SLD (g = 0.37).

Homework Problems

For parent-rated homework problems, the mixed model
ANOVA was significant for a main effect of time, F(1, 71)
= 183.44, p < .001, indicating significant, large-magnitude improvement in parent-rated homework problems following CLAS (g = 1.45). As shown in Figure 1d, the main effect of SLD Status was also significant, F(1, 71) = 4.73, p = .03, indicating that children with comorbid ADHD-I+SLD experienced significantly more homework management and completion challenges relative to those with an ADHD-I monodiagnosis. However, the SLD Status × Time interaction failed to reach significance, F(1, 72) = 0.05, p = .84.

Post Hoc Analyses: Symptom Normalization

The preceding analyses indicate that larger treatment
effects were observed within the school setting for chil-
dren with ADHD-I relative to those with ADHD-I
+SLD. In a final set of analyses, we examine whether

a.)

c.)

b.)

d.)

FIGURE 1 Graphs depicting teacher-rated (a) CSI inattention symptom count, (b) COSS organizational skills deficits T score, and (c) ACES study skills
decile score, and parent-rated (d) HPC mean score for children with ADHD-I (solid line) and comorbid ADHD-I+ SLD (dashed line) before and after the
CLAS intervention.

LEARNING DISORDER CONFERS SETTING-SPECIFIC TREATMENT RESISTANCE FOR CHILDREN 861

rates of symptom normalization varied as a function of
SLD Status for significant models. Normalization was
defined as evincing subclinical symptoms of inattention
(i.e., five or fewer symptoms endorsed on the CSI-IV as
occurring often or very often), and minimal organiza-
tion (i.e., T score less than 65 indicating organizational
skills within 1.5 SDs of the mean on the COSS), and
study skills (i.e., decile scores 2 or below, as

recommended; DiPerna & Elliott, 2001) deficits on
posttreatment measures.

Results

revealed that children
with ADHD-I were significantly more likely to experi-
ence symptom normalization on teacher-rated inatten-
tion (χ2 = 7.14, p = .008, ADHD-I = 87.2%
normalized, ADHD-I+SLD = 60.0%), organizational
deficits (χ2 =4.03, p = .045, ADHD-I = 89.7% normal-
ized, ADHD-I+SLD = 71.4%), and study skills (χ2 =

TABLE 2
The Effect of Comorbid SLD on Parent- and Teacher-rated Outcomes

ADHD-Ia
ADHD-I
+ SLDb Pairwise Comparisons ESc

Outcome M SD M SD
SLD Status × Time

Interaction, F
ADHD-I vs. ADHD-I

+SLD
ADHD-I: Baseline

vs. Post

ADHD-I+SLD: Baseline

vs. Post

Teacher-Rated CSI
Inattention Symptoms

13.05* 2.08† 0.80†

[1.53, 2.63] [0.31, 1.29]
Baseline 6.56 1.96 6.31 2.22 −0.12

[−0.34, 0.58]
Posttreatment 1.92 2.43 4.14 3.08 0.80†

[0.32, 1.27]
Teacher-Rated COSS
Organizational Skills

3.95* 1.19† 0.62†

[0.71, 1.67] [0.14, 1.10]
Baseline 63.11 7.40 64.49 8.20 0.18

[0.28, 0.63]
Posttreatment 54.59 6.73 59.17 8.65 0.59†

[0.12, 1.05]
Teacher-Rated ACES
Study Skills

4.12* 0.89† 0.37†

[0.42, 1.35] [−0.10, 0.84]
Baseline 2.87 1.42 2.54 2.06 0.19

[−0.27, 0.64]
Posttreatment 4.49 2.12 3.31 2.04 0.56†

[0.10, 1.03]
Parent-Rated CSI
Inattention Symptoms

0.24 1.24 1.73
[0.75, 1.72] [1.18, 2.28]

Baseline 6.00 2.34 6.40 1.94 0.18
[−0.27, 0.64]

Posttreatment 2.66 2.96 2.74 2.24 0.03
[−0.43, 0.49]

Parent-Rated COSS
Organizational Skills

0.56 1.23 1.07
[0.75, 1.71] [0.57, 1.57]

Baseline 62.34 8.31 63.43 7.18 0.14
[−0.32, 0.60]

Posttreatment 53.61 5.44 55.94 6.69 0.38
[−0.08, 0.84]

Parent-Rated HPC
Homework Problems

0.05 1.59 1.42
[1.08, 2.10] [0.90, 1.59]

Baseline 2.47 0.46 2.69 0.53 0.44
[−0.02, 0.90]

Posttreatment 1.80 0.37 1.99 0.44 0.46
[0.00, 0.93]

Note: ACES = Academic Competence Evaluation Scale (DiPerna & Elliott, 2001); ADHD = attention-deficit/hyperactivity disorder; SLD = specific
learning disorder; COSS = Child Organizational Skills Scale (Abikoff & Gallagher, 2003); CSI = Child Symptom Inventory (Gadow & Sprafkin, 2002);
ES = effect size; HPC = Homework Problems Checklist (Anesko et al., 1987).

an = 39.
bn = 35.
cEffect sizes: Standardized mean differences corrected for sample size bias (Hedges’s g). Numbers within brackets represent 95% confidence interval of

Hedges’s g estimates.

*p < .05. †Significant after within-domain Benjamini–Hochberg false discovery rate correction following significant SLD Status × Time interaction.

862 FRIEDMAN ET AL.

7.74, p = .005, ADHD-I = 79.4% normalized, ADHD-I
+SLD = 48.6%) relative to those with ADHD and an
SLD.

Discussion

The current study is the first, to our knowledge, to
empirically examine whether the presence of an SLD
among school-age children with ADHD-I differentially
predicts response to a behavioral intervention targeted at
ADHD-I-related impairment (i.e., CLAS). It extends the
relatively limited prior literature addressing treatment
recommendations for children with comorbid ADHD-I
and SLD. The presence of academic deficits significantly
moderated improvement in teacher-rated inattention,
organizational deficits, and study skills, such that all
children improved across the domains assessed, irrespec-
tive of SLD Status, but children without a comorbid
academic weaknesses evinced greater treatment-related
improvement than those with a comorbid learning disor-
der. Children with ADHD-I were also more likely to
experience symptom normalization relative to children
with ADHD-I and an SLD on teacher-rated measures.
We did not find evidence for such moderation with
respect to parent-reported outcomes.

One possible explanation for the present findings is that
the attentional challenges observed in the school setting for
children with ADHD-I/SLD comorbidity are qualitatively
different from those of children with an ADHD monodiag-
nosis, reflecting specific difficulties with reading and math
rather than ADHD-related inattention, organizational defi-
cits, and study skills challenges. That is, children with
reading or math learning disabilities may appear inattentive
phenotypically during academic tasks because they lose
focus, engage in off-task behaviors, and become frustrated
due to the arduous nature of learning tasks (Pennington
et al., 1993). Therefore, the attenuated response to beha-
vioral intervention observed among children with ADHD/
SLD comorbidity could be because CLAS may not ade-
quately target the proximal etiological mechanisms contri-
buting to the fraction of inattentive symptoms that emanate
from learning challenges. It is important to note that, con-
sistent with a DSM diagnosis of ADHD-I, children in the
present study displayed symptoms and impairments across
multiple settings, including situations in which learning
demands are either minimized or less relevant (e.g., at
home, during social situations) as reported by both parents
and teachers. Although learning challenges might exacer-
bate inattentive symptoms within classroom settings among
children with comorbid ADHD/SLD, it is unlikely that
learning-related inattention can explain the totality of
impairments experienced by children with ADHD/SLD

comorbidity given the separate, additive symptoms and
impairment associated with each disorder.

The classroom supports provided by CLAS targeting
ADHD-related impairments (e.g., school–home daily
report card, behavioral classroom management interven-
tions, promotion of child skills within the classroom such
as organization, independence, time management, and
following routines) may be necessary but not sufficient
to address the cross-domain and unique challenges among
children with dual ADHD/SLD deficits. That is, inatten-
tion among children with comorbid ADHD/SLD appears
to emanate from two disparate underlying causes—one
related to ADHD and amenable to behavioral interven-
tions and another stemming from specific academic chal-
lenges. Children with comorbid ADHD/SLD are therefore
likely to require intervention aimed at reducing both
ADHD and SLD symptoms and related impairments.
This account is supported by current etiological models
of ADHD/SLD comorbidity (cf. DuPaul et al., 2013, for
a review) wherein comorbidity is associated with either
more severe or numerous neurocognitive and structural
deficits relative to only one disorder. Specifically, ADHD
and SLD are each linked to shared and unique neurocog-
nitive deficits (DuPaul et al., 2013; Purvis & Tannock,
2000; Willcutt et al., 2005, 2007) and structural/morpho-
logical differences (Hynd et al., 1990; Jagger-Rickels
et al., 2018; Kibby et al., 2009). Even more, ADHD/
SLD comorbidity is associated with neurocognitive defi-
cits in an additive fashion relative to those with only one
disorder. This explanation is also consistent with recent
evidence of neural morphology differences among chil-
dren with ADHD/SLD comorbidity (e.g., right thalamus
and left medial frontal cortical volume) that are absent in
children with monodiagnoses (Jagger-Rickels et al.,
2018). This, coupled with the observed differences in
symptom normalization rates among children with comor-
bid SLD, underscores the need for adjunctive, SLD-
specific intervention within this population to target the
multiple underlying deficits absent in those with an
ADHD-I monodiagnosis.

The presence of an SLD diagnosis did not signifi-
cantly affect treatment response on parent-rated inatten-
tion and organizational deficits at baseline or
posttreatment (i.e., a main effect). For parent-rated home-
work problems, all children exhibited large-magnitude
improvements (g = 1.45) following intervention.
Children with comorbid ADHD-I and SLD, however,
showed greater parent-rated homework problems at base-
line and posttreatment relative to those with an ADHD-I
monodiagnosis (i.e., significant main effect of SLD sta-
tus). Treatment response on parent-rated homework pro-
blems, however, did not significantly differ for the
diagnostic subgroups following the CLAS intervention

LEARNING DISORDER CONFERS SETTING-SPECIFIC TREATMENT RESISTANCE FOR CHILDREN 863

(i.e., nonsignificant interaction). This finding was surpris-
ing, particularly in light recent results from Breaux et al.
(2019) that middle-school-age adolescents with ADHD
and low to below-average academic performance pre-
dicted poor treatment response to contingency-
management and skills-based homework interventions.
However, the absence of treatment response differences
is consistent with findings from the MTA study, in which
SLD Status neither moderated nor predicted improve-
ments in parent-rated homework performance among
elementary-school-age children (Langberg et al., 2010).
It is possible that differences in age-related homework
expectations (e.g., increased time spent completing
homework, more long-term projects, and greater expecta-
tions for homework independence in middle school rela-
tive to elementary school) affect parent-rated impairment.
The age-demographic differences among the studies,
coupled with the homework focused intervention used
in the Breaux and colleagues study relative to the MTA
and CLAS interventions that target varied areas of
impairment, may account for the discrepant findings.

Limitations and Future Directions

Several caveats warrant discussion despite multiple meth-
odological strengths (e.g., multimethod/multi-informant
ADHD diagnosis; intensive multimodal intervention; and
stringent SLD delineation scores). Although the sample
size of the present study was sufficient to assess the
questions of interest, the limited number of participants
precluded consideration of the differential effects of indi-
vidual learning disorders (i.e., specific learning disorder in
reading relative to math). Future studies should examine
whether results are consistent across learning disorder
modalities and replicate the findings of the current study
using larger and more diverse samples (e.g., larger range
of socioeconomic levels and racial ethnicity/backgrounds,
differing age ranges of participants) as well as samples
with clinically confirmed SLD. In a related vein, the
parents of study participants were highly educated (i.e.,
85% of parents reported graduating from college), and
therefore the generalizability of the present findings may
be limited, particularly in light of potential relations
between parental academic success and child school func-
tioning. However, parent education level did not vary as
a function of SLD Status, and it is therefore unlikely that
parent education level accounted for systematic variance
in the attenuated treatment response observed within the
school setting.

We also recognize that many clinical disorders, particularly
ADHD-I and SLDs, exist on a continuum of normally distrib-
uted scores, and the use of a cutoff score artificially dichot-
omizes inattention and academic achievement abilities.
However, our decision to operationalize ADHD-I and SLD

as binary constructs is consistent with that of many school
districts within the United States and abroad, wherein provi-
sion of intervention services is considered only following
a diagnosis. Future studies should examine if findings are
consistent across varying degrees of attention and learning
challenges, particularly because the presentation of ADHD-I
is heterogeneous and may include children with subthreshold
combined presentation.3

Despite the use of a posteriori procedures to identify cases of
potential SLDs because of the absence of full
a psychoeducational evaluation, the observed ADHD/SLD
comorbidity rate (i.e., 47.3%) is nearly identical to that identi-
fied in extant literature (i.e., 45.1%; DuPaul et al., 2013). Rates
of SLDs in reading also fell within the range of previously
reported comorbidities, albeit within the lower portion of the
reported range. However, the comorbidity rate for math SLD
(i.e., 42%) is slightly higher than the range identified in extant
literature, which primarily usedDSM-IV diagnostic procedures.
(i.e., 5%–30%; DuPaul et al., 2013). This discrepancy likely
reflects the current study’s consideration of math fluency for
SLD diagnosis, consistent with the DSM-5, which was absent
in DSM-IV criteria used within extant studies. In addition,
recent evidence suggests that mathematics deficits are more
closely related to inattention rather than hyperactivity/impul-
sivity (Bauermeister et al., 2012; Garner et al., 2013) and the
genetic overlap between specific academic weaknesses in math
and ADHD is largely driven by inattention symptoms (Greven
et al., 2014, Plourde et al., 2015). Therefore, children with
ADHD-I, of which our study sample was comprised exclu-
sively, may be at a greater risk for SLDs in math relative to
other presentations of the disorder and likely accounts for this
observed discrepancy. Future studies should examine whether
findings are consistent among samples using clinically diag-
nosed SLD and differing ADHD presentations.

It might be argued that our measures of reading com-
prehension and fluency reflect inattention more than they
indicate a true learning disability because of their high
correlation with inattention (Arrington et al., 2014;
Plourde et al., 2015). Were that true, we would expect the
SLD group to have higher inattention scores at baseline,
and this was not the case. Conversely, it might be claimed
that our measures of reading comprehension and fluency
led to overidentification of learning disorder due to this
correlation. The lack of baseline differences cast doubt on
this critique, as well as the fact that our rate of comorbid
learning disorder fell within the lower range of estimates
identified in extant literature (DuPaul et al., 2013). Note
that we do not deny the correlation, we simply assert that it
does not threaten our findings. Future studies should exam-
ine whether outcomes are consistent when reading

3Reexamination of the study models excluding participants with more
than three symptoms of hyperactivity/impulsivity on the KSADS clinical
interview (n = 3) did not change the pattern or interpretation of findings.

864 FRIEDMAN ET AL.

decoding measures are considered, although we hypothe-
size that findings will be consistent with our own.

The use of parent- and teacher-rated outcome measures
may overestimate the magnitude of treatment-related
improvements because of their active involvement in treat-
ment (i.e., Hawthorne effects). Future studies may wish to
use objective outcome measures (e.g., blinded, direct obser-
vations) to more accurately characterize the magnitude
treatment attenuation among children with specific learning
difficulties. Likewise, future investigations should also
determine whether SLD affects treatment-related changes
on a broader range of academic outcomes (e.g., grades,
daily report cards, academic achievement tests).

Clinical Implications

Collectively, the present results indicate that CLAS is an
effective intervention for children with ADHD-I regardless
of SLD comorbidity status, as robust improvements were
observed across home and school settings and within several
domains of functioning including inattention symptoms, orga-
nization deficits, homework problems, and study skills.
Additional intervention to address the underlying learning
challenges among those with a comorbid SLD is warranted
to produce maximal improvements. That is, multimodal treat-
ment targeting ADHD-I (e.g., behavioral interventions) and
SLD (e.g., direct instruction, tutoring) may be necessary to
address the cross-domain challenges associated with ADHD-
I/SLD comorbidity. Further study would be needed to evalu-
ate the temporal sequencing of interventions to determine
whether (a) ADHD and SLD intervention should occur con-
comitantly or (b) the symptoms and impairment related to one
disorder require amelioration prior to initiating intervention
for the comorbid condition.

Our findings are also important for informing diagnostic
assessment, treatment planning, and intervention monitoring
practices. Currently, full psychoeducational evaluations for
ADHD are used with diminished frequency within clinical
settings because (in part) of insurance reimbursement chal-
lenges, ever-increasing patient quotas, and long waitlists for
services (Handler & DuPaul, 2005; Nelson, Whipple,
Lindstrom, & Foels, 2014). However, the present results sug-
gest that psychoeducational testing for SLD may be a valuable
component of ADHD assessment and treatment planning given
high comorbidity rates and varying responses to treatment.
Current medical guidelines state that testing is unnecessary
for making the diagnosis of ADHD. Although this may be
technically true for applying diagnostic criteria, it leaves unseen
critical cognitive and academic features that influence treatment
expectations. Poor academic achievement, or another sign of
a learning disorder, will indicate the possibility that treatment
gains may be limited within the school setting and, based on
these data, that only a fraction of the variance in teacher-rated
inattention may respond to ADHD treatment.

Despite the increased parent–teacher communication
that occurred during the CLAS intervention (i.e., as
many as five parent–teacher conferences over a 10-
week span), parents were not as perceptive to SLD-
related effects on functioning relative to classroom
teachers. This might be explained by the greater sensi-
tivity on the part of teachers to inattention that is
secondary to SLD and more readily observed in the
classroom, underscoring the importance of gathering
diagnostic and treatment response data from children’s
classroom teachers both during assessment and while
administering behavioral interventions for ADHD.

Conclusions

As advances continue toward developing effective and
lasting interventions for children with ADHD, it is impor-
tant to consider the synergistic effect of comorbid condi-
tions on ADHD-related sequela, as well as intraindividual
strengths and weaknesses when designing intervention
plans to maximize treatment effectiveness. Although the
current findings underscore the importance of academic
achievement deficits in the context of a comprehensive
intervention for ADHD-I, additional factors including neu-
rocognitive profiles, comorbid internalizing symptoms,
family and interpersonal dynamics, and sociocultural iden-
tities may also affect treatment response and should be
taken into consideration to inform more tailored and pre-
cise interventions for the disorder.

DISCLOSURE STATEMENT

No potential conflict of interest was reported by the authors.

FUNDING

This research was supported by National Institute of Mental
Health Grant MH077671.

Lauren Friedman and Melissa Dvorsky are supported by
award number T32MH018261 from the National Institute
of Mental Health (NIMH). The content is solely the respon-
sibility of the authors and does not necessarily represent the
official views of the National Institutes of Health.

ORCID

Melissa R. Dvorsky http://orcid.org/0000-0002-3790-
1334

LEARNING DISORDER CONFERS SETTING-SPECIFIC TREATMENT RESISTANCE FOR CHILDREN 865

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Abstract
Method

Participants

Procedure

Intervention

Parent component

Child component

Teacher component

Measures

Specific learning disorder

Outcome Measures

Inattention

Organizational deficits

Study skills

Homework problems

Data Analytic Plan

Results

Preliminary Analyses

Inattention

Organizational Deficits

Study Skills

Homework Problems

Post Hoc Analyses: Symptom Normalization

Discussion

Limitations and Future Directions

Clinical Implications

Conclusions

Disclosure statement
Funding
References

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