Randomized Controlled Trial of Web Based Tools to Improve Medication Continuity in Adolescents With ADHD
Phase: NA
Conditions: Attention Deficit Hyperactivity Disorder, Adherence, Medication
Sponsor: Children's Hospital Medical Center, Cincinnati

 
 
 
 
 
Official Title of the study: Randomized Controlled Trial of Web Based Tools to Improve 
Medication Continuity in Adolescents with ADHD 
 
NCT number: NCT04386096 
 
Document name: Study Protocol 
 
Date of the document: 2/12/2021

 
 
Page 1 of 20 
2/12/2021 
ABSTRACT:  
Medication is an efficacious treatment strategy for adolescents with attention-
deficit/hyperactivity disorder (ADHD) (Chan et al. 2016), however use significantly declines 
during adolescence when the consequences of ADHD are most severe (e.g. dropping out of 
school, delinquency, etc.) (Visser et al. 2014). The Unified Theory of Behavior Change (UTBC) 
(Fishbein et al. 2001) has been proposed as a conceptual model to explain the mechanism 
underlying ADHD medication adherence and to guide the development of interventions to 
improve the continuity of treatment (Chacko et al. 2010). The UTBC is a well-established and 
empirically tested model that identifies factors that influence an individual’s intention to perform 
a behavior as well as factors that influence whether a behavior is actually carried out (Fishbein 
et al. 2001). Indeed, our preliminary data support the relevance of pre-intention factors and 
implementation factors for medication continuity among adolescents with ADHD. For example, 
we found that a significant majority of adolescents intentionally stop taking medicine because 
they question the medicine’s benefits (i.e., Expectations in model). We also found that 
adolescents who intend to take medicine experience a variety of barriers to taking it regularly, 
including deficient organizational and problem solving skills, inconsistent access to timely refills, 
and lack of daily routines to support continuity (Brinkman et al. 2012). For example, an 
adolescent may repeatedly forget to take their medicine. 
Customizable interventions are available to address these factors. For example, 
pediatrician-supervised trials on and off medicine are recommended in ADHD practice 
guidelines (Pliszka 2007; AAP 2011) to shape expectations related to benefit vs. unwanted 
effects of continued medicine use. However, these rarely occur in practice, leaving adolescents 
to conduct impromptu experiments stopping their medicine and often experiencing a negative 
outcome before realizing that medicine is still needed (Brinkman et al. 2012). Forgetting to take 
medicine can be addressed by programming regular text message reminders, which may help 
make medicine taking more automatic. 
Currently, no interventions target medication continuity for adolescents with ADHD. Our 
research team is well positioned to create an intervention that addresses each of the main 
UTBC factors influencing the intention and implementation of regular medicine taking. With NIH 
funding, we have developed web-based interventions that improve the care and outcomes for 
young children with ADHD (Epstein et al. 2011, 2016) and improve adolescent medication 
continuity for other chronic conditions (Hommel et al. 2013). Such an intervention would 
transform care for adolescents with ADHD and help prevent the alarming fall-off in effect size 
from medication efficacy studies to effectiveness in real world practice caused by poor 
adherence. 
 
PURPOSE OF STUDY:  
 
The primary goal of the proposed project is to test a multi-component intervention that 
systematically identifies and targets aspects of the UTBC model most relevant for each 
adolescent with poor ADHD medication continuity. Our central hypothesis is that our tailored 
intervention will support ADHD medication continuity, and ultimately improve outcomes for 
adolescents with ADHD.  
 
BACKGROUND: 
 
Statement of the problem 
ADHD is the most common mental health condition of childhood (Perou et al. 2013) 
affecting 6.4 million children aged 4-17 years in the United States (Visser et al. 2014). Children 

 
 
Page 2 of 20 
2/12/2021 
with ADHD experience impairments across a wide range of areas of functioning including 
academics, social relationships, and family functioning (Wehmeier et al. 2010). Fortunately, 
efficacious treatments for ADHD exist. Medications, either alone or in combination with behavior 
therapy, reduce ADHD symptoms and some areas of impairment (MTA 1999; Chan et al. 2016) 
and are recommended as a first-line treatment in clinical practice guidelines (Pliszka 2007; 
Wolraich et al. 2011). Medication use is quite common among children with ADHD, but use 
plummets after age 11 even though adolescents continue to demonstrate symptoms and 
impairment (Visser et al. 2014; Howard et al. 2016). Moreover, those who continue to take 
medicine take their medications inconsistently (i.e., only 50% of days covered with medicine; 
Molina et al. 2009). 
 
Developmental influences 
Changes during adolescence likley contribute to the decline in medication continuity. 
Most teenagers expect to have a voice in decisions that concern them. Collaborative decision 
making between parents and children is a part of normative development that precedes full 
decision-making autonomy (White 1996; Wills et al. 1996). Teen involvement in medical 
decisions may positively impact self-efficacy, satisfaction with medical care, adherence, and, 
ultimately, the transition to adult health care (McCabe 1996; White 1996; Wills et al. 1996; 
Walker et al. 2001; Schmidt et al. 2003; Miller et al. 2014). However, many parents are afraid to 
give their teen with ADHD a say in decisions about medicine because they believe it helps and 
worry that teen goals are short sighted (Brinkman et al. 2009; Brinkman et al. 2012). Many 
adolescents desire to stop taking medicine because they don’t believe it helps or they don’t like 
how it makes them feel. Some teens describe feeling ‘zoned out’ or less social, less creative, 
more irritable, or experience other somatic side effects (e.g. headache, etc.) (Knipp 2006; 
Meaux et al. 2006; Singh et al. 2010; Brinkman et al. 2012). Moreover, many teens are given 
the day-to-day responsibility for medication taking, and are increasingly without the safety net of 
parental supervision (Brinkman et al. 2012; Brinkman et al. 2016). 
 
Impact of poor medication continuity 
As a result of these developmental changes, teens with ADHD evidence low rates of 
medication continuity. Unfortunately, at the same time medication continuity declines, the 
outcomes of ADHD become increasingly consequential. For example, adolescents with ADHD 
are more likely than their peers to have fewer friends, drop out of school, use tobacco and illicit 
drugs, interact with the juvenile justice system, be treated for sexually transmitted infections, 
and have teen age pregnancies (Barkley et al. 2006; Molina et al. 2009; Bussing et al. 2010). 
Given that medicine has large effects on adolescent performance across a variety of domains 
(e.g. academic tasks, social skills, etc.) (Smith et al. 1998; Evans et al. 2001; Chan et al. 2016), 
poor medication continuity represents a significant public health problem. Because the vast 
majority of adolescents receive ADHD care from pediatricians in primary care practices (Albert 
et al. 2017), any intervention that will address this problem must be amenable to this setting. An 
intervention that improves medicine continuity during the transition from family- to self-
management of a teen’s mental health condition would transform care and outcomes by closing 
the gap between medication efficacy and effectiveness in real world practice. 
 
Mechanisms supporting medication continuity 
Maintaining continuity of medication treatment among adolescents with ADHD is often 
difficult and influenced by heterogeneous factors. Indeed, different families have different needs 
at different times. A large body of basic behavioral science research has shown that behavioral 
change and maintenance of that change is best accomplished by addressing underlying 
mechanisms of change (i.e., beliefs about the pros and cons of the behavior, social norms and 

 
 
Page 3 of 20 
2/12/2021 
influences, self-efficacy beliefs, and the degree to which any individual actually intends to adopt 
a behavior) (Armitage et al. 2000). Hundreds of studies have demonstrated that interventions 
must address these underlying mechanisms in order to reliably change behavior (Ajzen 1991; 
Jaccard et al. 1999; Fishbein et al. 2001; Rhodes et al. 2013). The UTBC (Fishbein et al. 2001) 
has been proposed as a conceptual model to explain the mechanism underlying ADHD 
medication continuity and guide the development of interventions to improve it (Chacko et al. 
2010). 
The UTBC identifies two processes in behavioral change (see Figure 1). The first process 
focuses on 5 determinants of an individual's willingness, intention, or decision to perform a 
critical behavior (see pre-intention factors on left of Figure 1): 1) Expectations (also called 
expected-values) refers to an individual's perceived advantages and disadvantages of 
performing the behavior. For example, in the case of taking a medication, an adolescent might 
believe with varying degrees of certainty that a medication will help her/him pay attention at 
school, but s/he may also believe that these benefits may be outweighed by other negative 
consequences (e.g., side effects). 2) Social Norms include two components, a) the adolescent’s 
perceptions about what their parents think s/he should do with respect to the behavior (i.e. 
taking medicine), and b) the adolescent’s perceptions about whether his/her peers would also 
approve of and/or perform the behavior. Thus, the more stigma an individual feels about taking 
medicine for ADHD (Pescosolido et al. 2007), the less likely it is that s/he will decide to do so. 3) 
Self-concept and image considerations refer to an individual’s concept of one’s self and whether 
performing the behavior is 
consistent with or contradicts 
one’s self-image, rendering 
the behavior more or less 
attractive. An individual who 
strongly feels that ADHD is a 
biomedical condition that 
requires biomedical treatment 
and s/he is the type of person 
who always takes action to 
improve their health will be 
more likely to take medicine 
for ADHD than one who does 
not (Leslie et al. 2007); 4) 
Affect and emotions refers to 
an individual’s affective and 
emotional reactions to 
behavioral performance: 
individuals who have a strong 
negative emotional reaction to taking medicine because they equate it to a battle for control with 
their parents will be less inclined to regularly take medicine than if one feels like their parent 
involves them in decisions that impact them. Adolescent-parent conflict often flows from 
differences of opinion about the benefit of medicine with parents worrying that adolescents are 
short sighted in their goals and overestimate their competence compared to objective criteria 
(Owens et al. 2007; Brinkman et al. 2009). Conversely, adolescent involvement in decision 
making (e.g. sharing opinions, negotiating with parent) has been related to higher levels of 
treatment regimen adherence in chronic conditions like diabetes (Miller et al. 2014). 5) Self-
efficacy refers to one's beliefs that s/he can perform the behavior, and how easy/difficult it is to 
perform the behavior. Thus, an adolescent who believes that s/he can easily take medicine 
regularly within their daily routines will be more willing to do so (i.e., higher self-efficacy beliefs 

 
 
Page 4 of 20 
2/12/2021 
will result in stronger behavioral intentions). Each of these five factors predicts variation in 
behavioral intentions or the decisions whether to perform specific behaviors. 
The second set of four factors affect whether strong behavioral intentions are actually 
carried out (see implementation factors on right side of Figure 1). One variable pertains to the 
requisite knowledge and skills for behavioral performance - one may intend to take ADHD 
medicine regularly, but may subsequently find that s/he does not have the skills needed to take 
medicine every day. For example, some adolescents struggle to swallow pills. Adolescents may 
also lack the organizational and/or problem-solving skills needed to take medicine reliably. 
Another variable is the environmental constraints that may render behavioral performance 
difficult or impossible. For example, adolescents taking ADHD medicine are often dependent on 
their parent(s) to obtain medicine refills. This is often relevant because parents of adolescents 
with ADHD are more likely to have ADHD and/or depression (Chronis et al. 2003) which may 
interfere with their ability to support medication continuity by obtaining timely refills. Third, 
salience of the behavior is important so that the person does not forget to enact it. Even when 
salience is present, forgetting can be a challenge for adolescents with ADHD. Finally, habit and 
automatic processes may influence behavior. For example, by force of habit, a person who has 
developed a routine to help them to remember to obtain and take their medicine regularly will be 
more likely to sustain this behavior when competing intentions are activated and distractions are 
present. 
We acknowledge that adolescent medication continuity is a complex phenomena and that 
no model can capture all of the factors and directionality that lead to medication continuity. 
Indeed, self-efficacy is likely influenced by past experiences managing pre-intention and 
implementation factors. In addition, Figure 1 fails to capture the important roles that parents and 
pediatricians play in supporting medication continuity. Regardless of these limitations, the UTBC 
conceptual model helps explain the mechanism underlying ADHD medication continuity and will 
help guide efforts to develop and test interventions (Chacko et al. 2010). 
 
Pre-intention factors influencing ADHD medication continuity 
We analyzed data from the Multimodal Treatment Study of Children with ADHD (MTA) to 
determine the prevalence of factors that impact adolescents’ intentions to take medicine 
regularly (Brinkman et al. 2016). Twelve years after enrolling in the MTA, patients completed a 
survey reporting their age when they last stopped taking medicine for a month or more and their 
reasons for stopping. 94% of the sample (350/372) reported stopping, with a mean (SD) age of 
14.2 (3.5) years when they last stopped taking medicine for ADHD. The most commonly 
endorsed reasons for stopping medicine related to questioning whether medicine was still 
needed or helped. Reasons related to side effect concerns were endorsed by a significant 
minority of adolescents (33-46%). The most commonly endorsed adolescent reasons for re-
starting medicine related to recognition that medicine was helping at school or work (86%), with 
45% of adolescents coming to realize that medicine was still needed after they had stopped 
taking it. For both stopping and restarting, the proportion endorsing some reasons differed by 
age range, with the overall pattern suggesting that parental involvement in stopping and 
restarting medications decreased with age. 98% of participants continued to have functional 
impairment after stopping medicine.  
 
Implementation factors influencing ADHD medication continuity  
We conducted focus groups with adolescents with ADHD (n=44) and parents (n=52) 
(Brinkman et al. 2009, 2012). Using an inductive approach to code transcripts and identify 
saturated themes, we elucidated a variety of barriers to medication continuity when adolescents 
intended to take medicine regularly. Some adolescents struggle with swallowing pills. Parental 
involvement in medication taking ranged from providing direct supervision, to reminders, to 
providing no supervision. Adolescent responsibility for medication taking increased with age and 

 
 
Page 5 of 20 
2/12/2021 
maturity. However, many adolescents acknowledged that forgetting to take their medication was 
still an issue. Indeed, the organizational difficulties experienced by many adolescents with 
ADHD and their parents, who are at higher risk for ADHD themselves (Chronis et al. 2003), are 
a significant barrier to reliably obtaining refills before medicine runs out and taking medicine 
regularly. Moreover, parents often benefit from training on how to set goals, use behavioral 
contracts and rewards/consequences to encourage desired behaviors from their children with 
ADHD (Chronis et al. 2006), though these approaches have not been applied to ADHD 
medication continuity. 
 
Intervention development requires adolescent, parent, and pediatrician participation to 
ensure all needs are met 
We have a strong record of success conducting ADHD research in partnership with primary 
care practices. 10 studies conducted by Drs. Brinkman and Epstein have involved 180 
practices, 616 pediatricians, and 3011 families (Epstein et al. 2007; Epstein et al. 2008; 
Brinkman et al. 2009; Epstein et al. 2010; Brinkman et al. 2011; Epstein et al. 2011; Brinkman et 
al. 2012; Brinkman et al. 2013; Brinkman et al. 2016; Brinkman et al. 2016; Epstein et al. 2016). 
Dr. Brinkman developed and is testing an intervention to improve adherence among 118 
children with ADHD ages 6-10 years cared for by 43 pediatricians. By engaging parents in the 
intervention development process for this study, we learned that the Vanderbilt ADHD Rating 
Scales (used by pediatricians around the country to monitor response to treatment) lack 
salience. Parents voiced a need to be able to track specific behaviors that were important for 
their child. As a result, we developed this capability in the intervention. In focus groups we’ve 
conducted in preparation for the proposed project, adolescents have voiced a similar need. 
Teens would like to be able to track outcomes that matter most to them and depend on their 
report. For example, parents and teachers have a perspective on how teens get along with 
peers, but only the teen can say whether they feel accepted by their peers or experience 
stigma. Teens we met with are eager to have their voice more fully integrated in the process of 
treatment monitoring. 
 
Leveraging a web-based intervention used by parents and pediatricians to efficiently 
conduct the proposed research and facilitate future dissemination 
Dr. Epstein developed a web-based intervention (mehealth for ADHD) which enables 
community-based pediatricians to deliver higher quality ADHD care (Epstein et al. 2011) leading 
to children with significantly fewer ADHD symptoms (Epstein et al. 2016). Subsequently, 
partnerships with the American Academy of Pediatrics and American Board of Pediatrics helped 
spread use of the portal beyond practices that participated in research and now includes 17,412 
patients cared for by 890 pediatricians in 659 practices across the US. These practices use the 
portal as a registry to manage their entire ADHD patient population. With pediatricians 
continuing to enroll patients on the portal as part of routine clinical care, opportunity exists to 
leverage this infrastucture to efficiently develop and test new interventions. The proposed 
research would fill a sizable gap as the current portal is focused exclusively on young school 
age children with ADHD and medication adherence has not been targeted nor improved. 
Specifically, while a randomized controlled trial testing the efficacy of the mehealth for ADHD 
web intervention demonstrated significant effects on children’s treatment outcomes, there was 
not a significant intervention effect on medication adherence (i.e., 59% of days covered by 
children in the mehealth for ADHD portal group vs. 54% in the control group) (Epstein et al. 
2016). Moreover, the portal is devoid of features for adolescents. In focus groups, pediatricians, 
parents, and adolescents have repeatedly requested such features. 
 

 
 
Page 6 of 20 
2/12/2021 
STUDY DESIGN: 
We will conduct a 4-month parallel group RCT among adolescents with poor medication 
continuity (see Figure 2) to test whether the intervention engages the mechanism underlying 
medication continuity and improves outcomes. We will recruit 44 adolescents with ADHD with 
poor medication continuity from Cincinnati Children’s Pediatric Primary Care Clinic (PPCC) to 
test the intervention. Currently, there are 230 adolescents aged 11-15 seen at PPC who are 
diagnosed with ADHD, 
taking ADHD medication, 
and are registered on 
mehealth for ADHD. 
Therefore, there is a large 
group of adolescents from 
which to recruit. In 
preparation for research, 
we will assess the number 
of prescriptions written for 
ADHD medicine from their 
electronic medical record 
to ascertain basic 
eligibility criteria. Because the medication experiment feature is not clinically relevant for 
adolescents taking a non-stimulant ADHD medication, and this is a key portion of the 
intervention, those who are taking non-stimulant medications will not be included. At the time of 
enrollment, families will schedule an in-person visit during which parents and adolescents will 
complete baseline measures and receive training on how to use mehealth for ADHD. If families 
are unable to complete this visit in-person, consent and assent will be completed over the 
phone, measures will be sent electronically via REDCap, and study staff will conduct training on 
how to use mehealth for ADHD remotely (i.e. using Zoom to share screen). Before participants 
are randomized, we will verify the number of days covered with medicine based on dispensing 
data. This estimate will be used for the stratified randomization procedure. Participants will be 
randomized into either the intervention group or control group. The control group will continue to 
use the standard mehealth for ADHD software, and the intervention group will receive access to 
the intervention features. Because medication use varies widely during the summer months and 
school holidays, the intervention will begin just prior to the start of the school year to reduce 
variation in medication continuity based on time of year. The trial will end 4 months later. At that 
time, families will complete end of study measures, and pharmacy dispensing records will be 
obtained. The end of study measures may be completed in-person or electronically. 
DURATION: 
This IRB protocol covers the second phase of the study during which we will test the 
medication continuity tools developed in collaboration with our stakeholders during the first 
phase of the study. Families will be enrolled in the study for approximately 10 months. 
PROCEDURES: 
Research Participant Recruitment and Obtaining Informed Consent 
All participants will be recruited from Cincinnati Children’s Hospital PPCC. A research 
assistant will initiate phone contact with PPCC patients who appear eligible based on their age, 

 
 
Page 7 of 20 
2/12/2021 
being registered on mehealth for ADHD, and having less than 80% of days covered with ADHD 
medicine based on prescriptions written in the past year.  Phone calls will serve to provide 
information about the study and answer questions. Those who express interest will complete 
screening questions needed to verify eligibility criteria. If they are eligible, the research assistant 
will schedule an in-person visit during which they will review the full consent and assent form 
with the parent and adolescent. After we review the content of the consent form with the parent, 
they will record their consent on REDCap using a study-specific consent form modeled after the 
eConsent demo on the REDCap Resource Center. We will also explain the study to children (in 
language appropriate to them; see below), and record their assent in REDCap.  Following this, 
participants will complete their baseline surveys and receive a ClinCard to reimbursement them 
for their study visit. If families are unable to complete this visit in-person, it will be completed 
remotely via phone call and/or video conferencing. 
Inclusion/Exclusion Criteria 
Inclusion Criteria: Participants for the study must meet all of the following criteria:  
a. Consent: The family must provide informed consent by parents or legal guardians 
b. Assent: Children must provide assent to participate in the study  
c. Ages 11-15 
d. Treated for ADHD by pediatrician 
e. First prescribed ADHD medicine more than one year prior to enrollment 
f. Have < 80% of days covered by ADHD medicine in the past year of treatment (based on 
pharmacy dispensing records) 
g. Filled at least one prescription for a stimulant medication in the past year 
Exclusion Criteria: Participants will be excluded from the study if they meet any of the following 
criteria: 
a. Poor understanding level: The participant and parent cannot understand or follow 
instructions given in the study. 
b. Have > 80% of days covered by ADHD medicine in the past year of treatment (based on 
pharmacy dispensing records) 
c. Do not have reliable access to the internet at their home or another location. 
d. Will not permit their child to access the internet for study related activities 
e. Are not able or willing to send or receive text messages 
 
Intervention 
The intervention addresses the main UTBC factors influencing the intention and 
implementation of regular medicine taking. Items from standard UTBC scales (Ajzen et al. 1981) 
will assess the relevance of pre-intention factors and items from the validated Adolescent and 
Parent Medication Barriers Scales (Simons et al. 2007; Simons et al. 2010) to assess the 
relevance of implementation factors (see Measurement). After this assessment battery is 
collected from adolescents and parents, automated algorithms identify and recommend the 
specific intervention components tied to UTBC factors that are most relevant to address the 
needs of each adolescent/parent.  
We will send weekly text message reminders to parents in the intervention group with 
prompts to use the new features on the mehealth for ADHD website. These messages will 
highlight a new intervention tool each week with a subject specific URL to take the parent 

 
 
Page 8 of 20 
2/12/2021 
directly to the tool. The parent will receive different text message prompts depending on what 
tools were recommended and have been used.  
We will also call parents in the intervention group to understand their experience with 
using the mehealth for ADHD website. The parent will be asked different questions depending 
on their level of engagement with the website. We will additionally ask about how their child is 
managing school and their ADHD symptoms. The phone call will take place as a semi-
structured interview. 
Intervention components targeting UTBC pre-intention factors 
1. Education (Targeting adolescent and parent expectations, self-concept, affect and 
emotions) 
The intervention delivers education about relevant topics (e.g. the etiology of ADHD; how 
medicine works; the importance of medication titration, how to mitigate side effects and 
minimize dosing regimen complexity, and how adolescents, parents, and doctors can work 
together to titrate medicine, conduct a trial on/off, and discourage diversion). 
2. Pediatrician supervised medication management (Targeting adolescent and parent 
expectations, self-concept, affect and emotions). 
Overview: Pediatricians can play a critical role supporting medication management and 
continuity of treatment, if they have the right information and teens and parents are actively 
engaged in the process. When teen and parent responses to the assessment battery suggest 
that the teen may benefit from additional titration or a trial on/off medication, the teen and parent 
will all be alerted to the recommendation. Adolescents and parents will be guided through a 
series of customized steps using program routines, called wizards. A software wizard is a user 
interface type that presents a sequence of dialog boxes that lead the user through a series of 
steps towards goal completion. Wizards will prompt patients and parents to identify, prioritize, 
and discuss behavioral targets to monitor during titration or trial on/off medicine.  
Medication titration: Dosage adjustment and/or titration of a medicine with a different 
chemical ingredient will be recommended to optimize effectiveness when a teen/parent indicate 
they are interested in trying a new medication or dose. Parents and adolescents who express 
interest in changing medicine or dose will be directed to make an appointment with their 
pediatrician to discuss what the best option is for the family. Videos that describe different 
medication/treatment options will also be available for the parents and adolescents.  
Pediatrician supervised trial on/off optimal dosage: A structured trial on/off medicine will be 
recommended when teen/parent responses to the assessment battery indicate uncertainty 
about whether medicine is still needed because the teen appears to be thriving. The intervention 
delivers training on how to conduct a high quality trial on/off medicine will include the ADHD 
clinical practice guideline recommendations (Pliszka 2007; AAP 2011) that differentiate these 
trials from the common clinical practice of stopping medication during summer or holiday breaks 
from school (e.g., best when there are few transitions or demands [mid school year], avoid at 
beginning of any school year, especially at the start of junior/senior high school, discontinue 
medication for 2-4 weeks, monitor target outcomes). The trial on/off medicine is designed to 
reduce ambivalence about medicine (i.e. document improvement among teens that still benefit) 
which may motivate self-directed changes to support medication continuity. Of note, trials on/off 
non-stimulant medication have limited utility given that atomoxetine and guanfacine take 4-6 
weeks before maximal response is achieved and guanfacine can’t be abruptly stopped due to 
risk of rebound hypertension (Froehlich et al. 2013). Accordingly, pediatricians will advise each 
family regarding the value of conducting an on/off trial in each situation. 
Symptom & side effect monitoring: The mehealth for ADHD intervention enables the tracking 
of ADHD symptoms, medicine side effects, and other outcomes that are important to 

 
 
Page 9 of 20 
2/12/2021 
adolescents and parents. In addition, adolescents and parents can construct their own 
measures using a structured approach with examples to ensure that adolescents and parents 
can translate what matters most to them into a measure that can be tracked over time. For 
example, an adolescent could decide to record the presence of a relevant side effect (e.g. 
irritability) on a daily basis. A parent could decide to track the time spent completing homework 
every night. Adolescents and parents can report on their chosen outcomes via an internet 
survey that has been optimized for completion on a mobile screen. The system provides 
reminders to adolescents and parents to rate targeted outcomes by cell phone text messages. 
At the conclusion each titration or trial on/off medicine, the pediatrician, adolescent and parents 
will regroup to discuss what was learned using a report generated by mehealth for ADHD to 
visualize the outcome data that was collected. The intervention also includes a tool that will 
enable parents and/or adolescents to indicate side effect(s) that are problematic for them. The 
tool will guide them through solutions that may mitigate the side effect(s) they are experiencing 
from their ADHD medication.  
3. Stigma (Targeting adolescent and parent social norms) 
Videos normalizing ADHD and medication taking: There are hundreds of videos available on 
YouTube related to ADHD (Kang et al. 2016). Some videos share information about successful 
people with ADHD. Other videos feature celebrities talking about how medication helps them 
manage ADHD. Yet other videos, like TED talks, feature adolescents and adults discussing how 
they have made sense of ADHD and have been successful managing ADHD symptoms. Other 
videos discourage diversion of ADHD medicine. The intervention includes links to videos that 
may help adolescents normalize ADHD and medication taking and discourage diversion. 
 
Intervention components targeting UTBC implementation factors 
4. Organizational interventions: Refill reminders; visual cues, pill taking 
reminders (Targeting adolescent and parent habits and automatic processing, and 
environmental constraints) 
The portal enables parents and/or adolescents to schedule reminders for when to request a 
refill from the pediatrician’s office. Adolescents and parents will also be oriented to strategies 
such as use of visual cues embedded within their daily routine to take medicine (e.g. putting pill 
bottle next to toothbrush, etc.). Adolescents will be able to schedule daily text message 
reminders to take medicine. 
5. Monitoring medication taking (Targeting adolescent, parent, and pediatrician 
salience) 
After receiving their text message reminders to take their medication, adolescents will be 
sent a second text message asking if the dosage was taken with response options of Yes/No. 
This will enable tracking of medication to inform a feedback loop for self-monitoring. Tracking 
results will be displayed graphically to make it easy to assess trends over time relative to 
interventions that have been implemented to improve medication continuity.  
 
Measures to characterize the sample 
1. Demographics: Adolescents, parents, and pediatricians will report on age and 
race/ethnicity. Parents will also report on child insurance status, and their own level of 
education and mental health history. 
2. Technology Use Survey: Adolescents and parents will complete this 30-item phone 
survey from the Pew Research Center’s Internet & American Life Project 
(PewResearchCenter 2011). Items query respondents about use of various types of 
devices (e.g. desktop, tablet, smartphone, etc.), internet connections (e.g. cable modem, 
etc.), and activities (e.g. internet browsing, emailing, texting, downloading apps, etc.). 

 
 
Page 10 of 20 
2/12/2021 
3. Vanderbilt ADHD Parent Rating Scale: (VADPRS) (Wolraich et al. 2003) has subscales 
for Inattention and Hyperactivity/Impulsivity. In addition, a symptom count score can be 
derived for DSM-IV items and includes a subscale to assess parents’ perceptions of 
youth school and social functioning. 
4. ADHD Self-Report Scale: The ASRS is a self-report measure of the 18 DSM ADHD 
symptoms (Kessler et al., 2005). Items reflect symptoms of inattention and hyperactivity-
impulsivity, and in this study all items will be rated by teens on a 4-point scale (0 = never; 
3 = very often) consistent with the parent- and teacher-completed VADRS. 
5. Pittsburgh Side Effects Rating Scale: (Pelham et al. 1993) is a 13-item measure that 
allows adolescents and parents to report whether ADHD medicine side effects were 
none, mild, moderate, or severe. 
6. The Columbia Impairment Rating Scale (CIS) Parent and Child Versions (Appendix Q & 
R): The Columbia Impairment Rating Scale (CIS) assesses impairment in behavioral, 
emotional, interpersonal, and task-related functioning. Behavioral functioning includes 
problems with behavior at home and school; emotional impairment involves feeling 
nervous or sad; interpersonal impairment taps problems in relationships with peers, 
siblings, parents, and other adults; and task-related functioning includes problems with 
schoolwork and involvement in leisure activities. Parents reported how much of a 
problem each of these areas of impairment was for their child on 13 items using a 7-
point scale (“No problem” to “Extreme problem”). The CIS has shown high internal 
consistency, excellent test–retest reliability, and good validity when correlated with a 
clinician’s score on the Children’s Global Assessment Scale. 
7. COVID-19 Adolescent Symptom and Psychological Experience Questionnaire (CASPE): 
The COVID-19 Adolescent Symptom and Psychological Experience (Ladouceur, 2020) 
is an adolescent and parent report of the psychological impacts of the pandemic. Items 
assess negative affect and changes in caregiver employment or income due to COVID-
19.  
8. Remote and In-Person Learning during COVID-19: This is a 25-item measure that allows 
parents to report on adolescent engagement in remote, blended, and in-person learning 
during COVID-19. Two items were used from the Home Adjustment to COVID-19 Scale 
(HACS) (Becker et al., 2020) to assess parent confidence and challenges experienced 
when assisting with remote learning. 
Outcome measures 
9. Fidelity to intended use of intervention components: For each adolescent and parent, we 
will calculate the proportion of intervention components completed relative to the 
components that were recommended by the portal based on adolescent/parent 
responses to the assessment battery. For intervention components that are used once 
(e.g. trial on/off medicine), we will identify a portal data element to characterize 
intervention component completion. For intervention components that are used more 
than once (e.g. refill reminders, pill taking reminders, etc.), we will define “intended use” 
of the feature as use for at least 2 months since research suggests that, on average, it 
takes 2 months to develop a new habit (Lally et al. 2010). Mehealth for ADHD will 
capture and report on these data elements to characterize fidelity to the intended use of 
intervention components for each adolescent and parent. 
10. Pre-intention factors of UTBC influencing medication continuity (Appendix G & H): Our 
measurement strategy for the adolescent and parent pre-intention factors closely follow 
well-developed procedures (Ajzen et al. 1981). We will use standard scales that have 
been used in hundreds of previous studies using the UTBC and closely related basic 
science theories. For example, an item to assess social norms would be ‘‘Most of the 

 
 
Page 11 of 20 
2/12/2021 
people who are important to me think I should take ADHD medicine regularly.’’ 
Responses are on a 7-point scale from strongly agree (+3) to strongly disagree (-3). The 
internal consistency of items within each construct is good (0.7 ≤ alpha ≤ 0.9) (Steele et 
al. 2005; Bentley et al. 2009; Cornelio et al. 2009; Boyko et al. 2011). For this study, we 
will assess pre-intention factors (i.e. expectations, social norms, self-concept/image, 
affect and emotions, and self-efficacy) framed around the behavior of ‘‘taking ADHD 
medicine regularly” following published methods (Francis et al. 2004) and informed by 
our prior qualitative research (Brinkman et al. 2009, 2012). 
11. Behavioral Intentions (Appendix I & J): Teen and parent intention for teen to take ADHD 
medicine regularly will be measured using the standard measure of intention from the 
UTBC (Ajzen and Fishbein, 1981). 
12. Implementation factors of UTBC influencing medication continuity (Appendix K & L): 
These factors will be measured using the Adolescent and Parent Medication Barriers 
Scales (AMBS and PMBS) (Simons et al. 2007; Simons et al. 2010). Adolescents and 
parents respond using a 5-point Likert-like scale from ‘‘strongly disagree’’ to ‘‘strongly 
agree’’ to report perceived barriers to medication taking. Both the adolescent scale (17-
items) and parent scale (16-items) have strong internal consistency for total score and 
the four factor-analytically derived subscales: ‘Disease frustration/adolescent issues’, 
‘Regimen adaptation/cognitive’, ‘Ingestion issues’, and ‘Parent reminder’. For criterion-
related validity, adolescents classified as non-adherent had significantly higher barrier 
scores than those classified as adherent. In prospective validation studies, the 
adolescent-perceived barriers of ‘Disease frustration/adolescent issues’ and parent-
perceived barriers of ‘Regimen adaptation/cognitive issues’ were associated with poorer 
adherence to medication taking (Simons et al. 2010). 
13. Medication Continuity: We will calculate the percentage of days covered with medicine 
based pharmacy dispensing records and verified by parent report of ADHD service use 
using the reliable Services for Children & Adolescents – Parent Interview (Eaton 
Hoagwood et al. 2004). This measures ADHD service use, including office visits and 
medication use. We have successfully obtained pharmacy dispensing records via 
parental permission for 95% (155/164) of subjects across 2 studies (R01 MH074770, 
K23 MH083027) (Brinkman et al. 2013; Brinkman et al. 2016). Pharmacy dispensing 
records provide an objective, unobtrusive, reliable measure that is a well-accepted proxy 
for medication consumption (Steiner et al. 1997) that was significantly correlated with the 
more expensive and invasive Medication Event Monitoring System (MEMSCap™) which 
uses a microprocessor in the medication container cap to record the day and time of 
each vial opening (Farley et al. 2003). 
14. Medication Diversion: Self-report of giving away, trading, or selling ADHD medicine to 
someone for whom it was not prescribed will be collected via a confidential web-based 
survey used in past population-based studies of middle/high school students. (Boyd et 
al. 2007; McCabe et al. 2011a). 
15. Client Satisfaction Questionnaire (CSQ) (Attkisson et al. 1982) is an 8-item 
unidimensional measure of client satisfaction with services. Psychometric properties, 
operating characteristics, and coefficient alpha (.93) are very strong for this measure 
which we will collect from adolescents and parents. 
16. Decision Making Involvement Scale (DMIS) (Miller et al., 2012): is a 30-item scale to 
measure adolescent involvement in a decision. The five subscales are: “Child Seek” 
(child asks for an opinion or information from parent), “Child Express” (child expresses 
an opinion or information to parent), “Parent Seek” (parent expresses advice or opinion 
to child), “Parent Express” (parent expresses advice or opinion to child), and 

 
 
Page 12 of 20 
2/12/2021 
“Joint/Options” (negotiation or brainstorming between parent and child). We will collect 
this measure from adolescents and parents. 
 
DATA ANALYSIS 
 
Hypothesis testing:  
 
Each hypothesis examines part of the mechanism underpinning intervention impact on 
medication continuity. 
Hypothesis #1: Adolescents will use greater than 80% of relevant intervention components. 
For each subject in the intervention group, we will calculate the proportion of recommended 
intervention components that were utilized by the subject during the study. The mean and 95% 
confidence interval (CI) will be computed to give a range estimate of the fidelity measure. To 
evaluate our hypothesis, we will utilize the computed CI to determine if 80% or greater is a 
plausible value, such that if the CI includes a value of 80% or greater we will reject the null 
hypothesis. We will also examine the temporal distribution of use for each of the recommended 
components. 
Hypothesis #2: Use of the intervention components will be related to improvements in the 
targeted UTBC factors. Using a generalized linear model, we will test whether the intervention 
addressed the UTBC factors (i.e., pre-intention factor scales and ABMS/PBMS total and 
subscale scores). Model predictors will include a fixed effect indicator of time point (baseline or 
end of study). A significant effect of time point in the expected direction would indicate UTBC 
factor improvement. 
Hypothesis #3: Medication continuity will be higher in the intervention group compared to 
the control group. We will compare the percentage of days covered with medicine using a two-
sample t-test. 
Hypothesis #4: Pre-post changes in UTBC factors will be related to increases in medication 
continuity. We will calculate the change score for each relevant UTBC factor (end of study 
minus baseline) and the change score for medication continuity (percentage of days covered at 
end of study minus percentage of days covered in the 12 months prior to study). We will model 
the association between change in UTBC factor scores (independent variable) with change in 
medication continuity (dependent variable) using generalized linear mixed model. A significant 
effect of change in UTBC factor scores (beta coefficient) in the expected direction would 
indicate changes in UTBC factor scores were associated with medication continuity 
improvement. 
Exploratory analyses: 
We will conduct descriptive analyses to characterize rates of diversion at baseline and at the 
end of study using a McNemar's test to see if rates differ. We will summarize responses to the 
client satisfaction questionnaire descriptively as this may facilitate future dissemination. 
Power and Sample Size:  
The study would require a sample size of 18 for each group (i.e. a total sample size of 36), to 
achieve a power of 80% and a level of significance of .05 (two sided), to detect a difference in 
means between the intervention and the control groups of 15.7% (i.e. 66.2% vs. 50.5%) on the 
percentage of days covered with medicine assuming a pooled standard deviation of 16.5.  Due 
to the low intra-class correlations observed in previous studies of ADHD medication continuity 
(ICC = 0; Brinkman et al. 2018), the analyses will not account for the nesting of patients within 
physicians.  We will recruit 44 patients to ensure that 36 are retained at the end of the study.  A 
retention rate of 80% (36/44) is conservative in light of the 12-month retention rate of 92% 
achieved by Dr. Hommel in his current trial.  We will use a stratified blocked randomization 
procedure to ensure baseline medication continuity is evenly distributed in both arms. 
 

 
 
Page 13 of 20 
2/12/2021 
Scientific Rigor: 
The RCT is a rigorous design to test efficacy or our intervention. We will explicitly address 
whether the intervention engages the mechanism underlying medication continuity and 
therefore warrants further testing in a future larger trial. Our preliminary data strongly supports 
the importance of the problem, intervention targets identified, and the feasibility of the approach 
in our hands. 
 
Randomizing at the patient level, introduces a risk of contamination because it is possible that 
physicians will have encounters with patients assigned to both intervention and control arms.  
We are taking several steps to mitigate this risk.  First, we have designed the software so that 
intervention components can be selectively “turned on” for patients allocated to the intervention 
group.  Second, most intervention components will be used directly by patients and parents.  
For example, teens might choose to receive daily text message reminders to take their 
medicine.  Parents might choose to receive text message reminders to obtain refills.  Teens 
and/or parents might watch videos about ADHD, medication, stigma, etc.  Again, these features 
won’t be “turned on” for patients in the control group.  Some intervention components, like 
medication experiments promote interactions between patient, parent, and pediatrician.  
Pediatricians will have awareness of these features and receive training on how to interact with 
families to discuss what they learned from conducting an experiment.  That said, it is unlikely 
that families allocated to the control group will conduct such experiments if they don’t have 
access to this intervention component in the mehealth for ADHD software. 
 
FACILITIES 
Cincinnati Children’s Hospital is the performance site for this study. 
POTENTIAL BENEFITS 
Although we cannot guarantee a benefit to any individual participating pediatrician, 
adolescent, or parent, the intervention components we propose to integrate into the ADHD web 
portal are theory- and evidence-based strategies with significant support from the research and 
clinical literature. Thus, families randomized to receive the intervention have the potential to 
benefit from state-of-the-art treatment.  Benefits of the study outweigh any potential risks 
because our interventions are likely to improve care and outcomes for children who receive 
them. 
 
POTENTIAL RISKS, DISCOMFORTS, INCONVENIENCES, AND PRECAUTIONS 
 
There is minimal risk to the participants in this study other than a potential for invasion of 
privacy. Because confidential information about study participants will be available to study staff, 
procedures to safeguard the confidentiality of this information are required. As an NIH funded 
study, a Certificate of Confidentiality protects the privacy of research subjects by prohibiting 
disclosure of identifiable, sensitive research information to anyone not connected to the 
research except when the subject consents. Additionally, several safeguards will be put in 
place.  All data collected on pediatricians, adolescents, and parents will be assigned a unique 
code that will be linked to identifying information.  The master coding sheet that will link the 
information will be kept in the study coordinator’s office under lock and key. In addition to 
assuring confidentiality of the research data, it is also critical that the confidentiality of the 
patient’s clinical information is protected in mehealth for ADHD.  The HIPAA regulations and 
their application to this product will be clearly defined to ensure compliance within their 
guidelines. Mehealth for ADHD was designed with a procedure for encrypting and storing the 

 
 
Page 14 of 20 
2/12/2021 
data in such a manner to only allow pediatricians to view identifiable data.  This design employs 
a key-based encryption structure.  This method does require extra security information to be 
maintained by the parties who are encrypting the data.  For example, parties needing access to 
the data are assigned a "key" that is used to encrypt and decrypt the data in addition to a user 
ID.  Such a key will be maintained by the PI and kept under lock and key.  Implementation of 
additional methodologies to keep the confidential information off the server will be implemented 
including such methodology as ensuring the CCHMC server is secure (i.e., firewalled). 
Data from this study may be submitted to the National Institute of Mental Health (NIMH) 
that allows researchers studying mental health and substance use to collect and share 
deidentified information with each other. If participants consent to have their information shared 
in the data repository, all personal information about research participants such as name, 
address, and phone number will be removed and replaced with a code number. Participants 
may decide at any point that they do not want to share their information to the NIMH data 
repository. If a family consents to have their data shared, the information required to create their 
deidentified code number will be collected during the phone screen by a member of the 
research team.  
 
 
PROTECTION OF VULNERABLE POPULATION 
Because children are being invited to participate in the study, the following procedures 
will be followed to avoid issues related to coercion or undue influence. First, study staff will 
review the assent form with participating children, in language appropriate for their intellectual 
functioning and developmental levels, and ask whether or not the child agrees to participate. 
Similarly, they will be told that they can opt not to participate or answer any questions which 
they do not want to answer at any time. This will be re-iterated whenever necessary.  
 
RISK/BENEFIT ANALYSIS 
The risks to participants are minimal and unlikely, largely stemming from the possibility 
of loss of confidentiality. We have instituted provisions to minimize this risk and will assure 
participants of the voluntariness of their participation and their right to withdraw participation at 
any time. We will also take appropriate steps to safeguard confidentiality. We would suggest 
that this study falls under the “Minimal Risk” category. 
 
ALTERNATIVES 
Participation in the present study is completely voluntary. The alternative to participation 
in the study is to choose not to participate in the study.  
DATA SAFETY & MONITORING 
Physicians, adolescents, and parents who agree to participate and are randomized to 
the intervention group will receive access to a version of the mehealth for ADHD that has been 
enhanced with new intervention components. Given that the risks to participants are minimal, 
there does not appear to be the need for an external monitoring board. Rather, the Drs. 
Brinkman (PI) and Epstein (co-I) will assume primary responsibility for the ongoing monitoring of 
the data and safety of the study, and will provide reports of this with annual renewal application 
to the IRB and annual progress report to the sponsor. Both are experts in ADHD management, 
ADHD research, and have experience conducting practice-based research such as that 
proposed in this application. Dr. Brinkman has medical expertise related to pharmacotherapy of 

 
 
Page 15 of 20 
2/12/2021 
children with ADHD to address study-related medical issues.  All research staff will complete 
education in the protection of human research subjects. 
Drs. Brinkman and Epstein will continuously evaluate the project’s performance, safety, 
and need to stop. Performance will be monitored by examining subject recruitment, comparison 
with targeted recruitment retention, protocol adherence, and quality of data collection 
procedures. This will primarily be accomplished in weekly staff meetings attended by Drs. 
Brinkman and Epstein.  
Drs. Brinkman and Epstein will be available at all times to address any safety issues. 
Any serious adverse events will be determined by Drs. Brinkman and Epstein and reported to 
the IRB within 24 hours, specifying the nature of the event and outcome, if related to the study 
and if anticipated or not. If a serious adverse event as a result of participation in the study 
occurs, recruitment will be immediately discontinued until the serious adverse event has been 
reported to the IRB and the IRB has deemed it appropriate for the study to continue. 
 
COST OF PARTICIPATION 
There will be no costs to the subject for participating in this study. 
PAYMENT FOR PARTICIPATION 
Each parent/adolescent dyad will be compensated $200 for the visit at the beginning of 
the study, and $100 for the visit and surveys at the end of the study for a total of $300 
throughout the intervention. All payments will be made at the end of each visit to the parent. 
ClinCards will be used for all payments.  
 
 
 
 
 

 
 
Page 16 of 20 
2/12/2021 
REFERENCES 
Ajzen, I. (1991). "The theory of planned behavior." Organ. Behav. Hum. Decis. Process. 50: 
179-211. 
Ajzen, I. and M. Fishbein (1981). Understanding attitudes and predicting social behavior. 
Englewood Cliffs, NJ, Prentice Hall. 
Albert, M., P. Rui, et al. (2017). Physician office visits for attention-deficit/hyperactivity disorder 
in children and adolescents aged 4–17 years: United States, 2012–2013. NCHS data 
brief. Hyattsville, MD, National Center for Health Statistics. 269. 
American Academy of Pediatrics. (2011). "Implementing the key action statements: An 
algorithm and explanation for process of care for the evaluation, diagnosis, treatment, 
and monitoring of ADHD in children and adolescents."   Retrieved May 8, 2017, from 
http://pediatrics.aappublications.org/content/suppl/2011/10/11/peds.2011-
2654.DC1/zpe611117822p.pdf. 
Armitage, C. J. and M. Conner (2000). "Social cognition models and health behaviour: A 
structured review." Psychology and Health 15: 173-189. 
Attkisson, C. C. and R. Zwick (1982). "The client satisfaction questionnaire. Psychometric 
properties and correlations with service utilization and psychotherapy outcome." Eval 
Program Plann 5(3): 233-237. 
Barkley, R. A., M. Fischer, et al. (2006). "Young adult outcome of hyperactive children: adaptive 
functioning in major life activities." J Am Acad Child Adolesc Psychiatry 45(2): 192-202. 
Becker SP, Quach ET, Dvorsky MR, et al. (2020). Home adjustment to COVID-19 scale 
(HACS). Cincinnati, OH. 
Bentley, B., T. A. Lennie, et al. (2009). "Demonstration of psychometric soundness of the 
Dietary Sodium Restriction Questionnaire in patients with heart failure." Heart Lung 
38(2): 121-128. 
Boyd, C. J., S. E. McCabe, et al. (2007). "Prescription drug abuse and diversion among 
adolescents in a southeast Michigan school district." Arch Pediatr Adolesc Med 161(3): 
276-281. 
Boyko, J. A., J. N. Lavis, et al. (2011). "Reliability of a tool for measuring theory of planned 
behaviour constructs for use in evaluating research use in policymaking." Health Res 
Policy Syst 9: 29. 
Brinkman, W. B. and J. N. Epstein (2016). Reasons why teens with ADHD stop and/or re-start 
taking medicine. Pediatric Academic Societies’ Annual Meeting. Baltimore, MD. 
Brinkman, W. B., H. Sucharew, et al. (2013). Predictors of medication continuity in children with 
ADHD Pediatric Academic Societies' Annual Meeting. Washington D.C. 
Brinkman W. B., H. Sucharew, et al. (2018). Predictors of Medication Continuity in Children with 
ADHD. Pediatrics. 141(6) 
Brinkman, W. B., H. Sucharew, et al. (2016). Predictors of medication continuity in children with 
ADHD. Pediatric Academic Societies’ Annual Meeting. Baltimore, MD. 
Brinkman, W. B., J. Hartl Majcher, et al. (2013). "Shared decision-making to improve attention-
deficit hyperactivity disorder care." Patient Educ Couns 93(1): 95-101. 
Brinkman, W. B., J. Hartl, et al. (2011). "Physicians' shared decision-making behaviors in 
attention-deficit/hyperactivity disorder care." Arch Pediatr Adolesc Med 165(11): 1013-
1019. 
Brinkman, W. B., R. Baum, et al. (2016). "Relationship Between Attention-Deficit/Hyperactivity 
Disorder Care and Medication Continuity." J Am Acad Child Adolesc Psychiatry 55(4): 
289-294. 
Brinkman, W. B., S. N. Sherman, et al. (2009). "Parental Angst Making and Revisiting Decisions 
About Treatment of ADHD." Pediatrics 124: 580-589. 

 
 
Page 17 of 20 
2/12/2021 
Brinkman, W. B., S. N. Sherman, et al. (2012). "In their own words: adolescent views on ADHD 
and their evolving role managing medication." Acad Pediatr 12(1): 53-61. 
Bussing, R., D. M. Mason, et al. (2010). "Adolescent Outcomes of Childhood Attention-
Deficit/Hyperactivity Disorder in a Diverse Community Sample." J Am Acad Child 
Adolesc Psychiatry 49(6): 595-605. 
Chacko, A., J. H. Newcorn, et al. (2010). "Improving medication adherence in chronic pediatric 
health conditions: a focus on ADHD in youth." Curr Pharm Des 16(22): 2416-2423. 
Chan, E., J. M. Fogler, et al. (2016). "Treatment of Attention-Deficit/Hyperactivity Disorder in 
Adolescents: A Systematic Review." JAMA 315(18): 1997-2008. 
Chronis, A. M., B. B. Lahey, et al. (2003). "Psychopathology and substance abuse in parents of 
young children with attention-deficit/hyperactivity disorder." J Am Acad Child Adolesc 
Psychiatry 42(12): 1424-1432. 
Chronis, A. M., H. A. Jones, et al. (2006). "Evidence-based psychosocial treatments for children 
and adolescents with attention-deficit/hyperactivity disorder." Clin Psychol Rev 26(4): 
486-502. 
Cornelio, M. E., M. C. Gallani, et al. (2009). "Development and reliability of an instrument to 
measure psychosocial determinants of salt consumption among hypertensive patients." 
Rev Lat Am Enfermagem 17(5): 701-707. 
Eaton Hoagwood, K., P. S. Jensen, et al. (2004). "Reliability of the services for children and 
adolescents-parent interview." J Am Acad Child Adolesc Psychiatry 43(11): 1345-1354. 
Efron, D., F. C. Jarman, et al. (1998). "Child and parent perceptions of stimulant medication 
treatment in attention deficit hyperactivity disorder." J Paediatr Child Health 34(3): 288-
292. 
Epstein, J. N., D. Rabiner, et al. (2007). "Improving attention-deficit/hyperactivity disorder 
treatment outcomes through use of a collaborative consultation treatment service by 
community-based pediatricians: a cluster randomized trial." Arch Pediatr Adolesc Med 
161(9): 835-840. 
Epstein, J. N., J. M. Langberg, et al. (2008). "Community-wide Intervention to Improve the 
Attention-Deficit/Hyperactivity Disorder Assessment and Treat-ment Practices of 
Community Physicians." Pediatrics 122: 19-27. 
Epstein, J. N., J. M. Langberg, et al. (2010). "Attention-deficit/hyperactivity disorder outcomes 
for children treated in community-based pediatric settings." Arch Pediatr Adolesc Med 
164(2): 160-165. 
Epstein, J. N., J. M. Langberg, et al. (2011). "Use of an Internet portal to improve community-
based pediatric ADHD care: a cluster randomized trial." Pediatrics 128(5): e1201-1208. 
Epstein, J. N., J. M. Langberg, et al. (2013). "The myADHDportal.com Improvement Program: 
An innovative quality improvement intervention for improving the quality of ADHD care 
among community-based pediatricians." Clin Pract Pediatr Psychol 1(1): 55-67. 
Epstein, J. N., K. J. Kelleher, et al. (2016). "Impact of a web-portal intervention on community 
ADHD care and outcomes." Pediatrics 138(2): 1-9. 
Epstein, J. N., K. J. Kelleher, et al. (2017). "Specific Components of Pediatricians’ Attention-
Deficit/Hyperactivity Disorder (ADHD) Medication-Related Care Predict ADHD Symptom 
Improvement." J Am Acad Child Adolesc Psychiatry Apr 4, 2017. Retrieved Apr 4, 2017, 
2017, from https://doi.org/10.1016/j.jaac.2017.03.014. 
Evans, S. W., W. E. Pelham, et al. (2001). "Dose-response effects of methylphenidate on 
ecologically valid measures of academic performance and classroom behavior in 
adolescents with ADHD." Exp Clin Psychopharmacol 9(2): 163-175. 
Farley, J., S. Hines, et al. (2003). "Assessment of adherence to antiviral therapy in HIV-infected 
children using the Medication Event Monitoring System, pharmacy refill, provider 
assessment, caregiver self-report, and appointment keeping." J Acquir Immune Defic 
Syndr 33(2): 211-218. 

 
 
Page 18 of 20 
2/12/2021 
Fishbein, M., H. C. Triandis, et al. (2001). Factors influencing behavior and behavior change. 
Handbook of Health Psychology. A. Baum, T. A. Revenson and J. E. Singer. Mahwah, 
NJ, Lawrence Erlbaum Associates: 3-16. 
Francis, J., M. P. Eccles, et al. (2004). "Constructing questionnaires based on the theory of 
planned behaviour: A manual for health services researchers."   Retrieved Jun 5 2016, 
2016, from http://openaccess.city.ac.uk/1735/. 
Froehlich, T. E., S. V. Delgado, et al. (2013). "Expanding medication options for pediatric 
ADHD." Curr Psychiatr 12(12): 20-29. 
Gollwitzer, P. M. and P. Sheeran (2006). "Implementation Intentions and Goal Achievement: A 
Meta-analysis of Effects and Processes." Advances in Experimental Social Psychology 
38: 69-119. 
Greenhill, L. L., J. M. Swanson, et al. (2001). "Impairment and deportment responses to 
different methylphenidate doses in children with ADHD: the MTA titration trial." J Am 
Acad Child Adolesc Psychiatry 40(2): 180-187. 
Hagger, M. S., A. Luszczynska, et al. (2016). "Implementation intention and planning 
interventions in Health Psychology: Recommendations from the Synergy Expert Group 
for research and practice." Psychol Health: 1-26. 
Hemming, K., T. P. Haines, et al. (2015). "The stepped wedge cluster randomised trial: 
rationale, design, analysis, and reporting." BMJ 350: h391. 
Hommel, K. A., E. Hente, et al. (2013). "Telehealth behavioral treatment for medication 
nonadherence: a pilot and feasibility study." Eur J Gastroenterol Hepatol 25(4): 469-473. 
Hommel, K. A., M. Herzer, et al. (2011). "Individually tailored treatment of medication 
nonadherence." J Pediatr Gastroenterol Nutr 53(4): 435-439. 
Howard, A. L., N. J. Strickland, et al. (2016). "Progression of impairment in adolescents with 
attention-deficit/hyperactivity disorder through the transition out of high school: 
Contributions of parent involvement and college attendance." J Abnorm Psychol 125(2): 
233-247. 
Jaccard, J., H. A. Litardo, et al. (1999). Social psychological models of behavior. Social 
psychology and cultural context. J. Adamopolis and Y. Kashima. Newbury Park, Sage. 
Kaplan, B. J., R. A. Steiger, et al. (2010). "Successful treatment of pill-swallowing difficulties with 
head posture practice." Paediatr Child Health 15(5): e1-5. 
Knipp, D. K. (2006). "Teens' Perceptions about Attention Deficit/Hyperactivity Disorder and 
Medications." The Journal of School Nursing 22(2): 120-125. 
Ladouceur, C.D. (2020). COVID-19 Adolescent Symptom & Psychological Experience 
Questionnaire. 
Lally, P., C. H. Van Jaarsveld, et al. (2010). "How are habits formed: modelling habit formation 
in the real world." Eur H Soc Psychol 40: 998-1009. 
Leslie, L. K., D. Plemmons, et al. (2007). "Investigating ADHD treatment trajectories: listening to 
families' stories about medication use." J Dev Behav Pediatr 28(3): 179-188. 
McCabe, S. E., B. T. West, et al. (2011a). "Medical misuse of controlled medications among 
adolescents." Arch Pediatr Adolesc Med 165(8): 729-735. 
Meaux, J. B., C. Hester, et al. (2006). "Stimulant medications: a trade-off? The lived experience 
of adolescents with ADHD." J Spec Pediatr Nurs 11(4): 214-226. 
Miller, V. A. and A. F. Jawad (2014). "Relationship of Youth Involvement in Diabetes-Related 
Decisions to Treatment Adherence." J Clin Psychol Med Settings. 
Molina, B. S., S. P. Hinshaw, et al. (2009). "The MTA at 8 years: prospective follow-up of 
children treated for combined-type ADHD in a multisite study." J Am Acad Child Adolesc 
Psychiatry 48(5): 484-500. 
MTA Cooperative Group (1999). "A 14-month randomized clinical trial of treatment strategies for 
attention-deficit/hyperactivity disorder.  Multimodal Treatment Study of Children with 
ADHD." Arch Gen Psychiatry 56(12): 1073-1086. 

 
 
Page 19 of 20 
2/12/2021 
Newcorn, J. H., C. J. Kratochvil, et al. (2008). "Atomoxetine and osmotically released 
methylphenidate for the treatment of attention deficit hyperactivity disorder: acute 
comparison and differential response." Am J Psychiatry 165(6): 721-730. 
Owens, J. S., M. E. Goldfine, et al. (2007). "A Critical Review of Self-perceptions and the 
Positive Illusory Bias in Children with ADHD." Clin Child Fam Psychol Rev 10(4): 335-
351. 
Pai, A. L., J. Rausch, et al. (2012). "System for integrated adherence monitoring: real-time non-
adherence risk assessment in pediatric kidney transplantation." Pediatr Transplant 16(4): 
329-334. 
Pelham, W. E., Jr., C. Carlson, et al. (1993). "Separate and combined effects of 
methylphenidate and behavior modification on boys with attention deficit-hyperactivity 
disorder in the classroom." J Consult Clin Psychol 61(3): 506-515. 
Perou, R., R. H. Bitsko, et al. (2013). "Mental health surveillance among children--United States, 
2005-2011." MMWR Surveill Summ 62 Suppl 2: 1-35. 
Pescosolido, B. A., B. L. Perry, et al. (2007). "Stigmatizing attitudes and beliefs about treatment 
and psychiatric medications for children with mental illness." Psychiatr Serv 58(5): 613-
618. 
PewResearchCenter. (2011). "Apps and Adult SNS Climate."   Retrieved May 31, 2013, from 
http://pewinternet.org/Shared-Content/Data-Sets/2011/August-2011--Apps-and-SNS-
Climate.aspx. 
Pliszka, S. (2007). "Practice parameter for the assessment and treatment of children and 
adolescents with attention-deficit/hyperactivity disorder." J Am Acad Child Adolesc 
Psychiatry 46(7): 894-921. 
Rhodes, R. E. and G. J. de Bruijn (2013). "What predicts intention-behavior discordance? A 
review of the action control framework." Exerc Sport Sci Rev 41(4): 201-207. 
Schmidt, S., C. Petersen, et al. (2003). "Coping with chronic disease from the perspective of 
children and adolescents--a conceptual framework and its implications for participation." 
Child Care Health Dev 29(1): 63-75. 
Simons, L. E. and R. L. Blount (2007). "Identifying barriers to medication adherence in 
adolescent transplant recipients." J Pediatr Psychol 32(7): 831-844. 
Simons, L. E., M. L. McCormick, et al. (2010). "Medication barriers predict adolescent transplant 
recipients' adherence and clinical outcomes at 18-month follow-up." J Pediatr Psychol 
35(9): 1038-1048. 
Singh, I., T. Kendall, et al. (2010). "Young People's Experience of ADHD and Stimulant 
Medication: A Qualitative Study for the NICE Guideline." Child and Adolescent Mental 
Health 15(4): 186-192. 
Smith, B. H., W. E. Pelham, et al. (1998). "Dosage effects of methylphenidate on the social 
behavior of adolescents diagnosed with attention-deficit hyperactivity disorder." Exp Clin 
Psychopharmacol 6(2): 187-204. 
Steele, S. and D. Porche (2005). "Questionnaire development to predict mammography 
intention among women in southeastern Louisiana." J Nurs Meas 13(1): 23-37. 
Steiner, J. F. and A. V. Prochazka (1997). "The assessment of refill compliance using pharmacy 
records: methods, validity, and applications." J Clin Epidemiol 50(1): 105-116. 
Tian, J. H., Z. X. Lu, et al. (2014). "Effectiveness of directly observed treatment of tuberculosis: 
a systematic review of controlled studies." Int J Tuberc Lung Dis 18(9): 1092-1098. 
Visser, S. N., M. L. Danielson, et al. (2014). "Trends in the parent-report of health care provider-
diagnosed and medicated attention-deficit/hyperactivity disorder: United States, 2003-
2011." J Am Acad Child Adolesc Psychiatry 53(1): 34-46 e32. 
Walker, N. E. and T. Doyon (2001). "'Fairness and reasonableness of the child's decision:' a 
proposed legal standard for children's participation in medical decision making." Behav 
Sci Law 19(5-6): 611-636. 

 
 
Page 20 of 20 
2/12/2021 
Wehmeier, P. M., A. Schacht, et al. (2010). "Social and emotional impairment in children and 
adolescents with ADHD and the impact on quality of life." J Adolesc Health 46(3): 209-
217. 
White, F. A. (1996). "Parent-adolescent communication and adolescent decision-making." 
Journal of Family Studies 2: 41-56. 
Wills, T., E. Blechman, et al. (1996). Family support, coping, and competence. Stress, coping, 
and resiliency in children and families. Mahwah, N.J., L. Erlbaum Associates: 107-133. 
Woertman, W., E. de Hoop, et al. (2013). "Stepped wedge designs could reduce the required 
sample size in cluster randomized trials." J Clin Epidemiol 66(7): 752-758. 
Wolraich, M. L., W. Lambert, et al. (2003). "Psychometric properties of the Vanderbilt ADHD 
diagnostic parent rating scale in a referred population." J Pediatr Psychol 28(8): 559-
567. 
Wolraich, M., L. Brown, et al. (2011). "ADHD: clinical practice guideline for the diagnosis, 
evaluation, and treatment of attention-deficit/hyperactivity disorder in children and 
adolescents." Pediatrics 128(5): 1007-1022.