Content uploaded by Alexandra L Quittner
Author content
All content in this area was uploaded by Alexandra L Quittner
Content may be subject to copyright.
Journal of Pediatric Psychology 31(8) pp. 846–858, 2006
doi:10.1093/jpepsy/jsj096
Advance Access publication January 9, 2006
Journal of Pediatric Psychology vol. 31 no. 8 © The Author 2006. Published by Oxford University Press on behalf of the Society of Pediatric Psychology.
All rights reserved. For permissions, please e-mail: journals.permissions@oxfordjournals.org
Barriers to Treatment Adherence for Children with Cystic Fibrosis
and Asthma: What Gets in the Way?
Avani C. Modi,1 PHD, and Alexandra L. Quittner,2 PHD
1Cincinnati Children’ s Hospital Medical Center, and 2University of Miami
Objectives The purpose of this study was to systematically identify barriers to treatment
adherence for children with cystic fibrosis (CF) and asthma, as well as to examine the
relationship between the number of barriers and adherence. Methods Participants included
73 children with CF or asthma and their parents. The mean age of the sample was 9.9 years, and
58% were males. Results Results indicated that barriers were quite similar by illness and
informant (e.g., parent and child) for the same treatments, but unique barriers were identified
for disease-specific treatments. Frequently mentioned barriers across diseases included forget-
ting, oppositional behaviors, and difficulties with time management. Trends were identified
between adherence and barriers, suggesting that a greater number of barriers were related to
poorer adherence. Conclusion Overall, this study provided evidence that patients and their
parents experience specific barriers within the context of their own illness and highlights the
need for disease-specific measures and interventions.
Key words barriers; knowledge; patient–provider communication; pulmonary; treatment.
It is assumed that patients will follow the treatment
recommendations prescribed by their physicians; how-
ever, growing evidence indicates that average rates of
adherence are 50% or less in young, chronically ill pop-
ulations (Rapoff, 1999). Poor adherence can have seri-
ous consequences, including increased morbidity and
mortality, reduced quality of life, and greater health care
costs. More than 10 years ago, the costs associated with
nonadherence were estimated to be over $100 billion per
year (Berg, Dischler, Wagner, Raia, & Palmer-Shevlin,
1993) and they continue to increase.
Adherence is particularly poor in pediatric pulmo-
nary diseases, such as cystic fibrosis (CF) and asthma,
because of the intensity and complexity of the treatment
regimen. Rates of adherence for children with CF are
estimated to be 40–47% for chest physical therapy, a
form of airway clearance (Passero, Remor, & Solomon,
1981; Quittner et al, 2000), whereas adherence to
dietary recommendations is even lower, ranging from 16
to 20% (Anthony, Paxon, Bines, & Phelan, 1999; Stark,
Jelalian, & Miller, 1995). Estimates of adherence for
children with asthma vary widely for inhaled medica-
tions, ranging from 46 to 58% (Bender et al, 2000;
Walders, Kopel, Koinis-Mitchell, & McQuaid, 2005).
For both of these populations, poor adherence may lead
to increased emergency room visits, more frequent hos-
pitalizations, declines in pulmonary functioning, and
shorter life span (Bauman et al, 2002; Warwick &
Hansen, 1991; Weiss, Gergen, & Hodgson, 1992). To
effectively address this problem, it is crucial to identify
the barriers associated with poor adherence.
Patients with chronic conditions encounter numer-
ous challenges in adhering to their treatment regimens
which include forgetting, side effects, and lack of
resources (Mansour, Lanphear, & DeWitt, 2000;
Naspitz & Tinkelman, 2001). However, these studies
present mainly anecdotal evidence provided by parents,
with few systematic efforts to identify barriers for children.
One exception to date is a study by Logan, Zelikovsky,
Labay, & Spergel (2003) that developed the illness
All correspondence concerning this article should be addressed to Avani C. Modi, PhD, Division of Behavioral
Medicine and Clinical Psychology, Cincinnati Children’s Hospital Medical Center, 3333 Burnet Ave. MLC 3015,
Cincinnati, Ohio 45229. E-mail: avani.modi@cchmc.org.
by guest on June 2, 2013http://jpepsy.oxfordjournals.org/Downloaded from
Barriers to Adherence in CF and Asthma 847
management survey (IMS), which examined adolescents’
perceptions of barriers to adherence for asthma. The
authors found that self-reported adherence was nega-
tively correlated with scores on the IMS, suggesting that
a greater number of barriers were associated with worse
adherence. This was an important first step in systemati-
cally measuring barriers to adherence for adolescents
with asthma; however, the perspective of younger chil-
dren and parents also needs to be assessed. This study
identified specific barriers for school-age children with
CF or asthma and their parents.
Potential Barriers to Adherence
Several factors influence patterns of adherence for chil-
dren with CF and asthma, including knowledge of the
disease and regimen, patient–provider communication,
and regimen characteristics. For children and their par-
ents to effectively manage treatments associated with a
chronic illness, they must understand the disease and its
treatment regimen (LaGreca & Bearman, 2003). Evi-
dence indicates that patients who are less knowledgeable
about their disease may be less adherent to their medical
regimens (Gudas, Koocher, & Wypig, 1991). For exam-
ple, Henley & Hill (1990) found that 14% of parents of
children with CF believed that chest physical therapy is
necessary only when the child is feeling sick. Similarly,
20% of parents of African-American children with
asthma felt they lacked knowledge about the disease,
triggers, and use of different medications (Mansour et al.,
2000). However, other studies have shown little rela-
tionship between knowledge and adherence in asthma
(Farber et al, 2003; McQuaid, Kopel, Klein, & Fritz,
2003). This may partly be because of the use of different
measures of knowledge and adherence that have not yet
been validated. The current study assessed relations
between adherence and knowledge for children with CF
or asthma and their parents.
Gaps in knowledge and misconceptions about
medication usage may be the result, in part, of inade-
quate or poor communication between the patient and
healthcare provider. Patient–provider communication
involves providing information in a culturally sensitive
manner, developing a partnership regarding the treat-
ment plan, responding to patient concerns, and making
sure patients understand treatment recommendations
(Brown, 1999). However, a majority of evidence sug-
gests that such optimal communication is not occurring,
and furthermore parents often do not recall what the
physician has told them (Heffer et al, 1997). For exam-
ple, Ievers et al (1999) reported that 12–33% of mothers
of school-age children with CF had incorrect informa-
tion about the types of treatment being prescribed. In
addition, physicians rarely provide a written treatment
plan to families, which may lead to misunderstanding
about the regimen. This is one of the first studies to
examine rates of adherence in a pediatric sample using
physician-reported prescriptions.
Research also suggests that complex regimens, nega-
tive side effects, and inconsistent efficacy can contribute
to lower rates of adherence in these populations (Rapoff,
1999). Treatment characteristics such as the number of
medications, the frequency of dosing, and routes of admin-
istration have all been shown to affect levels of adherence
(Becker, Drachman, & Kirscht, 1972; Kelloway, Wyatt, &
Adlis, 1994). For example, in the asthma population,
71% of mothers reported changing medication schedules
for reasons of convenience, whereas 60% reported occa-
sionally forgetting to dispense medications (Donnelly,
Donnelly, & Thong, 1987). This study is the first to sys-
tematically examine parent- and child-reported barriers
to adherence in two pediatric populations.
The central purpose of this study was to identify the
most frequent barriers to adherence for children with
CF or asthma and their parents. Similar types of barriers
were expected to be reported by both disease groups for
treatments that were similar; however, their frequency
was expected to differ. Parents of children with CF were
expected to identify a greater number of barriers than
parents of children with asthma, because of the com-
plexity of the treatment regimen. It was also hypothe-
sized that the number of barriers would be significantly
related to rates of adherence, with a greater number of
barriers associated with lower adherence. Finally, it was
hypothesized that disease and treatment knowledge
would be strongly associated with adherence.
Method
Participants
Study participants included 73 children between the
ages of 6 and 13 with a primary diagnosis of CF (n = 37)
or asthma (n = 36) and their parents. Participants were
recruited from two pediatric pulmonary clinics in Florida.
Eligibility criteria included: (a) age between 6 and 13
years, (b) a proven diagnosis of CF or asthma for more
than 1 year (e.g., sweat test, genetic test, and NHLBI
guidelines), (c) no major comorbid medical diagnoses
(e.g., cerebral palsy and cancer), and (d) use of routine
or daily medications.
Ninety-four potential participants were mailed
information letters and brochures explaining the study.
by guest on June 2, 2013http://jpepsy.oxfordjournals.org/Downloaded from
848 Modi and Quittner
Participants were then contacted by phone or during
routine clinic visits to review the informed consent.
Twenty-one eligible participants were not included for
the following reasons: (a) 16 parents declined to participate
(quoting reasons as “too busy” and “moving”), (b) one
participant was excluded from a set of twins, (c) one
participant was no longer prescribed medications, (d) two
participants did not return to the clinic for follow-up
visits after they were recruited, and (e) one participant
did not complete the initial assessment. Overall, data for
barriers to adherence were collected for 37 children with
CF and 36 children with asthma. In terms of adherence
data, three children with CF and six children with
asthma dropped out of the study because of busy sched-
ules or family illness before completion of the 3-month
assessment; however, self-reported adherence and barri-
ers data were available for all of these participants.
The mean age of participants with CF and asthma
was 10.1 and 9.7 years, respectively. Forty-nine percent
of the CF sample and 36% of the asthma sample were girls.
Eighty-nine percent of the CF sample were Caucasian,
3% African-American, 3% Hispanic, and 3% biracial.
Forty-seven percent of the asthma sample were Caucasian,
42% African-American, and 11% Hispanic. For the CF
sample, mean forced expiratory volume in 1 s predicated
(FEV1 % predicted) and forced expiratory flow25–75
(FEF25-75) were 79.6 and 91.4%, respectively. Sixty-six
percent of the CF sample were mildly ill, 28% were
moderately ill, and 6% were severely ill. In the asthma
sample, mean FEV1 % predicted and FEF25-75 were 72.2
and 74.0%, respectively. Thus, 70% were mildly ill, 26%
were moderately ill, and 3% were severely ill. Seventy-
four percent of primary caregivers of children with CF
were married, and median family income was $30,000–
$49,999. Fifty-three percent of primary caregivers of
children with asthma were married, and median family
income was $20,000–$29,999. Significant differences
were found between the groups in terms of pulmonary
functioning, race, and marital status of primary caregiv-
ers. As expected, children with CF had lower pulmonary
functioning [t(67) = –2.5, p < .05], and a greater pro-
portion of children in the asthma group were from
minorities [χ2(1, n = 73) = 14.9, p < .0001]. Parents of
children with CF were also more likely to be married
than parents of children with asthma [χ2(1, n = 73) = 3.9,
p < .05].
Procedure
Patients and their parents were recruited during a rou-
tine clinic visit and were asked to complete the follow-
ing questionnaires: (a) background information form,
(b) self-report of adherence, (c) barriers to adherence,
and (d) knowledge questionnaires. They were also
scheduled to complete a daily phone diary (DPD) over
2 days before their next clinic visit and utilize electronic
monitors for particular medications over a 3-month
period (e.g., MEMS cap for enzymes and MDILog for
inhaled corticosteroids). The institutional review board
approved the protocol and consent forms, which
included permission to contact pharmacies. To decrease
social desirability responding, participants were told
that information from the interviews would not be
shared with the health care team. Pulmonary function
tests (PFTs) were also conducted to assess the health
status. Participants were given a $5 gift certificate for
participating in the study, $10 for completing daily
phone diaries, and $10 gift certificates for returning
electronic monitors.
Measures
Background Information Form
Parents completed a form assessing the child’s date of
birth, gender, parents’ age, socioeconomic status, occu-
pation, and composition of the family.
Prescribed Treatment Plan
The prescribed treatment plan (PTP) (Modi, 2002;
Quittner, Espelage, Ievers-Landis, & Drotar, 2000) is a
brief instrument completed by physicians in less than
2 min, which documents the current treatment regimen.
Each component of the child’s treatment (like medication,
type, dosage, timing of dosage, and method of administra-
tion) is listed, and the current prescription is circled by the
physician. A PTP was completed by a nurse, based on a
chart review, for the initial clinic visit and later completed
by the physician to document treatment changes.
Disease Management Interview
The disease management interview-CF (DMI-CF) is a
51-item self-report measure of adherence behaviors for
patients with CF that was modified from the treatment
adherence questionnaire-CF (TAQ-CF) (Quittner et al.,
2000). Before administering the interview, the chal-
lenges of managing the child’s regimen were normalized
for the family to promote honest responding. For each
component of the regimen, children (over 10 years of
age) and parents were asked separately about the fre-
quency and duration of each treatment performed (e.g.,
chest physical therapy for 30 min, twice a day). Children
were given pictures of all possible medications to help
them accurately report their treatment regimen. Ievers et al
(1999) found satisfactory levels of agreement between
children and mothers on an earlier version of this
by guest on June 2, 2013http://jpepsy.oxfordjournals.org/Downloaded from
Barriers to Adherence in CF and Asthma 849
instrument (r = .69 for aerosol frequency and r = .99 for
chest physical therapy).
The DMI-Asthma was modified from the DMI-CF
for parents and children with asthma. The DMI-Asthma
is a 28-item questionnaire which asks when, how often,
and how much of each medication they took [e.g.,
metered-dose inhalers (MDI), two puffs twice a day].
The same administration procedures were followed. In
conjunction with the PTP, the DMI was utilized to cal-
culate rates of self-reported adherence for each compo-
nent of the child’s treatment regimen.
Prescription Refill Data
Consent to obtain prescription refill data from all of the
patients’ pharmacies was obtained at the initial clinic
visit. Each pharmacy was asked for comprehensive refill
histories over the 3-month period of the study, and these
data were combined for each patient. However, because
of the implementation of new HIPPA guidelines, phar-
macy refill history could not be obtained for 49% of
patients with CF and 53% of patients with asthma.
Daily Phone Diary
The DPD uses a cued recall procedure to track parents
through their activities over the past 24-hr (Quittner &
Espelage, 1999; Quittner & Opipari, 1994). It is an
unobtrusive measure of adherence that is likely to
reduce social desirability responding because the full
range of daily activities are elicited from parents, not just
treatment behaviors. The DPD has yielded reliable
stability coefficients over a 3-week period (rs = .61–.71,
p < .01) and high levels of interrater reliability (>90%) in
a CF population (Quittner, Opipari, Regoli, Jacobsen, &
Eigen, 1992). Furthermore, strong convergent validity
(77–80%; Quittner et al, 1992) was found for daily rou-
tines between the DPD and self-observation report tech-
nique (Stephens, Norris-Baker, & Willems, 1983).
Moderate correlations have been found between the
DPD and objective, electronic monitors, suggesting
good convergence between these methods (Modi &
Quittner, in press). The DPD procedure is computerized
and yields both the number of treatments performed
each day and their duration. A set of two DPDs (one
weekday and one weekend day) were conducted with
the primary caretaker by phone, and data were averaged
to obtain rates of adherence for each treatment compo-
nent. The 24-hr recall procedure has been adapted for
use with parents of children with asthma.
Electronic Monitoring
Electronic monitoring provides an “objective” method
of assessing adherence. However, owing to the high
costs of these devices, only the primary medications for
CF and asthma were monitored. These included enzyme
medications and MDIs (e.g., Flovent) for patients with
CF and MDIs/diskus for patients with asthma. For
patients with multiple inhalers in multiple locations
(e.g., grandmother’s house), separate MDILogs were
given for each inhaler.
The Electronic Drug Exposure Monitor (eDEM®)
made by AARDEX Corporation was used to monitor
adherence to enzyme medications. It stores the dates
and times for over 2000 doses, with data transferred to a
Windows-based computer. The MDILog II®, developed
by Westmed, records the date and time inhaled medica-
tions (e.g., bronchodilators and corticosteroids) were
taken, whether the canister was shaken appropriately,
and whether the medication was properly inhaled. Par-
ents were instructed to bring current medications to
their initial clinic visit. The MDILog was initialized and
attached to their current MDI, and they were given
instructions for attaching the MDILog for new prescrip-
tions. These data were downloaded to a central docking
station via computer. For MDILog data, only inhaled
doses (not actuations without inhalation) were included
in the calculation of adherence. The Advair discus is
equipped with a counter that identifies the dosages left
in the discus. This number was recorded at the initial
visit and approximately 3 months later. These data were
triangulated with pharmacy refill history to calculate
rates of adherence.
Forty-six children were prescribed inhaled corticos-
teroids during the initial visit (29 Advair Diskus© and
17 traditional MDIs). Of those with MDIs, one patient
utilized samples and thus did not use electronic moni-
tors, and three patients were prescribed Pulmicort, for
which no monitor exists. Of the remaining 13 patients,
five monitors were faulty (because of improper down-
loading and no data), two did not fit the particular med-
ication, three had missing data because of lost monitors,
and three had complete adherence data. Twenty-nine
patients were prescribed the Advair Diskus©, and
counter data were available for nine patients. Missing
counter data was because of patients utilizing multiple
diskuses, lack of initial baseline counter readings, with-
drawal from the study, or lost device.
Barriers to Adherence Interview
In conjunction with the disease-specific DMI, children
and parents were interviewed separately about barriers
to adherence. For each component of the treatment regi-
men, open-ended questions about the reasons why tak-
ing medications and doing treatments is difficult were
asked. Participants were then given a list of 25 common
by guest on June 2, 2013http://jpepsy.oxfordjournals.org/Downloaded from
850 Modi and Quittner
barriers [e.g., forgetting, oppositional behaviors, embar-
rassing, inconvenient, patient started feeling better and
did not feel they needed medication, eating/feeding
issues (feels full, rushes to eat)] and asked to choose any
additional barriers that were relevant. Next, participants
rated the frequency with which these barriers occurred
on a 7-point Likert scale, ranging from (1) very rarely to
(7) daily. The barriers to adherence interview for CF and
asthma was also administered to children over 10 years
of age.
Cystic Fibrosis Knowledge Questionnaire
The cystic fibrosis knowledge questionnaire (CFKQ)
was specifically developed for studies conducted by
Quittner et al (2000). This questionnaire assesses three
broad domains of knowledge: respiratory/treatment,
digestion, and nutrition. There are two versions of the
CFKQ, one for school-age children (21 items) and one
for parents (36 items). Because the responses were
dichotomous, Kuder–Richardson 20 coefficients were
calculated to assess reliability, with coefficients of .67
for an earlier version and .92 for a revised version
reported for the parent versions and .77 for the child
version.
Asthma Questionnaire
The asthma questionnaire (AQ) is a knowledge measure
developed for children with asthma and their parents
(Adams et al, 2001). Two versions were developed: the
AQ-P for parents of children between 2 and 17 years and
AQ-Y for children between 9 and 13 years of age. Alpha
coefficients for the AQ-P and AQ-Y were .81 and .80,
respectively, indicating good reliability (Adams et al,
2001). In this study, an adapted version of the AQ-Y was
utilized so that younger children, aged 6 and older,
could be tested. Questions were reworded with fewer
answer options. Reliability of this younger version was
.64 in this study.
Health Status
PFTs are the gold standard for measuring respiratory
functioning and lung damage for patients with CF and
asthma. For CF, FEV1 % predicted is used as the primary
indicator of health status, using the Knudson equations
for age, sex, and weight (Knudson, Slatin, Lebowitz, &
Burrows, 1976). Illness severity ratings are based on
established cut-offs for mild (>70%), moderate (>40%
and <69%), and severe (<39%) disease (Taussig, 1995)
for CF. For asthma, severity is classified as mild inter-
mittent, mild persistent, moderate persistent, and severe
persistent. These classifications are not only based on
lung function as measured by FEV1 % predicted but also
on daytime and nighttime symptoms, as well as peak
expiratory flow (PEF) variability. However, to compare
children with asthma and CF, FEV1 % predicted was uti-
lized to calculate severity based on the following classifi-
cation guidelines: mild intermittent or mild persistent
(>80%), moderate (>60% and <80%), and severe (<60%)
disease (National Institutes of Health: National Heart,
Lung, and Blood Institute, 1997). PFTs were conducted
at the clinic visit in the pulmonary function laboratory by
a trained technician.
Statistical Analyses
Calculating Adherence Scores
For each adherence behavior, the number of treatments
performed each day divided by the number of treat-
ments prescribed was multiplied by 100 to determine
percent adherence (e.g., % of prescribed inhaled medica-
tions taken each day). This procedure was used to calcu-
late rates of adherence from the self-report, diary, and
electronic measures. Rates of adherence were capped at
100% to decrease inflation for all medications, a method
which has been used successfully in studies of children
with asthma (Bender et al, 2000). It is important to note
that rates of adherence could not be calculated for medi-
cations that were prescribed PRN (i.e., as needed).
A different procedure was utilized to calculate rates
of adherence for the Advair discus. Because the Advair
discus counter did not account for the number of
devices utilized by families over the 3-month period, the
technique described above was used in conjunction with
pharmacy refill history data to determine how much
medication was available. For example, if the counter
indicated that 40 doses were available on the discus at
the initial visit and 30 doses were available at the end of
the study period, 90 days later, pharmacy refill data were
checked to determine whether the family had acquired
more Advair discuses during the 90-day time period.
Prescription refill data were calculated for each
medication. Rates of adherence for a single medication
taken continuously were calculated by dividing the sup-
ply obtained during a 3-month interval by the total
number of days in that interval (90 days). For example,
if 30 days of medication were obtained over a period of
90 days, the prescription refill rate was 33%. All medica-
tions obtained through pharmacies were recorded and
included in the analyses.
Descriptive analyses, including the types of barriers
endorsed and a rank ordering of the top three barriers,
were examined. First, McNemar tests were conducted to
examine differences in the endorsement of barriers
across treatment components within each disease group.
by guest on June 2, 2013http://jpepsy.oxfordjournals.org/Downloaded from
Barriers to Adherence in CF and Asthma 851
Next, Fisher’s exact tests were conducted to examine
differences between the two disease groups regarding
the presence of barriers (i.e., % endorsement of a
barrier) for similar treatment components (e.g., MDIs,
allergy medications, nebulizer treatment, and oral anti-
biotics). Student’s t tests were conducted to examine
group differences between the numbers of barriers iden-
tified. Pearson correlation coefficients were calculated
between the different measures of adherence and num-
ber of barriers identified. Finally, Pearson correlation
coefficients were calculated between disease-related
knowledge and adherence. No significant relationships
were found between disease severity and adherence and
barriers (p > .05); thus, disease severity was not con-
trolled in the analyses. Significance was identified as
p< .05, and corrections for Type I error rates were not
made owing to the exploratory nature of the study.
Results
Endorsement and Types of Barriers
Parents of children with CF and asthma were divided
into two groups—those who endorsed one or more
barriers and those who did not report any barriers.
McNemar tests were conducted to examine differences
in the endorsement of barriers by parents within each
disease group. (Owing to small sample size, child com-
parisons were not conducted.) Only treatments that
were prescribed for most children were utilized in these
analyses (CF: enzymes, airway clearance, nutrition, and
nebulized medications; asthma: inhaled corticosteroids,
rescue inhalers, nebulized medications, and allergy med-
ications). Seventy-seven percent of parents of children
with CF endorsed barriers for enzymes, 92% for airway
clearance, 69% for nutrition, and 73% for nebulized
medications (e.g., dornase alpha, inhaled tobramycin,
and albuterol). Fifty percent of children with CF
endorsed barriers for enzymes, 75% for airway clear-
ance, 44% for nutrition, and 75% for nebulized medica-
tions. Seventy-one percent of parents of children with
asthma endorsed barriers for inhaled corticosteroids,
52% for bronchodilators, 46% for nebulized medications,
and 41% for allergy medications. Sixty-seven percent of
children with asthma endorsed barriers for inhaled corti-
costeroids, 50% for bronchodilators, 29% for nebulized
medications, and 40% for allergy medications (e.g., nasal
sprays, antihistamines, and decongestants).
For parents of children with CF, no significant dif-
ferences were found in the endorsement of barriers for
different treatment components. In contrast, parents of
children with asthma endorsed a higher number of
barriers for inhaled corticosteroids compared to rescue
inhalers (p < .05) and allergy medications (p > .01).
Next, a comparison of four treatments—inhaled
corticosteroids, allergy medications, nebulizers to open
airways, and rescue inhalers—common across the two
disease conditions was made. First, Fisher’s exact tests
evaluated differences in the frequency of identified bar-
riers per treatment component reported by parents for
each group. Results indicated a significant difference
between the frequencies of identified barriers for inhaled
corticosteroids (p < .01). Parents of children with
asthma were more likely to identify barriers to this treat-
ment compared to parents of children with CF. Second,
Student’s t tests were conducted to examine differences
in the number of barriers identified, with a significant
difference being found only for inhaled corticosteroids
[t(42) = –2.9; p < .01]. Parents of children with asthma
reported three times as many barriers to inhaled corti-
costeroids as parents of children with CF. Additional
analyses were conducted to examine whether marital
status contributed to disease group differences in the
number of barriers. The interaction term (marital status ×
disease group status) was not significant for the four
treatments examined, suggesting that single marital sta-
tus does not account for the higher number of barriers
that parents of children with asthma reported.
It was hypothesized that similar types of barriers
would be identified across the two chronic conditions
for similar treatments (e.g., inhaled corticosteroids, res-
cue inhalers, albuterol nebulizers, and oral antibiotics).
The top three barriers across these two pulmonary con-
ditions were rank ordered by frequency of parent and
child endorsement. Although the rank ordering varied
slightly, this hypothesis received considerable support,
with similar barriers endorsed by parents and children
in both groups (Table I). For example, “forgetting” was
identified as the primary barrier by both groups for
inhaled corticosteroid use. Children and parents also
endorsed similar barriers, although the sample sizes
were small. Finally, parents and children tended to agree
with each other about these barriers. For example, par-
ents and children with asthma reported oppositional
behaviors as one of the most common types of barriers
for inhaled corticosteroids.
In terms of disease-specific barriers, parents of chil-
dren with CF identified oppositional behaviors, forget-
ting, and difficulties with time management as the most
significant barriers to treatments such as airway clear-
ance and enzymes (Table II). Although children
endorsed similar barriers, they also identified several
that were unique, such as difficulty swallowing pills and
by guest on June 2, 2013http://jpepsy.oxfordjournals.org/Downloaded from
852 Modi and Quittner
disliking the taste of inhaled tobramycin. For the asthma
group, barriers were examined for allergy medications
and leukotriene modifiers (Table II). In general, parents
in the asthma group identified barriers that were similar
to their children, with “forgetting” endorsed most fre-
quently by both across treatments.
Barriers and Adherence
The relationship between number of barriers and rates
of adherence was also examined. Although no statisti-
cally significant relationships were found, several
trends were identified, defined as two separate meth-
ods of measurement supporting the hypothesized rela-
tionship. Moderate correlations suggested that a
greater number of barriers for inhaled corticosteroids
were associated with lower adherence across several
measures (e.g., child self-report, pharmacy refill his-
tory, and electronic monitoring) (Table III). Similarly,
moderate negative correlations were observed between
barriers for pulmozyme and adherence (e.g., parent
self-report, pharmacy refill history, and DPDs). In
contrast, child self-reported adherence was positively
correlated with the number of barriers for airway clear-
ance and enzymes.
Disease-Related Knowledge and Adherence
The relationship between disease-related knowledge and
adherence was examined for both samples utilizing all
methods of adherence measurement. Substantial gaps in
knowledge were identified for children with CF and
their parents. Children with CF answered 55% of items
correctly, evidencing substantial gaps in knowledge.
They understood that CF primarily affects the lungs
(82%); however, they lacked knowledge about nutrition,
including the importance of adding snacks and boosting
calories, and approximately one-quarter (26%) were
unaware that enzymes should be taken before a meal or
snack. Parents of children with CF correctly answered
68% of items. They had a good understanding of the
symptoms of CF (like coughing and stomach cramps);
however, their knowledge of nutrition was incomplete.
For example, a large percentage (92%) were unaware
that fat has more calories than carbohydrates and pro-
teins, and 19% of parents were unaware that children
Table I. Most Frequently Endorsed Barriers by Parents and Children for Similar Treatment Components
Note. Nebulizer refers to nebulized bronchodilators. All single responses indicate endorsement by only one individual for a barrier.
Cystic fibrosis Asthma
Parent Child Parent Child
Inhaled corticosteroids
n = 13 n = 7 n = 31 n = 9
Forgetting (15%) All single responses Forgetting (55%) Forgetting (68%)
Dislikes taste (15%) Taste (19%) Time management (22%)
Oppositional
behaviors (19%)
Oppositional
behaviors (22%)
Nebulizer
n = 18 n = 5 n = 24 n = 7
Oppositional
behaviors (50%)
Oppositional
behaviors (40%)
Time management (25%)
Oppositional
behaviors (21%)
All single responses
Time management (17%)
Started feeling better (13%)
Oral antibiotics
n = 19 n = 8 n = 17 n = 4
Forgetting (26%) Forgetting (25%) Forgetting (24%) All single responses
Taste (16%) Swallowing (25%) Taste (24%)
Oppositional
behaviors (11%)
Time management (25%) Side effects (12%)
Short term MDI
n = 19 n = 11 n = 29 n = 12
Forgetting (21%) Forgetting (27%) Forgetting (25%) Forgetting (42%)
Side effects (21%) Taste (18%) Time management (21%) Taste (17%)
Oppositional
behaviors (16%)
Side effects (13%)
by guest on June 2, 2013http://jpepsy.oxfordjournals.org/Downloaded from
Barriers to Adherence in CF and Asthma 853
with CF need 125–150% of the recommended daily
allowance of calories.
Children with asthma answered 50% of the items cor-
rectly, suggesting significant gaps in their understanding
of asthma and its treatments. They appeared to under-
stand why they should avoid cigarette smoke, dust, and
strong perfumes (94%); however, approximately half
did not know that asthma results in airway tightening or
Table II. Most Frequently Endorsed Barriers by Parents and Children for Disease-Specific Treatments
Parent Child
Cystic fibrosis
Airway clearance
n = 37 n = 16
Oppositional behaviors (60%) Time management (50%)
Time management (57%) Oppositional behaviors (38%)
Embarrassment (22%) Forgetting (25%)
Enzymes
n = 35 n = 16
Forgetting (46%) Forgetting (44%)
Embarrassment (17%) Swallowing (13%)
Oppositional behaviors (11%)
Nutrition
n = 35 n = 18
Eating/feeding issues (22%) Eating/feeding issues (22%)
Oppositional behaviors (23%) Forgetting (11%)
Taste (17%)
Pulmozyme
n = 18 n = 9
Oppositional behaviors (39%) Forgetting (22%)
Time management (22%) Oppositional behaviors (22%)
Forgetting (11%)
Inhaled tobramycin
n = 16 n = 9
Time management (31%) Taste (44%)
Oppositional behaviors (25%) Time management (33%)
Taste (19%) Forgetting (22%)
Asthma
Allergy
n = 22 n = 10
Forgetting (18%) Forgetting (18%)
Swallowing (14%)
Leukotriene modifiers
n = 14 n = 4
Forgetting (29%) All single responses
Time management (14%)
Table III. Correlations Between Adherence and Number of Barriers
Note. Owing to the small sample size for allergy medications and inhaled tobramycin, they were not included in analyses. Although no statistically significant relationships
were found between adherence and barriers, several trends were identified, defined as two separate methods of measurement supporting a particular relationship.
Number of barriers reported by parents
Inhaled corticosteroids Airway clearance Enzymes Pulmozyme
Adherence measures
Parent self-report 0.28 (n = 41) –0.09 (n = 36) 0.05 (n = 35) –0.41 (n = 15)
Child self-report –0.46 (n = 18) 0.32 (n = 18) 0.32 (n = 17) –0.17 (n = 8)
Pharmacy refill history –0.39 (n = 18) — 0.09 (n=16) –0.65 (n=9)
Diary data 0.13 (n = 34) 0.27 (n = 31) –0.02 (n = 30) –0.42 (n = 13)
Electronic monitoring –0.45 (n = 12) — 0.10 (n = 26) —
by guest on June 2, 2013http://jpepsy.oxfordjournals.org/Downloaded from
854 Modi and Quittner
that a bronchodilator should be carried at all times. Parents
answered an average of 80.6% of the items correctly.
Parents had a thorough understanding of asthma trig-
gers; however, only 72% understood the need to carry a
bronchodilator at all times. Interestingly, no significant
relationships were found between child or parent
knowledge and rates of adherence (CF: rs = –.34 to .43;
asthma: rs = –.34 to .21). However, the sample sizes for
these analyses were relatively small (max n = 30).
Patient–Provider Miscommunication
Discrepancies between the physician’s PTP and parents’
understanding of the prescription were also found
across all medications for both patient groups. Note that
these data do not address confusion regarding frequency
or dosage of medications, but simply awareness that a
particular treatment was prescribed. Physicians and par-
ents of children with CF disagreed on 17% of the medi-
cations prescribed, with even less agreement, only 31%,
reported by parents of children with asthma. These data
indicated significant problems with patient–provider
communication.
Regimen Complexity
Pearson correlation coefficients were calculated between
the four adherence measures and the number of treat-
ments prescribed. Results indicated a trend between the
DPD and the number of prescribed treatments (r = –0.24,
p < .06), with fewer treatments associated with better
rates of adherence for both CF and asthma.
Discussion
A key objective of this study was to systematically assess
barriers to adherence for children with CF or asthma
and their parents. To date, no studies have examined
parent- and child-reported barriers to adherence for
individual components of the medical regimen. Across
treatments, parents were most likely to identify barriers
for the primary and most time-consuming treatments, in
particular airway clearance for CF and inhaled corticos-
teroids for asthma. Parents in the CF group also identi-
fied significant barriers to taking enzymes, which are
typically given five times a day. Parents of children with
asthma were more likely to report barriers for inhaled
corticosteroids than rescue inhalers and allergy medica-
tions, and they also identified significantly more barriers
for this treatment than parents of children with CF. This
may be attributable to the fact that inhaled corticosteroids
are the primary daily treatment for children with asthma,
highlighting the importance of examining barriers
within the context of each illness group. For example,
the salience of inhaled corticosteroids is likely to be
different for parents of children with CF and asthma.
Children with CF are required to perform numerous
treatments each day (e.g., airway clearance, boosting
calories, taking enzymes, and nebulized medications),
whereas inhaled corticosteroids are the major treatment
component for children with asthma. This suggests that
adherence interventions need to be both context (fitting
medications into daily routines) and disease specific,
with a focus on increasing the salience of treatments that
are most important for long-term health.
Common barriers for parents in both groups
included forgetting, oppositional behaviors, difficulties
with time management, and side effects. Children with
CF also identified difficulty swallowing pills as a key
barrier to oral medications (like oral antibiotics and
enzymes) and disliked the taste of particular medica-
tions. Although the frequency and types of barriers dif-
fered between parents of children with CF and asthma,
this study clearly indicated that parents can identify bar-
riers for the treatments they perceive to be important
and potentially more stressful.
For other treatment components (e.g., nebulizers
and rescue inhalers), approximately half of the parents
were unable to identify any barriers. Given the poor
adherence documented for these two populations, par-
ents are surprisingly unaware of what is getting in the
way. There are several possible reasons for this. First,
physicians do not routinely ask patients about adher-
ence behaviors, partly because of time constraints and
partly because of their discomfort in dealing with these
issues. Second, parents may be unaware of activities dur-
ing the day that interfere with completing treatment reg-
imens and thus may not anticipate the optimal ordering
of tasks to accommodate treatments, especially when
less typical events arise (like birthday party and soccer
games). Third, parents need to be sensitized to the com-
mon barriers they face in fitting these treatments in,
with practical suggestions for overcoming them. Inter-
vention efforts should focus on helping families identify
key barriers, followed by problem-solving strategies to
reduce them; such intervention efforts are now being
evaluated (Johnson & Quittner, 2001). Several of the
commonly identified barriers in this study, including
oppositional behaviors and difficulty swallowing pills,
can easily be targeted with behaviorally based interven-
tions (DeLambo, Ievers-Landis, Drotar, & Quittner,
2004; Stark et al, 2003).
In terms of the association between number of bar-
riers and adherence, although no statistically significant
by guest on June 2, 2013http://jpepsy.oxfordjournals.org/Downloaded from
Barriers to Adherence in CF and Asthma 855
relationships were found, the strength of several of these
relationships was notable. For example, a greater number
of barriers were moderately related to poorer adherence
recorded by electronic monitors. In contrast, positive
relationships were found between barriers and child-
reported adherence to enzymes and airway clearance,
which may be because of differences in respondents
(e.g., parent-reported barriers and child self-reported
adherence). In addition, some of these analyses were
constrained by a lack of power to detect significant rela-
tions. Future studies need to examine this important
relationship with larger samples.
No significant relationship was found between disease-
specific knowledge and adherence. These results are
consistent with studies conducted by McQuaid and col-
leagues (2003), which indicated a weak relationship
between knowledge and adherence for both children
with asthma and their parents. To date, this is the first
study to examine this important relationship for patients
with CF. Despite these findings, most intervention stud-
ies for children with asthma have focused on providing
education to children with asthma and their parents
(da Costa, Rapoff, Lemanek, & Goldstein, 1997; LeBaron,
Zeltzer, Ratner, & Kniker, 1985), and similar approaches
have been used in CF (Goldbeck & Babka, 2001). These
data suggest that intervention efforts should focus not
only on education but also on individualized barriers
identified by children and their parents. Empirically
supported strategies that incorporate skills training
(e.g., nebulizer or MDI use) as well as problem solving
(DeLambo et al, 2004; Wysocki et al, 2000) might prove
to be more effective than education alone.
Another barrier to adherence for patients with CF and
asthma is patient–provider communication. A significant
discrepancy was found between what physicians prescribed
and what parents understood. Several reasons may account
for this discrepancy: (a) confusion about current versus
past prescriptions, (b) prescription of new treatments that
have not been adequately described, and (c) parents’ modi-
fication of long-term prescriptions. Despite the complexi-
ties of these medical regimens and frequent changes to
prescriptions, no written PTPs were provided to parents or
patients. This may be a central cause of patient–provider
miscommunication and could be addressed fairly simply by
providing patients with a simple, user-friendly written
treatment plan (Quittner et al., 2000). In our current inter-
vention trial, copies are provided to both parents and phy-
sicians to enhance their communication.
Although this study represents an innovative method
for examining barriers to effective disease management
for children with CF and asthma, several limitations
should be noted. Prescribed treatment regimens for
these populations change frequently, making it difficult
to measure both rates of adherence and barriers over
time. We also encountered difficulties in determining
what physicians had prescribed before enrollment in the
study based on medical charts, which were often incom-
plete. Without a clear prescription, it is impossible to
calculate accurate rates of adherence for these patients.
The study was also limited by small sample sizes and
missing data, which was compounded by different regi-
mens for each child. This led to unequal samples for dif-
ferent medications and measurement methods.
The measures themselves also have limitations. For
example, it was difficult to obtain pharmacy refill data
because of the use of multiple pharmacies, dispensing of
free samples, and an increasing use of online pharma-
cies. Although electronic monitors are often viewed as
the “gold” standard, in this study, 77% of MDILogs
failed, did not fit properly, or were lost. Furthermore,
electronic monitors were not available for all compo-
nents of the treatment regimen (e.g., airway clearance).
As a result, there were limited objective data on rates of
adherence for inhaled corticosteroids. These problems
reduced our sample sizes and resulted in an emphasis on
descriptive rather than inferential statistics.
Finally, our sample had a restricted range of disease
severity, with approximately three-quarters of the sam-
ple in the mildly ill range. Comparisons of disease sever-
ity in the CF and asthma groups were also limited by the
use of FEV1 % predicted. Future studies should examine
disease severity based on the complete National Heart,
Lung, and Blood Institute (1997) guidelines for asthma,
which include PEF variability and nighttime and day-
time symptoms. It is also possible that patients with
more severe disease have different adherence rates and
barriers compared to patients with milder disease. Thus,
examining these relationships in an older sample with a
greater variability in disease severity will be important.
Future Directions
Adherence research is in its infancy and has focused to a
large extent on measurement issues (see Quittner et al.,
2000 and Riekert & Rand, 2002 for recent reviews). How-
ever, a more important question concerns the processes that
contribute to poor adherence based on the patient’s and
parent’s own perspective. Given the negative trend between
the number of prescribed treatments and adherence
reported on the daily diary, one suggestion is that physi-
cians may want to prioritize the number of treatments pre-
scribed each day in a negotiated contract with the family.
by guest on June 2, 2013http://jpepsy.oxfordjournals.org/Downloaded from
856 Modi and Quittner
An important next step is to assess barriers and rates
of adherence for individuals with CF and asthma across
different developmental stages. This study focused on
school-age children; however, few studies have exam-
ined these issues in younger children (ages 6 and
younger) and adolescents. Assessing barriers to adher-
ence for adolescents may be particularly beneficial
because they typically have the poorest adherence across
the life span (Rapoff, 1999). Adolescents may be better
able to articulate barriers to disease management than
the younger children in this study, who identified fewer
barriers than their parents, and these barriers may be
unique to this developmental period (e.g., wanting to be
“normal,” adolescent rebellion and time management
because of homework/school activities). Results of this
study indicated that interventions to improve adherence
should focus on barriers identified by individual
patients, within the context of their own illness. This
highlights the need for disease-specific tools that are
developmentally appropriate for the patient. For exam-
ple, if oppositional behaviors are identified as a primary
barrier for a teen with CF, interventions should utilize
behavioral and communication strategies, including
positive reinforcement, contracting, and contingency
management. Interventions will also have to be multi-
faceted, including education, skills training, provision of
written treatment plans to improve patient–provider
communication, and pragmatic solutions aimed at the
barriers that are so commonly faced by children with
these medical conditions and their families.
Acknowledgments
This study was funded in part by the Agency for Health-
care and Research Quality at the National Institutes of
Health (F31-H511768-01) and a grant awarded to
Johnson and Quittner (National Institutes of Health—
HL69736). We extend our deepest appreciation to the
children with cystic fibrosis and asthma and their families
who participated in this study, as well as the research
assistants who recruited participants and collected the data.
Received February 23, 2005; revision received August 3, 2005,
September 30, 2005 and November 28, 2005; accepted
December 7, 2005
References
Adams, C. D., Brestan, E. V., Ruggiero, K. J., Hogan, M. B.,
Wilson, N. W., Shigaki, C. L., & Sherman, J. M.
(2001). Asthma questionnaire: Psychometric
properties and clinical utility in pediatric asthma.
Children’s Health Care, 30, 253–270.
Anthony, H., Paxon, S., Bines, J., & Phelan, P. (1999).
Psychosocial predictors of adherence of nutritional
recommendations and growth outcomes in children
with cystic fibrosis. Journal of Psychosomatic
Research, 47, 623–634.
Bauman, L. J., Wright, E., Leickly, F. E., Crain, E.,
Kruszon-Moran, D., Wade, S. L., & Visness, C. M.
(2002). Relationship of adherence to pediatric
asthma morbidity among inner-city children. Pedi-
atrics, 110, e6.
Becker, M. H., Drachman, R. H., & Kirscht, J. P. (1972).
Predicting mother’s compliance with pediatric med-
ical regimens. Journal of Pediatrics, 81, 843–854.
Bender, B., Wamboldt, F. S., O’Conner, S. L., Rand, C.,
Szefler, S., Milgrom, H., & Wamboldt, M. Z. (2000).
Measurement of children’s asthma medication
adherence by self-report, mother report, canister
weight, and Doser CT. Annals of Allergy, Asthma &
Immunology, 85, 416–421.
Berg, J. S., Dischler, J., Wagner, D. J., Raia, J., &
Palmer-Shevlin, N. (1993). Medication compliance:
a health care problem. Annals of Pharmacotherapy,
27(Suppl.), 2–21.
Brown, S. J. (1999). Patient-centered communication.
Annual Review of Nursing Research, 17, 85–104.
da Costa, I. G., Rapoff, M. A., Lemanek, K., & Goldstein,
G. L. (1997). Improving adherence to medication
regimens for children with asthma and its effect on
clinical outcome. Journal of Applied Behavior
Analysis, 30, 687–691.
DeLambo, K. E., Ievers-Landis, C. E., Drotar, D., &
Quittner, A. L. (2004). Association of observed fam-
ily relationship quality and problem-solving skills
with treatment adherence in older children and
adolescents with cystic fibrosis. Journal of Pediatric
Psychology, 29, 343–353.
Donnelly, J. E., Donnelly, W. J., & Thong, Y. H. (1987).
Parental perceptions and attitudes toward asthma
and its treatment: a controlled study. Social Sciences
and Medicine, 24, 431–437.
Farber, H. J., Capra, A. M., Finkelstein, J. A., Lozano, P.,
Quesenberry, C. P., Jensvold, N. G., Chi, F. W., &
Lieu, T. A. (2003). Misunderstanding of asthma
controller medications: Association with nonadher-
ence. Journal of Asthma, 40, 17–25.
Goldbeck, L., & Babka, C. (2001). Development and
evaluation of a multi-family psychoeducational
program for cystic fibrosis. Patient Education and
Counseling, 44, 187–192.
by guest on June 2, 2013http://jpepsy.oxfordjournals.org/Downloaded from
Barriers to Adherence in CF and Asthma 857
Gudas, L. J., Koocher, G. P., & Wypig, D. (1991).
Perceptions of medical compliance in children and
adolescents with cystic fibrosis. Journal of Develop-
mental and Behavioral Pediatrics, 12, 236–242.
Heffer, R. W., Worchel-Prevatt, F., Rae, W. A., Lopez,
M. A., Young-Saleme, T., Orr, K., Aikman, G.,
Krause, M., & Wier, M. (1997). The effects of oral
versus written instructions on parents’ recall and
satisfaction after pediatric appointments. Journal of
Developmental and Behavioral Pediatrics, 18,
377–382.
Henley, L. D., & Hill, I. D. (1990). Global and specific
disease-related information needs of cystic fibrosis
patients and their families. Pediatrics, 85,
1015–1021.
Ievers, C. E., Brown, R. T., Drotar, D., Caplan, D.,
Pishevar, B., & Lambert, R. G. (1999). Knowledge
of physician prescriptions and adherence to
treatment among children with cystic fibrosis and
their mothers. Journal of Developmental and
Behavioral Pediatrics, 2, 335–343.
Johnson, S. B., & Quittner, A. L. (2001). Clinic-based
adherence intervention for diabetes and cystic
fibrosis. HL69736.
Kelloway, J. S., Wyatt, R. A., & Adlis, S. A. (1994).
Comparison of patients’ compliance with prescribed
oral and inhaled asthma medications. Archives of
Internal Medicine, 154, 1349–1352.
Knudson, R. J., Slatin, R. C., Lebowitz, M. D., &
Burrows, B. (1976). The maximal expiratory flow–
volume curve. American Review of Respiratory
Disease, 113, 587–600.
LaGreca, A. M., & Bearman, K. J. (2003). Adherence to
prescribed medical regimens. In M. C. Roberts
(Ed.), Handbook of pediatric psychology (3rd ed.,
pp. 119–140). New York: Guilford.
LeBaron, S., Zeltzer, L. K., Ratner, P., & Kniker, W. T.
(1985). A controlled study of education for improving
compliance with cromolyn sodium (Intal®): The
importance of physician–patient communication.
Annals of Allergy, 55, 811–818.
Logan, D., Zelikovsky, N., Labay, L., & Spergel, J.
(2003). The illness management survey. Journal of
Pediatric Psychology, 28, 383–392.
Mansour, M. E., Lanphear, B. P., & DeWitt, T. G.
(2000). Barriers to asthma care in urban children:
Parent perspectives. Pediatrics, 106, 512–519.
McQuaid, E. L., Kopel, S. J., Klein, R. B., & Fritz, G. K.
(2003). Medication adherence in pediatric asthma:
Reasoning, responsibility, and behavior. Journal of
Pediatric Psychology, 28, 3232–3333.
Modi, A. C. (2002). Adherence in children with cystic
fibrosis and asthma. F31-HS11768–01.
Modi, A. C., & Quittner, A. L. (in press). Utilizing com-
puterized phone diary procedures to assess health
behaviors in family and social contexts. Children’s
Health Care.
Naspitz, C. K., & Tinkelman, D. G. (2001). Barriers to
measuring and achieving optimal outcomes in
pediatric asthma. Journal of Allergy and Clinical
Immunology, 107, S482–S484.
National Institutes of Health: National Heart, Lung, and
Blood Institute (1997). National Asthma Education
and Prevention Program Expert Panel Report 2:
Guidelines for the Diagnosis and Management of
Asthma (NIH Publication No. 97-4051).
Passero, M. A., Remor, B., & Solomon, J. (1981).
Patient-reported compliance with cystic fibrosis
therapy. Clinical Pediatrics, 20, 264–268.
Quittner, A. L., Drotar, D., Ievers-Landis, C., Seidner, D.,
Slocum, N., & Jacobsen, J. (2000). Adherence to
medical treatments in adolescents with cystic fibrosis:
The development and evaluation of family-based inter-
ventions. In D. Drotar (Ed.), Promoting adherence to
medical treatment in childhood chronic illness: Interven-
tions and methods. Hillsdale, NJ: Erlbaum Associates.
Quittner, A. L., & Espelage, D. L. (1999, August).
Assessing complex family interactions using the
daily phone diary. In A. L. Quittner (Chair),
Strengthening self-report: Diary methods for
measuring child and family processes. Symposium
conducted at the Annual Meeting of the American
Psychological Association, Boston, MA.
Quittner, A. L., Espelage, D. L., Ievers-Landis, C., &
Drotar, D. (2000). Measuring adherence to medical
treatments in childhood chronic illness: Considering
multiple methods and sources of information. Journal
of Clinical and Psychology in Medical Settings, 7, 41–54.
Quittner, A. L., & Opipari, L. C. (1994). Differential
treatment of siblings: Interviews and diary analyses
comparing two family contexts. Child Development,
65, 800–814.
Quittner, A. L., Opipari, L. C., Regoli, M. J., Jacobsen, J., &
Eigen, H. (1992). The impact of caregiving and role
strain on family life: Comparisons between mothers
of children with cystic fibrosis and matched con-
trols. Rehabilitation Psychology, 37, 289–304.
Rapoff, M. A. (1999). Adherence to pediatric medical regi-
mens. New York, NY: Kluwer Academic/Plenum
Publishers.
Riekert, K. A., & Rand, C. S. (2002). Electronic
monitoring of medication adherence: When is
by guest on June 2, 2013http://jpepsy.oxfordjournals.org/Downloaded from
858 Modi and Quittner
high-tech best? Journal of Clinical Psychology in
Medical Settings, 9, 25–34.
Stark, L. J., Jelalian, E., & Miller, D. L. (1995). Cystic
fibrosis. In M. C. Roberts (Ed.), Handbook of
pediatric psychology (2nd ed., pp. 241–262).
New York, NY: The Guilford Press.
Stark, L. J., Opipari, L. C., Spieth, L. E., Jelalian, E.,
Quittner, A. L., Higgins, L., Mackner, L., Byars, K.,
Lapey, A., Stallings, V., & Duggan, C. (2003). Con-
tribution of behavior therapy to dietary treatment in
cystic fibrosis: a randomized controlled study within
2-year follow-up. Behavior Therapy, 34, 237–258.
Stephens, M. A., Norris-Baker, C., & Willems, E. P.
(1983). Patient behavior monitoring through self-
reports. Archives of Physical Medicine and Rehabilita-
tion, 64, 167–171.
Taussig, L. M. (1995). Advances in cystic fibrosis: Bring
the bench to the bedside. European Journal of
Pediatrics, 154(Suppl. 4), S9–S10.
Walders, N., Kopel, S. J., Koinis-Mitchell, D., &
McQuaid, E. (2005). Patterns of quick-relief
and long-term controller medication use in
pediatric asthma. Journal of Pediatrics, 146,
177–182.
Warwick, W. J., & Hansen, L. G. (1991). The long-term
effect of high-frequency chest compression therapy
on pulmonary complications of cystic fibrosis.
Pediatric Pulmonology, 11, 265–271.
Weiss, K., Gergen, P., & Hodgson, T. (1992). An
economic evaluation of asthma in the United States.
The New England Journal of Medicine, 326,
862–868.
Wysocki, T., Harris, M. A., Greco, P., Bubb, J., Danda, C. E.,
Harvey, L. M., McDonell, K., Taylor, A., & White,
N. H. (2000). Randomized, controlled trial of
behavior therapy for families of adolescents with
insulin-dependent diabetes mellitus. Journal of
Pediatric Psychology, 25, 23–33.
by guest on June 2, 2013http://jpepsy.oxfordjournals.org/Downloaded from
