Ediger JP, Walker JR, Graff L, et al.. Predictors of medication adherence in inflammatory bowel disease

University of Manitoba, Winnipeg, Manitoba, Canada
The American Journal of Gastroenterology (Impact Factor: 10.76). 08/2007; 102(7):1417-26. DOI: 10.1111/j.1572-0241.2007.01212.x
Source: PubMed
ABSTRACT
This study reports cross-sectional medication adherence data from year 1 of the Manitoba Inflammatory Bowel Disease (IBD) Cohort Study, a longitudinal, population-based study of multiple determinants of health outcomes in IBD in those diagnosed within 7 yr.
A total of 326 participants completed a validated multi-item self-report measure of adherence, which assesses a range of adherence behaviors. Demographic, clinical, and psycho-social characteristics were also assessed by survey. Adherence was initially considered as a continuous variable and then categorized as high or low adherence for logistic regression analysis to determine predictors of adherence behavior.
Using the cutoff score of 20/25 on the Medication Adherence Report Scale, high adherence was reported by 73% of men and 63% of women. For men, predictors of low adherence included diagnosis (UC: OR 4.42, 95% CI 1.66-11.75) and employment status (employed: OR 11.27, 95% CI 2.05-62.08). For women, predictors of low adherence included younger age (under 30 versus over 50 OR 3.64, 95% CI 1.41-9.43; under 30 vs. 40-49 yr: OR 2.62, 95% CI 1.07-6.42). High scores on the Obstacles to Medication Use Scale strongly related to low adherence for both men (OR 4.05, 95% CI 1.40-11.70) and women (OR 3.89, 95% CI 1.90-7.99). 5-ASA use (oral or rectal) was not related to adherence. For women, immunosuppressant use versus no use was associated with high adherence (OR 4.49, 95% CI 1.58-12.76). Low trait agreeableness was associated with low adherence (OR 2.03, 95% CI 1.12-3.66).
Approximately one-third of IBD patients were low adherers. Predictors of adherence differed markedly between genders, although obstacles such as medication cost were relevant for both men and women.

Full-text

Available from: Norine Miller, Sep 02, 2014
American Journal of Gastroenterology ISSN 0002-9270
C
2007 by Am. Coll. of Gastroenterology doi: 10.1111/j.1572-0241.2007.01212.x
Published by Blackwell Publishing
Predictors of Medication Adherence in Inflammatory
Bowel Disease
Jason P. Ediger, Ph.D.,
1,2
John R. Walker, Ph.D.,
1,2
Lesley Graff, Ph.D.,
1,2
Lisa Lix, Ph.D.,
1,2
Ian Clara, Ph.D.,
1,2
Patricia Rawsthorne, R.N.,
1,3
Linda Rogala, R.N.,
1,3
Norine Miller, R.N.,
1,3
Cory McPhail, B.A.,
1,2
Kathleen Deering, B.A.,
1,2
and Charles N. Bernstein, M.D.
1,3
1
University of Manitoba Inflammatory Bowel Disease Clinical and Research Centre, Winnipeg, Manitoba,
Canada; and Departments of
2
Clinical Health Psychology and
3
Internal Medicine, University of Manitoba,
Winnipeg, Manitoba, Canada
BACKGROUND This study reports cross-sectional medication adherence data from year 1 of the Manitoba
AND AIMS: Inflammatory Bowel Disease (IBD) Cohort Study, a longitudinal, population-based study of multiple
determinants of health outcomes in IBD in those diagnosed within 7 yr.
METHODS: A total of 326 participants completed a validated multi-item self-report measure of adherence,
which assesses a range of adherence behaviors. Demographic, clinical, and psycho-social
characteristics were also assessed by survey. Adherence was initially considered as a continuous
variable and then categorized as high or low adherence for logistic regression analysis to determine
predictors of adherence behavior.
RESULTS: Using the cutoff score of 20/25 on the Medication Adherence Report Scale, high adherence was
reported by 73% of men and 63% of women. For men, predictors of low adherence included
diagnosis (UC: OR 4.42, 95% CI 1.66–11.75) and employment status (employed: OR 11.27, 95% CI
2.05–62.08). For women, predictors of low adherence included younger age (under 30 versus over
50 OR 3.64, 95% CI 1.41–9.43; under 30 vs. 40–49 yr: OR 2.62, 95% CI 1.07–6.42). High scores
on the Obstacles to Medication Use Scale strongly related to low adherence for both men (OR 4.05,
95% CI 1.40–11.70) and women (OR 3.89, 95% CI 1.90–7.99). 5-ASA use (oral or rectal) was not
related to adherence. For women, immunosuppressant use versus no use was associated with high
adherence (OR 4.49, 95% CI 1.58–12.76). Low trait agreeableness was associated with low
adherence (OR 2.03, 95% CI 1.12–3.66).
CONCLUSIONS: Approximately one-third of IBD patients were low adherers. Predictors of adherence differed
markedly between genders, although obstacles such as medication cost were relevant for both men
and women.
(Am J Gastroenterol 2007;102:1417–1426)
INTRODUCTION
Medication represents a cornerstone of modern treatment
strategies for inflammatory bowel disease (IBD). Appropriate
use can help patients to induce remission and maintain those
gains over time (1–4). Nevertheless, the medication can be
costly and difficult to take with unpleasant side effects, all of
which may result in less than optimal adherence to the treat-
ment regimen and poorer outcomes for disease management.
In this context, treatment adherence has significant implica-
tions for patient well-being and treatment outcome. Given
that physicians typically have limited control over this facet
of treatment, adherence also represents the greatest point of
vulnerability in this intervention. This is particularly salient
in the treatment of chronic disease when patients may be
asked to adhere to a specific regimen for several years at a
time. Poor medication adherence has been well established in
this context when assessing hypertension and diabetes with
rates varying between 50% and 65% (5, 6). Hence, it is im-
portant to identify factors related to poor treatment adherence
in IBD.
IBD has previously been identified as a particularly high-
risk illness for poor adherence (7, 8). Individuals are often
diagnosed relatively young and must cope with the disease for
many years. Treatments can be inconvenient and difficult to
follow. Furthermore, the disease has an unpredictable course
with potentially long periods of inactivity. IBD patients must
have a strong belief in their doctor’s plan and strong convic-
tions about the necessity of the treatment to optimally follow
through with the treatment plan (8). Nonadherence rates for
short-term therapy have been described as varying from 20%
to 40% and rise as high as 72% for longer-term therapies
(8–10).
1417
Page 1
1418 Ediger et al.
Low medication adherence for those with IBD has been
linked to male gender, younger age, a higher number of pre-
scribed medications, high disease activity, shorter disease
duration, and psychiatric comorbidity (911). Other research
has highlighted the importance of doctorpatient relation-
ships, frequency of medical appointments, and beliefs about
medication in predicting medication adherence (8). Replica-
tion of these predictors across studies has been inconsistent,
however. As such, there is currently no well-validated prole
for IBD patients with low medication adherence. Many of
the studies done to date have been hampered by a variety of
methodological limitations including small and potentially
unrepresentative samples.
It has been challenging to develop valid and inexpensive
measures of adherence. Determination of high and low ad-
herence often differs based on methodology and the types
of medication under examination. Adherence has been mea-
sured in a variety of different waysincluding pill counts, phar-
macy data, assays of blood or urine, electronic medication
dispensers, and verbal reports of compliance (12). The more
objective methods of adherence have most often been used
in treatment studies where patients have frequent monitoring
and contact with treatment staff. This frequent monitoring
(designed to improve adherence) is clearly not characteristic
of usual treatment and can result in adherence behavior that is
not typical. In situations where patients are receiving diverse
forms of treatment and have less frequent contact from treat-
ment staff, verbal report has been used most often because it
is less costly and allows assessment of a more diverse range of
treatment recommendations. However, the degree of agree-
ment among these various forms of assessment for treatment
adherence can vary.
Standardized self-report approaches have proven to be an
efcient and effective method of determining medication ad-
herence (12). They have established validity, positively cor-
relating with pill counts (13), blood pressure control (14), and
virological outcome (15). However, self-report on treatment
adherence has been most often assessed using very brief mea-
sures, and a limited scale of responses (yes/no). Commonly
used measures, such as the Moriskey (16), can lead to a fairly
arbitrary denition of adherence that is often dependent on
the answer to a single question.
An obstacle inherent in adherence research is obtain-
ing data that are representative of the broad spectrum of
the patient population regarding their adherence behavior.
That is, studies typically rely on patient samples seeking
treatment in specialty clinics (7, 8, 17). These data, while
important, may reect a sampling bias by assessing pa-
tients in specialized follow-up settings. Patients may be
more likely to have active disease and/or more positive be-
liefs about the medical system under these circumstances.
Our aim was to study factors related to treatment adher-
ence in a population-based community sample of those with
IBD that includes patients across the spectrum of disease
activity.
MATERIALS AND METHODS
Participants
The Manitoba IBD Cohort Study was initiated in 2002, draw-
ing on participants from the University of Manitoba IBD Re-
search Registry. Participating individuals were required to be
at least 18 yr of age and diagnosed within the previous 7 yr.
The population-based Registry was established in 1995. Res-
idents of the province of Manitoba, Canada (population ap-
proximately 1,150,000), identied as having IBD through the
administrative health database of Manitoba Health (the gov-
ernment agency that provides comprehensive health coverage
to all residents), were eligible for inclusion in the registry. Of
those eligible, that is, all those with IBD in the province, just
over half participated in the Registry (18).
The Manitoba IBD Cohort Study was approved by the Uni-
versity of Manitoba Health Research Ethics Board and par-
ticipants provided written informed consent for their involve-
ment in the research. At the time of study recruitment, there
were 3,192 participants in the Research Registry, of which
606 were eligible for this study, given the age and recent on-
set criteria. A total of 492 could be contacted over a period
of 18 months, and of those, 418 agreed to enroll in the study.
Complete data were obtained in the rst contact of the longi-
tudinal Manitoba IBD Cohort from 388 of those enrolled, and
they have subsequently served as the cohort. More details on
the creation of this sample are provided in an earlier report by
our group (19). Complete data on medication adherence and
related variables were available for 326 of those participating
and were collected 12 months after entry into the cohort.
The mean age of participants was 41 yr (SD = 14.06),
with a range from 18 to 80 yr. Sixty percent of partici-
pants were female. Forty-eight percent of participants were
taking 5-ASA, 21% were taking immunosuppresants, and
5% were taking prednisone. The average duration of disease
was 5.4 yr (SD = 2.1). The sample was 95% Caucasian,
with few having self-described backgrounds as East Indian,
Hispanic, or Metis. Approximately two-thirds of patients
were categorized as married (65%) and employed full time
(66%). One quarter of the sample was university educated
(25%).
Assessment of Disease Type and Activity
IBD diagnosis subtype was veried through chart review in
the early stages of cohort development. A total of 162 partic-
ipants in this substudy (50%) had Crohns disease (CD), 146
(45%) had ulcerative colitis (UC, either ulcerative colitis or
ulcerative proctitis), and 18 (5%) had indeterminate colitis.
Individuals with indeterminate colitis were excluded from
categorical logistic regressions. Information regarding dis-
ease activitywas collected at the same time point as adherence
measurement and was determined by patient report of symp-
tom persistence for the previous 6 months based on a six-level
response scale. Active disease was dened as experiencing
symptoms constantly to occasionally at some point during
Page 2
Predictors of Medication Adherence in IBD 1419
the prior 6 months, and inactive disease was dened as expe-
riencing infrequent symptoms or feeling well. Standardized
clinical indices for disease activity, the HarveyBradshaw for
CD (20) and Powell-Tuck for UC (21) obtained during the
clinical interview, were used to validate self-reported disease
activity and these ndings are described in a previous study
(19). Active disease in the previous 6 months was reported
by 66% of respondents, whereas 34% reported they had no
disease activity in that same period.
Assessment of Medication Adherence and Related
Variables
Medication adherence wasassessedusing the Medication Ad-
herence Report Scale (MARS) (2225), which measures a
range of adherence behaviors. Nonadherence in this context
is operationalized by both the tendency to avoid, forget, or
stop taking medication, and the tendency to adjust or alter
the dose from that recommended by the physician (26). The
number of items, and range of response options, emphasizes a
continuum of adherence behavior, in contrast to other scales
with dichotomous responses. Items are aggregated so that
no single item determines categorization as adherent. The
MARS allows patients to describe their typical pattern of
medication adherence behavior, which facilitates its use even
whenthey are not currentlytakinga medication. This measure
has been found to have adequate reliability, as well as good
criterion and discriminative validity (22, 27). The MARS
has been used to assess medication adherence in a variety of
health populations, including asthma, COPD, chronic pain,
high cholesterol, and diabetes (25, 2831). There are also un-
published data validating this measure with an IBD sample
(Horne, personal communication, 2/18/06).
A few versions of this scale exist. While all nine items
were collected in this study (see Table 1), the most recent
ve-item version (MARS-5) was used for all statistical anal-
yses. Items are scored on a 5-point Likert scale and added
to create a cumulative score with a total of 25 indicating
complete adherence. The scale can be analyzed either con-
Table 1. Adherence Behaviors from the Medication Adherence Re-
port Scale and Proportion of Respondents Indicating Frequent Dif-
culties in These Areas
Ver y
Often Often
Adherence Items % %
I alter the dose
47
I forget to use it
05
I stop taking it for a while
45
I only use it if I feel sick 4 7
I decide to miss out on a dose
24
I take less than instructed
65
I avoid using it if I can 5 4
I use it only if I have to, if other things dont work 4 5
I use it regularly every day 57 15
N = 326;
Items on the ve-item version of the Medication Adherence Report Scale.
Rating descriptions for this scale were: never, rarely, sometimes, often, and very often.
tinuously or categorically. Based on the positive skewing of
the sample distribution and consultation with the developer
of the MARS (Horne, personal communication, 2/18/2006),
those with scores of 20 or higher were categorized as hav-
ing high adherence. This cutoff is close to the mean and also
represents 80% of a total adherence score. A total of 213 par-
ticipants (65%) were classied as having high adherence and
113 (35%) as having low adherence.
Several other adherence-related measures were also col-
lected at the same time. The Beliefs About Medication Ques-
tionnaire (BMQ) (32) is a 17-item standardized scale assess-
ing specic concerns about medication the person is taking
and general beliefs about the importanceof that medication. It
also measures beliefs about the potential for harmand overuse
of medications in general. Item responses are summed to pro-
vide a total score, with a higher score indicating greater con-
cern about medications. Psychometric data suggest that this
measure is both reliable and valid in a variety of medical pop-
ulations including those being treated for asthma, diabetes,
cardiac problems, and psychiatric illness (32).
In addition, two self-report scales were developed specif-
ically for this study to assess potential obstacles and use of
reminders, both of which can impact adherence. The items on
both scales were generated based on the general adherence
literature, as well as clinical experience and patient report.
The Obstacles to Medication Use Scale is a list of 10 discrete
items concerning difculties in taking medication regularly
(see Table 2 for the items on this scale). Each item had a
5-point Likert response scale; the items were summed and a
higher score indicated a greater number of perceived barri-
ers. The scale was found to have good internal consistency
(Cronbachs alpha = 0.77). The Medication Reminders Scale
used a 5-point Likert response scale with 7 discrete items
Table 2. Items on the Obstacles to Medication Use Scale and Pro-
portion of Respondents Indicating Frequent Difculties in These
Areas
Ver y
Often Often
Types of Obstacles % %
I forget to take the medication when it is
scheduled
010
I am too busy to take the medication 1 4
The medication causes unpleasant side effects 5 8
The medication is costly 15 10
I feel ill at times when I am scheduled to take
the medication
23
I dont have the medication with me when I
am scheduled to take it
06
Taking the medication reminds me that I have
had problems with IBD
57
I am not sure that the medication makes me
feel better
48
There are too many pills to take all at once 2 5
I have to take the medication too often during
the day
16
N = 326.
Page 3
1420 Ediger et al.
listing different methods people use to remind themselves to
take medication regularly. The responses were summed, and
a higher score equates to more use of reminders. It was antic-
ipated that greater medication concerns and obstacles would
be associated with lower adherence, whereas greater use of
reminders would be associated with higher adherence.
Assessment of Psychological Variables
Standardized self-report and interview measures were used
to assess psychological functioning. All of these measures
are widely used with established satisfactory psychometric
properties. Distress was measured using the Brief Symptom
Inventory (BSI) (33), a 53-item scale that assesses common
mental health symptoms. The Health Anxiety Questionnaire
(HAQ) is a 21-item scale measuring extent of health con-
cerns and somatic focus (34). The Neuroticism Extraversion
OpennessFive Factor Inventory (NEO-FFI) (35) is a sta-
ble personality inventory that assesses the ve core person-
ality factors identied in empirical research: Neuroticism,
Extraversion, Openness, Agreeableness, and Conscientious-
ness. The inventory has 60 items rated on a 5-point Likert
scale. The Mastery Scale (36, 37) was used to assess the per-
sons perceived control or efcacy in their life. All of these
measures were collected in the same period as the adherence
data with the exception of the NEO-FFI, which was collected
on entry into the cohort 12 months earlier.
Statistical Methods
Descriptive analyses were carried out for the demographic,
adherence, and psychological variables. The distribution of
adherence variables, and potential correlates such as age, gen-
der, socioeconomic status, distress, health anxiety, beliefs
about medication, mastery, and personality variables were
examined, and participants scores on continuous variables
were categorized as high or low based on the observed dis-
tribution of the sample to evaluate the relationships through
logistic regression. Subsequent analysis with logistic condi-
tional regression methods examined the relationship between
adherence and the explanatory variables. Given previous nd-
ings of gender differences in variables related to adherence
(9), the presence of a main effect of gender in our data (odds
ratio [OR] 1.80, 95% condence interval [CI] 1.063.05), and
a large number of gender interactions with other variables,
models were run separately for men and women to facilitate
interpretation of ndings. In one model, however, small cell
sizes forced the reintegration of genders. Thus, the rst model
included demographic variables, the second model examined
associations between psychological variables and adherence
(with men and women combined due to small cell sizes),
and the third model focused on medication factors and obsta-
cles to adherence. Minor variations in sample size among the
three analyses were caused by attrition due to small amounts
of missing data in the predictor variables. Both the second
and third model controlled for the effects of signicant de-
mographic variables from the rst model. ORs and the cor-
responding 95% CIs were estimated.
RESULTS
Adherence and Beliefs About Medication
Cumulative scores on the MARS-5 ranged from 8 to 25
with an average score of 20.67 (SD = 4.01). Responses
were skewed toward higher levels of adherence. Using the
score of 19 or lower to identify low adherence, approxi-
mately 35% of participants were classied as having low
adherence. Table 1 summarizes the frequency of adherence
behaviors. Eleven percent reported often or very often alter-
ing the dose or taking less than instructed. Likewise, 11%
also reported only taking their medication when they felt
sick. Interestingly, while forgetfulness has been reported to
play a key role in adherence difculties (16), this item re-
ceived the lowest amount of endorsement with only 5% of
respondents acknowledging that they often forget to take their
medication.
Responses to the Medication Reminders Scale suggested
that the most common memory strategy (often or very of-
ten used by 78% of respondents) was using your own day-
time cues such as taking medication when brushing teeth,
with meals, or at bedtime. Other strategies were much
less common with only 17% using a medication dispenser,
6% using a calendar or checklist, 6% a reminder from a
family member, 3% a blister pack provided by the phar-
macy, and 0% using a medication timer. The total score
on the Medication Reminders Scale had a relatively low
correlation with the total MARS-5 score (r = 0.13, P <
0.05) probably because few respondents used most types
of reminders, skewing responses to the low end of the
scale.
Item responses on the Obstacles to Medication Use Scale
are summarized in Table 2. Total scores were negatively cor-
related with responses on the MARS-5 (r =−0.37, P <
0.01) indicating that as the number of obstacles to medica-
tion use increased, adherence scores dropped. Among these
items, cost of medication was the most salient issue with
25% of patients indicating that cost often makes it difcult to
takemedication regularly. Other obstacles include side effects
(13%), unpleasant associations with medication (13%), un-
certainties about the effectiveness of their medication (12%),
and forgetfulness (10%).
Participants perceptions about IBD medication were
largely positive, based on their responses to the Beliefs about
Medication Questionnaire. While 62% of respondents re-
ported some degree of worry about the long-term effects
of their medication, an equal number (62%) also believed
their medicines kept them from getting worse. A majority of
participants (76%) did not believe that their medication was
disruptive to their life. This perspective appears to have ex-
tended to general beliefs about medication. Participants were
prone to disagree with statements suggesting that all medica-
tion is addictive (61%) or that medications typically do more
harm than good (76%). In contrast, 45% of respondents en-
dorsed the idea that stopping medications periodically was a
good thing.
Page 4
Predictors of Medication Adherence in IBD 1421
Table 3. Relationship Between Reported Adherence and Demographic and Disease Variables by Gender
N Male Female
% High % Low OR for Being a % High % Low OR for Being
Demographic Factors M F Adherence Adherence Low Adherer CI (95%) Adherence Adherence Low Adherer CI (95%)
Gender 121 183 73 27 63 37
Age
Under 30-yr old 29 53 83 17 53 47
3039-yr old 31 39 65 35 2.08 0.498.78 54 46 0.67 0.281.64
4049-yr old 26 48 73 27 0.83 0.183.77 69 31 0.38
0.160.94
50-yr old and over 35 43 71 29 2.50 0.5112.25 76 24 0.27
∗∗
0.110.71
Disease activity
Inactive 46 61 74 26 64 36
Active 75 122 72 28 1.68 0.604.67 63 38 1.29 0.662.54
Diagnosis
Crohns disease 65 96 85 15 63 37
Ulcerative colitis 56 87 59 41 4.42
∗∗
1.6611.75 63 37 1.10 0.582.10
Marital status
Married 77 124 71 29 62 38
Unmarried 44 59 75 25 1.29 0.433.86 65 36 0.74 0.361.51
Employment status
Working 91 112 66 34 58 42
Not working 30 71 93 7 0.09
∗∗
0.020.49 70 30 0.53 0.261.06
Education status
High schl/trades 84 143 73 27 64 36
University 37 40 73 27 0.93 0.322.70 58 42 1.22 0.572.59
Disease duration
4 yr or less 41 64 80 20 58 42
5 yr or more 87 125 72 28 1.62 0.554.74 62 38 0.95 0.491.85
P < 0.05;
∗∗
P < 0.01.
M = male; F = female; OR = odds ratio; CI = condence interval.
OR >1 indicates more nonadherence; OR <1 indicates more adherence.
Male: Not working vs working (OR 11.27, 95% CI 2.0562.08)
Female: Over 50 yr vs under 30 (OR 3.64, 95% CI 1.419.43)
Female: 4049 yr vs under 30 yr (OR 2.62, 95% CI 1.076.42)
Demographic and Disease Variables Predicting Adherence
Logistic regression identied a few signicant relationships
between medication adherence and both demographic and
disease variables (i.e., age, disease activity, diagnosis, mar-
ital status, employment, education, duration of disease) for
each gender. As can be seen in Table 3, the pattern of rela-
tionships differed between men and women. Men with lower
medication adherence were more likely to have a diagnosis
of UC (OR 4.42, 95% CI 1.6611.75) and be employed on a
full-time basis (OR 11.27, 95% CI 2.0562.08). These rela-
tionships were not signicant for women, however. Age was
the only signicant demographic predictor of medication ad-
herence in women. That is, women under 40 yr were more
likely to report low adherence than their older counterparts.
Age differences in adherence were not evident in men. Fur-
thermore, the proportion of men with low adherence across
the age range was generally similar to that of women over
40 yr of age. Disease activity, marital status, education, and
duration of disease were not signicant.
Psychological Variables Predicting Adherence
Preliminary analyses of psychological predictors were con-
ducted examining men and women separately. However,
small cell sizes for several variables made this strategy un-
tenable. As a result, psychological predictors of adherence
were analyzed in a logistic regression with men and women
combined, controlling for gender, age, employment, diagno-
sis, and the interactions of gender with those variables. Once
these variables were accounted for, the overall model only
identied one additional variable that predicted medication
adherence. As shown in Table 4, a persons level of agree-
ableness on the NEO-FFI signicantly predicted adherence.
Individuals who scored lower on the agreeableness scale were
twice as likely to report low adherence (OR 2.03, 95% CI
1.123.66). While no other variables met statistical signi-
cance, an examination of trends also suggests the utility of
distress as a potential predictor of adherence. This variable
marginally missed statistical signicance and suggests the
possibility that more distressed individuals may also have
greater difculty with medication adherence.
Medication Variables Predicting Adherence
A nal model was created to determine if differences in med-
ication characteristics helped to explain differences in ad-
herence. Type of medication and the frequency with which
that medication was administered were assessed through lo-
gistic regression controlling for age and employment. The
Obstacles to Medication Use Scale was also included in this
analysis. Medications were categorized by type as 5-ASA and
immunosuppressants. Data on prednisone were not included
Page 5
1422 Ediger et al.
Table 4. Relationship Between Reported Adherence and Psychological Variables
Low Logistic Regression
High Adherence Adherence
Psychological Variables N % % OR for Being a Low Adherer CI (95%)
Brief Symptom Inventory
Low-medium distress 276 68 32
High distress 27 42 58 2.34 0.866.41
Health Anxiety Questionnaire
Low-medium anxiety 271 66 34
High anxiety 32 62 38 0.76 0.332.22
Beliefs about medication
Low-medium concerns 256 68 32
High concerns 47 53 47 1.35 0.563.07
Low-medium necessity 62 60 40
High necessity 241 67 33 0.59 0.321.08
Low-medium overuse 89 74 26
High overuse 214 62 38 0.84 0.4591.55
Low-medium harm 99 72 28
High harm 204 62 38 1.66 0.913.00
Mastery
High mastery 217 62 38
Low-medium mastery 64 66 34 1.84 0.893.77
NEO-FFI (Personality Inventory)
Low agreeableness 141 59 41
High agreeableness 162 72 28 0.49
0.270.89
Low openness to experience 180 66 33
High openness to experience 123 65 35 1.17 0.662.07
Low conscientiousness 171 61 39
High conscientiousness 132 72 28 0.83 0.461.50
Low extraversion 186 66 34
High extraversion 117 66 34 0.93 0.491.75
Low neuroticism 146 70 30
High neuroticism 157 62 38 0.88 0.461.68
P < 0.05;
∗∗
P < 0.01 (N = 303).
Controlling for demographic factors: age, gender, employment, diagnosis, gender age, gender diagnosis gender employment.
OR = odds ratio; CI = condence interval.
OR >1 indicates more nonadherence; OR <1 indicates more adherence.
High agreeableness vs low agreeableness (OR 2.03, 95% CI 1.123.66).
in this analysis because only 17 participants were taking this
medication at the time of the survey. Table 5 illustrates that
women were less likely to report low adherence when they
were taking immunosuppressants (OR 0.20, 95% CI 0.05
0.77), or in other words, women on immunosuppressants
were more likely to report high adherence. This pattern did
not extend to women taking 5-ASA or to men. Obstacles to
adherence were strongly related to low medication adherence
for both men (OR 4.28, 95% CI 1.4912.31) and women (OR
3.94, 95% CI 1.928.08). There was no relationship between
treatment adherence and the number of pill administrations
per day. It is interesting to note that UC diagnosis remained a
signicant predictor of low medication adherence (OR 5.89,
95% CI 2.0616.88) for men even when these medication-
related variables were included in the analysis.
DISCUSSION
This study is the largest analysis of predictors of treatment
adherence for IBD and the rst to use a population-based
sample. All participants were in their rst 8 yr of illness.
One-third were classied as being low in adherence, which is
generally consistent with adherence data from clinical trials
for a range of chronic diseases, and may be slightly better than
what occurs in usual management of patients with chronic
diseases (12). Predictors of adherence, on the other hand,
demonstrated a somewhat different pattern than that which
has been previously described.
Gender has been implicated as a signicant predictor of
adherence in previous research (9), and was also found to be
relevant in our study. However, a markedly different pattern
of relationships was identied. Contrary to previous nd-
ings, women in our sample were more likely to report low
adherence than men. Furthermore, gender had a clear effect
on the impact of other predictors. That is, all of the other
demographic predictors identied were only signicant for
one gender or the other. Full-time employment and UC were
related to lower adherence, but only for men. Younger age
was predictive of more difculties with adherence, but only
for women. Likewise, women taking immunosuppressants
reported better adherence than those on other medications,
but this nding did not generalize to men. Interestingly, these
variables were also signicant during preliminary analyses
collapsed across gender. This highlights the importance of
Page 6
Predictors of Medication Adherence in IBD 1423
Table 5. Relationship Between Reported Adherence, Medication, and Obstacles to Adherence
Male Female
N
% High % Low OR for Being a % High % Low OR for Being
Demographic Factors M F Adherence Adherence Low Adherer CI (95%) Adherence Adherence Low Adherer CI (95%)
Gender 124 182 73 27 63 37
Medication prescribed
5-ASA no 64 98 72 28 59 41
5-ASA yes 60 84 73 26 0.34 0.721.57 67 33 1.13 0.403.22
Immunosuppressants no 92 147 72 28 58 42
Immunosuppressants yes 32 35 75 25 1.40 0.277.26 83 17 0.20
∗∗
0.050.77
Number of pill administrations
per day
None 48 76 73 27 53 47
12 per day 41 61 83 17 0.74 0.134.15 67 33 1.15 0.393.52
34 per day 35 46 60 40 3.00 0.5715.72 74 26 0.45 0.131.54
Obstacles to medication use
Low reported obstacles 63 84 87 13 80 20
High reported obstacles 61 98 57 43 4.28
∗∗
1.4912.31 48 52 3.94
∗∗
1.928.08
Diagnosis
Crohns disease 66 95 85 15 62 38
Ulcerative colitis 58 87 59 41 5.89
∗∗
2.0616.88 63 37 1.02 0.512.03
P < 0.05;
∗∗
P < 0.01.
Controlling for demographic factors: age, employment.
M = male; F = female; OR = odds ratio; CI = condence interval.
OR >1 indicates more nonadherence; OR <1 indicates more adherence.
Immunosuppressants yes vs immunosuppressants no (OR 4.49, 95% CI 1.5812.76).
looking for gender interactions in future adherence research.
Adherence has varied by gender in other studies and no sin-
gle prole of a low adherer specic to men or women has
emerged (38).
In our study, for men, disease subtype was clearly relevant
for adherence. Those with Crohns disease were much more
likely to be high adherers than men with UC. It is accepted that
Crohns disease may be more difcult to control. Certainly,
stulas and bowel obstructions that may present in Crohns
disease and do not in UC may enhance patients desire to
adhere to a medication regimen. We have recently shown
that patients with Crohns disease have greater health-care
utilization relative to patients with UC (39). This is true for
both outpatient visits and hospitalizations. It is possible that
men with Crohns disease are more likely to be high adherers
either because of more severe disease requiring more health
care, or because of more health-care contacts that reinforce
medication plans.
It was anticipated that disease activity, disease duration,
and beliefs about medication would have an impact on treat-
ment adherence. Nevertheless, results of our study did not
support this assumption. Only two variables were clearly pre-
dictive of adherence across gender once demographic factors
were controlled for.Individualswith a higher tendencytoward
interpersonal agreeableness were more likely to report higher
levels of treatment adherence. This result is not surprising in
the light of previous ndings regarding the importance of
the doctorpatient relationship and agreement for adherence
behavior (8).
The strongest predictor of adherence for both genders over-
all was the measure of obstacles to adherence. The more
obstacles a person identied to adherence, the more likely
they were to have low adherence. This suggests that low
adherence is not merely carelessness or attitude, but a re-
sponse to realities in the patients lives. Financial pressures
and cost of medication, for instance, may force patients to
make difcult choices about when and how they will take
their medication. While it is possible that self-reported ob-
stacles are merely excuses created by poor adherers to ex-
plain their behavior, this is a testable hypothesis. Physicians
would only need to eliminate identied obstacles to see if
this changes adherence. These realities are important for
physicians to consider when they are planning a treatment
regime.
It is possible that adherence may be improved by engaging
the patient in creative problem solving or seeking treatment
alternativesthat take known obstacles into account. Even with
Canadas universal health-care program where basic medical
visits are covered and many individuals have good benets
to cover much of the medication cost, cost was still the most
commonly reported obstacle to medication adherence. This
problem might be expected to be even more inuential in sit-
uations with more limited coverage for medical appointments
and associated medication. Thus, a less costly drug may im-
prove adherence in situations where cost is an important issue
for the patient. While not explicitly supported in this analy-
sis, previous studies have shown that a simpler regime (pills
taken once or twice a day vs multiple times in the day) can
improve adherence (40). Memory strategies such as medica-
tion dispensers, pharmacybubblepacks, or medication timers
may be useful to overcome memory problems (12). Education
may address unrealistic fears and associations the patient has
with their medication (41, 42). Engaging the patient in the
problem and having them help design a solution may be an
Page 7
1424 Ediger et al.
empowering experience while at the same time highlighting
how important adherence is for their health.
While the broad denition of adherence as doing what
the health professional recommends (43) may be relatively
straightforward, the measurement of it is not. A gold standard
for adherence assessment has not yet been agreed upon. Fur-
ther, the level of adherence required for effective treatment
will vary depending on the medical condition and the type of
treatment. Self-report measures that have been standardized
and validated are well accepted in the adherence literature
(12).
This study contributes several factors not previously ad-
dressed in the adherence literature for IBD. The sample size
was the largest assessed to date to look at predictors of
treatment adherence, and participants were recruited from
a population-based sample, providing a broader spectrum
of IBD patients. While the fact that they have volunteered
for the project may suggest greater bias for adherence and
other socially conforming behaviors, this bias would not be
unique to this study. Further, this sample represents a closer
approximation of IBD patients in the community than pre-
viously available. As well, since individuals are not being
assessed by members of their treatment team, there may be
fewer of the demand characteristics that are frequently as-
sociated with adherence research. Finally, while there are
challenges in the measurement of adherence, the measure
used in this study assesses a range of adherence behaviors
and allows for differing degrees of adherence. It should be
noted that this measure assesses self-report of typical medi-
cation adherenceit does not directly assess adherence be-
havior in the context of a specic treatment as a pill count
would.
This study considered many of the important variables re-
lated to adherence, however,not all of them could be included.
For example, there was no information available on the qual-
ity of the relationship with the prescribing physician or the
frequency of medical appointments. There were no measures
of psychiatric comorbidity, although the measure of distress
would capture some of this information. The primarily Cau-
casian sample should also encourage some caution in apply-
ing these ndings to a more ethnically diverse population.
In addition to broadening the range of factors for concur-
rent assessment, future studies could incorporate more than
one method of assessing adherence, such as self-report and
administrative data that document prescription lls, to allow
an evaluation of agreement among different adherence mea-
sures.
In summary, we found that while many with IBD were
generally good at adhering to treatment, a signicant portion
of individuals reported difculties taking their medication
as directed. Thirty-ve percent of participants met our cri-
terion cutoff for poor adherence behaviors. Our ndings un-
derscore the complex relationships among adherence, demo-
graphic variables, psychological variables, and medication
variables. Of particular note were the differences between
men and women in these relationships. Self-reported obsta-
cles to adherence predicted low adherence in both men and
women. Brief screening of obstacles can promote problem
solving and dialogue between the patient and physician to
facilitate improved adherence.
ACKNOWLEDGMENTS
This study was supported by a grant from the Canadian Insti-
tutes of Health Research. Dr. Bernstein is supported in part
by a Crohns and Colitis Foundation of Canada Research Sci-
entist Award. The authors would also like to thank Dr. R.
Horne of the University of London, U.K., for permission to
use the MARS and BMQ along with technical advice on the
project.
STUDY HIGHLIGHTS
What Is Current Knowledge
r
There is an increasing interest in understanding the
degree of adherence to medications among the patients
with inammatory bowel disease (IBD).
r
There is currently no well-validated prole for IBD
patients with low medication adherence.
What Is New Here
r
This is the rst population-based study of medication
adherence in IBD, and the largest sample size.
r
Approximately one-third of IBD patients are low med-
ication adherers.
r
There are different factors affecting medication adher-
ence in men versus women.
r
For men, important predictors of low adherence include
a diagnosis of ulcerative colitis (vs Crohns disease),
being employed, having high scores on the Obstacles
to Medication Use Scale and, having a low level of the
personality trait of agreeableness.
r
For women, important predictors of low adherence in-
clude younger age than 30 yr, having high scores on the
Obstacles to Medication Use Scale, and having a low
level of the personality trait of agreeableness. Immuno-
suppressant use was associated with high adherence in
women.
r
Among the Obstacles to Medication Use, assessed cost
of medication was the most salient issue with 25% of
patients indicating that cost often makes it difcult to
take medication regularly.
Reprint requests and correspondence: Charles N. Bernstein,
M.D., 804F-715 McDermot Avenue, Winnipeg, Manitoba, Canada
R3E 3P4.
Received December 19, 2006; accepted January 31, 2007.
Page 8
Predictors of Medication Adherence in IBD 1425
REFERENCES
1. Hanauer SB, Baert FJ. The management of ulcerative colitis.
Ann Rev Med 1995;46:497505.
2. Kane S. Patient compliance and outcomes. Inamm Bowel
Dis 1999;5:1347.
3. Feagan BG, Fedorak RN, Irvine EJ. A comparison of
methotrexate with placebo for the maintenance of remission
in Crohns disease. N Engl J Med 2000;342:162732.
4. Steinhart H. Maintenance therapy in Crohns disease. Can J
Gastroenterol 2001;14:238C.
5. Nichol MB, Venturini F, Sung JCY. A critical evaluation of
the methodology of the literature on medication compliance.
Ann Pharmacother 1999;33:53140.
6. Schlenk EA, Burke LE, Rand C. Behavioral strategies to im-
prove medication-taking compliance. In: Burke LE, Ockene
LS, eds. Compliance in healthcare and research. New York:
Futura Publishing Co, 2001:5770.
7. L´opez San Rom´an A, Bermejo F, Carrera E, et al. Adher-
ence to treatment in inammatory bowel disease. Rev Esanp
Enferm Digest 2005;97:24957.
8. Sewitch MJ, Abrahamowicz M, Barkun A, et al. Patient
nonadherence to medication in inammatory bowel disease.
Am J Gastroenterol 2003;98:153544.
9. Kane SV, Cohen RD, Aikens JE, et al. Prevalence of nonad-
herence with maintenance mesalamine in quiescent ulcera-
tive colitis. Am J Gastroenterol 2001;96:292933.
10. Nigro G, Angelini G, Brosso SB, et al. Psychiatric predictors
of noncompliance in inammatory bowel disease. J Clin
Gastroenterol 2001;32:668.
11. Shale MJ, Riley A. Studies of compliance with delayed-
release mesalazine therapy in patients with inammatory
bowel disease. Aliment Pharmacol Ther 2003;18:1918.
12. Bosworth HB. Medication treatment adherence. In:
Bosworth HB, Oddone EZ, Weinberger M, eds. Patient treat-
ment adherence, concepts, interventions, and measurement.
Mahwah, NJ: Lawrence Erlbaum Associates, 2006:147
94.
13. Haynes R, Taylor DW, Sackett DL. Can simple clinical
measurement detect patient noncompliance? Hypertension
1980;2:75982.
14. Fleece L, Summers MA, Schnaper H, et al. Adherence to
pharmacotherapeutic regimen: Assessment and interven-
tion. Alabama J Med Sci 1988;25:1338.
15. Haubrich RH, Little SJ, Currier JS, et al. The value
of patient-reported adherence to antiretroviral therapy in
predicting virologic and immunologic response. Califor-
nia Collaborative Treatment Group. AIDS 1999;13:1099
107.
16. Morisky DE, Green LW, Levine DM. Concurrent and pre-
dictive validity of a self-reported measure of medication
adherence. Med Care 1986;24:6774.
17. Kane S, Huo D, Aikens J, et al. Medication nonadherence
and the outcomes of patients with quiescent ulcerative coli-
tis. Am J Med 2003;14:3943.
18. Bernstein CN, Blanchard, JF, Rawsthorne P, et al. Epidemi-
ology of Crohns disease and ulcerative colitis in a central
Canadian province: A population-based study. Am J Epi-
demiol 1999;149:91624.
19. Graff LA, Walker JR, Lix L, et al. The relationship of in-
ammatory bowel disease type and activity to psychological
functioning and quality of life. Clin Gastroenterol Hepatol
2006;4:1491501.
20. HarveyRF, Bradshaw JM. A simple index of Crohns disease
activity. Lancet 1980;1:514.
21. Powell-Tuck J, Brown RL, Lennard-Jones JE. A comparison
of oral prednisolone given as single or multiple daily doses
for active proctocolitis. Scand J Gastroenterol 1978;13:833
7.
22. Horne R. The medication adherence report scale. University
of Brighton, Brighton, UK, 2004.
23. Horne R. Non-adherence to medication: Causes and impli-
cations for care. In: Gard P, ed. A behavioural approach to
pharmacy practice. Oxford: Blackwell, 2001:11130.
24. Horne R, Weinman J. Patients beliefs about prescribed
medicines and their role in adherence to treatment in chronic
physical illness. J Psychosom Res 1999;47:55567.
25. Horne R, Weinman J. Self-regulation and self-management
in asthma: Exploring the role of illness perceptions and treat-
ment beliefs in explaining non-adherence to preventer med-
ication. Psychol Health 2002;17:1732.
26. Horne R, Hankins M, Jenkins R. The Satisfaction with Infor-
mation about Medicines Scale (SIMS): A new measurement
tool for audit and research. Qual Health Care 2001;10:135
40.
27. Ohm R, Aaronson L. The symptom perception and ad-
herence to asthma controller medications. J Nurs Scholar
2006;38:2927.
28. GeorgeJ, Kong DC, Thoman R, et al. Factorsassociated with
medication nonadherence in patients with COPD. Chest
2005;128:3198204.
29. Kendrew P, Ward F, Buick D, et al. Satisfaction with infor-
mation and its relationship with adherence in patients with
chronic pain. Int J Pharm Pract 2001;9:R5.
30. Senior V, Marteau TM, Weinman J. Self-reported adherence
to cholesterol-lowering medication in patients with hyper-
cholesterolaemia: The role of illness perceptions. Cardio-
vasc Drugs Ther 2004;18:47581.
31. Barnes L, Moss-Morris R, Kaufusi M. Illness beliefs and ad-
herence in diabetes mellitus: A comparison between Tongan
and European patients. N Z Med J 2004;117:108.
32. Horne R, Weinman J, Hankins M. The Beliefs about
Medicines Questionnaire: The development and evaluation
of a new method for assessing the cognitive representation
of medication. Psychol Health 1999;14:124.
33. Derogatis L. The Brief Symptom Inventory: Administration,
scoring, and procedures manual, 3rd Ed. Minneapolis, MN:
National Computer Systems, Inc., 1993.
34. Lucock MP, Morley S. The Health Anxiety Questionnaire.
Br J Health Psychol 1996;1:13750.
35. Costa PT Jr, McCrae RR. Revised NEO Personality Inven-
tory (NEO PI-R) and the NEO Five-Factor Inventory (NEO-
FFI) professional manual. Odessa, FL: Psychological As-
sessment Resources, 1992.
36. Pearlin LI, Schooler C. The structure of coping. J Health
Soc Behav 1978;19:221.
37. Pearlin LI, Menaghan EG, Lieberman MA, et al. The stress
process. J Health Soc Behav 1982;22:33756.
38. Osterberg L, Blaschke T. Adherence to medication. N Engl
J Med 2005;353:48797.
39. Longobardi T, Bernstein CN. Health care resource uti-
lization in IBD. Clin Gastroenterol Hepatol 2006;4:731
43.
40. Morningstar BA, Sketris IS, Kephart GC, et al. Variation
in pharmacy prescription rell adherence measures by type
of oral antihyperglycemic drug therapy in seniors in Nova
Scotia, Canada. J Clin Pharm Ther 2002;27:18.
41. Burgoon JK, Pfau M, Parrott R, et al. Relational communi-
cation, satisfaction, compliance-gaining strategies and com-
pliance in communication between physicians and patients.
Commun Monogr 1987;54:30724.
42. Roter Dl, Hall JA, Merisca R, et al. Effectiveness of inter-
ventions to improve patient compliance: A meta analysis.
Med Care 1998;36:113861.
Page 9
1426 Ediger et al.
43. DiMatteo MR. Variations in patients adherence to medi-
cal recommendations: A quantitative review of 50 years of
research. Med Care 2004;42:2009.
CONFLICT OF INTEREST
Guarantor of the article: Charles Bernstein
Specific author contributions: Jason Ediger: study plan-
ning, data analysis, writing of the paper, and nal review of
the paper.
John Walker: study planning, data analysis, writing of the
paper, nal review of the paper.
Lesley Graff: study planning, data analysis, writing of the
paper, nal review of the paper.
Lisa Lix: study planning, statistical consultation, nal review
of the paper.
Ian Clara: statistical consultation, nal review of the paper.
Trish Rawsthorne: study planning, data collection, nal re-
view of the paper.
Linda Rogala: study planning, data collection, nal review
of the paper.
Norine Miller: study planning, data collection, nal review
of the paper.
Cory McPhail: data collection, nal review of the paper.
Kathleen Deering: data collection, nal review of the
manuscript.
Charles Bernstein: study planning, data analysis, writing of
the paper, nal review of the paper.
Potential competing interests: None.
Page 10
  • Source
    • "Thus, we might expect that this group would benefit from adherence support in the form of help with developing routines for taking antibiotics. The current results are in line with previous research showing associations between personality traits and adherence behaviour in individuals prescribed longterm medication treatments for various chronic diseases (Christensen and Smith 1995; Ediger, et al. 2007; O'Cleirigh, et al. 2007; Stilley, et al. 2004), which could be seen as a strength. However, it could be argued that assessing and taking personality into consideration is unrealistic in daily clinical practice when prescribing antibiotics for shorter treatment periods for common infections. "
    [Show abstract] [Hide abstract] ABSTRACT: Antimicrobial resistance results from inappropriate use of antibiotics and makes common or life-threatening infections more difficult or sometimes impossible to treat. Proper adherence to antibiotic therapy is one among several measures required to prevent antimicrobial resistance. Knowledge of personality traits could help in identifying patients who need support with their adherence behaviour. Previous research has presented associations between personality traits and adherence to long-term medication treatment in individuals with different chronic diseases. However, there is limited knowledge about associations between personality traits and adherence to both antibiotic therapy and to shorter treatment periods. The aim was to explore the relation between personality and adherence behaviour in people prescribed antibiotics for common infections. In a population-based study, 445 respondents reported on their prescribed antibiotic therapy and completed the Neuroticism, Extraversion, and Openness to experience Five-factor Inventory and the Medication Adherence Report Scale. Data were statistically analysed using descriptive statistics, t-tests, bivariate correlations, multiple and logistic regressions. Non-adherence was estimated to be 9.4%. The most common reasons for stopping therapy prematurely was that the respondent was now healthy and that the respondents experienced side-effects. Non-adherent respondents scored lower on the personality traits Agreeableness and Conscientiousness. A logistic regression showed that higher scores on Agreeableness decreased the risk for non-adherence to antibiotic therapy. In a multiple regression, Neuroticism was identified as a negative predictor, and both Agreeableness and Conscientiousness were identified as positive predictors of adherence behaviour. Preventive measures to decrease non-adherence may be to inform patients not to interrupt the antibiotic therapy when they start to feel healthy and to inform them about how to prevent and handle common side-effects. As associations between personality and adherence mainly have been described in relation to long-term treatments in chronic diseases, the current study add to the literature by showing that personality traits also seem to be reflected in adherence to shorter treatment periods with antibiotics for common infections. More studies in this specific area of adherence research are recommended.
    Full-text · Article · Nov 2013 · BMC Psychology
  • Source
    • "The data were collected from September 2009 until March 2012. Patients with inflammatory bowel disease (IBD) were identified as a target population for the pre-tests as high rates of poor medication intake behavior among this patient group have been reported [22]. In the pre-tests eight nurses of six different Dutch hospitals participated. "
    [Show abstract] [Hide abstract] ABSTRACT: OBJECTIVE: To describe the development of a theoretical and evidence-based tailored multimedia intervention to improve medication intake behavior in patients with inflammatory bowel disease (IBD). The intervention integrates interpersonal and technology-mediated strategies with the expectation that this will work synergistically. METHODS: The development followed the Medical Research Council's framework. Three literature reviews and three pre-tests among 84 IBD patients and eight nurses were conducted to guide the development of the intervention. A feasibility study was carried out among four nurses and 29 patients. RESULTS: The components include: (1) an online preparatory assessment (OPA); (2) tailored interpersonal communication; and (3) tailored text messaging. To support the development, the feasibility was tested. Results indicated that the OPA was comprehensive and could be a helpful tool for both patients and nurses to prepare for the consultation. The training was evaluated as being instructive and applicable with a mean mark of 8.5. Of the developed messages, 65.6% received positive evaluations and were used in the intervention. CONCLUSION: By applying the framework, we were able to describe the logic behind the development of a tailored multimedia intervention to improve medication intake behavior. PRACTICE IMPLICATIONS: This study could serve as a guide for the development of other health interventions.
    Full-text · Article · Apr 2013 · Patient Education and Counseling
  • Source
    • "Participants were asked to complete the Medication Adherence Report Scale (MARS). The MARS has been used as a self-reported measure of adherence in a number of chronic diseases, including chronic obstructive pulmonary disease,38 asthma,39 chronic pain management in cancer,40 bipolar disorder,17 and inflammatory bowel disease.41,42 The MARS includes a preamble encouraging honest responses. "
    [Show abstract] [Hide abstract] ABSTRACT: Beliefs about medicines impact on adherence, but eliciting core beliefs about medicines in individual patients is difficult. One method that has the potential to elicit individual core beliefs is the "repertory grid technique." This study utilized the repertory grid technique to elicit individuals' beliefs about their heart failure treatment and to investigate whether generated constructs were different between adherent and nonadherent patients. Ninety-two patients with heart failure were interviewed using a structured questionnaire that applied the repertory grid technique. Patients were asked to compare and contrast their medicines and self-care activities for their heart failure. This lead to the generation of individual constructs (perceptions towards medicines), and from these, beliefs were elicited about their heart failure treatment, resulting in the generation of a repertory grid. Adherence was measured using the Medication Adherence Report Scale (MARS). Patients with a MARS score ≥ 23 were categorized as "adherent" and those with a score ≤ 22 as "nonadherent." The generated grids were analyzed descriptively and constructs from all grids themed and the frequency of these constructs compared between adherent and nonadherent patients. Individual grids provided insight into the different beliefs that patients held about their heart failure treatment. The themed constructs "related to water," "affect the heart," "related to weight," and "benefit to the heart" occurred more frequently in adherent patients compared with nonadherent patients. The repertory grid technique elicited beliefs of individual participants about the treatment of their heart failure. Constructs from self-reported adherent patients were more likely to reflect that their medicines and self-care activities were related to water and weight, and affect and benefit to the heart. Providing clinicians with better insight into individuals' beliefs about their treatment may facilitate the development of tailored interventions to improve adherence.
    Full-text · Article · Feb 2013 · Patient Preference and Adherence
Show more