ORIGINAL ARTICLE
Anti-psychotics adherence among out-patients withschizophrenia in Hong Kong
Christy LM Hui,1 Eric YH Chen,1 CS Kan,3 KC Yip,4 CW Law2 and Cindy PY Chiu2
1University of Hong Kong, 2Queen Mary Hospital, 3Castle Peak Hospital, 4Kowloon Hospital, Hong Kong
(Received for publication on September 7, 2005)(Revised for publication on December 12, 2005)(Accepted for publication on January 26, 2006)

Abstract. Objective: Adherence to antipsychotic treatment is an important aspect of long term management of schizophrenia and other related psychotic disorders. The evaluation of adherence is often
difﬁcult in clinical settings. This study compared patients self-reports and clinician judgment of adherence behavior and explored their relationship with attitudes toward taking medication. Methods: Clinician rated questionnaire and matching patient self rated questionnaires were administered to 508
consecutive outpatients and their clinicians in four hospital clinic sites in Hong Kong. Items in thequestionnaires address adherence behaviors as well as attitudes toward medication. In addition, clinicians also estimate the presence of factors unfavorable to adherence such as substance abuse, cognitive
impairments etc. Results: Non-adherence was reported in at least 26% of patients. Clinician’s detectionof non-adherence behaviors achieved relative high speciﬁcity (0.84) but has low sensitivity (0.33). A
logistic regression analysis on patients’ decision to stop medication revealed that signiﬁcant predictors
include patients’ reported lack of perception from the beneﬁts of medication, patients’ reported negative feelings associated with regular medication and younger age. Conclusion: Non-adherence is a
widespread phenomenon affecting a signiﬁcant proportion of outpatients under treatment. Clinicians
have relatively low sensitivity in detecting which patients are non-adherent. Non-adherence behavior ispredicted by level of awareness of illness, perceived beneﬁts of medication, negative feelings toward
medication and age. (Keio J Med 55 (1): 9–14, March 2006)
Key words: medication adherence, compliance, schizophrenia

has important implications over the risk of exacerbation
and relapse.
Agarwal et al. found that non-compliant patientswere generally younger, had a shorter duration of illness and had an episodic course of illness. They also
reported less side-effects, made more incorrect attributions to current positive symptoms and had a morenegative subjective view of medication.7 Coldham et al.
conﬁrmed that non-adherent patients were younger,
had an earlier age of onset and less likely to have afamily member involved in treatment. In addition, nonadherent patients demonstrated more positive symptoms, more relapses, more alcohol and cannabis use,
reduced insight, and poorer quality of life.4 Kampman
et al. found that determinants of non-complianceincluded side effects, male gender, young age, lack ofIntroduction
Medication adherence is a signiﬁcant challenge in the
management of many chronic disorders.1 For patientswith schizophrenia, although regular antipsychotic
medication is essential for symptomatic treatment andrelapse prevention,2–4 non-compliance rates for persons discharged from inpatient care are found to be atleast 50% after 1 year and 75% at 2 years.5 The problems with adherence are not conﬁned to patients withchronic illness, in ﬁrst episode schizophrenia, 39% of
patients were estimated to be non-adherent and 20%
were estimated to be inadequately adherent.4 It is generally accepted that the risk of relapse can be as muchas ﬁve times higher upon discontinuation of treatment.6
Therefore, non-adherence to antipsychotic medications

Reprint requests to: Dr. Eric YH Chen, Department of Psychiatry, The University of Hong Kong, Queen Mary Hospital, Pokfulam Road, Hong
Kong, e-mail: eyhchen@hkusua.hku.hk
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Hui CLM, et al: Medication adherence in schizophrenia

social activities, and high PANSS (Positive and Negative Syndrome Scale) total score but with a low score on
PANSS positive symptoms.8 The most common patientreported barriers were related to the stigma of taking
medications, side-effects, forgetfulness, and lack of social support.9
Effective intervention for non-adherence includes behavioral, educational and cognitive approaches.3,10–12 One of the difﬁculties related to intervention for non-adherence is the lack of information
over the optimal screening method for patients atincreased risk of non-adherence. In real life clinicalpractice, often the clinician’s judgments are relied upon
to identify patients with potential adherence problems.
Little is known, however, about the sensitivity and thespeciﬁcity of the clinicians screening evaluations.
In this study, we would like to compare clinicians’
detection of non-adherence behavior against patientsself report in a sample of outpatients with schizophrenia. In addition, we wish to explore the relationshipbetween reported non-adherence behavior and factors
such as gender, age, illness duration, and whether
atypical or conventional medication is involved as well
as non-adherence attitudes toward medication.
Methods
Participants
Patients were recruited from four outpatient clinics
in Hong Kong. They were Queen Mary Hospital(QMH), Pamela Youde Nethersole Eastern Hospital(PYNEH), Castle Peak Hospital (CPH) and Kowloon
Hospital (KH). Patients of QMH and PYNEH attended
the Early Assessment Service for Young People with
Psychotic Disorders (EASY), in which, patients weremainly younger and had shorter illness durations.
Patients in the other clinics attended the general adultpsychiatry clinics and were older and had longer illness
durations. 508 out of 590 (86%) patients approached
for the study had participated. The recruitment period
lasted for 2 months in total.
Procedure and measures
Patients must be over 18 and clinically diagnosed
with schizophrenia, schizoaffective disorder or schizophreniform disorder. After providing written informed
consent, patients were required to complete an
abridged version of the Medication Adherence Rating
Scale (MARS),13 in which, the six selected items thatpertained to the adherence of patients to medication
behaviors and attitudes (which went through satisfactory translation and back-translation procedures into
Cantonese, Cantonese version available upon request).

At the same time, their corresponding clinicians would
complete a questionnaire, and some of the items werecomparable to the MARS i.e. matching adherence behavior items that enable further comparison. The 10
items included adherence behaviors, attitudes and factors that may affect medication adherence. Other relevant information that was collected included ClinicalGlobal Impression (CGI), duration of illness and theclass of medication used (i.e. either conventional or
atypical).
Data analysis
Statistical analyses were carried out using the Statistical Package for Social Sciences (SPSS) version 12.0.
First of all, results of clinicians and patients on respective medication adherence items were reported in frequency. Then, the relationship between the clinicians’
evaluations and the patients’ perceptions was assessedby using Chi-square tests. Signiﬁcant items were thenfurther examined by comparing their sensitivity andspeciﬁcity levels. To assess the associations between
factors (gender, age, illness duration and class of medication) and the reported level of adherence, patientswere divided into groups to compare (using Chi-square
tests) their effects on different adherence factors. A binary logistic regression was carried out to explore relative contribution of relevant factors toward patients’
self-reported adherence behavior. Model chi-squareand the Hosmer and Lemeshow Goodness-of-Fit Test
were used to determine the extent to which the regression model’s estimates ﬁt the data. The Nagelkerke Rsquare was presented to indicate the overall strengthof association. A classiﬁcation table was calculated tosummarize the proportion of cases that would be correctly categorized by the model.
Results
1. Participants
A total of 508 participants (256 male and 252 female)with a mean age was 37.8 (SD ¼ 15.2) years took partin the study. The mean duration of illness was 11.1
years (SD ¼ 10.5). 61% were taking conventional antipsychotic medication and 39% were taking atypicalantipsychotic medication.
2. Descriptive results
Patients’ reported adherence behaviors and attitudes toward medication
There was 27% of patients claimed that they had
forgotten to take the medication sometimes. 19% of

Keio J Med 2006; 55 (1): 9–14

patients reported that they had decided to stop taking
the medication on their own accord. 13% of patients
admitted to taking the medication only when they werefeeling unwell. On the other hand, 39% patients felt
their situation deteriorated when they did not take their
medication. A high percentage (81%) of patients feltthat medication was beneﬁcial, however, about one
third (30%) of patients felt negative about the need totake medication regularly.

11
Table 1 The Relationship between Clinicians’ and Patients’ Perceptions on Forgetting to Take Medication
Forgetting to take medication

Clinicians’ judgments

No
Yes

Total

Patients’
self-reports
No

Yes

313
60
373

91
44
135

Total

404
104
508

Clinicians’ evaluations of adherence
Based on clinicians’ evaluation, they believed thatabout 21% of patients had forgotten to take the medication as prescribed and had stopped taking the medication of their own accord. Clinicians also believed that
24% of their patients had irregular daily routines thatmight affect adherence. Clinicians’ also consideredthat 40% of patients needed reminders from others inorder to take medication as prescribed. In addition,
about half (46%) of the patients was rated by clinicians
to be unaware of their illness. 21% of patients was
judged to have cognitive deterioration which might affect their compliance. On the other hand, clinicianssuspected only 5% of their patients to have abused alcohol or drugs. Besides, clinicians thought that 18% of
their patients felt embarrassed or upset about having totake tablets regularly. Clinicians felt that about one
third (31%) of patients, when they felt better, would
consider that medication was unnecessary and stopped
taking them.
Comparisons between patients’ and clinicians’ perceptions
Clinicians’ and patients’ ratings on behaviors werecompared with regards to two measures of adherence
behavior: (A) forgetting to take medication and (B)deciding to stop medication on their own. Patients’ self
report non-compliant behaviour were taken as a reference, providing a pragmatic proxy measure for true
non-compliant behaviour which is difﬁcult to measureobjectively on a large scale.
A. Forgetting to take medication
Concerning whether patients had forgotten to takethe medication, the contrast between patients’ selfreport and clinicians’ judgment is shown in Table 1.
The sensitivity rate is 0.33 which means that theclinicians were only able to identify one third of thepatients who themselves admitted to forgetting to taketheir medication. The speciﬁcity rate was 0.84, which
implied that in 84% patients who did not report forgetting (i.e. remember) the medication, clinicians’ did not
feel there is a problem.

Table 2 The Relationship between Clinicians’ and Patients’ Perceptions on Deciding to Stop Medication
Deciding to stop medication

Clinicians’ judgments
Total

Patients’
self-report

No
Yes

Total

No

Yes

337
74
411

66
31
97

403
105
508

B. Deciding unilaterally to stop medication
Table 2 shows the comparison between patients self
report and clinician judgment on whether there had
been a unilateral decision to stop medication by
patients.
The sensitivity of clinicians detecting patients who
stopped medication on their own was 0.32, which meansthat only 32% of patients who had stopped taking the
medication on their own were identiﬁed by their clinicians. Besides, the speciﬁcity was 0.82, that is, 82% of
patients who did not stop the medication by themselves
were considered as such by their clinicians.
3. Factors associated with the reported level of adherence
1. Gender
Gender effect could not be found between clinicians’
and patients’ ratings on factors affecting medication
adherence. In other words, there was no signiﬁcant different between male and female patients in theirreports on adherence behaviors. However, variables
affecting adherence in clinicians’ items had signiﬁcantresults. More males (30%) than females (18%) wereconsidered to have irregular routine that would affectdaily adherence (Chi-square ¼ 9.8, p ¼ 0.002). Moreover, clinicians’ considered that there were more males(8%) than females (2%) had a problem with alcohol ordrugs abuse (Chi-square ¼ 10.93, p < 0.001).
2. AgeTo examine the effects of age on adherence behaviors and attitudes, patients’ were divided into ﬁve

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Hui CLM, et al: Medication adherence in schizophrenia

patients taking atypical medication were younger(t ¼ 7.24, p < 0.001) and had shorter illness durations(t ¼ 5.71, p < 0.001), and both of these factors wereassociated with increased tendency to stop medication.
We attempted to remove this potential confound by
dividing patients into ﬁve groups according to age andcompared between patients taking atypical and conventional medication within each age group. We foundno signiﬁcant difference in the likelihood to stop medication between patients taking atypical and conventional medication. Likewise, patients were compared
between two groups according to illness duration(<5 years and >5 years). We again found no signiﬁcantdifference in the likelihood to stop medication between
patients taking atypical and conventional medication
within each group.

Fig. 1Age effects on adherence behaviors.

groups according to their age. The ﬁrst group was 15 to
25 years; the second group was 25 to 35 years; the thirdgroup was 35 to 45 years; the fourth group was 45 to 55
years and the last group was 55 years onwards. Figure 1
showed the items with signiﬁcant age effects.
Patients report of having forgotten to take the medication were most prevalent among the youngest group(41%), this trend decreased with increasing age (Chisquare ¼ 24.1, p < 0.001). Similarly, decision to stop
the medication on their own was more often found inyounger patients (Chi-square ¼ 11.74, p ¼ 0.019).
In addition, patients generally tended to believe that
medication is beneﬁcial, with older patients showing a
relatively higher rate of endorsement (Chi-square ¼
14.9, p ¼ 0.005). Likewise, younger patients tended
to feel more negative about taking regular medication(Chi-square ¼ 13.95, p ¼ 0.007).
3. Illness Duration
Patients were divided into two groups according toduration of illness using 5 years as the cutoff. Patients’
illness duration of less than 5 years was more likely tostop the medication (24% vs 15%, Chi-square ¼ 6.8,
p ¼ 0.012). This pattern was observed with different
cutoff points between 5 to 10 years. None of the othervariables were related to illness duration.
4. Type of medication
The 508 patients were then divided into two groups(conventional or atypical medication). It appeared thatpatients taking the atypical medications were more
likely to report stopping the medication as compared to
the group taking only the conventional medication(25% vs 15%; Chi-square ¼ 7.2; p ¼ 0.007). However,

5. Logistic regression results
As the dependent variable (patients reported selfinitiated decision to stop medication) is dichotomous, abinary logistic regression analysis was carried out toinvestigate relative contribution of the independent
variables. The independent variables were age, illness
duration, attitude items from the clinician and the patient rated scales that did not involve behavior, and did
not involved circularity i.e. items that were only ratable
when there had been a decision to stop medication.
The regression model has a model chi-square of
40.68 (p < 0.001). The Hosmer and Lemeshow Goodness of Fit Test has a Chi-Square of 7.1, p ¼ 0.525.
These suggested that the model’s estimates ﬁt the data
to an acceptable level. The R-square (Nagelkerke) for
the regression model was 0.124. The model correctlyclassiﬁed 97.3% of patients who did not report stopping
medication and 7.2% of patients who decided to stop
medication (overall percentage 80.1%). Patients’reported lack of medication beneﬁt, and negative feelings toward taking regular medication, and younger age
were signiﬁcant predictors of patients’ report of selfinitiated decision to stop medication, with odds ratios of
0.46, 2.9, and 0.98 respectively (Table 3).
Discussion
In this study, we compared patients’ self-report withclinician’s judgment of non-adherence. We found thatclinicians are relatively accurate in judging patients
without non-adherence problems but are less effectivein identifying patients with non-adherence problems.
Besides, the overall rate of non-adherence was around
20% in both clinicians’ estimation and patients’ reports.
This indicates that the problem may not be simply oneof under-recognition by the clinicians. Instead, the difﬁculty lies in the identiﬁcation of the individuals with
non-adherence problems.

Keio J Med 2006; 55 (1): 9–14

13

Table 3 Logistic Regression Statistics for Prediction of Clinicians and Patients’ Attitudes Toward Medication Adherence to Patients’ Decision
to Stop Taking the Medication (n ¼ 508, binary logistic regression analysis, stepwise forward)
B

Patients perceived
beneﬁt of
medication
Patient negative
feelings toward
regular medication
Age
Constant

S.E.

Wald

df

Sig.

Exp(B)

95.0% C.I. for EXP(B)
Lower

Upper

.777

.265

8.607

1

.003

.460

.274

.773

1.064

.240

19.621

1

.000

2.898

1.810

4.641

.016
.661

.008
.385

4.074
2.956

1
1

.044
.086

.984
.516

.968

1.000

It is worth noting that clinicians’ judgment in thisstudy closely resembles real life clinical situations, inwhich, in both cases clinicians have access to medical
notes and information provided by patients andinformants during interviews. Despite the ability to access information from a number of sources, clinicians’
evaluation of patients’ non-adherence is still suboptimal,
as revealed in the discrepancies between clinicians’
judgments and patients’ self-reports of non-adherence.
Therefore, our results show that it is not adequate torely solely on clinicians’ judgments in identifying
patients with potential adherence problems. The needfor more reﬁned screening assessment is in line with theprevious suggestions that screening should consist ofassessment of a wider range of factors such as knowledge and beliefs about the illness, as well as service
utilization patterns.
In this study we compared patients’ self-report withclinician judgment. It is recognized that patients’ selfreport may still represent an under-reporting of themagnitude of the problem. Though compared to interview, self-report questionnaires are less prone to suppression of undesirable responses. Therefore it offersa better approximation to the true adherence statuscompared with open interview.
We found that out-patients in Hong Kong who report non-adherence behaviors have a speciﬁc proﬁle.
We found that non-adherent patients are likely to be
younger in age. This ﬁnding is consistent with resultsfrom a number of previous studies.5,15,16 In a naturalistic sample, younger age is likely to be associated witha shorter illness duration. Indeed we also ﬁnd thatpatients with a shorter illness duration tended to havemore non-compliance behaviors, as was also observedin previous study.16 Two mechanisms may underlie thisobservation. The ﬁrst mechanism may involve patients
early in the course of their illness being more willing totake risk to ﬁnd out if they could remain well without
medication, especially before they encounter repeatedepisodes of relapses. The second mechanism relates toselection bias of an outpatient population, in which
patients with longer illness duration and is still regularin clinic attendance are more likely also to be relativecompliant with their treatment.
Patients’ negative attitude toward regular medication
is found to be a signiﬁcant factor associated with
reported non-adherence behavior. This replicates aﬁnding that has been reported in several previous
studies.16–18 Likewise, the perceived beneﬁt of medication is also related to adherence behavior, consistent
with previous ﬁndings.15–17,19
Unlike a number of other studies in Western settings,8,15 we do not ﬁnd that male patients report more
non-adherence behaviors. Flaskerud and Hu found that
substance abuse was lower for Asians than for white,black, and Latino groups.23 The overall rate of substance abuse is also estimated to be low in our sample.
The relationship between substance abuse and noncompliance may contribute to the observed excess of
non-adherence in male patients in other sites. The low
prevalence of substance abuse may partially explain thelack of gender effect in our sample.
We found that patients on atypical antipsychotic
medication reported more non-adherent behaviors.
This is contrary to our initial expectation, as atypicalanti-psychotics are generally considered to have a morefavorable adverse effect proﬁle24 and are associatedwith better adherence behavior.25,26 However, this relationship has been challenged by some studies.27 A
more important reason for the discrepancy may lies
with the selective prescribing practice in which younger
patients with shorter illness duration are more likely tobe prescribed atypical anti-psychotics medication. Sinceboth youth and short illness duration are associatedwith increased noncompliance, these factors may mediate the observed trend for patients on atypical antipsychotics to appear more non compliant. This possibility is conﬁrmed by our further analysis comparing
patients on atypical and convention anti-psychotics
within groups with similar age and illness duration.

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Hui CLM, et al: Medication adherence in schizophrenia

While this study provides unique information allowing for an assessment of clinical judgment of nonadherence compared to patients’ self-reports, there areseveral limitations. Firstly, patients’ self-reports are not
the most accurate measure for medication adherence.
Despite the advantages of using a self-administeredquestionnaire, under-reporting may still occur. Therefore, the present 20% non-adherence rate represents
the minimum level. In this study, informant information
is taken up by the clinician and contributed to the clinician’s judgment. Informant perspective might be morerichly captured by a separated questionnaire. While thesample size is substantial in this study, the range of information obtained for each individual is selective. This
enables us to identify certain relationship of interests,
but not other potentially relevant factors such as social
support and ethnicity.
This cross-section study of a large sample of outpatients in Hong Kong enabled the evaluation of sensitivity and speciﬁcity of clinical screening for nonadherence behavior. The result suggests that clinicalscreening on its own is inadequate in identifying
patients at risk of non-adherence problems. More inclusive screening instruments are required to enhancedetection of non-adherence. Assessment of patients’attitudes to medication, perceived beneﬁts of medication and insight into the illness may be included as
items closely related to adherence behavior. Screening
should be particularly vigilant for younger patients withshort illness duration. Good clinician-patient relationship, as well as speciﬁc intervention models may facilitate the detection and modiﬁcation of non-adherence inpatients.
Acknowledgement: We acknowledge partial support for this study
from an unrestricted education grant from Janssen Pharmaceuticals.

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