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Validation of Chinese version of the Morisky Medication Adherence Scale in patients with epilepsy
Seizure 23 (2014) 295–299
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Validation of Chinese version of the Morisky Medication Adherence Scale in patients with epilepsy Aifang Yang a,1, Bin Wang a,*, Guoxing Zhu b, Zheng Jiao a, Youxin Fang b, Fengmin Tang a, Chunlai Ma a, Yue Zhao a, Cai Cheng a, Mingkang Zhong a a b
Department of Pharmacy, HuaShan Hospital, Fudan University, Shanghai, China Department of Neurology, HuaShan Hospital, Fudan University, Shanghai, China
A R T I C L E I N F O
A B S T R A C T
Article history: Received 18 October 2013 Received in revised form 26 December 2013 Accepted 3 January 2014
Purpose: This study aimed to validate a Chinese version of the Morisky Medication Adherence Scale (MMAS-8) in patients with epilepsy. The relationships between adherence, seizure frequency, and adverse effects were assessed using this method. Methods: Data from patients diagnosed with epilepsy at the Department of Neurology of Huashan Hospital were collected between January and June 2013. To validate the MMAS-8, internal consistency, test–retest reliability, and factor analysis were calculated. Relationships between adherence, seizure frequency, and adverse effects were assessed using Pearson’s correlation. Results: One hundred and eleven patients were recruited. The MMAS-8 had moderate internal consistency (Cronbach’s a = 0.556) and good test–retest reliability (intraclass correlation coefficient = 0.729). The MMAS-8 adherence rate was 79.2%. MMAS-8 adherence was negatively correlated with seizure frequency and adverse effects (r = –0.708, p < 0.001; r = –0.484, p < 0.001). Conclusion: The MMAS-8 scale can be used as a tool to assess medication adherence in Chinese patients with epilepsy. Better seizure control and lower rates of adverse effects were significantly correlated with higher adherence scores. ß 2014 British Epilepsy Association. Published by Elsevier Ltd. All rights reserved.
Keywords: Adherence Validation Epilepsy Scale
1. Introduction Epilepsy is a common neurological problem affecting approximately 65 million people globally.1 In China, the lifetime prevalence of epilepsy is approximately nine million people (7 per 1000), whereas currently six million people (4.6 per 1000) have active epilepsy.2 Antiepileptic drug (AED) regimens can dramatically control seizure occurrence and improve the prognosis for patients with epilepsy. However, it can be difficult to achieve ideal efficacy in practice. One main reason for this is the non-adherence to AED regimens. Cramer and colleagues have defined adherence to ‘‘the extent to which a patient acts in accordance with the prescribed interval and dose of a dosing regimen.’’3 Non-adherence to AEDs is common, with an average range from 30% to 60% and dose omission of approximately 70%.4,5 Non-adherence to AEDs, co-medications, seizure type, and factors such as gender and
* Corresponding author. Department of Pharmacy, HuaShan Hospital, Fudan University, No. 12 Middle Wu Lu Mu Qi Road, Shanghai 200040, China, Tel.: +86 13916606721; fax: +86 21 52888379. E-mail addresses: [email protected] (A. Yang), [email protected], [email protected] (B. Wang). 1 Tel.: +86 15921765601.
co-morbidity6,7 may influence seizure risk. Furthermore, nonadherence to AEDs may be associated with more serious outcomes (increased hospitalization, inpatient days, and emergency department visits) and increases in the cost of treatment.8,9 Thus, it is important to assess medication adherence and discuss it with patients when treatment appears to fail.10 Despite the lack of a gold standard for measuring adherence to medication, both direct and indirect measures are currently used in clinical practice. Direct methods, the most common measures of adherence, involve monitoring metabolite concentration through body fluid (plasma and saliva) and therapeutic drug monitoring. However, in clinical settings, it is often unreliable to measure adherence through plasma concentration because a number of factors can influence the results such as drug interaction and physiological changes.11 In addition, assessing plasma concentration is expensive and time intensive. Thus, health care researchers have begun developing indirect instruments (pill counts, medication event monitoring systems [MEMS], and self-reporting),12,13 which are non-invasive. Each of these has different advantages and disadvantages.14 One self-reported questionnaire, the 8-item Morisky Medication Adherence Scale (MMAS-8),15 is used to assess adherence in outpatients with chronic disease. It is widely used because it is free to administer, simple, and has a good relationships with other measures of adherence.16 Because some studies have
1059-1311/$ – see front matter ß 2014 British Epilepsy Association. Published by Elsevier Ltd. All rights reserved. http://dx.doi.org/10.1016/j.seizure.2014.01.003
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been conducted in Chinese populations17,18 and the scale has not been validated in China, we were interested in translating the scale and validating some of its psychometric properties in Chinese patients with epilepsy. The utility of this scale in different languages aids international studies,19 and it can meet the requirements of non-English speaking people in China. In addition, three main factors were revealed to be associated with medication adherence: patient-related factors (e.g., beliefs about AEDs),20 illness-related factors (e.g., seizure frequency),10,21 and medication-related factors (e.g., adverse effects).22 Currently, studies have focused on assessing the relationship between adherence and seizure frequency, suggesting patients experience a lower seizure frequency when they are more adherent to their AEDs.10,21 It is also important for health care providers to not only understand how adherence is associated with seizure frequency, but also potential factors related to adherence, such as adverse effects. There have been a few studies conducted, and they found that adherence is related to adverse effects.23 Because of the lack of relevant research among Chinese patients with epilepsy, an investigation of the relationships between adherence, seizure frequency, and side effects is needed. Therefore, the two main objectives in this study were: (a) to validate a Chinese version of the MMAS-8 in patients with epilepsy and (b) to evaluate the relationships between adherence, seizure frequency, and adverse effects. In addition, the study hypothesized MMAS-8 is moderately reliable in Chinese patients with epilepsy, and adherence is negatively correlated with seizure frequency and adverse effects. There have been: (a) studies validating MMAS-8 with moderate psychometric properties in patients with hypertension,24 diabetes mellitus,25,26 osteoporosis,27 and those taking warfarin28 and (b) two studies revealed that the relationship between adherence and seizure frequency was negative.10,21 2. Methods 2.1. Study Design This was a prospective, cross-sectional study. It was approved by the Ethics Committee of Huashan Hospital (2013-006) before data collection. Outpatients with epilepsy were recruited from January to June 2013. To be eligible for participation, patients had to: (a) be patients with epilepsy, (b) have been taking AEDs for at least 3 months, and (c) provide written informed consent. Patients with epilepsy were asked to complete a self-designed questionnaire that contained three parts: history information form (socio-demographic, age, education background, etc.; clinical: etiology, age of onset of epilepsy, seizure frequency, etc.; and medication data), the MMAS-8 scale, and the Liverpool Adverse Event Profile (LAEP). In addition, to assess the test-retest reliability of the MMAS-8 scale, a random sample of 10% of the patients with epilepsy was asked to complete the scale again 2-4 weeks later. Finally, the relationships between adherence, seizure frequency, and adverse effects were accessed by statistical methods.
Responses of ‘‘never,’’ ‘‘once in a while,’’ ‘‘sometimes,’’ ‘‘usually,’’ and ‘‘all the time’’ were scored 1, 0.75, 0.50, 0.25, and 0, respectively, whereas for item were scored ‘‘1’’ for ‘‘never’’ and ‘‘0’’ for other responses. The total scores ranged from 0 to 8. Scores of 8, 6-8, and < 6 indicate high, medium, and low adherence, respectively. Patients with scores of 8 and 6-8 were considered adherent, and a score < 6 was considered as non-adherent in our study. 2.2.2. LAEP The adverse effects to AEDs were assessed using the Chinese version of the LAEP.29 The LAEP is a validated 22-item questionnaire consisting of two factors: central nervous system (CNS) doserelated (unsteadiness, tiredness, headache, double/blurred vision, difficulty in concentration, shaky hands, dizziness, sleepiness, memory problems and disturbed sleep), non-CNS dose-related and psychiatric adverse effects (restlessness, feelings of aggression, nervousness/agitation, hair loss, skin problems, upset stomach, trouble with mouth, trouble with gums, weight gain, weight loss, depression, and paresthesia).29 All items were scored using a fourpoint Likert scale in which 1 = never, 2 = rarely, 3 = sometimes, and 4 = always. The scores for the LAEP range from 22 to 88, with higher scores indicating greater adverse effects in these patients. Based on a prior study,29 the mean score is 34.77 on the LEAP for Chinese patients, and thus, patients with a score > 34.77 were considered to be suffering severe adverse effects. 2.2.3. Seizure Frequency The seizure frequency during the preceding month was selfreported. 2.3. Statistical Analysis Internal consistency reliability was assessed by calculating the Cronbach’s a coefficient. A Cronbach’s a 0.5 is considered acceptable.26 To assess test-retest reliability, a random sample of 10% of the patients with epilepsy was readministered the MMAS8 after 2–4 weeks. Based on the results, we calculated an intraclass correlation coefficient (ICC). An ICC over 0.60 indicates good test-retest reliability.30 Finally, factor analysis was conducted to assess construct validity when the p value of Bartlett’s test of sphericity was less than 0.001 and the value of KaiserMeyer-Olkin measure of sampling adequacy (KMO) was more than 0.5.31 Eigenvalues > 1 were used to assess the number of factors, and items with loading on each 0.4 were viewed as the corresponding factors.32 The relationships between MMAS-8 scores and continuous variables were calculated using Pearson’s correlation, and associations with MMAS-8 scores and categorical variables were examined by univariate analysis. The significance threshold was set as 0.05. Statistical analysis was conducted by SPSS 16.0 for Windows. 3. Results
2.2. Measures 3.1. Patient and Clinical Data 2.2.1. MMAS-8 First, the scale was translated into Chinese by the author (see Appendix A). To ensure consistency between the original and translated versions, an expert clinician and an experienced clinical pharmacist translated the initial translation back to English to ensure that the content was the same (see Appendix B). The scale is composed of eight items.15 Seven items (item 1 to item 7) are yes/ no questions, in which a ‘‘no’’ answer received a score of 1, and a ‘‘yes’’ answer received a score of 0, except for item 5, which was reverse scored. Item 8 is measured on a five-point Likert scale.
A total of 111 patients with epilepsy were recruited for our study (56 women and 55 men). The patients’ mean age (SD) was 32.9 (14.9) years. Approximately 91.9% were educated above the elementary school (36.9% middle school, 21.6% high school, 32.4% university, 0.9% Masters degree). The mean time (SD) since the first seizure was 22.3 (17.0) years. Around half of the patients (47.7%) reported that they had less than one seizure in the previous month. One type of AED (55.9%) was administered by patients, followed by two types of AEDs (36.0%) and three types of AEDs (7.2%). The mean
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LAEP score was 30.45, and 24 (21.6%) of patient scores were higher than 34.77, indicating patients more severe adverse effects than those whose LAEP score were less than or equal to 34.77. All the main socio-demographic and clinical characteristics are summarized in Table 1. 3.2. MMAS-8 Adherence Measures The mean MMAS-8 score was 6.64. The distribution of each item is shown in Fig. 1. Of the total 111 patients, 32.4% (36) had high adherence, 46.8% (52) had medium adherence, and 20.7% (23) had low adherence. In total, 79.2% of the patients displayed some adherence to their medication, and 20.7% patients did not display much adherence. Significant differences were not noted between MMAS-8 scores and age (p = 0.209), time from first seizure (p = 0.394), duration of seizure (p = 0.680), educational level (p = 0.566), gender (p = 0.098), type of seizure (p = 0.089), and number of AEDs (p = 0.769). 3.3. Internal Consistency Reliability The internal consistent reliability (Cronbach’s a) of the MMAS8 Chinese version was 0.556, indicating moderate reliability. Cronbach’s a was slightly higher (0.649) when item 4 was deleted.
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3.4. Test-Retest Reliability A total of 11 patients were asked to recomplete the scale 2-4 weeks later. The mean score of adherence was 7.41. A total of 9.1% (1 of 11), 27.3% (3 of 11), and 63.6% (7 of 11) patients reported low, medium, and high adherence, respectively. According to our criterion, 90.9% (10 of 11) of patients were considered as adherent, and 9.1% (1 of 11) of patients were viewed as non-adherent. The ICC of the Chinese MMAS-8 was 0.729, indicating good reproducibility. 3.5. Construct Validity Bartlett’s test of sphericity (p < 0.001) and the Kaiser-MeyerOlkin (p = 0.694) test were performed, which indicated that the Chinese MMAS-8 was suitable for factor analysis. Three factors (eigenvalue > 1) were extracted in our study, explaining a total variance of 58.2%. The factor loadings for each item are illustrated in Table 2. Factor 1 had an eigenvalue of 2.440, accounted for 30.495% of the variance and comprised items 1, 2, 3, 6, 7, and 8. Factor 2 had an eigenvalue of 1.139, explained 14.239% of the variance and comprised items 3 and 6. Factor 3 had an eigenvalue of 1.074, explained 13.421% of the variance and comprised items 5 and 6. 3.6. Relationship between Adherence, Seizure Frequency, and Adverse Effects
Table 1 Socio-demographic and clinical characteristics (N = 111). Variables
Number
Association with MMAS-8 scores (p value)
Age (Mean, SD) Gender (N, %) Male Female Education level (N, %) No primary studies Primary studies Secondary studies Senior high studies University studies Master studies Seizure type (N, %) SPS CPS SGTC SGTC + CPS GTCS Time from first seizure in years (mean, SD) Time from seizure in years (mean, SD) Number of AEDs (N, %) One AED Two AEDs Three AEDs Four AEDs Seizure frequencyy (N, %) 0 >1 LAEP scores z(N, %) >34.77 34.77
32 .9 (14.9)
0.209 0.098
55 (49.5%) 56 (50.5%) 0.566 2 (1.8%) 7 (6.3%) 41 (36.9%) 24 (21.6%) 36 (32.4%) 1 (0.9%) 5 (4.5%) 14 (12.6%) 13 (11.7%) 46 (41.4%) 33 (29.7%) 22.3 (17.0)
0.089
0.394 0.680 0.769
10.6 (10.0) 0.001* 62 (55.9%) 40 (36.0%) 8 (7.2%) 1 (0.9%)
0.001*
53 (47.7%) 58 (52.3%) 24 (21.6%) 87 (78.4%)
SPS, simple partial seizure; CPS, complex partial seizure; SGTC, secondarily generalized tonic-clonic seizure; GTCS, generalized tonic-clonic seizure; AEDs, antiepileptic drugs; SD, standard deviation; MMAS, Morisky Medication Adherence Scale; LAEP, Liverpool Adverse Events Profile. y Seizure frequency during the preceding month. z The mean scores were 34.77 in LAEP for Chinese patients in a prior study, and those patients with a score >34.77 were considered to have suffered more severe adverse effects than patients with a score 34.77. * p < 0.001.
There was a significant correlation found between adherence and seizure frequency (r = 0.708, p < 0.001), adherence and adverse effects (r = 0.484, p < 0.001). Also, adherence was associated with CNS (r = 0.453, p < 0.001) and non-CNS (r = 0.362, p < 0.001) factors. To take into account the influence of adverse effects, we assessed the relationship between adherence and seizure frequency, using partial analysis. Adherence was also significantly associated with seizure frequency (r = 0.166, p < 0.001) after controlling for the influence of adverse effects. 4. Discussion The main objective of our study was to validate the MMAS-8 in epilepsy patients in China. To the best of our knowledge, this is also the first study to validate this scale in Chinese patients. Several validation studies focused on different languages for this scale have been conducted.24–28 Korb-Savoldelli et al.24 validated the French version of this scale in patients with hypertension, and the Cronbach’s a was 0.54. Lee et al.25 and Harith et al.26 validated the version Korean and Malaysian version in patients with type 2 diabetes, and the Cronbach’s a scores were 0.66 and 0.675, respectively. Wang et al.28 validated the Singaporean version in patients who taken warfarin, with a Cronbach’s a of 0.56. These previous studies validating the MMAS-8 indicate this scale was moderately reliable, and similar results were found in our study: moderate reliability (Cronbach’s a = 0.556) and good test-retest reliability (ICC = 0.729). These results might be explained by: (a) the small number of participants involved into our study, as the number size would influence the internal consistency 33 and (b) this scale is composed of seven yes/no questions and one five-point Likert scale, and yes/no questions can lower the value of Cronbach’s a because of higher measurement error.34 Even though a Cronbach’s a 0.8 is recommended, a Cronbach’s a 0.5 is considered acceptable according to Bowling and Robinson et al.35,36 The Cronbach’s a for the Chinese MMAS-8 was 0.556, which was viewed as acceptable. Accordingly, this indicates the Chinese MMAS-8 has potential as a tool to help in assessing medication adherence in epileptic patients.
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Fig. 1. Distribution of each item of Morisky Medication Adherence Scale.
As for the distribution of MMAS-8 adherence across the participants, 32.4%, 46.8%, and 20.7% displayed high, medium, and low adherence, respectively, with 79.2% displaying some adherence, and 20.7% displayed no adherence. These results are consistent with those of a previous study that used the four-item MMAS, which reported a total adherence of approximately 74.8% (high adherence and medium adherence) in Chinese patients with epilepsy.22 Similarly, Avani et al. reported a total adherence of approximately 79.4% in patients with new-onset epilepsy, using MEMS TrackCap which is viewed as a more accurate measure than others.37 In this context, the Chinese version of the MMAS-8 can be used as a tool to evaluate medication adherence, as well as to capture the non-adherence among Chinese patients with epilepsy. This is the first study in China to assess the relationships between adherence, seizure frequency, and adverse effects using the MMAS-8. As we expected, the findings of our study, including the negative relation between adherence and seizure frequency and adherence and adverse effects, resulting in lower seizure frequency and adverse effects, were associated with higher adherence. Similar results regarding the relationship between adherence and seizure frequency were found by Jones et al. and Collin et al.10,21 Collin and his colleagues demonstrated that nonadherence was associated with reduced seizure control.21 Another study in the UK demonstrated a negative correlation between adherence and seizure frequency even though there was no significant difference.10 With respect to the relationship between adherence and adverse effects, the results in our study are not consistent with another published study which demonstrated that a significant difference was not found among patients with different levels of adherence.23 The discrepancy might be explained by the fact that a different scale was used for assessing adverse effects. Compared with the scale only containing five items
Table 2 Factorial loading on the eight-item Morisky Medication Adherence Scale. Factor
Item 1 Item 2 Item 3 Item 4 Item 5 Item 6 Item 7 Item 8 Eigenvalue Explained variance (58.2%) *
Indicates items loading 0.4.
1
2
3
0.685* 0.678* 0.629* 0.258 0.031 0.552* 0.604* 0.614* 2.440 30.495%
0.352 0.353 0.474* 0.396 0.535 0.471* 0.017 0.032 1.139 14.239%
0.213 0.069 0.331 0.249 0.615* 0.483* 0.309 0.382 1.074 13.421%
used by Sweileh et al.,23 the LAEP scale we used contains 22 items and covers both systemic and neurological problems.38 In addition, the validity and reliability of this scale has been assessed in Chinese patients with epilepsy. These results indicate that assessing adherence with the Morisky scale may be able to predict the seizure frequency and side effects in clinical settings, which, consequently, would result in better management of epilepsy in China. Despite the important implications of our findings, our study has several limitations. (a) This was a cross-sectional study rather than a randomized clinical trial. Thus, it can only illustrate the adherence rate for a certain period of time, which is problematic because adherence rates have been demonstrated to change with time.37,39,40 (b) Patients with epilepsy experience some physical disorders similar to adverse effects, making it difficult to distinguish whether the cause of the symptoms is either the drug or seizures. To avoid this bias, we reminded the patients that the questionnaire items were mainly evaluating drug behavior and not seizures. (c) The accuracy of the self-reported seizure frequency is a concern because the frequency was likely under-reported because of a lack of cognition of the clinical manifestation or the lack of a witness at the time the seizure occurred.41 Even though EEG monitoring is a vital tool to capture seizure occurrence, continuous EEG monitoring is impractical for outpatients. As a result, many studies use self-reporting.20,21 In our study, the seizure frequency was mostly extracted from self-reported diaries, and these data may be subject to incorrect reporting.
5. Conclusion The Chinese version of the MMAS-8 is a simple, free to administer, and convenient measurement of medication adherence in patients with epilepsy. In addition, it was demonstrated to have acceptable reliability and validity. Using this scale, the relationships between adherence, seizure frequency, and adverse effects were revealed in our study. Our results indicate that better seizure control and lower adverse effects were significantly correlated with higher adherence scores. As we mentioned earlier, almost all validated MMAS-8 versions in different languages have displayed moderate reliability. Therefore, further studies are needed to investigate the reliability and validity of this scale in different clinical settings and different populations. Acknowledgements This study was supported by the Department of Neurology of Huashan Hospital. The authors would like to thank Prof. Zhu
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(Gouxing Zhu) and his student Youxin Fang for assistance in recruitment. Appendix A. Supplementary data Supplementary data associated with this article can be found, in the online version, at http://dx.doi.org/10.1016/j.seizure.2014. 01.003. References 1. Thurman DJ, Beghi E, Begley CE, Berg AT, Buchhalter JR, Ding D, et al. Standards for epidemiologic studies and surveillance of epilepsy. Epilepsia 2011;52:2–26. 2. Wang WZ, Wu JZ, Wang DS, Dai XY, Yang B, Wang TP, et al. The prevalence and treatment gap in epilepsy in China: an ILAE/IBE/WHO study. Neurology 2003; 60:1544–5. 3. Cramer JA, Roy A, Burrell A, Fairchild CJ, Fuldeore MJ, Ollendorf DA, et al. Medication compliance and persistence: terminology and definitions. Value Health 2008;11:44–7. 4. Ettinger AB, Manjunath R, Candrilli SD, Davis KL. Prevalence and cost of nonadherence to antiepileptic drugs in elderly patients with epilepsy. Epilepsy & Behavior 2009;14:324–9. 5. Cramer JA, Glassman M, Rienzi V. The relationship between poor medication compliance and seizures. Epilepsy & Behavior 2002;3:338–42. 6. Manjunath R, Davis KL, Candrilli SD, Ettinger AB. Association of antiepileptic drug nonadherence with risk of seizures in adults with epilepsy. Epilepsy & Behavior 2009;14:372–8. 7. Modi AC, Guilfoyle SM, Rausch J. Preliminary feasibility, acceptability, and efficacy of an innovative adherence intervention for children with newly diagnosed epilepsy. Journal of Pediatric Psychology 2013;38:605–16. 8. Faught RE, Weiner JR, Guerin A, Cunnington MC, Duh MS. Impact of nonadherence to antiepileptic drugs on health care utilization and costs: findings from the RANSOM study. Epilepsia 2009;50:501–9. 9. Davis KL, Candrilli SD, Edin HM. Prevalence and cost of nonadherence with antiepileptic drugs in an adult managed care population. Epilepsia 2008;49: 446–54. 10. Jones RM, Butler JA, Thomas VA, Peveler RC, Prevett M. Adherence to treatment in patients with epilepsy: associations with seizure control and illness beliefs. Seizure 2006;15:504–8. 11. Johannessen SI, Landmark CJ. Value of therapeutic drug monitoring in epilepsy. Expert Review of Neurotherapeutics 2008;8:929–39. 12. Rosen MI, Rigsby MO, Salahi JT, Ryan CE, Cramer JA. Electronic monitoring and counseling to improve medication adherence. Behaviour Research and Therapy 2004;42:409–22. 13. Modi AC, Zeller MH, Xanthakos SA, Jenkins TM, Inge TH. Adherence to vitamin supplementation following adolescent bariatric surgery. Obesity (Silver Spring) 2013;21:E190–5. 14. Vermeire E, Hearnshaw H, Van Royen P, Denekens J. Patient adherence to treatment: three decades of research. A comprehensive review. Journal of Clinical Pharmacy and Therapeutics 2001;26:331–42. 15. Morisky DE, Ang A, Krousel-Wood M, Ward HJ. Predictive validity of a medication adherence measure in an outpatient setting. Journal of Clinical Hypertension (Greenwich) 2008;10:348–54. 16. Garber MC, Nau DP, Erickson SR, Aikens JE, Lawrence JB. The concordance of self-report with other measures of medication adherence: a summary of the literature. Medical Care 2004;42:649–52. 17. Lee VW, Pang KK, Hui KC, Kwok JC, Leung SL, Yu DS, et al. Medication adherence: is it a hidden drug-related problem in hidden elderly? Geriatrics & Gerontology International 2013;13:978–85. 18. Lee GK, Wang HH, Liu KQ, Cheung Y, Morisky DE, Wong MC. Determinants of medication adherence to antihypertensive medications among a Chinese population using Morisky Medication Adherence Scale. PLoS One 2013;8:e62775.
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Seizure journal homepage: www.elsevier.com/locate/yseiz
Validation of Chinese version of the Morisky Medication Adherence Scale in patients with epilepsy Aifang Yang a,1, Bin Wang a,*, Guoxing Zhu b, Zheng Jiao a, Youxin Fang b, Fengmin Tang a, Chunlai Ma a, Yue Zhao a, Cai Cheng a, Mingkang Zhong a a b
Department of Pharmacy, HuaShan Hospital, Fudan University, Shanghai, China Department of Neurology, HuaShan Hospital, Fudan University, Shanghai, China
A R T I C L E I N F O
A B S T R A C T
Article history: Received 18 October 2013 Received in revised form 26 December 2013 Accepted 3 January 2014
Purpose: This study aimed to validate a Chinese version of the Morisky Medication Adherence Scale (MMAS-8) in patients with epilepsy. The relationships between adherence, seizure frequency, and adverse effects were assessed using this method. Methods: Data from patients diagnosed with epilepsy at the Department of Neurology of Huashan Hospital were collected between January and June 2013. To validate the MMAS-8, internal consistency, test–retest reliability, and factor analysis were calculated. Relationships between adherence, seizure frequency, and adverse effects were assessed using Pearson’s correlation. Results: One hundred and eleven patients were recruited. The MMAS-8 had moderate internal consistency (Cronbach’s a = 0.556) and good test–retest reliability (intraclass correlation coefficient = 0.729). The MMAS-8 adherence rate was 79.2%. MMAS-8 adherence was negatively correlated with seizure frequency and adverse effects (r = –0.708, p < 0.001; r = –0.484, p < 0.001). Conclusion: The MMAS-8 scale can be used as a tool to assess medication adherence in Chinese patients with epilepsy. Better seizure control and lower rates of adverse effects were significantly correlated with higher adherence scores. ß 2014 British Epilepsy Association. Published by Elsevier Ltd. All rights reserved.
Keywords: Adherence Validation Epilepsy Scale
1. Introduction Epilepsy is a common neurological problem affecting approximately 65 million people globally.1 In China, the lifetime prevalence of epilepsy is approximately nine million people (7 per 1000), whereas currently six million people (4.6 per 1000) have active epilepsy.2 Antiepileptic drug (AED) regimens can dramatically control seizure occurrence and improve the prognosis for patients with epilepsy. However, it can be difficult to achieve ideal efficacy in practice. One main reason for this is the non-adherence to AED regimens. Cramer and colleagues have defined adherence to ‘‘the extent to which a patient acts in accordance with the prescribed interval and dose of a dosing regimen.’’3 Non-adherence to AEDs is common, with an average range from 30% to 60% and dose omission of approximately 70%.4,5 Non-adherence to AEDs, co-medications, seizure type, and factors such as gender and
* Corresponding author. Department of Pharmacy, HuaShan Hospital, Fudan University, No. 12 Middle Wu Lu Mu Qi Road, Shanghai 200040, China, Tel.: +86 13916606721; fax: +86 21 52888379. E-mail addresses: [email protected] (A. Yang), [email protected], [email protected] (B. Wang). 1 Tel.: +86 15921765601.
co-morbidity6,7 may influence seizure risk. Furthermore, nonadherence to AEDs may be associated with more serious outcomes (increased hospitalization, inpatient days, and emergency department visits) and increases in the cost of treatment.8,9 Thus, it is important to assess medication adherence and discuss it with patients when treatment appears to fail.10 Despite the lack of a gold standard for measuring adherence to medication, both direct and indirect measures are currently used in clinical practice. Direct methods, the most common measures of adherence, involve monitoring metabolite concentration through body fluid (plasma and saliva) and therapeutic drug monitoring. However, in clinical settings, it is often unreliable to measure adherence through plasma concentration because a number of factors can influence the results such as drug interaction and physiological changes.11 In addition, assessing plasma concentration is expensive and time intensive. Thus, health care researchers have begun developing indirect instruments (pill counts, medication event monitoring systems [MEMS], and self-reporting),12,13 which are non-invasive. Each of these has different advantages and disadvantages.14 One self-reported questionnaire, the 8-item Morisky Medication Adherence Scale (MMAS-8),15 is used to assess adherence in outpatients with chronic disease. It is widely used because it is free to administer, simple, and has a good relationships with other measures of adherence.16 Because some studies have
1059-1311/$ – see front matter ß 2014 British Epilepsy Association. Published by Elsevier Ltd. All rights reserved. http://dx.doi.org/10.1016/j.seizure.2014.01.003
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been conducted in Chinese populations17,18 and the scale has not been validated in China, we were interested in translating the scale and validating some of its psychometric properties in Chinese patients with epilepsy. The utility of this scale in different languages aids international studies,19 and it can meet the requirements of non-English speaking people in China. In addition, three main factors were revealed to be associated with medication adherence: patient-related factors (e.g., beliefs about AEDs),20 illness-related factors (e.g., seizure frequency),10,21 and medication-related factors (e.g., adverse effects).22 Currently, studies have focused on assessing the relationship between adherence and seizure frequency, suggesting patients experience a lower seizure frequency when they are more adherent to their AEDs.10,21 It is also important for health care providers to not only understand how adherence is associated with seizure frequency, but also potential factors related to adherence, such as adverse effects. There have been a few studies conducted, and they found that adherence is related to adverse effects.23 Because of the lack of relevant research among Chinese patients with epilepsy, an investigation of the relationships between adherence, seizure frequency, and side effects is needed. Therefore, the two main objectives in this study were: (a) to validate a Chinese version of the MMAS-8 in patients with epilepsy and (b) to evaluate the relationships between adherence, seizure frequency, and adverse effects. In addition, the study hypothesized MMAS-8 is moderately reliable in Chinese patients with epilepsy, and adherence is negatively correlated with seizure frequency and adverse effects. There have been: (a) studies validating MMAS-8 with moderate psychometric properties in patients with hypertension,24 diabetes mellitus,25,26 osteoporosis,27 and those taking warfarin28 and (b) two studies revealed that the relationship between adherence and seizure frequency was negative.10,21 2. Methods 2.1. Study Design This was a prospective, cross-sectional study. It was approved by the Ethics Committee of Huashan Hospital (2013-006) before data collection. Outpatients with epilepsy were recruited from January to June 2013. To be eligible for participation, patients had to: (a) be patients with epilepsy, (b) have been taking AEDs for at least 3 months, and (c) provide written informed consent. Patients with epilepsy were asked to complete a self-designed questionnaire that contained three parts: history information form (socio-demographic, age, education background, etc.; clinical: etiology, age of onset of epilepsy, seizure frequency, etc.; and medication data), the MMAS-8 scale, and the Liverpool Adverse Event Profile (LAEP). In addition, to assess the test-retest reliability of the MMAS-8 scale, a random sample of 10% of the patients with epilepsy was asked to complete the scale again 2-4 weeks later. Finally, the relationships between adherence, seizure frequency, and adverse effects were accessed by statistical methods.
Responses of ‘‘never,’’ ‘‘once in a while,’’ ‘‘sometimes,’’ ‘‘usually,’’ and ‘‘all the time’’ were scored 1, 0.75, 0.50, 0.25, and 0, respectively, whereas for item were scored ‘‘1’’ for ‘‘never’’ and ‘‘0’’ for other responses. The total scores ranged from 0 to 8. Scores of 8, 6-8, and < 6 indicate high, medium, and low adherence, respectively. Patients with scores of 8 and 6-8 were considered adherent, and a score < 6 was considered as non-adherent in our study. 2.2.2. LAEP The adverse effects to AEDs were assessed using the Chinese version of the LAEP.29 The LAEP is a validated 22-item questionnaire consisting of two factors: central nervous system (CNS) doserelated (unsteadiness, tiredness, headache, double/blurred vision, difficulty in concentration, shaky hands, dizziness, sleepiness, memory problems and disturbed sleep), non-CNS dose-related and psychiatric adverse effects (restlessness, feelings of aggression, nervousness/agitation, hair loss, skin problems, upset stomach, trouble with mouth, trouble with gums, weight gain, weight loss, depression, and paresthesia).29 All items were scored using a fourpoint Likert scale in which 1 = never, 2 = rarely, 3 = sometimes, and 4 = always. The scores for the LAEP range from 22 to 88, with higher scores indicating greater adverse effects in these patients. Based on a prior study,29 the mean score is 34.77 on the LEAP for Chinese patients, and thus, patients with a score > 34.77 were considered to be suffering severe adverse effects. 2.2.3. Seizure Frequency The seizure frequency during the preceding month was selfreported. 2.3. Statistical Analysis Internal consistency reliability was assessed by calculating the Cronbach’s a coefficient. A Cronbach’s a 0.5 is considered acceptable.26 To assess test-retest reliability, a random sample of 10% of the patients with epilepsy was readministered the MMAS8 after 2–4 weeks. Based on the results, we calculated an intraclass correlation coefficient (ICC). An ICC over 0.60 indicates good test-retest reliability.30 Finally, factor analysis was conducted to assess construct validity when the p value of Bartlett’s test of sphericity was less than 0.001 and the value of KaiserMeyer-Olkin measure of sampling adequacy (KMO) was more than 0.5.31 Eigenvalues > 1 were used to assess the number of factors, and items with loading on each 0.4 were viewed as the corresponding factors.32 The relationships between MMAS-8 scores and continuous variables were calculated using Pearson’s correlation, and associations with MMAS-8 scores and categorical variables were examined by univariate analysis. The significance threshold was set as 0.05. Statistical analysis was conducted by SPSS 16.0 for Windows. 3. Results
2.2. Measures 3.1. Patient and Clinical Data 2.2.1. MMAS-8 First, the scale was translated into Chinese by the author (see Appendix A). To ensure consistency between the original and translated versions, an expert clinician and an experienced clinical pharmacist translated the initial translation back to English to ensure that the content was the same (see Appendix B). The scale is composed of eight items.15 Seven items (item 1 to item 7) are yes/ no questions, in which a ‘‘no’’ answer received a score of 1, and a ‘‘yes’’ answer received a score of 0, except for item 5, which was reverse scored. Item 8 is measured on a five-point Likert scale.
A total of 111 patients with epilepsy were recruited for our study (56 women and 55 men). The patients’ mean age (SD) was 32.9 (14.9) years. Approximately 91.9% were educated above the elementary school (36.9% middle school, 21.6% high school, 32.4% university, 0.9% Masters degree). The mean time (SD) since the first seizure was 22.3 (17.0) years. Around half of the patients (47.7%) reported that they had less than one seizure in the previous month. One type of AED (55.9%) was administered by patients, followed by two types of AEDs (36.0%) and three types of AEDs (7.2%). The mean
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LAEP score was 30.45, and 24 (21.6%) of patient scores were higher than 34.77, indicating patients more severe adverse effects than those whose LAEP score were less than or equal to 34.77. All the main socio-demographic and clinical characteristics are summarized in Table 1. 3.2. MMAS-8 Adherence Measures The mean MMAS-8 score was 6.64. The distribution of each item is shown in Fig. 1. Of the total 111 patients, 32.4% (36) had high adherence, 46.8% (52) had medium adherence, and 20.7% (23) had low adherence. In total, 79.2% of the patients displayed some adherence to their medication, and 20.7% patients did not display much adherence. Significant differences were not noted between MMAS-8 scores and age (p = 0.209), time from first seizure (p = 0.394), duration of seizure (p = 0.680), educational level (p = 0.566), gender (p = 0.098), type of seizure (p = 0.089), and number of AEDs (p = 0.769). 3.3. Internal Consistency Reliability The internal consistent reliability (Cronbach’s a) of the MMAS8 Chinese version was 0.556, indicating moderate reliability. Cronbach’s a was slightly higher (0.649) when item 4 was deleted.
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3.4. Test-Retest Reliability A total of 11 patients were asked to recomplete the scale 2-4 weeks later. The mean score of adherence was 7.41. A total of 9.1% (1 of 11), 27.3% (3 of 11), and 63.6% (7 of 11) patients reported low, medium, and high adherence, respectively. According to our criterion, 90.9% (10 of 11) of patients were considered as adherent, and 9.1% (1 of 11) of patients were viewed as non-adherent. The ICC of the Chinese MMAS-8 was 0.729, indicating good reproducibility. 3.5. Construct Validity Bartlett’s test of sphericity (p < 0.001) and the Kaiser-MeyerOlkin (p = 0.694) test were performed, which indicated that the Chinese MMAS-8 was suitable for factor analysis. Three factors (eigenvalue > 1) were extracted in our study, explaining a total variance of 58.2%. The factor loadings for each item are illustrated in Table 2. Factor 1 had an eigenvalue of 2.440, accounted for 30.495% of the variance and comprised items 1, 2, 3, 6, 7, and 8. Factor 2 had an eigenvalue of 1.139, explained 14.239% of the variance and comprised items 3 and 6. Factor 3 had an eigenvalue of 1.074, explained 13.421% of the variance and comprised items 5 and 6. 3.6. Relationship between Adherence, Seizure Frequency, and Adverse Effects
Table 1 Socio-demographic and clinical characteristics (N = 111). Variables
Number
Association with MMAS-8 scores (p value)
Age (Mean, SD) Gender (N, %) Male Female Education level (N, %) No primary studies Primary studies Secondary studies Senior high studies University studies Master studies Seizure type (N, %) SPS CPS SGTC SGTC + CPS GTCS Time from first seizure in years (mean, SD) Time from seizure in years (mean, SD) Number of AEDs (N, %) One AED Two AEDs Three AEDs Four AEDs Seizure frequencyy (N, %) 0 >1 LAEP scores z(N, %) >34.77 34.77
32 .9 (14.9)
0.209 0.098
55 (49.5%) 56 (50.5%) 0.566 2 (1.8%) 7 (6.3%) 41 (36.9%) 24 (21.6%) 36 (32.4%) 1 (0.9%) 5 (4.5%) 14 (12.6%) 13 (11.7%) 46 (41.4%) 33 (29.7%) 22.3 (17.0)
0.089
0.394 0.680 0.769
10.6 (10.0) 0.001* 62 (55.9%) 40 (36.0%) 8 (7.2%) 1 (0.9%)
0.001*
53 (47.7%) 58 (52.3%) 24 (21.6%) 87 (78.4%)
SPS, simple partial seizure; CPS, complex partial seizure; SGTC, secondarily generalized tonic-clonic seizure; GTCS, generalized tonic-clonic seizure; AEDs, antiepileptic drugs; SD, standard deviation; MMAS, Morisky Medication Adherence Scale; LAEP, Liverpool Adverse Events Profile. y Seizure frequency during the preceding month. z The mean scores were 34.77 in LAEP for Chinese patients in a prior study, and those patients with a score >34.77 were considered to have suffered more severe adverse effects than patients with a score 34.77. * p < 0.001.
There was a significant correlation found between adherence and seizure frequency (r = 0.708, p < 0.001), adherence and adverse effects (r = 0.484, p < 0.001). Also, adherence was associated with CNS (r = 0.453, p < 0.001) and non-CNS (r = 0.362, p < 0.001) factors. To take into account the influence of adverse effects, we assessed the relationship between adherence and seizure frequency, using partial analysis. Adherence was also significantly associated with seizure frequency (r = 0.166, p < 0.001) after controlling for the influence of adverse effects. 4. Discussion The main objective of our study was to validate the MMAS-8 in epilepsy patients in China. To the best of our knowledge, this is also the first study to validate this scale in Chinese patients. Several validation studies focused on different languages for this scale have been conducted.24–28 Korb-Savoldelli et al.24 validated the French version of this scale in patients with hypertension, and the Cronbach’s a was 0.54. Lee et al.25 and Harith et al.26 validated the version Korean and Malaysian version in patients with type 2 diabetes, and the Cronbach’s a scores were 0.66 and 0.675, respectively. Wang et al.28 validated the Singaporean version in patients who taken warfarin, with a Cronbach’s a of 0.56. These previous studies validating the MMAS-8 indicate this scale was moderately reliable, and similar results were found in our study: moderate reliability (Cronbach’s a = 0.556) and good test-retest reliability (ICC = 0.729). These results might be explained by: (a) the small number of participants involved into our study, as the number size would influence the internal consistency 33 and (b) this scale is composed of seven yes/no questions and one five-point Likert scale, and yes/no questions can lower the value of Cronbach’s a because of higher measurement error.34 Even though a Cronbach’s a 0.8 is recommended, a Cronbach’s a 0.5 is considered acceptable according to Bowling and Robinson et al.35,36 The Cronbach’s a for the Chinese MMAS-8 was 0.556, which was viewed as acceptable. Accordingly, this indicates the Chinese MMAS-8 has potential as a tool to help in assessing medication adherence in epileptic patients.
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Fig. 1. Distribution of each item of Morisky Medication Adherence Scale.
As for the distribution of MMAS-8 adherence across the participants, 32.4%, 46.8%, and 20.7% displayed high, medium, and low adherence, respectively, with 79.2% displaying some adherence, and 20.7% displayed no adherence. These results are consistent with those of a previous study that used the four-item MMAS, which reported a total adherence of approximately 74.8% (high adherence and medium adherence) in Chinese patients with epilepsy.22 Similarly, Avani et al. reported a total adherence of approximately 79.4% in patients with new-onset epilepsy, using MEMS TrackCap which is viewed as a more accurate measure than others.37 In this context, the Chinese version of the MMAS-8 can be used as a tool to evaluate medication adherence, as well as to capture the non-adherence among Chinese patients with epilepsy. This is the first study in China to assess the relationships between adherence, seizure frequency, and adverse effects using the MMAS-8. As we expected, the findings of our study, including the negative relation between adherence and seizure frequency and adherence and adverse effects, resulting in lower seizure frequency and adverse effects, were associated with higher adherence. Similar results regarding the relationship between adherence and seizure frequency were found by Jones et al. and Collin et al.10,21 Collin and his colleagues demonstrated that nonadherence was associated with reduced seizure control.21 Another study in the UK demonstrated a negative correlation between adherence and seizure frequency even though there was no significant difference.10 With respect to the relationship between adherence and adverse effects, the results in our study are not consistent with another published study which demonstrated that a significant difference was not found among patients with different levels of adherence.23 The discrepancy might be explained by the fact that a different scale was used for assessing adverse effects. Compared with the scale only containing five items
Table 2 Factorial loading on the eight-item Morisky Medication Adherence Scale. Factor
Item 1 Item 2 Item 3 Item 4 Item 5 Item 6 Item 7 Item 8 Eigenvalue Explained variance (58.2%) *
Indicates items loading 0.4.
1
2
3
0.685* 0.678* 0.629* 0.258 0.031 0.552* 0.604* 0.614* 2.440 30.495%
0.352 0.353 0.474* 0.396 0.535 0.471* 0.017 0.032 1.139 14.239%
0.213 0.069 0.331 0.249 0.615* 0.483* 0.309 0.382 1.074 13.421%
used by Sweileh et al.,23 the LAEP scale we used contains 22 items and covers both systemic and neurological problems.38 In addition, the validity and reliability of this scale has been assessed in Chinese patients with epilepsy. These results indicate that assessing adherence with the Morisky scale may be able to predict the seizure frequency and side effects in clinical settings, which, consequently, would result in better management of epilepsy in China. Despite the important implications of our findings, our study has several limitations. (a) This was a cross-sectional study rather than a randomized clinical trial. Thus, it can only illustrate the adherence rate for a certain period of time, which is problematic because adherence rates have been demonstrated to change with time.37,39,40 (b) Patients with epilepsy experience some physical disorders similar to adverse effects, making it difficult to distinguish whether the cause of the symptoms is either the drug or seizures. To avoid this bias, we reminded the patients that the questionnaire items were mainly evaluating drug behavior and not seizures. (c) The accuracy of the self-reported seizure frequency is a concern because the frequency was likely under-reported because of a lack of cognition of the clinical manifestation or the lack of a witness at the time the seizure occurred.41 Even though EEG monitoring is a vital tool to capture seizure occurrence, continuous EEG monitoring is impractical for outpatients. As a result, many studies use self-reporting.20,21 In our study, the seizure frequency was mostly extracted from self-reported diaries, and these data may be subject to incorrect reporting.
5. Conclusion The Chinese version of the MMAS-8 is a simple, free to administer, and convenient measurement of medication adherence in patients with epilepsy. In addition, it was demonstrated to have acceptable reliability and validity. Using this scale, the relationships between adherence, seizure frequency, and adverse effects were revealed in our study. Our results indicate that better seizure control and lower adverse effects were significantly correlated with higher adherence scores. As we mentioned earlier, almost all validated MMAS-8 versions in different languages have displayed moderate reliability. Therefore, further studies are needed to investigate the reliability and validity of this scale in different clinical settings and different populations. Acknowledgements This study was supported by the Department of Neurology of Huashan Hospital. The authors would like to thank Prof. Zhu
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(Gouxing Zhu) and his student Youxin Fang for assistance in recruitment. Appendix A. Supplementary data Supplementary data associated with this article can be found, in the online version, at http://dx.doi.org/10.1016/j.seizure.2014. 01.003. References 1. Thurman DJ, Beghi E, Begley CE, Berg AT, Buchhalter JR, Ding D, et al. Standards for epidemiologic studies and surveillance of epilepsy. Epilepsia 2011;52:2–26. 2. Wang WZ, Wu JZ, Wang DS, Dai XY, Yang B, Wang TP, et al. The prevalence and treatment gap in epilepsy in China: an ILAE/IBE/WHO study. Neurology 2003; 60:1544–5. 3. Cramer JA, Roy A, Burrell A, Fairchild CJ, Fuldeore MJ, Ollendorf DA, et al. Medication compliance and persistence: terminology and definitions. Value Health 2008;11:44–7. 4. Ettinger AB, Manjunath R, Candrilli SD, Davis KL. Prevalence and cost of nonadherence to antiepileptic drugs in elderly patients with epilepsy. Epilepsy & Behavior 2009;14:324–9. 5. Cramer JA, Glassman M, Rienzi V. The relationship between poor medication compliance and seizures. Epilepsy & Behavior 2002;3:338–42. 6. Manjunath R, Davis KL, Candrilli SD, Ettinger AB. Association of antiepileptic drug nonadherence with risk of seizures in adults with epilepsy. Epilepsy & Behavior 2009;14:372–8. 7. Modi AC, Guilfoyle SM, Rausch J. Preliminary feasibility, acceptability, and efficacy of an innovative adherence intervention for children with newly diagnosed epilepsy. Journal of Pediatric Psychology 2013;38:605–16. 8. Faught RE, Weiner JR, Guerin A, Cunnington MC, Duh MS. Impact of nonadherence to antiepileptic drugs on health care utilization and costs: findings from the RANSOM study. Epilepsia 2009;50:501–9. 9. Davis KL, Candrilli SD, Edin HM. Prevalence and cost of nonadherence with antiepileptic drugs in an adult managed care population. Epilepsia 2008;49: 446–54. 10. Jones RM, Butler JA, Thomas VA, Peveler RC, Prevett M. Adherence to treatment in patients with epilepsy: associations with seizure control and illness beliefs. Seizure 2006;15:504–8. 11. Johannessen SI, Landmark CJ. Value of therapeutic drug monitoring in epilepsy. Expert Review of Neurotherapeutics 2008;8:929–39. 12. Rosen MI, Rigsby MO, Salahi JT, Ryan CE, Cramer JA. Electronic monitoring and counseling to improve medication adherence. Behaviour Research and Therapy 2004;42:409–22. 13. Modi AC, Zeller MH, Xanthakos SA, Jenkins TM, Inge TH. Adherence to vitamin supplementation following adolescent bariatric surgery. Obesity (Silver Spring) 2013;21:E190–5. 14. Vermeire E, Hearnshaw H, Van Royen P, Denekens J. Patient adherence to treatment: three decades of research. A comprehensive review. Journal of Clinical Pharmacy and Therapeutics 2001;26:331–42. 15. Morisky DE, Ang A, Krousel-Wood M, Ward HJ. Predictive validity of a medication adherence measure in an outpatient setting. Journal of Clinical Hypertension (Greenwich) 2008;10:348–54. 16. Garber MC, Nau DP, Erickson SR, Aikens JE, Lawrence JB. The concordance of self-report with other measures of medication adherence: a summary of the literature. Medical Care 2004;42:649–52. 17. Lee VW, Pang KK, Hui KC, Kwok JC, Leung SL, Yu DS, et al. Medication adherence: is it a hidden drug-related problem in hidden elderly? Geriatrics & Gerontology International 2013;13:978–85. 18. Lee GK, Wang HH, Liu KQ, Cheung Y, Morisky DE, Wong MC. Determinants of medication adherence to antihypertensive medications among a Chinese population using Morisky Medication Adherence Scale. PLoS One 2013;8:e62775.
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