Sage Journals: Discover world-class research

Abstract

Objective:

This study is designed to assess the pattern of nonadherence, and associated factors among ambulatory patients with epilepsy at Jimma Medical Center, Southwestern Ethiopia, from November 2020 to April 2021.

Methods:

A hospital-based prospective observational study was employed. A consecutive sampling method was used to recruit study participants. Nonadherence was assessed by the Hill–Bone compliance to the high blood pressure therapy scale. A threshold of 18 scores was used to classify adherence status. Epi-Data manager version 4.6 was used for data entry and all statistical analysis was performed by Statistical Package for Social Science 25.0. Multivariable logistic regression was performed to explore associated factors.

Results:

A survey included 334 patients with epilepsy. One hundred twenty-two (36.52%) of the study participants were found to be non-adherent. The factors associated with nonadherence were poor involvement of the patient in the therapeutic decision (adjusted odds ratio = 1.74; 95% confidence interval: 1.04–2.90; p = 0.034), per month income of lesser than1000 Ethiopian birr (adjusted odds ratio = 2.66; 95% confidence interval: 1.03–6.84; p = 0.042), recent seizure episodes (adjusted odds ratio = 1.97; 95% confidence interval: 1.20–3.23; p = 0.007), adverse drug reaction (AOR = 2.13; 95% confidence interval: 1.31–3.47; p = 0.002), and negative medication belief (adjusted odds ratio = 1.28; 95% confidence interval: 1.53–2.25; p = 0.043).

Conclusions:

In our setting, the magnitude of nonadherence was substantially high. Hence, providing regular health-related information about the disease and treatment, supplying free antiepileptic drugs, routine assessment of adverse drug reactions, and a multidisciplinary approach involving patients may improve adherence.

Keywords

Adherence medication belief antiepileptic drugs Ethiopia

Introduction

Epilepsy is a neurologic condition that affects all people and has no social, racial, or geographic boundaries.¹ Epilepsy is known by repeated seizures involving the entire body or a part of the body accompanied by loss of consciousness and bowel control.² Worldwide there are seventy million patients with epilepsy (PWE), of which 90% are living in low- and middle-income countries.³ Due to multifaceted and complex factors, 90% of PWE in developing regions are not receiving appropriate treatments.^4,5

The prevalence of epilepsy in Ethiopia ranges from 0.064% to 2.95% with the highest incidence in ages 1–19 years.^6,7 Studies suggested that epilepsy fails to come quickly under control with currently available antiepileptic medicines in about one-third of cases.⁴ The probable reasons for uncontrolled seizures were wrong medication, wrong dose, inappropriate seizure classification, comorbidities, medically refractory epilepsy, and nonadherence to antiepileptic drugs.^8,9

Nonadherence is a complex and multidimensional healthcare-related problem. It refers to the degree to which the patients failed to respect and follow recommendations from a healthcare provider about taking medication, the daily timing, dosage, frequency, duration of medication use, and executing lifestyle changes.^10,11 The causes of nonadherence are multifactorial and can be classified as system-related, patient-related, medication-related, sociocultural, and financial-related.¹² Knowledge about the treatment or diseases, beliefs about medication, resources, and trust in healthcare professionals were critical factors in determining adherence from the patient’s perspective.^12–14 Nonadherence to antiepileptic drugs (AEDs) aggravates the consequences of unmet therapeutic outcomes, increases the risk of seizures by 21%, and increases overall mortality by more than three-fold among epileptic patients.^15,16

Nonadherence imposes different economic and health consequences like frequent hospitalization, increased morbidity, and mortality along with poor quality of life and poor seizure control.^17–19 It is undeniable that many patients experience difficulty in following treatment recommendations. Studies in developed countries showed that 50% of the chronic medication users failed to adhere and in developing countries like Ethiopia the rates are even higher.^11,20

The magnitude of nonadherence varied across different continents. It was 66.2% in Brazil,²¹ 49.3% in Malaysia,²² 68 % in Ethiopia,²³ and 71% in India.²⁴ Generally, nonadherence to long-term therapies severely compromises the effectiveness of treatment and it is a critical issue in epileptic patients from the perspective of health economics and quality of life. Irrespective of this, a limited study has been conducted on the Pattern of Anti-Epileptic Medications Non-Adherence and Associated Factors in Ethiopia. Accordingly, this study is designed to explore the pattern of nonadherence to antiepileptic drugs and associated factors among ambulatory PWE, in Southwestern Ethiopia.

Methods and materials

Setting, period, and design

A prospective observational study was conducted from November 2020 to April 2021 at the Jimma Medical Center (JMC). JMC is in Jimma town, 352 km from Addis Ababa, Ethiopia. Currently, 160,000 outpatient attendants are being served at this hospital of which 1127 were PWE.

Source population and study population

All people with confirmed diagnosis of epilepsy, and having had regular follow-up at the ambulatory clinic of JMC were our source population, and those patients who fulfilled eligibility criteria were our study population.

Inclusion and exclusion criteria

Inclusion criteria

We included patients with age of 18 years and above, with complete medical records, regular follow-up of six months or above, and willingness to participate in the study.

Exclusion criteria

We excluded patients with acute psychotic features, and those with incomplete medical information.

Study variables

Nonadherence was a dependent variable and our primary outcome of interest as well. Adherence was assessed by using nine items of medication-taking subsections (high blood pressure therapy scale (HBTS)).²⁵ Each of the nine items contains a four-point Likert-type scale. The score represented as 1 = all of the time, 2 = mostly, 3 = sometimes, and 4 = never. The total Item scores were added to give an overall score of 9–36. A score above a threshold of 18 indicates adherence, otherwise nonadherence.^25,26 The involvement of the patients in their therapeutic decision was measured by a questionnaire containing two items. Each of the two items contains a five-point Likert-type scale, 1 = never, 2 = rarely, 3 = sometimes, 4 = most of the time, 5 = all times. The total score ranged from 2 to 10, and a score below the midpoint (<5) indicates poor involvement and the score above the midpoint showed active involvement.²⁷ Belief about medication questionnaire)²⁸ is 10-items Likert-type scale divided into two sections, medication necessity, and concern. Having the average score on the medication necessity scale exceeding the average score on the medication concerns scale is a positive belief, if not it is a negative belief.²⁷

Sample size and sampling techniques

A sample of 334 was calculated using a single population proportion formula by using the following assumptions: Z = 1.96, p = 68% proportion of nonadherence at Yirgalem general hospital,²³ 95% confidence level, d = 5% margin of error, n = minimum sample size.

n = \frac{{(Z a / 2)}^{2} P (1 - P)}{d^{2}} = \frac{{(1.96)}^{2} 0.68 (1 - 0.68)}{{(0.05)}^{2}} = 334

A consecutive sampling method was used to recruit study participants during the follow-up schedule for a medication refill.

Data collection process and quality assurance

The data was collected through interviews and chart review. A pretest was done on 17 PWE at a nearby hospital, and necessary amendments were undertaken. Three data collectors participated in the whole process of data collection. At all stages of the process, the patient’s confidentiality was preserved.

Statistical analysis

Epi-Data manager version 4.6 and Statistical Package for Social Science version 25.0 was used for data entry and statistical analysis. A descriptive statistic was used to explain frequency, percentage, and mean or standard deviation. The association between each independent variable and nonadherence was assessed by performing binary regression and associated factors were identified by multivariable regression. The p-value < 0.05 was used to declare statistical significance.

Operational definitions

Recent seizure episode: is experiencing at least one seizure attack in the last month.

Adherence: Respondents were deemed adherent if their score on nine HBTS questions was above a threshold of 18 points.^25,26

Nonadherence: Respondents were deemed non-adherent if their score on nine HBTS questions was below the threshold of 18 points.^25,26

Adverse drug reaction is the response to a drug that can be noxious or unintended and occurs at the normal doses used in humans for prophylaxis, diagnosis, or treatment.²⁹

Results

Demographic distribution of study participants

The survey included a total of 334 PWE. One hundred eighty-three (54.79%) of them were male and 151 (45.21%) of the participants were female. The mean age was 29.91 ± 11.26 years. Majorities, 244 (73.05%) had a formal education, whereas 90 (26.94%) had a nonformal education. With regards to the patient’s involvement in the therapeutic decision-making and medication belief, about one-third (34.13%), of study participants were actively involved, and two-third (65.5%) of participants had positive beliefs about the medications (Table 1).

Table 1.

Demographic distributions of study participants (n = 334).

Variable	Category	Frequency	Percentage (%)
Age	18–28	180	53.89
	29–39	79	23.65
	40–49	40	11.97
	⩾50	35	10.47
Gender	Male	183	54.79
Gender	Female	151	45.21
Religion	Muslim	218	65.26
	Orthodox	80	23.95
	Protestant	23	6.88
	Catholic	13	3.89
Educational status	Formal education	244	73.05
Educational status	No formal education	90	26.94
Marital status	Single	166	49.70
	Married	142	42.51
	Widowed	14	4.19
	Divorced	12	3.59
Occupation	Unemployed	298	89.22
Occupation	Employed	36	10.77
Monthly income (Ethiopian birr)	Lesser than 1000	287	85.92
Monthly income (Ethiopian birr)	Greater than 1000	47	14.07
Patient involvement	Actively involved	114	34.13
Patient involvement	Poorly involved	220	65.86
Medication belief	Positive belief	219	65.56
Medication belief	Negative belief	115	34.43

Therapy and clinical related factors

In this finding, the commonest diagnosed type of seizure was generalized tonic-clonic seizures 221 (66.16%) followed by unclassified seizures 77 (23.05%), and focal seizures 36 (10.77%). About half (48.50%), and one-fourth (25.14%) of participants had a seizure duration of more than 10 years, and 6–10 years, respectively. One hundred thirty-eight (41.31%) of patients had been diagnosed at 11–20 years old, and 117 (35.02%) were reported to have recent seizure episodes. One hundred sixty patients (47.90%) were on a single antiepileptic drug, followed by dual (44.01%), and triple therapy (8.08%). Of the study participants about one-third of the patients had experienced antiepileptic drug-associated adverse drug reactions (ADR) (Table 2).

Table 2.

Therapy and clinical related distribution of study participants (n = 334).

Variable	Categories	Frequency	Percentage (%)
Age at diagnosis of seizure	1–10	83	24.85
	11–20	138	41.31
	21–30	66	19.76
	>30	47	14.07
Types of seizure	Generalized tonic-clonic	221	66.16
	Focal seizure	36	10.77
	Unclassified seizure	77	23.05
Seizure duration (years)	1–5	88	26.34
	6–10	84	25.14
	>10	162	48.50
Recent seizure episode	Yes	117	35.02
Recent seizure episode	No	217	64.97
Comorbidity	Yes	60	17.96
Comorbidity	No	274	82.03
History of admission	Yes	75	22.45
History of admission	No	259	77.54
Number of antiepileptic drugs	One	160	47.90
	Two	147	44.01
	Three	27	8.08
Adverse drug reaction	Yes	112	33.53
Adverse drug reaction	No	222	66.46

Prevalence and reasons for nonadherence

Our study results showed that 212 (63.48%) respondents were fully adherent and 122 (36.52%) of them were non-adherent. According to the respondent, forgetfulness 46 (37.70%) and unavailability of antiepileptic drugs 35 (28.68%) were the top two reasons for their nonadherence. With regards to which AED the patients were non-adherent, phenobarbital monotherapy 43 (35.24%) and combination with phenytoin 33 (27.04%) were the top two medications to which the patients were non-adherent (Table 3).

Table 3.

Adherence status, reasons for nonadherence, and to which AEDs patients were non-adherent (n = 334).

Variable	Category	Frequency	Percentage
Adherence status	Adherent	212	63.48
Adherence status	Non-adherent	122	36.52
Reasons for nonadherence	Forget to take medications	46	37.70
	The drug is not available	35	28.68
	The drug is too expensive	32	26.22
	Prefer not to take the drug	18	14.75
	Not understood the direction	9	7.37
Antiepileptic drugs to which the patients were non-adherent	Phenobarbital	43	35.24
	Phenobarbital + phenytoin	33	27.04
	Phenytoin	26	21.31
	Carbamazepine	8	6.55
	Valproic acid	7	5.73
	Phenobarbital + carbamazepine	5	4.09

Scores and distribution of responses to nine items of HBTS (n = 334)

In the adherence assessment scale, 36.52% of the study participant’s adherence score was below eighteen, 29.35% scored 18–26 and 34.13% scored 27–36 (Figure 1).

Figure 1.

Distributions of patient score to HBTS (9–36).

Factors associated with nonadherence

The association between nonadherence and different independent variables was identified. From a binary logistic regression analysis all independent variables with a p-value of <0.25 % were transferred to the multivariable logistic regression model. In the multivariable model patient having a monthly income of lesser than 1000 ETB were 2.66 times (adjusted odds ratio (AOR): 2.66; 95% confidence interval (CI): 1.03, 6.84) less likely to be adherent as compared to their counterparts. Patients with recent seizure episodes were 1.97 times (AOR: 1.97; 95% CI: 1.20, 3.23) less likely adherent when compared with their counterparts. Additionally, a group of patients with ADR was 2.13 times (AOR: 2.13; 95% CI: 1.31, 3.47) less adherent than another group of patients. Furthermore, those patients with positive medication beliefs and active involvement in their therapeutic decision-making were 1.28 times (AOR: 1.28, 95% CI: 1.53, 2.25), and 1.74 times (AOR: 1.74, 95% CI: 1.04, 2.90) more likely to be adherent than their counterparts respectively (Table 4).

Table 4.

Association of dependent and independent variables among study participants (n = 334).

Variables	Categories	Adherence Yes No		Crude odds ratio	Adjusted odds ratio	p-Value
Age	18–28	111	69	1
	29–39	48	31	1.04 (0.60–1.7)
	40–49	31	9	0.37 (0.15–0.90)
	⩾50	21	14	0.81 (0.32–1.97)
Gender	Male	129	54	1.92 (1.23–3.11)	1.35 (0.80–2.28)	0.247
Gender	Female	84	67	1	1
Education	Formal	152	92	1
Education	Nonformal	60	30	1.11 (0.70–1.95)
Marital status	Single	107	59	1
	Married	92	50	0.97 (0.61–1.56)
	Widowed	9	5	4.5 (0.85–24)
	Divorced	5	7	0.72 (0.13–3.85)
Occupation	Employed	25	11	1
Occupation	Unemployed	180	118	1.32 (0.62–2.77)
Monthly income (Ethiopian birr)	<1000	178	109	2.75 (1.10–6.88)	2.66 (1.03–6.84)	0.042
Monthly income (Ethiopian birr)	>1000	34	13	1	1
Age at diagnosis of seizure	1–10	48	35	2.54 (1.07–6.04)	2.26 (0.90–5.65)	0.083
	11–20	87	51	2.01 (0.89–4.57)	1.95 (0.83–4.61)	0.124
	21–30	43	23	1.76 (0.71–4.38)	1.39 (0.54–3.62)	0.489
	>30	34	13	1	1
Types of seizure	GTC	142	79	1
	Focal seizure	19	17	1.65 (0.72–3.86)
	Unclassified	50	27	0.86 (0.49–1.54)
Seizure duration	1–5	62	26	1
	6–10	51	33	1.61 (0.82–3.13)	1.47 (0.71–3.02)	0.295
	>10	100	62	1.56 (0.87–2.78)	1.42 (0.72–2.82)	0.310
Recent seizure episodes	Yes	62	55	2.09 (1.29–3.37)	1.97 (1.20–3.23)	0.007
Recent seizure episodes	No	150	67	1	1
Comorbidity	Yes	65	45	1.43 (0.93–2.39)	1.06 (0.55–1.82)	0.997
Comorbidity	No	147	77	1	1
Admission history	Yes	42	33	0.7 (0.39–1.24)	1.40 (0.75–2.50)	0.28
Admission history	No	170	89	1	1
Number of antiepileptic drugs	One	111	49	1	1
	Two	86	61	1.52 (0.95–2.45)	1.20 (0.71–2.05)	0.487
	Three	15	12	2.26 (0.8–6.38)	1.16 (0.35–3.84)	0.803
Adverse drug reactions	Yes	64	48	1.62 (1.06–2.66)	2.13 (1.31–3.47)	0.002
Adverse drug reactions	No	149	73	1	1
Patient involvement	Active	84	30	1	1
Patient involvement	Poor	128	92	1.72 (1.05–2.81)	1.74 (1.04–2.90)	0.034
Medication belief	Positive	149	70	1	1
Medication belief	Negative	64	51	1.73 (1.07–2.79)	1.28 (1.53–2.25)	0.043

GTC: Generalized tonic clonic seizure.

Discussion

Prevalence of antiepileptic medication nonadherence

In chronic diseases like epilepsy, nonadherence is the critical factor that leads to failure of treatment and disease recurrence. In this study, 36.52% of the participants were found to be non-adherent. In line with the current finding, the study conducted in Debre Markos Referral Hospital,³⁰ Dilla University Referral Hospital,³¹ United Kingdom,¹⁶ Finland,³² and Mettu Karl comprehensive specialized hospital (MKCSH)²⁶ identified that 37.8%, 38.1%, 36.4%, 34%, and 40% of participants were non-adherent.

Nevertheless, the reported study from the United Kingdom (20.5%),²¹ India (27.7%),³³ and France (21%),³⁴ showed a much lower level of nonadherence. The justifications for this variation may be, due to differences in the educational status, availability of AED, types of AED used, and cultural differences. In Ethiopia, the most frequently used AEDs are old generations like Phenytoin and Phenobarbital which are associated with higher ADR that may lower the level of adherence.³⁵

Factors associated with nonadherence

Patient autonomy and active participation in shared decision-making with Healthcare professionals will significantly enhance adherence.³⁶ Evidence showed that poor involvement of patients in shared therapeutic decision-making increases healthcare-associated complications and treatment-related costs.³⁷ In the present study, the less likely part of shared decision-making lowered the level of adherence by 1.74 (AOR, 1.74; 95% CI: 1.04–2.90) when compared to actively involved patients. Therefore, healthcare professionals should encourage patients to be a part of shared therapeutic decision-making, as this may enhance patient adherence.

In a developing country like Ethiopia, where there is a shortage of medications, the monthly income of the patient is highly associated with nonadherence. In this study, a monthly income of lesser than 1000 ETB lowered the level of adherence by 2.66 times (AOR, 2.66; 95% CI: 1.03–6.84) as compared to the groups of patients earning more than 1000 ETB monthly. This is supported by the former studies from Ethiopia³⁸ and Kenya,³⁹ where the level of adherence was negatively affected by the low monthly income. This is probably due to the unavailability of some AED in public hospitals, patients with low monthly incomes became non-adherent as those medications are unaffordable from non-governmental institutions.

Additionally, in the current study experiencing recent seizure episodes increased the likelihood of nonadherence by a factor of 2.09 (AOR, 2.09; 95% CI: 1.29–3.37) as compared to the groups of patients without recent seizure episodes. A similar finding was reported from India⁴⁰; Hawassa University Comprehensive Specialized Hospital⁴¹; Indonesia⁴²; and Bangladesh.⁴³ This is because experiencing frequent seizures negatively affects belief about the diagnosis and effectiveness of the current regimen which may lead to failure to take the drugs.

Epileptic patients are highly concerned about the harmful effects associated with their treatment and they may be questioned about the importance of their medicines.⁴⁴ The Necessity–Concerns Framework declared that adherence is the interaction between positive and negative beliefs about the medicine.¹⁶ Similarly, in our study, 115 (34.4%) of the participants had negative medication beliefs, and nonadherence was increased by 1.28 factors among this group of patients when compared with positive beliefs patients (AOR, 1.28; 95% CI: 1.53–2.25).

Finally, adverse drug reactions affect adherence and may result in the discontinuation of medications.^45,46 In line with this finding, our study revealed that nonadherence was higher by 2.13 among the group of epileptic patients with ADR as compared to the other group of patients without ADR (AOR, 2.13; 95% CI: 1.31–3.47). This finding is augmented by other studies reported from Khartoum and the University of Gondar Referral Hospital.^47,48

Limitations

This study was conducted in a single setting which makes it difficult for generalizations. The adherence status, and other important variables including ADR, medication beliefs, and involvement of the patients in the therapeutic decisions were measured based on a self-reported questionnaire which is prone to recall and social desirability bias.

Recommendations

The hospital and ministry of health should work firmly with locally and nationally available suppliers to make AEDs available and affordable for all patients. Healthcare professionals should routinely assess and monitor PWE for signs of adverse drug effects and provide appropriate management with the safest possible alternative drug. Furthermore, health education targeting patients, families, and communities should be given as it may help adherence to their regular follow-up and medication as well. Finally, patients need to be motivated enough to be adherent.

Conclusions

In our study more than one-third of PWE were non-adherent. The primary reasons for nonadherence were forgetfulness and unavailability of antiepileptic drugs. Nearly half of the patients were taking a single antiepileptic drug. Lesser monthly income, negative medication belief, the experience of ADR, and a history of recent seizures were among identified factors associated with nonadherence. Whatever measures that can enhance patients’ belief or seizure control or accessibility to antiepileptic drugs and encourage the patients to be part of the decision-maker would help the patients to be adherent.

Supplemental Material

sj-docx-1-smo-10.1177_20503121231160817 – Supplemental material for Pattern of anti-epileptic medications nonadherence and associated factors at ambulatory clinic of Jimma Medical Center, Southwestern Ethiopia: A prospective observational study

Supplemental material, sj-docx-1-smo-10.1177_20503121231160817 for Pattern of anti-epileptic medications nonadherence and associated factors at ambulatory clinic of Jimma Medical Center, Southwestern Ethiopia: A prospective observational study by Yadeta Babu Bayane and Birbirsa Sefera Senbeta in SAGE Open Medicine

Footnotes

Acknowledgements

Our special appreciation goes to the Jimma University Medical Center, study participants, data collectors, and supervisors for their considerable contributions to conducting this study.

Author contributions

YBB and BSS participated in the proposal development, designing of the study, and formal analysis. YBB and BSS participated in writing up the original version of the document. YBB has checked and modified the manuscript. Both authors agreed to submission and publication with this journal.

Declaration of conflicting interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

Ethical approval

The protocol of this study has adhered to the Declaration of Helsinki’s guidelines and an ethical approval letter was obtained from the Jimma University Institutional Review Board (JUIRB 00025220/2020).

Informed consent

Written informed consent was obtained from the study subjects themselves. All study subjects had the decisional capacity to provide written informed consent. Participation was entirely voluntary, and participants were free to withdraw from the study at any time without any consequence. Confidentiality of all information has been maintained. The JUIRB approved the form of informed consent before the installation of the study.

ORCID iD

Yadeta Babu Bayane

Data availability

The corresponding author can provide an additional resource upon reasonable request.

Supplemental material

Supplemental material for this article is available online.

References

Sander

. The epidemiology of epilepsy revisited. Curr Opin Neurol 2003; 16(2): 165–170.

Epilepsy [Internet]. [cited 5 September 2022]. Available at: https://www.who.int/news-room/fact-sheets/detail/epilepsy

Singh

Trevick

. The epidemiology of global epilepsy. Neurol Clin 2016; 34(4): 837–847.

Singh

Trevick

. The epidemiology of global epilepsy. Neurol Clin [Internet] 2016 Nov 1 [cited 25 October 2021]; 34(4): 837–847. Available at: https://europepmc.org/article/med/27719996

Dika

Nkola

Iddi

, et al. Limited care offered to people with epilepsy in Mwanza, Tanzania : need for intervention. Pan Afr Med J 2021; 38: 407.

Tekle-Haimanot

Forsgren

Ekstedt

. Incidence of epilepsy in rural central Ethiopia. Epilepsia 1997; 38(5): 541–546.

Almu

Tadesse

Cooper

, et al. The prevalence of epilepsy in the Zay Society, Ethiopia – An area of high prevalence. Seizure 2006; 15(3): 211–213.

Asadi-pooya

Emami

Ashjazadeh

, et al. Reasons for uncontrolled seizures in adults ; the impact of pseudointractability. Seizure 2013; 22: 271–274.

Asadi-Pooya

Emami

Ashjazadeh

, et al. Reasons for uncontrolled seizures in adults; The impact of pseudointractability. Seizure [Internet] 2013; 22(4): 271–274. Available from: http://dx.doi.org/10.1016/j.seizure.2013.01.010

10.

Hugtenburg

Timmers

Elders

PJM

, et al. Definitions, variants, and causes of nonadherence with medication: a challenge for tailored interventions. Patient Prefer Adherence 2013; 7: 675–682.

11.

. A D H E R E N C E To Lo N G - T E R M T H E R A P I E S World Health Organization 2003. 2003

12.

Kvarnström

Westerholm

Airaksinen

, et al. Factors contributing to medication adherence in patients with a chronic condition: a scoping review of qualitative research. Pharmaceutics 2021; 13(7): 1–41.

13.

Verma

Kiran

Kumar

. Belief in medication and adherence to antiepileptic drugs in people with epilepsy: a cross-sectional study from rural India. Int J Neurosci [Internet] 2018 [cited 3 October 2022]; 128(12): 1168–1173. Available at: https://www.tandfonline.com/doi/abs/10.1080/00207454.2018.1501048

14.

Linn

van Weert

JCM

Schouten

, et al. Words that make pills easier to swallow: a communication typology to address practical and perceptual barriers to medication intake behavior. Patient Prefer Adherence 2012; 6: 871–885.

15.

Egenasi

Steinberg

Raubenheimer

. Beliefs about medication, medication adherence and seizure control among adult epilepsy patients in Kimberley, South Africa Beliefs about medication, medication adherence and seizure control among adult epilepsy patients in Kimberley, South Africa. South African Fam Pract [Internet] 2015; 57(5): 326–332. Available at: http://dx.doi.org/10.1080/20786190.2015.1078152

16.

Chapman

SCE

Horne

Chater

, et al. Epilepsy and behavior patients ’ perspectives on antiepileptic medication : relationships between beliefs about medicines and adherence among patients with epilepsy in UK primary care. Epilepsy Behav [Internet] 2014; 31: 312–320. Available at: http://dx.doi.org/10.1016/j.yebeh.2013.10.016

17.

Hovinga

Asato

Manjunath

, et al. Association of non-adherence to antiepileptic drugs and seizures, quality of life, and productivity: survey of patients with epilepsy and physicians. Epilepsy Behav 2008; 13(2): 316–322.

18.

Kaddumukasa

Matovu

, et al. The frequency and precipitating factors for breakthrough seizures among patients with epilepsy in Uganda. BMC Neurol 2013; 13: 182.

19.

Cramer

Wang

Chang

, et al. Healthcare utilization and costs in adults with stable and uncontrolled epilepsy. Epilepsy Behav [Internet] 2014; 31: 356–362. Available at: http://dx.doi.org/10.1016/j.yebeh.2013.09.046

20.

Chew

Lee

Lim

, et al. Prevalence and predictors of medication non-adherence among older community-dwelling people with chronic disease in Singapore. J Adv Nurs 2021; 77(10): 4069–4080.

21.

Ferrari

CMM

De Sousa

RMC

Castro

LHM

. Factors associated with treatment non-adherence in patients with epilepsy in Brazil. Seizure 2013; 22(5): 384–389.

22.

Article

. Evaluation of self – reported medication adherence and its associated factors among epilepsy patients in Hospital Kuala Lumpur. J Basic Clin Pharm 2016; 7(4): 105–109.

23.

Hasiso

Desse

. Adherence to treatment and factors affecting adherence of epileptic patients at Yirgalem General Hospital, Southern Ethiopia : a prospective cross-sectional study. PLoS One 2016; 11(9): e0163040.

24.

Das

Ramamoorthy

Narayan

, et al. Barriers of drug adherence among patients with epilepsy : in Tertiary Care Hospital, South India. J Caring Sci 2018; 7(4): 177–181.

25.

Pan

, et al. The Translation, reliability and validity of the Chinese version of the Hill-Bone compliance to high blood pressure therapy scale in adults with hypertension. Patient Prefer Adherence [Internet] 2020 [cited 3 October 2022]; 14: 1853–1860. Available at: https://pubmed.ncbi.nlm.nih.gov/33116429/

26.

Bekele

. Non-adherence to antiepileptic drugs and associated factors among epileptic patients at Ambulatory Clinic of Southwestern Ethiopian Hospital : a cross-sectional study. Patient Prefer Adherence 2022; 16: 1865–1873.

27.

Niriayo

Kumela

Kassa

, et al. Drug therapy problems and contributing factors in the management of heart failure patients in Jimma University Specialized Hospital, Southwest Ethiopia. PLoS One 2018; 13(10): 1–14.

28.

Tsianou

Giannakeas

Tsipouras

, et al. Accessing patient views about medication in chronic conditions using the beliefs about medicine questionnaire (BMQ): a review study. J Drug Res Dev 2017; 3(2): 1–9.

29.

Amran

. Adverse drug reactions and pharmacovigilance. New Insights into Futur Pharmacoepidemiol Drug Saf [Internet] 2021 [cited 3 October 2022]. Available at: https://www.intechopen.com/state.item.id

30.

Getnet

Woldeyohannes

Bekana

, et al. Antiepileptic drug nonadherence and its predictors among people with epilepsy. Behav Neurol 2016; 2016: 3189108.

31.

Shegaw

Addissu

. Prevalence and associated factors of antiepileptic drug non-department of Dilla University Referral Hospital, Dilla, Gedeo, SN- NPR, Southern Ethiopia adherence among epileptic patients attending at out patient. J Psychiatry Cogn Behav 2017; 2(1): 1–8.

32.

Kyngas

. Compliance with health regimens of adolescents with epilepsy. Seizure 2000; 9(8): 598–604.

33.

Gurumurthy

Chanda

Sarma

GRK

. An evaluation of factors affecting adherence to antiepileptic drugs in patients with epilepsy: a cross-sectional study. Singapore Med J [Internet] 2017 [cited 26 October 2021]; 58(2): 98–102. Available at: /pmc/articles/PMC5311891/

34.

Laville

Montana

Roux

, et al. Factors limiting adherence to antiepileptic treatment: a French online patient survey. J Clin Pharm Ther [Internet] 2018 [cited 26 October 2021]; 43(1): 73–79. Available at: https://onlinelibrary.wiley.com/doi/full/10.1111/jcpt.12615

35.

Babu

Daba

, et al. Drug therapy problems and predicting factors among ambulatory epileptic patients in Jimma Medical Center, Southwest Ethiopia. PLoS One 2022; 115: 1–15. Available at: http://dx.doi.org/10.1371/journal.pone.0267673

36.

Nuwagaba

Olum

Bananyiza

, et al. Patients’ involvement in decision-making during healthcare in a developing country: a cross-sectional study. Patient Prefer Adherence 2021; 15: 1133–1140.

37.

Elwyn

Frosch

Thomson

, et al. Shared decision making: a model for clinical practice. J Gen Intern Med 2012; 27(10): 1361–1367.

38.

Dima

Shibeshi

. Antiepileptic drug adherence in children in southern Ethiopia: a cross sectional study. Plos One 2022;17(2): e0263821.

39.

Mbuba

Ngugi

Fegan

, et al. Risk factors associated with the epilepsy treatment gap in Kilifi, Kenya: a cross-sectional study. Lancet Neurol 2012; 11(8): 688–696.

40.

Chauhan

Prasad

Khurana

, et al. Self-reported medication adherence to antiepileptic drugs and treatment satisfaction among paediatric patients having epilepsy : a cross sectional study from the Indian subcontinent. Sri Lanka J Child Health 2018; 47(2): 129–136.

41.

Dubale

Gizaw

Aklog

, et al. Treatment outcome and associated factors among adult epileptic patients at Hawassa University Specialized Hospital, Southern Ethiopia. J Bioanal Biomed [Internet] 2020 [cited 3 April 2022]; 12(6): 1–7. Available at: https://www.hilarispublisher.com/open-access/treatment-outcome-and-associated-factors-among-adult-epileptic-patients-at-hawassa-university-specialized-hospital-southern-ethiop-51898.html

42.

Ernawati I, Islamiyah WR and Sumarno.

How to improve clinical outcome of epileptic seizure control based on medication adherence? A literature review. Open Access Maced J Med Sci 2018; 6(6): 1174–1179.

43.

Hasan

ATMH

. Antiepileptic drug utilization in Bangladesh : experience from Dhaka Medical College Hospital. BMC Res Notes 2013; 6: 473.

44.

Dayapoğlu

Turan

Özer

. Evaluation of medication adherence and medication beliefs among patients with epilepsy. Epilepsy Behav 2021; 124: 108366.

45.

Leporini

De Sarro

Russo

. Adherence to therapy and adverse drug reactions: is there a link? [Internet]. Expert Opin Drug Saf 2014 [cited 26 October 2022]; 13 (Suppl.1): S41–D55. Available at: https://www.tandfonline.com/doi/abs/10.1517/14740338.2014.947260

46.

Golpayegani

Salari

Gharagozli

. Newer antiepileptic drugs discontinuation due to adverse effects: an observational study. Ann Indian Acad Neurol 2019; 22(1): 27–30.

47.

Elsayed

El-Sayed

Badi

, et al. Factors affecting adherence to antiepileptic medications among Sudanese individuals with epilepsy: a cross-sectional survey. J Fam Med Prim Care [Internet] 2019 [cited 26 October 2022]; 8(7): 2312. Available at: https://pubmed.ncbi.nlm.nih.gov/31463248/

48.

Tilahun

Habte

Mekonnen

, et al. Nonadherence to antiepileptic medications and its determinants among epileptic patients at the University of Gondar Referral Hospital, Gondar, Ethiopia, 2019: an institutional-based cross-sectional study. Neurol Res Int 2020; 2020.

Supplementary Material

Please find the following supplemental material available below.

For Open Access articles published under a Creative Commons License, all supplemental material carries the same license as the article it is associated with.

For non-Open Access articles published, all supplemental material carries a non-exclusive license, and permission requests for re-use of supplemental material or any part of supplemental material shall be sent directly to the copyright owner as specified in the copyright notice associated with the article.

0.00 MB

0.02 MB

Pattern of anti-epileptic medications nonadherence and associated factors at ambulatory clinic of Jimma Medical Center,Southwestern Ethiopia: A prospective observational study

Abstract

Objective:

Methods:

Results:

Conclusions:

Keywords

Introduction

Methods and materials

Setting, period, and design

Source population and study population

Inclusion and exclusion criteria

Inclusion criteria

Exclusion criteria

Study variables

Sample size and sampling techniques

Data collection process and quality assurance

Statistical analysis

Operational definitions

Results

Demographic distribution of study participants

Therapy and clinical related factors

Prevalence and reasons for nonadherence

Scores and distribution of responses to nine items of HBTS (n = 334)

Factors associated with nonadherence

Discussion

Prevalence of antiepileptic medication nonadherence

Factors associated with nonadherence

Limitations

Recommendations

Conclusions

Supplemental Material

sj-docx-1-smo-10.1177_20503121231160817 – Supplemental material for Pattern of anti-epileptic medications nonadherence and associated factors at ambulatory clinic of Jimma Medical Center, Southwestern Ethiopia: A prospective observational study

Footnotes

Acknowledgements

Author contributions

Declaration of conflicting interests

Funding

Ethical approval

Informed consent

ORCID iD

Data availability

Supplemental material

References

Supplementary Material