Seizure control and adherence to antiseizure medications among epileptic hospital patients in Addis Ababa, Ethiopia

Seizure control and adherence to antiseizure medications among epileptic hospital patients in Addis Ababa, Ethiopia | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Seizure control and adherence to antiseizure medications among epileptic hospital patients in Addis Ababa, Ethiopia Betsadkan Kebede, Yemane Berhane This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9281210/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 5 You are reading this latest preprint version Abstract Background: Epilepsy remains a significant global public health concern, affecting people across all regions of the world. The burden is disproportionately higher in low-income settings, where approximately 90% of people with epilepsy reside. In these contexts, achieving optimal seizure control is often difficult due to limited treatment guidelines and challenges in tailoring therapy to individual patient needs. In Ethiopia, the proportion of patients experiencing uncontrolled seizures varies widely, ranging from 18.6% to 82.4%, with non adherence to antiseizure medications identified as a key contributing factor. Objective: The objective of this study was to assess the association between uncontrolled seizures and Non-adherence to antiseizure medications(ASMs). Methods: A hospital-based age-matched case-control study was conducted among epileptic patients at the neurologic clinic of Eka Kotebe General Hospital and Amanuel Mental Specialized Hospital. Cases were defined as patients who reported at least one seizure episode within the last 12 months, while controls were those who had no seizure episodes during the same period from October 2024 to March 2025. A total of 68 cases and 136 controls were involved in the study, with a matching ratio of 1:2. Data was anayzed using Stata. Bivariate and multivariate logistic regression analyses were used to examine the relationship between the dependent and independent variables. Statistical significance was declared at a p-value less than 0.05. Results: Non-adherance to Antiseizure medication (ASM) was significantly associated with uncontrolled seizures (AOR = 4.67, 95% CI: 1.42–15.36, p = 0.011). History of cigarette smoking was another important factor, with smokers having higher odds of uncontrolled seizures (AOR = 7.63, 95% CI: 1.73–33, p = 0.007). Patients on polytherapy were also more likely to have uncontrolled seizures compared to those on monotherapy (AOR = 3.07, 95% CI: 1.36–6.94, p = 0.007). Moreover, participants with a negative overall belief about medications (BMQ) were significantly more likely to experience uncontrolled seizures (AOR = 7.75, 95% CI: 1.9–30.82, p = 0.004). Conclusion and Recommendations: This study found that uncontrolled seizures among individuals on antiseizure medications (ASMs) were strongly associated with non-adherence, history of cigarette smoking, polytherapy, and negative beliefs about medications, with non-adherence emerging as the most significant predictor. To enhance outcomes, the study recommends strengthening ASMs adherence through education, reminders, and counseling, addressing misconceptions about ASMs, and regularly assessing and supporting patients in reducing substance use, alongside promoting consistent clinic follow-up. Figures Figure 1 1. Introduction Epilepsy is a chronic neurological condition marked by a persistent tendency to develop recurrent seizures, along with associated neurobiological, cognitive, psychological, and social consequences.(1) The diagnosis of epilepsy can be established after the occurrence of at least one unprovoked seizure, which is defined as a brief episode of clinical signs and/or symptoms resulting from abnormal, excessive, or synchronized electrical activity in the brain. (2) Epilepsy affects populations worldwide, but its distribution is markedly uneven, with the majority of cases occurring in low- and middle-income countries, including Ethiopia. Globally, it was estimated that approximately 45.9 million individuals were living with active epilepsy in 2016. (1,1,3–7) Epilepsy is considered a treatable condition with high rates of therapeutic response. Antiseizure medications remain the cornerstone of treatment and are effective in achieving seizure control for a substantial proportion of individuals. However, despite the availability of effective therapies, a large number of people in low-income settings do not receive adequate treatment. (6). The principal determinant of treatment success in epilepsy is adherence to treatments. Nonadherence has been consistently linked to unfavorable consequences, including seizure recurrence, increased risk of mortality, frequent hospitalizations, and a higher likelihood of injuries and fractures. ((8–11,11–15)Verma et al., 2020a). Studies found that there is a high burden of anti-epileptic medication non-adherence among people with epilepsy in Ethiopia(17). The extent of nonadherence to antiseizure medications in Ethiopia shows substantial variation across different settings. Reported estimates range from relatively low levels in some urban areas to markedly higher proportions in other regions (16,17). The primary objective of antiseizure medication therapy is to achieve complete seizure control while minimizing adverse effects. Selection of an appropriate medication is typically guided by its effectiveness for specific seizure types and its safety profile. Evidence from studies conducted in Ethiopia and other settings has identified multiple factors linked to poor seizure control among individuals with epilepsy. These include demographic and clinical characteristics such as age at onset, sex, type of epilepsy, baseline seizure frequency, duration of illness and treatment, and the number of medications used. Additional contributors include underlying etiology, electroencephalographic abnormalities, coexisting medical conditions, negative beliefs about medications, substance use, nutritional factors, prior head injury, and inadequate adherence to prescribed therapy. (4,15,16,18–22). Evaluating seizure control and adherence to antiseizure medications is essential for optimizing treatment outcomes and enhancing the quality of life of individuals living with epilepsy. Evidence suggests that medication adherence is a key challenge in epilepsy management. Patients’ medication-taking behavior is often variable and can change over time, with nonadherence occurring either intentionally or unintentionally. Intentional nonadherence may be driven by psychological and perceptual factors, including concerns about side effects, doubts regarding the necessity of long-term therapy, or insufficient understanding of the disease and its treatment (18) . In low-income settings, additional systemic and social factors further widen the treatment gap, including cultural beliefs about illness, unequal access to healthcare services, limited availability of antiseizure medications, shortage of specialists such as neurologists, and the stigma associated with epilepsy, all of which contribute to the overall burden of the disease. The majority of the epileptic patients were nonadherent to their medications, and more than one-third of the patients had a negative medication belief (21). Low medication necessity belief, high medication concern belief, negative medication belief, comorbidity, and seizure encounters were predictors of medication nonadherence (6,18,19,21,23-25). Most previous studies employed a cross-sectional design to determine the prevalence of seizure control, ASM adherance and its associated factors. However, our study employed a case-control design, which enabled a direct comparison between individuals with good seizure control (controls) and those without (cases) based on ASMS non-adherence while controlling for factors such as sociodemographic characteristics, beliefs about antiseizure medications, comorbidities, Social drug use and other variables. This approach was particularly well-suited for examining multiple exposures in relation to a single outcome, namely seizure control. The outcome of this study provided valuable insights into how non-adherence to antiseizure medication, Social drug use, beliefs about medication, and comorbidities were associated with seizure control status. The findings offered critical information for clinicians, emphasizing the need for greater attention to the monitoring and evaluation of antiseizure medication adherence within healthcare services. Additionally, the study supported the adoption of standardized and contextualized adherence screening tools. It identified patients' beliefs about medication that could affect seizure control and highlighted the importance of screening and treating comorbid conditions. Based on the research findings, clinicians could recognize the need for health education to reinforce and encourage positive beliefs while discouraging negative ones, ultimately improving patients’ seizure control. This, in turn, helped policymakers design people-centered care (PCC) strategies to enhance overall health outcomes. Therefore, our study compared antiseizure medication Non-adherence and uncontrolled seizure while controlling for factors such as sociodemographic characteristics, beliefs about antiseizure medications, social drug use, comorbidities, adverse effects, and other variables in epileptic hospital patients in Addis Ababa, Ethiopia, by considering seizure freedom in one year preceding the study period. 2. Objective The objective of the study was to assess the association between uncontrolled seizure and Non-adherence to antiseizure medications(ASMs). 3. METHODS 3.1 Study Setting The study was conducted at Amanuel Mental Specialized Hospital and Eka Kotebe General Hospital. Amanuel Mental Specialized Hospital was established by Italian invaders in 1938 and has been serving as the only public specialized mental hospital in Ethiopia since its inception. Eka Kotebe General Hospital, located in the eastern part of Addis Ababa, the capital city of Ethiopia, was established as an extension of Amanuel Mental Specialized Hospital. It began operations in 2017 and became a stand-alone federal hospital in April 2020. These two hospitals are the major referral centers for mental health and epilepsy disorders. Approximately 2,478 epileptic patients had regular follow-ups at the outpatient department of Eka Kotebe General Hospital annually, while about 21,149 epileptic patients had regular follow-ups each year at the outpatient department of Amanuel Mental Specialized Hospital. Seizure management at Amanuel Mental Specialized Hospital is well-structured, with three outpatient rooms dedicated solely to the follow-up of epileptic patients, in addition to an emergency unit that manages acute seizure cases. Patients are treated with either monotherapy or polytherapy, using antiepileptic drugs such as Phenobarbital, Phenytoin, Carbamazepine, Valproic Acid, and Lamotrigine, with dosing frequencies of once daily (OD), twice daily (BID), or three times daily (TID). Follow-up intervals range from one to four months, depending on seizure control, medication adherence, and the availability of antiepileptic medications (ASM). Care is primarily provided by general practitioners, supported by trained nurses and overseen by consultant neurologists for complex cases. Similarly, Eka Kotebe General Hospital delivers essential epilepsy care through its three general medical outpatient rooms and emergency services. Patients receive similar treatment modalities with individualized dosing schedules and are followed up every one to three months, depending on clinical stability. Here too, general practitioners manage most cases, with assistance from nurses and input from consultant neurologists when necessary. 3.2 Study design An institution-based, age-matched case-control study was conducted in the outpatient neurology departments of the two selected hospitals. 3.3 Source population and Study population The source population consisted of all adult patients with known epilepsy who visited the neurologic departments of the two hospitals between October 2024 and March 2025. The study population consisted of individuals with epilepsy who met the inclusion criteria. Cases were defined as patients who reported at least one seizure episode within the last 12 months, while controls were those who had no seizure episodes during the same period. The treating physicians identified cases and controls during regular follow-up clinics. Inclusion criteria : adult patients aged 20 years and above, specifically adults with known epilepsy who had been on at least one antiepileptic medication in the past two years. Participants were also required to provide informed consent to participate in the study. Exclusion criteria : patients presenting with emergencies, such as those experiencing severe epileptic attacks at the time of the study, and patients who were unable to communicate. 3.4 Sample size determination The sample size included 70 cases and 140 controls, determined initially based on the formula for case-control study. The sample size, which included 70 cases and 140 controls (1:2 ratio), was determined based on the proportions and odds ratios reported in a previous study conducted in Ethiopia, which provided relevant epidemiological estimates for the outcome of interest. Key assumptions for the sample size calculation included: A confidence level of 95%, A power of 80% to detect a significant association. The 2:1 control-to-case ratio was chosen to enhance statistical power without substantially increasing resource needs. Additionally, the final sample size was adjusted to remain feasible within the limited time frame available for data collection. The sample size was proportionally allocated according to the patient flow at the two hospitals. 3.5 Sampling procedures: Cases (epileptic patients with seizures in the last 12 months) who fulfilled the inclusion criteria were identified by treating physicians and enrolled in the study by trained data collectors. Controls (epileptic patients who had not had seizures in the last 12 months) were also identified by treating physicians and enrolled in the study by trained data collectors. Treating physicians only assisted in identifying potential participants who met the inclusion criteria (cases and controls). Treating physicians had no role in administering the study interview. Study Participants was selected sequentially during their follow-up visits for medication refills until the predetermined daily sample size of 10 was attained. 3.6 Data collection tools and procedures Data were collected through an investigator-administered structured questionnaire. It included sections on sociodemographic characteristics, clinical history, comorbidities, social drug use, and MARS and BMQ scales.Trained healthcare professionals (two general practitionars and two psychiatric nurses) collected data. All team members were trained on the study protocol, ethical considerations, and data collection techniques. Data were collected in private examination rooms within the outpatient departments of the study hospitals during patients' routine visits. This ensured privacy and minimized interruptions. The data collection period spanned three months, from December 2024 to March 2025. The Medication Adherence Rating Scale (MARS) is a 10-item self-report tool that evaluates medication adherence across three domains: adherence behavior, attitudes toward medication, and perceived side effects. It assesses patients’ consistency in taking medication, their beliefs about treatment, and the extent to which side effects influence adherence. Each item is answered as “yes” or “no” and scored to reflect adherence, with higher total scores (ranging from 0 to 10) indicating better medication adherence (28,28–30). Adherence to ASMs was defined as a MARS score of ≥6, while non-adherence was defined as a MARS score of <6. (28,28–30) The Beliefs about Medicines Questionnaire (BMQ) was used to assess patients’ beliefs regarding their medications. It is a self-reported tool comprising two five-item scales that measure perceived necessity of medication for disease control and concerns about potential adverse effects, as well as two four-item scales assessing beliefs about medication harm and overuse. All items are rated on a five-point Likert scale ranging from strongly disagree to strongly agree. Subscale scores for necessity, concerns, harm, and overuse are obtained by summing the relevant items (19,21,31,32). The overall patient’s belief about their medication was determined by a necessity-concern differential, in which the patient’s belief was considered positive when the average sum of the 5-item patient’s medication necessity scale score exceeded the average of the 5-item patient’s medication concerns scale; otherwise, it was considered negative. 3.7 Quality control The questionnaire was prepared in English and then translated into the local language (Amharic) for data collection purposes. It was subsequently back-translated into English to ensure consistency by the principal investigator (PI) and a bilingual data collector. The questionnaire was pretested on 10 patients in a similar setup before actual data collection commenced to check the understandability of the questionnaire. Based on the feedback obtained during the pretest, minor modifications were made to improve the clarity of a few questions. Recall periods for patient-reported outcomes were 12 months to minimize recall bias; recall periods of 4 weeks was also tested. Regular supervision and periodic feedback sessions were conducted throughout the data collection period to maintain consistency of the data collection procedures and address any challenges encountered during data collection. The principal investigator and trained supervisors closely monitored the data collection process. 3.8 Data Management The collected data were reviewed for completeness and consistency immediately after collection. After checking the collected data for its completeness and accuracy, codes were given to the questionnaire; then, the data were entered into Epi-Info software to ensure a structured and error-minimized entry process. Then exported to Stata statistical software for analysis. Cleaning of the data occurred after data entry by running frequencies and checking for out of range responses. 3.9 Data Analysis Procedures Data were entered into EPI INFO, then exported to and analyzed using STATA. Descriptive statistics, such as frequency, percentage, mean, and standard deviation (SD), were employed to summarize the BMQ and MARS scales. Binary logistic regression was done for each variable to see the relationship between each factor with the outcome(one to one) and those with a level of significant (p value) less than or equal to 0.2 were taken for multivariate logistic regression. The association was presented as an adjusted odds ratio (AOR) with a 95% confidence interval(CI). A p-value of less than or equal to 0.05 was used to declare statistical significance. The model’s fitness was assessed using Hosmer-Lemeshow test, and the result indicated that the model adequately fit the data. 3.10 Operational definitions Uncontrolled seizure(cases) : defined as a patient reporting at least one seizure in the last 12 months. Controlled seizure (controls): defined as the absence of any seizure report in the preceding 12 months. Adherence to ASMs : MARS score of ≥6 (28,28–30) Non-adherence to ASMs: MARS score of <6 Seizure frequency refers to the number of seizure episodes or attacks that have occurred within the past 12 months. Seizure duration : This refers to the period (in years) that has elapsed since diagnosis. Types of seizure : This refers to the classification of seizures by healthcare professionals at the time of diagnosis as generalized tonic clonic, focal and other-unsecified. Comorbidity : any self reported chronic disease coexisting with epilepsy Adverse drug reaction : self-reported an unwanted, undesirable effect of a medication that occurs during the usual clinical use of an antiepileptic drug. Polytherapy: refers to the use of more than one AEDs for controlling seizure 3.11 Study Variables Dependent Variables : Uncontrol seizure recorded as Yes or No. Independent Variables : Non-Adherence to antiseizure medications, beliefs about antiseizure medications, comorbidities, social drug use, regular follow-up, adverse effects, and sociodemographic factors. 3.12 Ethical consideration Ethical clearance was obtained from the Addis Continental Institute of Public Health Research Ethics Committee before conducting the study. Permission to undertake the study was obtained from hospital officials. A written informed consent was obtained from each study participant. Patient privacy and confidentiality of information were maintained by creating a private space for interviews, and patient names were removed from the database, which was shared with others. Non-research persons did not access data. Participation was voluntary, and study participants could withdraw from the study at any time during the study process. 4. Results 4.1 Socio-demographic characteristics of the study participants In this study, the sociodemographic characteristics of patients with controlled and uncontrolled seizures were compared. Age distribution was similar, with each age group from 20–59 years accounting for 20.6% and those aged 60 and above for 17.6% in both groups. Males were more affected, representing 60.3% of cases and 61.8% of controls. Singles and married individuals were predominant, with 48.5% and 36.8% cases, and 43.4% and 46.3% among controlled seizure patients, respectively. Educational attainment was slightly higher in the controls group, with 27.9% completing grades 9–12 and 20.6% having college education, compared to 23.6% and 22.1% in the cases. Most patients lived far or very far from the hospital, with 29.4% and 32.3% in the cases, and 26.5% and 30.1% in the controls group living very far or outside Addis Ababa. Unemployment was more common among cases (57.4%) compared to controls(33.8%), who had higher rates of full-time (28.7%) and self-employment (30.1%). 4.2 Social drug use characteristics of study participants Substance use patterns were compared between patients with cases and controls. Regarding alcohol consumption, 54.4% of cases had never consumed alcohol, compared to 67.7% among controls. Recent alcohol use was more common in the cases, with 10.2% drinking at least once a month, 6.0% at least once a week, and 4.4% more than two days per week, while such frequent use was rare or absent in the controls. For khat consumption, 85.3% of cases and 90.5% of controls reported never using khat. Regular khat use (at least once a month or more) was slightly higher among cases (5.9%) than among controlled ones (1.4%). Regarding cigarette smoking, 80.9% of cases had never smoked, while 19.1% had smoked at some time but not within the last 12 months. In comparison, 95.6% of controls had never smoked, and 3.7% had smoked more than 12 months ago. Overall, alcohol, khat, and cigarette use were more frequent among patients with uncontrolled seizures(cases). 4.3 Clinical Characterstics of the the study participants Clinical characteristics were compared between patients with controlled and uncontrolled seizures. Among patients with cases, 35.3% had their first seizure before age 20, compared to 43.4% in the control group. A higher proportion of cases (70.6%) had more than five seizures before starting medication, compared to 54.4% among control group. Most patients in both groups had lived with epilepsy for more than 10 years, with 60.3% among cases and 69.1% among controls. Regarding duration of medication, 52.9% of cases and 64% of controls had been on treatment for more than 10 years. Comorbid conditions were more frequent among cases (41.2%) than controls (26.5%). Polytherapy was more common in cases (64.7%), whereas monotherapy was dominant in the control group (64%). Appointment intervals of two months were the most common in both groups, though a longer four-month interval was more frequent in control group (17% vs. 10.3%). Regular follow-up was significantly better in the controlled group (97.8% vs. 85.3%). Adverse effects were more commonly reported among cases (55.9%) compared to 28.7% of the controls. Generalized tonic-clonic (GTC) seizures were the most common type in both groups, representing 97% of cases and 89% of control group. 4.4 BMQ scale characterstic of the study participants The Beliefs about Medicines Questionnaire (BMQ) necessity scale revealed that the majority of participants had a strong belief in the importance of their antiseizure medication. Specifically, 70.6% agreed and 3.9% strongly agreed that their current health depends on their medication, while 75.5% agreed and 11.8% strongly agreed that without it, they would be very ill. Additionally, 79.4% agreed and 15.2% strongly agreed that their antiseizure medicine protects them from worsening health. The mean necessity score was 18.00 (SD = 2.76), with scores ranging from 9 to 24. When comparing cases and controls, a greater proportion of controls (90.4%) held a belief above the midpoint (strong necessity belief) compared to cases (78%). The odds of having a strong belief about medication necessity were significantly lower among cases than controls (OR = 0.37, 95% CI: 0.16–0.83, p = 0.017), suggesting that stronger belief in the necessity of medication is associated with better seizure control. On the BMQ concern scale , most participants expressed low concern about their antiseizure medication. For instance, 67.2% disagreed and 24.5% agreed that having to take antiseizure medication worries them, while 59.3% disagreed and 30.4% agreed that they worry about the long-term effects. The mean concern score was 12.94 (SD = 3.59), ranging from 5 to 25. Comparing groups, 41.2% of cases and 20.6% of controls had concern scores above the midpoint, indicating higher medication-related concerns among cases. The odds of having high concern were significantly greater among cases than controls (OR = 2.7, 95% CI: 1.42–5.10, p = 0.002). Regarding the overall necessity–concern differential , 64.7% of cases had a positive belief (necessity outweighing concern) compared to 94.1% of controls. Cases were significantly more likely to have a negative overall belief compared to controls (OR = 8.72, 95% CI: 3.65–20.83, p < 0.001), suggesting that stronger positive beliefs about medication are associated with better seizure control. On the Overuse Scale , most participants disagreed with statements suggesting excessive use of antiseizure medications. For example, 79.4% disagreed that doctors use too many antiseizure medicines, and 76.5% disagreed that natural remedies are safer than antiseizure medicines. The mean score for overuse was 9.84 (SD = 2.19), with scores ranging from 4 to 18. When comparing cases and controls, 39.7%% of cases and 14.7%% of controls scored above the midpoint, indicating stronger beliefs about the overuse of antiseizure medications among cases. The odds of having such beliefs were significantly higher in cases than controls (OR = 3.81, 95% CI: 1.93–7.53, p < 0.001), suggesting that uncontrolled seizure patients are more likely to believe in the overuse of medication. For the Harm Scale , most participants disagreed with the notion that antiseizure medications cause harm, with 97% disagreeing that people should stop treatment occasionally and 92.6% disagreeing that antiseizure medications do more harm than good. The mean score for harm was 7.84 (SD = 1.76), with scores ranging from 4 to 17. While there was no significant difference between cases and controls in terms of beliefs about harm, with no controlss scoring above the midpoint and only 5 cases scoring above the midpoint, these results suggest little belief in harm from antiseizure medications among the study participants. 4.5 Antiseizure drug adherance ( MARS ) score characteristics of study participants The table 5. compares medication adherence between cases (uncontrolled seizure) and controls (controlled seizure) based on various behavioral and attitudinal questions about antiseizure medication. The overall mean adherence score for all participants was 7.82 (SD = 1.71), with scores ranging from 1 to 10. The adherence status revealed that 22 cases (32.4%) were non-adherent, whereas 7 controls (5.2%) were non-adherent. The odds ratio for non-adherence was 8.81 (95% CI: 3.53–21.99, p = 0.000), indicating a significantly higher likelihood of non-adherence among cases with uncontrolled seizure. A higher percentage of cases reported forgetting to take their medication at various intervals. For instance, 73.53% of cases had ever forgotten to take their medication, compared to 48.5% of controls. Over the past 12 months, 61.76% of cases forgot, while only 9.55% of controls did. In the past 4 weeks, 29.41% of cases missed doses, compared to only 2.2% of controls. Carelessness and Stopping Medication: Cases were also more likely to be careless about taking their medication (19.12%) compared to controls (1.47%). Similarly, 26.47% of cases reported stopping their medication when feeling better, whereas only 0.74% of controls did. Additionally, 20.59% of cases stopped medication when feeling worse, compared to just 1.47% of controls. In terms of taking medication only when feeling sick, 1.47% of cases and 0.74% of controls answered affirmatively. When asked if it felt unnatural for their mind and body to be controlled by medication, 30.9% of cases and 17.7% of controls agreed. Regarding cognitive effects, 44.1% of cases and 45.6% of controls reported that their thoughts were clearer on medication. significant number of participants, both cases (95.6%) and controls (94.9%), agreed that staying on medication helped prevent illness. In terms of side effects, 19.1% of cases felt like a "zombie" on medication, compared to only 7.4% of controls. Additionally, 63.2% of cases reported feeling tired and sluggish on medication, compared to 31.6% of controls. 4.6 Medication regimen in the last 12 months medication regimens over the past 12 months revealed notable differences between cases (uncontrolled seizures) and controls (controlled seizures). Monotherapy with phenobarbitone (PHB) was more common among controls (n=44) than cases (n=7), suggesting its relative effectiveness in seizure control for some patients. Similarly, valproate (VPA) and carbamazepine (CBM) monotherapies were also more prevalent among controls than cases. In contrast, polytherapy—especially combinations involving PHB and VPAwas more frequently observed in the uncontrolled seizure group. For instance, the combination of PHB + VPA was the most common regimen among cases (n=16), followed by PHB + CBM (n=7) and PHB + PHT + VPA (n=5), which appeared exclusively in the uncontrolled group. This trend suggests that patients with uncontrolled seizures were more likely to be on multiple medications, possibly reflecting more severe or treatment-resistant epilepsy. 4.7 Factor associated with uncontrolled seizure and ASM adherence in a multivariate logistic regression model Non-adherence to medication was strongly associated with uncontrolled seizures. Participants who were non-adherent had an odds ratio (OR) of 8.81 (p < 0.000) for uncontrolled seizures(cases), which decreased to(AOR= 4.67, 95% CI:1.42-15.36, p =0.011) after adjusting for other variables, highlighting the critical role of Non adherence in seizure control .Monthly or more frequent alcohol consumption was associated with increased odds of cases. However, after adjusting for other factors, this relationship became less pronounced, with no statistically significant effect. History of smoking but not active smokers was a significant predictor of uncontrolled seizures. Those who had history of smkiong had a much higher likelihood of experiencing uncontrolled seizures (OR = 6.14, p = 0.001), and this remained significant even after adjusting for other factors (AOR = 7.63, 95% CI: 1.73-33, p = 0.007). Having more than five seizures before starting medication was initially associated with an increased likelihood of uncontrolled seizures (OR = 2.01, p =0.028), but this association lost significance after adjustment, suggesting other factors may be more influential. Participants on polytherapy (multiple medications) were more likely to have uncontrolled seizures than those on monotherapy (single medication), both before (OR = 3.25, p < 0.000) and after adjustment (AOR = 3.07, 1.36-6.94, p = 0.007). Regular follow-up care significantly reduced the odds of uncontrolled seizures (OR = 0.13, p = 0.003), although this effect was not maintained after adjusting for other factors. Experiencing adverse effects from medications was strongly associated with uncontrolled seizures (OR = 3.15, p = 0.00), but this association was no longer significant after adjustment. Beliefs about medication, such as concerns about overuse and necessity, influenced seizure control. A negative overall belief about medication was strongly associated with uncontrolled seizures (OR = 8.72, p = 0.000), and this effect remained significant after adjusting for other variables (AOR = 7.75, 95% CI: 1.9-30.82 p p = 0.004). 5. Discussion This study identified several key factors associated with uncontrolled seizures. Non-adherence to antiseizure medications emerged as a major contributor to poor seizure control. Cigarette smoking and being on polytherapy, rather than monotherapy, were also linked to higher likelihood of uncontrolled seizures. Additionally, participants who held negative beliefs about their medications were more likely to have uncontrolled seizures. In contrast, other factors such as alcohol use, presence of comorbidities, frequency of seizures before treatment, adverse effects, treatment beliefs (necessity, concerns, overuse), and regular follow-up did not show a meaningful association with seizure control after adjusting for other variables. Notably, Non-adherence to ASMs showed a strong and statistically significant association with uncontrolled seizures. Participants who were non-adherent had an odds ratio OR of 8.81 for experiencing uncontrolled seizures, which remained significant even after adjusting for other variables (AOR = 4.67 ). This finding aligns with multiple studies conducted in Ethiopia and South Africa, which similarly identified poor adherence to ASMs as a significant predictor of seizure recurrence ( 11 , 12 , 16 , 19 , 20 , 33 – 37 ). For example, A study done in Gonder ( 36 ), reported an AOR of 9.37 for seizure recurrence among patients with poor adherence. Similarly, A study done in Southern Ethiopia ( 33 ), found poor medication adherence to be significantly associated with uncontrolled seizures (AOR = 4.03). A study dne in Ayder Comprehensive specialized hospital ( 34 ), also reported a strong association (AOR = 11.52), while a sudy in Mezan tepi university teaching hospital ( 37 ) demonstrated that both medium (AOR = 5.4) and poor adherence (AOR = 8.16) were significantly linked to poor seizure control. Beliefs about medication, such as necessity, concerns, overuse and harm belief about ASM, influenced seizure control. A negative overall belief about medication was strongly associated with uncontrolled seizures (OR = 8.72), and this effect remained significant after adjusting for other variables (AOR = 7.75) which is similar with study done here and other countries. ( 19 , 21 , 26 ) Similarly, substance use particularly a history of cigarette smoking, even if not current was associated with poor seizure control (AOR = 7.63). This finding aligns with existing research that highlights the negative impact of lifestyle factors on seizure outcomes. Although alcohol use showed an association with uncontrolled seizures in the unadjusted analysis, it was not independently significant after controlling for confounders. However, other studies have found a significant association between alcohol use and uncontrolled seizures.( 26 ) Comorbidities were associated with uncontrolled seizures in the unadjusted analysis, this relationship did not remain statistically significant after adjusting for confounding variables. In contrast, other studies have reported a strong association between comorbid condition and uncontrolled seizure( 4 , 21 , 26 ). In our study, this discrepancy may be partly explained by underreporting, as some participants initially stated they had no comorbidities, but were later found to have additional illnesses, especially mental health conditions, upon reviewing patients data. The odds of uncontrolled seizures was 3 fold higher in epileptic patients on 2 or more ASMs (polytherapy) as compared with those on single ASMs (AOR = 3.07). This finding was supported by studies done in the United Kingdom (UK), Saudi Arabia, and Ethiopia which showed taking two or more ASMs was a predictor of uncontrolled seizure.( 7 , 11 , 12 , 22 , 38 ) The plausible explanation could be that patients on dual or polytherapy might have more pill burden, more drug-related side effects, and more financial expenses which predispose to poor ASM adherence. Polypharmacy causes drug–drug interactions and altered drugs metabolism. In addition, PWE on poly-therapy might have inherent intractable epilepsy, and might require other interventions. All these clinical scenarios could lead to uncontrolled seizure in epileptic patients. 6 .Strength and Limitation 6.1 Strength of the study A key strength of this study lies in its use of a case-control design, which allowed for a robust comparison between patients with and without seizure control while adjusting for multiple confounding variables, such as sociodemographic factors, medication beliefs, comorbidities, and substance use. The inclusion of validated tools like the Medication Adherence Rating Scale (MARS) ( 28 , 28 – 30 ) and the Beliefs about Medicines Questionnaire (BMQ) ( 19 , 21 , 31 , 32 ) further enhanced the reliability and validity of the findings. 6.2 Limitation of the study One limitation of this study is its reliance on self-reported measures to assess medication adherence and patient beliefs, which may be subject to recall bias and social desirability bias, potentially leading to an overestimation of adherence levels. To mitigate this limitation, the study used seizure control over a one-year period as an objective outcome measure, and by ensuring confidentiality and employing trained data collectors. Additionally, the relatively small sample size may have limited the statistical power to detect associations, particularly in the multivariable analysis. 7. Conclusion This study identified several factors associated with uncontrolled seizures among epileptic individuals on antiseizure medications (ASMs). Non-adherance to antiseizure medication (ASM), history of cigarette smoking, polytherapy, and negative beliefs about medications were significantly linked to a higher risk of uncontrolled seizures. Non-adherence was the strongest predictor, emphasizing the vital role of consistent medication use. Although alcohol use, seizure frequency before treatment, and adverse drug effects showed associations in unadjusted analysis, they were not independently significant after adjusting for confounders. Overall, these results highlight that beyond clinical treatment, patient behavior and beliefs greatly influence seizure control outcomes. 8.Recommendations To improve seizure control and ASM adherence, interventions should focus on enhancing patient education, addressing misconceptions about long-term medication use, and providing regular reminders and counseling. Strategies may include patient education programs, reminder systems, involvement of community health workers, and policy-level actions. Healthcare providers should also assess and address substance use, including smoking, and offer support for cessation. Given the challenges of polytherapy, treatment plans should be personalized to meet individual patient needs. Strengthening follow-up visits with structured adherence counseling, psychoeducation, and family or community engagement can help overcome behavioral and psychological barriers. Future longitudinal research is needed to examine the causal impact of these interventions on adherence, seizure control, and overall patient outcomes. Abbreviations ACIPH Addis Continental Institute of Public Health AEDs Anti-eEpileptic Drugs ASMs Anti -Seizure Medications MARS Medication Adherence Rating Scale (MARS) BMQ Belief about AntiSeizure Medication Questioner(BMQ) PCC People-Centered Care PWE People With Epilepsy WHO World Health Organization Declarations Acknowledgment I would like to thank my advisor, Prof. Yemane Berhane, for his unreserved advice and constructive comments, as well as the Addis Continental Institute of Public Health for providing me with this opportunity Ethics approval and consent to participate Ethical clearance was obtained from the Addis Continental Institute of Public Health Research Ethics Committee before conducting the study. Permission to undertake the study was obtained from hospital officials. A written informed consent was obtained from each study participant. Patient privacy and confidentiality of information were maintained by creating a private space for interviews, and patient names were removed from the database, which was shared with others. Non-research persons did not access data. Participation was voluntary, and study participants could withdraw from the study at any time during the study process. Consent for publication Not applicable Availability of data and materials The datasets used and analyzed during the current study are not publicly available due to ethical restriction and personal data protections but are available from the corresponding author on reasonable request. Competing interests The authors declare that they have no competing interests. Funding This study was self-funded. The authors received no external funding, and no funding body had any role in the study design, data collection, analysis, interpretation, or manuscript preparation. Authors' contributions Dr. Betsadkan Kebede conceived and conducted the research and drafted the manuscript. Prof. Yemane Berhane supervised the study, provided methodological guidance. Data were collected by trained data collectors. All authors critically reviewed and approved the final manuscript. References Fisher RS, Acevedo C, Arzimanoglou A, Bogacz A, Cross JH, Elger CE, et al. ILAE Official Report: A practical clinical definition of epilepsy. Epilepsia. 2014 Apr;55(4):475–82. ref 1 . Fisher R.S. concdefofepil USA 2014. Beghi E, Giussani G, Nichols E, Abd-Allah F, Abdela J, Abdelalim A, et al. Global, regional, and national burden of epilepsy, 1990–2016: a systematic analysis for the Global Burden of Disease Study 2016. Lancet Neurol. 2019 Apr;18(4):357–75. Bekele F, Gezimu W. Treatment outcome and associated factors among epileptic patients at ambulatory clinic of Mettu Karl Comprehensive Specialized Hospital: A cross-sectional study. SAGE Open Med. 2022 Jan;10:20503121221125149. Epilepsy in the WHO Eastern Mediterranean region: bridging the gap. Cairo, Egypt: World Health Organization, Regional Office for the Eastern Mediterranean; 2010. Espinosa-Jovel C, Toledano R, Aledo-Serrano Á, García-Morales I, Gil-Nagel A. Epidemiological profile of epilepsy in low income populations. Seizure. 2018 Mar;56:67–72. Moran NF, Poole K, Bell G, Solomon J, Kendall S, McCarthy M, et al. Epilepsy in the United Kingdom: seizure frequency and severity, anti-epileptic drug utilization and impact on life in 1652people with epilepsy. Bekele F. 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 Aug;Volume 16:1865–73. Golyala A, Kwan P. Drug development for refractory epilepsy: The past 25 years and beyond. Seizure. 2017 Jan;44:147–56. Hamdy NA, Alamgir MJ, Mohammad EGE, Khedr MH, Fazili S. Profile of Epilepsy in a Regional Hospital in Al Qassim , Saudi Arabia. Int J Health Sci. 2014 Sep;8(3):247–55. Mohammed A, Mishore K, Tafesse T, Jambo A, Husen A, Alemu A. Seizure Remission and Its Predictors Among Epileptic Patients on Follow-Up at Public Hospitals in Eastern Ethiopia: A Retrospective Cohort Study. Int J Gen Med. 2023 Nov;Volume 16:5343–54. Nasir BB, Yifru YM, Engidawork E, Gebrewold MA, Woldu MA, Berha AB. Antiepileptic Drug Treatment Outcomes and Seizure-Related Injuries Among Adult Patients with Epilepsy in a Tertiary Care Hospital in Ethiopia. Patient Relat Outcome Meas. 2020 Apr;Volume 11:119–27. Shumet S, Wondie M, Ayano G, Asfaw H, Kassew T, Mesafint G. Antiepileptic Drug Adherence and Its Associated Factors among Epilepsy Patients on Follow-ups at Amanuel Mental Specialized Hospital, Ethiopia. Ethiop J Health Sci. 2022 Sep 20;32(5):913–22. Tan X, Patel I, Chang J. Review of the four item Morisky Medication Adherence Scale (MMAS-4) and eight item Morisky Medication Adherence Scale (MMAS-8). Innov Pharm [Internet]. 2014 Jan 1 [cited 2025 May 26];5(3). Available from: https://pubs.lib.umn.edu/index.php/innovations/article/view/347 Zewudie A, Mamo Y, Feyissa D, Yimam M, Mekonen G, Abdela A. Epilepsy Treatment Outcome and Its Predictors among Ambulatory Patients with Epilepsy at Mizan-Tepi University Teaching Hospital, Southwest Ethiopia. Neurol Res Int. 2020 Apr 8;2020:1–8. Hasiso TY, Desse TA. Adherence to Treatment and Factors Affecting Adherence of Epileptic Patients at Yirgalem General Hospital, Southern Ethiopia: A Prospective Cross-Sectional Study. Romigi A, editor. PLOS ONE. 2016 Sep 29;11(9):e0163040. Belayneh Z, Mekuriaw B. A systematic review and meta-analysis of anti-epileptic medication non-adherence among people with epilepsy in Ethiopia. Arch Public Health. 2020 Dec;78(1):23. Chapman SCE, Horne R, Chater A, Hukins D, Smithson WH. Patients’ perspectives on antiepileptic medication: Relationships between beliefs about medicines and adherence among patients with epilepsy in UK primary care. Epilepsy Behav. 2014 Feb;31:312–20. Egenasi C, Steinberg W, Raubenheimer J. Beliefs about medication, medication adherence and seizure control among adult epilepsy patients in Kimberley, South Africa. South Afr Fam Pract. 2015 Sep 3;57(5):326–32. Kariuki SM. Electroencephalographic features of convulsive epilepsy in Africa: A multicentre study of prevalence, pattern and associated factors. Niriayo YL, Mamo A, Gidey K, Demoz GT. Medication Belief and Adherence among Patients with Epilepsy. Behav Neurol. 2019 Apr 23;2019:1–7. Zena D, Tadesse A, Bekele N, Yaregal S, Sualih N, Worku E. Seizure control and its associated factors among epileptic patients at Neurology Clinic, University of Gondar hospital, Northwest Ethiopia. SAGE Open Med. 2022 Jan;10:20503121221100612. Bhalla D, Lotfalinezhad E, Amini F, Delbari A, Fadaye-Vatan R, Saii V, et al. Medication Beliefs and Adherence to Antiseizure Medications. Di Lazzaro V, editor. Neurol Res Int. 2020 Oct 23;2020:1–9. Dilles T, Mortelmans L, Loots E, Sabbe K, Feyen H, Wauters M, et al. People-centered care and patients’ beliefs about medicines and adherence: A cross-sectional study. Heliyon. 2023 May;9(5):e15795. Wei L, Champman S, Li X, Li X, Li S, Chen R, et al. Beliefs about medicines and non-adherence in patients with stroke, diabetes mellitus and rheumatoid arthritis: a cross-sectional study in China. BMJ Open. 2017 Oct;7(10):e017293. Niriayo YL, Mamo A, Kassa TD, Asgedom SW, Atey TM, Gidey K, et al. Treatment outcome and associated factors among patients with epilepsy. Sci Rep. 2018 Nov 26;8(1):17354. Verma A, K K, Kumar A. Relationships Between Beliefs about Medication, Seizure Control and Adherence to Antiepileptic Drugs Among People with Epilepsy. Arch Clin Med Case Rep [Internet]. 2020 [cited 2025 Apr 26];04(06). Available from: http://www.fortunejournals.com/articles/relationships-between-beliefs-about-medication-seizure-control-and-adherence-to-antiepileptic-drugs-among-people-with-epilepsy.html Fialko L, Garety PA, Kuipers E, Dunn G, Bebbington PE, Fowler D, et al. A large-scale validation study of the Medication Adherence Rating Scale (MARS). Schizophr Res. 2008;100(1-3):53-9. Owie GO, Olotu SO, James BO. Reliability and validity of the Medication Adherence Rating Scale in a cohort of patients with schizophrenia from Nigeria. Trends Psychiatry Psychother. 2018 May 14;40(2):85–92. Ross B, Wang D, Xi C, Pan Y, Zhou L, Yang X, et al. T217. MEDICATION ADHERENCE AND ITS CORRELATES AMONG PATIENTS WITH RECURRENT SCHIZOPHRENIA: A LARGE- SCALE STUDY IN CHINA. Nakhutina L, Gonzalez JS, Margolis SA, Spada A, Grant A. Adherence to antiepileptic drugs and beliefs about medication among predominantly ethnic minority patients with epilepsy. Epilepsy Behav. 2011 Nov;22(3):584–6. Porteous T, Francis J, Bond C, Hannaford P. Temporal stability of beliefs about medicines: Implications for optimising adherence. Patient Educ Couns. 2010 May;79(2):225–30. Ahmed M, Nasir M, Yalew S, Getahun F, Getahun F. Assessment of Treatment Outcome and Its Associated Factors among Adult Epileptic Patients in Public Hospitals in the Southern Ethiopia: A Multi-center Cross-sectional Study. Ethiop J Health Sci [Internet]. 2023 Apr 6 [cited 2025 Apr 26];33(2). Available from: https://www.ajol.info/index.php/ejhs/article/view/245330 Niriayo YL, Mamo A, Kassa TD, Asgedom SW, Atey TM, Gidey K, et al. Treatment outcome and associated factors among patients with epilepsy. Sci Rep. 2018 Nov 26;8(1):17354. Rawat C, Guin D, Talwar P, Grover S, Baghel R, Kushwaha S, et al. outcome in North Indian patients. Zena D, Tadesse A, Bekele N, Yaregal S, Sualih N, Worku E. Seizure control and its associated factors among epileptic patients at Neurology Clinic, University of Gondar hospital, Northwest Ethiopia. SAGE Open Med. 2022 Jan;10:20503121221100612. Zewudie A, Mamo Y, Feyissa D, Yimam M, Mekonen G, Abdela A. Epilepsy Treatment Outcome and Its Predictors among Ambulatory Patients with Epilepsy at Mizan-Tepi University Teaching Hospital, Southwest Ethiopia. Neurol Res Int. 2020 Apr 8;2020:1–8. Hamdy NA, Alamgir MJ, Mohammad EGE, Khedr MH, Fazili S. Profile of Epilepsy in a Regional Hospital in Al Qassim, Saudi Arabia. Saudi Arab. Tables Tables 1 to 8 are available in the supplementary files section Additional Declarations No competing interests reported. Supplementary Files Englishversionquestionnaireandconsentfor1.docx Tables.docx Cite Share Download PDF Status: Under Review Version 1 posted Reviewers invited by journal 06 May, 2026 Editor assigned by journal 06 May, 2026 Editor invited by journal 20 Apr, 2026 Submission checks completed at journal 20 Apr, 2026 First submitted to journal 20 Apr, 2026 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-9281210","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":637825321,"identity":"b56660c4-5260-4586-8116-63cbc2bcc29b","order_by":0,"name":"Betsadkan Kebede","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA4UlEQVRIiWNgGAWjYBACAzDJlgAkmA8ACQkZIrQww7SACQkeUrTwgG0krMWcvf/whx9lafLm/Gc+v7pRY8HDwH746AZ8Wix7DrNJ9pzLMdzZcHabdc4xoMN40tJu4HXYjWQ2Bt62CsYNB3u3GeewAbVI8Jjh13L/MfPHv20V9hsO8zwzzvlHjJYbzAzSvG05iRuO8TA/zm0jQotlT7KZtMy5tOQNZ9jMmHP7JHjYCPnFnP3g449vypJtN5w//Phzzrc6OX72w8fwakEGbBJgkljlIMD8gRTVo2AUjIJRMHIAAAb0R3ZlcS6OAAAAAElFTkSuQmCC","orcid":"","institution":"Eka Kotebe General Hospital","correspondingAuthor":true,"prefix":"","firstName":"Betsadkan","middleName":"","lastName":"Kebede","suffix":""},{"id":637825322,"identity":"60cc1d26-4501-43b1-85ff-2a00f63f5926","order_by":1,"name":"Yemane Berhane","email":"","orcid":"","institution":"Addis Continental Institute of Public Health","correspondingAuthor":false,"prefix":"","firstName":"Yemane","middleName":"","lastName":"Berhane","suffix":""}],"badges":[],"createdAt":"2026-03-31 14:25:29","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9281210/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9281210/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":109330723,"identity":"4bde5afa-cd6c-4152-8e0a-d6666ec51ea0","added_by":"auto","created_at":"2026-05-15 16:08:01","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":475904,"visible":true,"origin":"","legend":"\u003cp\u003eSee image above for figure legend.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-9281210/v1/19ceb0435b9184db091215d1.png"},{"id":109405344,"identity":"9bfe6b29-9cbc-4e16-8fbb-1d9346b24433","added_by":"auto","created_at":"2026-05-17 13:17:21","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":538926,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9281210/v1/1a89ce68-e060-42c6-b0b3-810abda165d7.pdf"},{"id":109405854,"identity":"9c38d84f-567e-427a-9b18-47cd092c0715","added_by":"auto","created_at":"2026-05-17 13:20:40","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":31003,"visible":true,"origin":"","legend":"","description":"","filename":"Englishversionquestionnaireandconsentfor1.docx","url":"https://assets-eu.researchsquare.com/files/rs-9281210/v1/157f5f901b48bb59a4ca00eb.docx"},{"id":109330726,"identity":"96b7d773-9bc2-44d7-a640-3630d19a6f39","added_by":"auto","created_at":"2026-05-15 16:08:01","extension":"docx","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":54287,"visible":true,"origin":"","legend":"","description":"","filename":"Tables.docx","url":"https://assets-eu.researchsquare.com/files/rs-9281210/v1/c37b0254f1d02d99b279c1ea.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Seizure control and adherence to antiseizure medications among epileptic hospital patients in Addis Ababa, Ethiopia","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eEpilepsy is a chronic neurological condition marked by a persistent tendency to develop recurrent seizures, along with associated neurobiological, cognitive, psychological, and social consequences.(1) The diagnosis of epilepsy can be established after the occurrence of at least one unprovoked seizure, which is defined as a brief episode of clinical signs and/or symptoms resulting from abnormal, excessive, or synchronized electrical activity in the brain. (2) \u0026nbsp;Epilepsy affects populations worldwide, but its distribution is markedly uneven, with the majority of cases occurring in low- and middle-income countries, including Ethiopia. Globally, it was estimated that approximately 45.9 million individuals were living with active epilepsy in 2016.\u0026nbsp;(1,1,3–7)\u003c/p\u003e\n\u003cp\u003eEpilepsy is considered a treatable condition with high rates of therapeutic response. Antiseizure medications remain the cornerstone of treatment and are effective in achieving seizure control for a substantial proportion of individuals. However, despite the availability of effective therapies, a large number of people in low-income settings do not receive adequate treatment. \u0026nbsp;(6). The principal determinant of treatment success in epilepsy is adherence to treatments. Nonadherence has been consistently linked to unfavorable consequences, including seizure recurrence, increased risk of mortality, frequent hospitalizations, and a higher likelihood of injuries and fractures. ((8–11,11–15)Verma et al., 2020a).\u003c/p\u003e\n\u003cp\u003eStudies found that there is a high burden of anti-epileptic medication non-adherence among people with epilepsy in Ethiopia(17). \u0026nbsp; The extent of nonadherence to antiseizure medications in Ethiopia shows substantial variation across different settings. Reported estimates range from relatively low levels in some urban areas to markedly higher proportions in other regions (16,17).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe primary objective of antiseizure medication therapy is to achieve complete seizure control while minimizing adverse effects. Selection of an appropriate medication is typically guided by its effectiveness for specific seizure types and its safety profile. Evidence from studies conducted in Ethiopia and other settings has identified multiple factors linked to poor seizure control among individuals with epilepsy. These include demographic and clinical characteristics such as age at onset, sex, type of epilepsy, baseline seizure frequency, duration of illness and treatment, and the number of medications used. Additional contributors include underlying etiology, electroencephalographic abnormalities, coexisting medical conditions, negative beliefs about medications, substance use, nutritional factors, prior head injury, and inadequate adherence to prescribed therapy. (4,15,16,18–22).\u003c/p\u003e\n\u003cp\u003eEvaluating seizure control and adherence to antiseizure medications is essential for optimizing treatment outcomes and enhancing the quality of life of individuals living with epilepsy. Evidence suggests that medication adherence is a key challenge in epilepsy management. Patients’ medication-taking behavior is often variable and can change over time, with nonadherence occurring either intentionally or unintentionally. Intentional nonadherence may be driven by psychological and perceptual factors, including concerns about side effects, doubts regarding the necessity of long-term therapy, or insufficient understanding of the disease and its treatment (18) .\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eIn low-income settings, additional systemic and social factors further widen the treatment gap, including cultural beliefs about illness, unequal access to healthcare services, limited availability of antiseizure medications, shortage of specialists such as neurologists, and the stigma associated with epilepsy, all of which contribute to the overall burden of the disease. The majority of the epileptic patients were nonadherent to their medications, and more than one-third of the patients had a negative medication belief (21). Low medication necessity belief, high medication concern belief, negative medication belief, comorbidity, and seizure encounters were predictors of medication nonadherence (6,18,19,21,23-25).\u003c/p\u003e\n\u003cp\u003eMost previous studies employed a cross-sectional design to determine the prevalence of seizure control, ASM adherance and its associated factors. However, our study employed a case-control design, which enabled a direct comparison between individuals with good seizure control (controls) and those without (cases) based on ASMS non-adherence while controlling for factors such as sociodemographic characteristics, beliefs about antiseizure medications, comorbidities, Social drug use and other variables. This approach was particularly well-suited for examining multiple exposures in relation to a single outcome, namely seizure control.\u003c/p\u003e\n\u003cp\u003eThe outcome of this study provided valuable insights into how non-adherence to antiseizure medication, Social drug use, beliefs about medication, and comorbidities were associated with seizure control status. The findings offered critical information for clinicians, emphasizing the need for greater attention to the monitoring and evaluation of antiseizure medication adherence within healthcare services. Additionally, the study supported the adoption of standardized and contextualized adherence screening tools. It identified patients' beliefs about medication that could affect seizure control and highlighted the importance of screening and treating comorbid conditions. Based on the research findings, clinicians could recognize the need for health education to reinforce and encourage positive beliefs while discouraging negative ones, ultimately improving patients’ seizure control. This, in turn, helped policymakers design people-centered care (PCC) strategies to enhance overall health outcomes.\u003c/p\u003e\n\u003cp\u003eTherefore, our study compared antiseizure medication Non-adherence and uncontrolled seizure while controlling for factors such as sociodemographic characteristics, beliefs about antiseizure medications, social drug use, comorbidities, adverse effects, and other variables in epileptic hospital patients in Addis Ababa, Ethiopia, by considering seizure freedom in one year preceding the study period.\u003c/p\u003e"},{"header":"2. Objective","content":"\u003cp\u003eThe objective of the study was to assess the association between uncontrolled seizure and Non-adherence to antiseizure medications(ASMs).\u003c/p\u003e"},{"header":"3. METHODS","content":"\u003cp\u003e\u003cstrong\u003e3.1 \u0026nbsp; \u0026nbsp;Study Setting\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study was conducted at Amanuel Mental Specialized Hospital and Eka Kotebe General Hospital. Amanuel Mental Specialized Hospital was established by Italian invaders in 1938 and has been serving as the only public specialized mental hospital in Ethiopia since its inception. Eka Kotebe General Hospital, located in the eastern part of Addis Ababa, the capital city of Ethiopia, was established as an extension of Amanuel Mental Specialized Hospital. It began operations in 2017 and became a stand-alone federal hospital in April 2020. These two hospitals are the major referral centers for mental health and epilepsy disorders. Approximately 2,478 epileptic patients had regular follow-ups at the outpatient department of Eka Kotebe General Hospital annually, while about 21,149 epileptic patients had regular follow-ups each year at the outpatient department of Amanuel Mental Specialized Hospital.\u003c/p\u003e\n\u003cp\u003eSeizure management at Amanuel Mental Specialized Hospital is well-structured, with three outpatient rooms dedicated solely to the follow-up of epileptic patients, in addition to an emergency unit that manages acute seizure cases. Patients are treated with either monotherapy or polytherapy, using antiepileptic drugs such as Phenobarbital, Phenytoin, Carbamazepine, Valproic Acid, and Lamotrigine, with dosing frequencies of once daily (OD), twice daily (BID), or three times daily (TID). Follow-up intervals range from one to four months, depending on seizure control, medication adherence, and the availability of antiepileptic medications (ASM). Care is primarily provided by general practitioners, supported by trained nurses and overseen by consultant neurologists for complex cases.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eSimilarly, Eka Kotebe General Hospital delivers essential epilepsy care through its three general medical outpatient rooms and emergency services. Patients receive similar treatment modalities with individualized dosing schedules and are followed up every one to three months, depending on clinical stability. Here too, general practitioners manage most cases, with assistance from nurses and input from consultant neurologists when necessary.\u003c/p\u003e\n\u003cp id=\"_Toc199231829\"\u003e\u003cstrong\u003e3.2\u0026nbsp; \u0026nbsp;Study design\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;An institution-based, age-matched case-control study was conducted in the outpatient neurology departments of the two selected hospitals.\u003c/p\u003e\n\u003cp id=\"_Toc199231830\"\u003e\u003cstrong\u003e3.3\u0026nbsp; \u0026nbsp;Source population and Study population\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe source population consisted of all adult patients with known epilepsy who visited the neurologic departments of the two hospitals between October 2024 and March 2025. The study population consisted of individuals with epilepsy who met the inclusion criteria. Cases were defined as patients who reported at least one seizure episode within the last 12 months, while controls were those who had no seizure episodes during the same period. The treating physicians identified cases and controls during regular follow-up clinics.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eInclusion criteria\u003c/strong\u003e: adult patients aged 20 years and above, specifically adults with known epilepsy who had been on at least one antiepileptic medication in the past two years. Participants were also required to provide informed consent to participate in the study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eExclusion criteria\u003c/strong\u003e: patients presenting with emergencies, such as those experiencing severe epileptic attacks at the time of the study, and patients who were unable to communicate.\u003c/p\u003e\n\u003cp id=\"_Toc199231831\"\u003e\u003cstrong\u003e3.4 Sample size determination\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe sample size included 70 cases and 140 controls, determined initially based on the formula for case-control study. \u0026nbsp;The sample size, which included 70 cases and 140 controls (1:2 ratio), was determined based on the proportions and odds ratios reported in a previous study conducted in Ethiopia, which provided relevant epidemiological estimates for the outcome of interest. Key assumptions for the sample size calculation included: A confidence level of 95%, A power of 80% to detect a significant association. The 2:1 control-to-case ratio was chosen to enhance statistical power without substantially increasing resource needs. Additionally, the final sample size was adjusted to remain feasible within the limited time frame available for data collection. The sample size was proportionally allocated according to the patient flow at the two hospitals.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.5 Sampling procedures:\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCases (epileptic patients with seizures in the last 12 months) who fulfilled the inclusion criteria were identified by treating physicians and enrolled in the study by trained data collectors. Controls (epileptic patients who had not had seizures in the last 12 months) were also identified by treating physicians and enrolled in the study by trained data collectors. Treating physicians only assisted in identifying potential participants who met the inclusion criteria (cases and controls). Treating physicians had no role in administering the study interview. Study Participants was selected sequentially during their follow-up visits for medication refills until the predetermined daily sample size of 10 was attained.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.6\u0026nbsp; \u0026nbsp;\u0026nbsp;Data collection tools and procedures\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eData were collected through an investigator-administered structured questionnaire. It included sections on sociodemographic characteristics, clinical history, comorbidities, social drug use, and MARS and BMQ scales.Trained healthcare professionals (two general practitionars and two psychiatric nurses) collected data. All team members were trained on the study protocol, ethical considerations, and data collection techniques.\u0026nbsp;Data were collected in private examination rooms within the outpatient departments of the study hospitals during patients\u0026apos; routine visits. This ensured privacy and minimized interruptions. The data collection period spanned three months, from December 2024 to March 2025. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe Medication Adherence Rating Scale (MARS) is a 10-item self-report tool that evaluates medication adherence across three domains: adherence behavior, attitudes toward medication, and perceived side effects. It assesses patients\u0026rsquo; consistency in taking medication, their beliefs about treatment, and the extent to which side effects influence adherence. Each item is answered as \u0026ldquo;yes\u0026rdquo; or \u0026ldquo;no\u0026rdquo; and scored to reflect adherence, with higher total scores (ranging from 0 to 10) indicating better medication adherence (28,28\u0026ndash;30). Adherence to ASMs was defined as a MARS score of \u0026ge;6, while non-adherence was defined as a MARS score of \u0026lt;6. (28,28\u0026ndash;30)\u003c/p\u003e\n\u003cp\u003eThe Beliefs about Medicines Questionnaire (BMQ) was used to assess patients\u0026rsquo; beliefs regarding their medications. It is a self-reported tool comprising two five-item scales that measure perceived necessity of medication for disease control and concerns about potential adverse effects, as well as two four-item scales assessing beliefs about medication harm and overuse. All items are rated on a five-point Likert scale ranging from strongly disagree to strongly agree. Subscale scores for necessity, concerns, harm, and overuse are obtained by summing the relevant items\u0026nbsp;(19,21,31,32). The overall patient\u0026rsquo;s belief about their medication was determined by a necessity-concern differential, in which the patient\u0026rsquo;s belief was considered positive when the average sum of the 5-item patient\u0026rsquo;s medication necessity scale score exceeded the average of the 5-item patient\u0026rsquo;s medication concerns scale; otherwise, it was considered negative.\u003c/p\u003e\n\u003cp id=\"_Toc199231834\"\u003e\u003cstrong\u003e3.7 Quality control\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe questionnaire was prepared in English and then translated into the local language (Amharic) for data collection purposes. It was subsequently back-translated into English to ensure consistency\u0026nbsp;by the principal investigator (PI) and a bilingual data collector. The questionnaire was pretested on 10 patients in a similar setup before actual data collection commenced to check the understandability of the questionnaire. Based on the feedback obtained during the pretest, minor modifications were made to improve the clarity of a few questions.\u0026nbsp;Recall periods for patient-reported outcomes were 12 months to minimize recall bias; recall periods of 4 weeks was also tested. Regular supervision and periodic feedback sessions were conducted throughout the data collection period to maintain consistency of the data collection procedures and address any challenges encountered during data collection.\u0026nbsp;The principal investigator and trained supervisors closely monitored the data collection process.\u003c/p\u003e\n\u003cp\u003e3.8\u0026nbsp;\u003cstrong\u003e\u0026nbsp;Data Management\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe collected data \u003cstrong\u003ewere\u003c/strong\u003ereviewed for \u003cstrong\u003ecompleteness and consistency\u003c/strong\u003e immediately after collection. After checking the collected data for its completeness and accuracy, codes were given to the questionnaire; then, the data \u003cstrong\u003ewere\u003c/strong\u003eentered into \u003cstrong\u003eEpi-Info software\u003c/strong\u003e to ensure a structured and error-minimized entry process. Then exported to \u003cstrong\u003eStata\u0026nbsp;\u003c/strong\u003estatistical software for analysis. \u0026nbsp;Cleaning of the data occurred after data entry by running frequencies and checking for out of range responses.\u003c/p\u003e\n\u003cp\u003e3.9\u0026nbsp;\u003cb id=\"_Toc199231836\"\u003e\u0026nbsp;Data Analysis Procedures\u003c/b\u003e\u003c/p\u003e\n\u003cp\u003eData were entered into EPI INFO, then exported to and analyzed using STATA. Descriptive statistics, such as frequency, percentage, mean, and standard deviation (SD), were employed to summarize the BMQ and MARS scales. Binary logistic regression was done for each variable to see the relationship between each factor with the outcome(one to one) and those with a level of significant (p value) less than or equal to 0.2 were taken for multivariate logistic regression. The association was presented as an adjusted odds ratio (AOR) with a 95% confidence interval(CI). A p-value of less than or equal to 0.05 was used to declare statistical significance. The model\u0026rsquo;s fitness was assessed using Hosmer-Lemeshow test, and the result indicated that the model adequately fit the data.\u003c/p\u003e\n\u003cp id=\"_Toc199231837\"\u003e3.10 \u003cstrong\u003eOperational definitions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eUncontrolled seizure(cases)\u003c/strong\u003e: defined as a patient reporting at least one seizure in the last 12 months.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eControlled seizure (controls):\u003c/strong\u003e defined as the absence of any seizure report in the preceding 12 months.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAdherence to ASMs\u003c/strong\u003e: MARS score of \u0026ge;6 \u0026nbsp;(28,28\u0026ndash;30)\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eNon-adherence to ASMs:\u003c/strong\u003e MARS score of \u0026lt;6\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSeizure frequency\u003c/strong\u003e refers to the number of seizure episodes or attacks that have occurred within the past 12 months.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSeizure duration\u003c/strong\u003e: This refers to the period (in years) that has elapsed since diagnosis.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTypes of seizure\u003c/strong\u003e: This refers to the classification of seizures by healthcare professionals at the time of diagnosis as generalized tonic clonic, focal and other-unsecified.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eComorbidity\u003c/strong\u003e: \u0026nbsp;any self reported chronic disease coexisting with epilepsy\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAdverse drug reaction\u003c/strong\u003e: self-reported \u0026nbsp;an unwanted, undesirable effect of a medication that occurs during the usual clinical use of an antiepileptic drug.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePolytherapy:\u003c/strong\u003e refers to the use of more than one AEDs for controlling seizure\u003c/p\u003e\n\u003cp id=\"_Toc199231838\"\u003e3.11 \u003cstrong\u003eStudy Variables\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDependent Variables\u003c/strong\u003e: Uncontrol seizure recorded as Yes or No.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eIndependent Variables\u003c/strong\u003e: Non-Adherence to antiseizure medications, beliefs about antiseizure medications, comorbidities, social drug use, regular follow-up, adverse effects, and sociodemographic factors.\u003c/p\u003e\n\u003cp id=\"_Toc199231839\"\u003e\u003cstrong\u003e3.12 \u003c/strong\u003e\u003cstrong\u003eEthical consideration\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eEthical clearance \u003cstrong\u003ewas\u003c/strong\u003eobtained from the Addis Continental Institute of Public Health Research Ethics Committee before conducting the study. Permission to undertake the study \u003cstrong\u003ewas\u003c/strong\u003eobtained from hospital officials. A written informed consent \u003cstrong\u003ewas\u003c/strong\u003eobtained from each study participant. Patient privacy and confidentiality of information \u003cstrong\u003ewere\u003c/strong\u003e maintained by creating a private space for interviews, and patient names \u003cstrong\u003ewere\u003c/strong\u003eremoved from the database, which \u003cstrong\u003ewas\u003c/strong\u003e shared with others. Non-research persons did not access data. Participation \u003cstrong\u003ewas\u003c/strong\u003evoluntary, and study participants \u003cstrong\u003ecould\u003c/strong\u003e withdraw from the study at any time during the study process.\u003c/p\u003e"},{"header":"4. Results","content":"\u003ch2\u003e\u003cstrong\u003e4.1 Socio-demographic characteristics of the study participants\u003c/strong\u003e\u003c/h2\u003e\n\u003cp\u003eIn this study, the sociodemographic characteristics of patients with controlled and uncontrolled seizures were compared. Age distribution was similar, with each age group from 20–59 years accounting for 20.6% and those aged 60 and above for 17.6% in both groups. Males were more affected, representing 60.3% of cases and 61.8% of controls. Singles and married individuals were predominant, with 48.5% and 36.8% cases, and 43.4% and 46.3% among controlled seizure patients, respectively. Educational attainment was slightly higher in the controls group, with 27.9% completing grades 9–12 and 20.6% having college education, compared to 23.6% and 22.1% in the cases. Most patients lived far or very far from the hospital, with 29.4% and 32.3% in the cases, and 26.5% and 30.1% in the controls group living very far or outside Addis Ababa. Unemployment was more common among cases (57.4%) compared to controls(33.8%), who had higher rates of full-time (28.7%) and self-employment (30.1%).\u003c/p\u003e\n\u003ch2\u003e\u003cstrong\u003e4.2 Social drug use characteristics of study participants\u003c/strong\u003e\u003c/h2\u003e\n\u003cp\u003eSubstance use patterns were compared between patients with cases and controls. Regarding alcohol consumption, 54.4% of cases had never consumed alcohol, compared to 67.7% among controls. Recent alcohol use was more common in the cases, with 10.2% drinking at least once a month, 6.0% at least once a week, and 4.4% more than two days per week, while such frequent use was rare or absent in the controls. For khat consumption, 85.3% of cases and 90.5% of controls reported never using khat. Regular khat use (at least once a month or more) was slightly higher among cases (5.9%) than among controlled ones (1.4%). Regarding cigarette smoking, 80.9% of cases had never smoked, while 19.1% had smoked at some time but not within the last 12 months. In comparison, 95.6% of controls had never smoked, and 3.7% had smoked more than 12 months ago. Overall, alcohol, khat, and cigarette use were more frequent among patients with uncontrolled seizures(cases).\u003c/p\u003e\n\u003ch2\u003e\u003cstrong\u003e4.3 Clinical Characterstics of the the study participants\u003c/strong\u003e\u003c/h2\u003e\n\u003cp\u003eClinical characteristics were compared between patients with controlled and uncontrolled seizures. Among patients with cases, 35.3% had their first seizure before age 20, compared to 43.4% in the control group. A higher proportion of cases (70.6%) had more than five seizures before starting medication, compared to 54.4% among control group. Most patients in both groups had lived with epilepsy for more than 10 years, with 60.3% among cases and 69.1% among controls. Regarding duration of medication, 52.9% of cases and 64% of controls had been on treatment for more than 10 years. Comorbid conditions were more frequent among cases (41.2%) than controls (26.5%). Polytherapy was more common in cases (64.7%), whereas monotherapy was dominant in the control group (64%). Appointment intervals of two months were the most common in both groups, though a longer four-month interval was more frequent in control group (17% vs. 10.3%). Regular follow-up was significantly better in the controlled group (97.8% vs. 85.3%). Adverse effects were more commonly reported among cases (55.9%) compared to 28.7% of the controls. Generalized tonic-clonic (GTC) seizures were the most common type in both groups, representing 97% of cases and 89% of control group.\u003c/p\u003e\n\u003ch2\u003e\u003cstrong\u003e4.4 BMQ scale characterstic of the study participants\u003c/strong\u003e\u003c/h2\u003e\n\u003cp\u003eThe Beliefs about Medicines Questionnaire (BMQ) \u003cstrong\u003enecessity scale\u003c/strong\u003e revealed that the majority of participants had a strong belief in the importance of their antiseizure medication. Specifically, 70.6% agreed and 3.9% strongly agreed that their current health depends on their medication, while 75.5% agreed and 11.8% strongly agreed that without it, they would be very ill. Additionally, 79.4% agreed and 15.2% strongly agreed that their antiseizure medicine protects them from worsening health. The mean necessity score was 18.00 (SD = 2.76), with scores ranging from 9 to 24. When comparing cases and controls, a greater proportion of controls (90.4%) held a belief above the midpoint (strong necessity belief) compared to cases (78%). The odds of having a strong belief about medication necessity were significantly lower among cases than controls (OR = 0.37, 95% CI: 0.16–0.83, p = 0.017), suggesting that stronger belief in the necessity of medication is associated with better seizure control.\u003c/p\u003e\n\u003cp\u003eOn the BMQ \u003cstrong\u003econcern scale\u003c/strong\u003e, most participants expressed low concern about their antiseizure medication. For instance, 67.2% disagreed and 24.5% agreed that having to take antiseizure medication worries them, while 59.3% disagreed and 30.4% agreed that they worry about the long-term effects. The mean concern score was 12.94 (SD = 3.59), ranging from 5 to 25. Comparing groups, 41.2% of cases and 20.6% of controls had concern scores above the midpoint, indicating higher medication-related concerns among cases. The odds of having high concern were significantly greater among cases than controls (OR = 2.7, 95% CI: 1.42–5.10, p = 0.002). Regarding the \u003cstrong\u003eoverall necessity–concern differential\u003c/strong\u003e, 64.7% of cases had a positive belief (necessity outweighing concern) compared to 94.1% of controls. Cases were significantly more likely to have a negative overall belief compared to controls (OR = 8.72, 95% CI: 3.65–20.83, p \u0026lt; 0.001), suggesting that stronger positive beliefs about medication are associated with better seizure control.\u003c/p\u003e\n\u003cp\u003eOn the \u003cstrong\u003eOveruse Scale\u003c/strong\u003e, most participants disagreed with statements suggesting excessive use of antiseizure medications. For example, 79.4% disagreed that doctors use too many antiseizure medicines, and 76.5% disagreed that natural remedies are safer than antiseizure medicines. The mean score for overuse was 9.84 (SD = 2.19), with scores ranging from 4 to 18. When comparing cases and controls, 39.7%% of cases and 14.7%% of controls scored above the midpoint, indicating stronger beliefs about the overuse of antiseizure medications among cases. The odds of having such beliefs were significantly higher in cases than controls (OR = 3.81, 95% CI: 1.93–7.53, p \u0026lt; 0.001), suggesting that uncontrolled seizure patients are more likely to believe in the overuse of medication.\u003c/p\u003e\n\u003cp\u003eFor the \u003cstrong\u003eHarm Scale\u003c/strong\u003e, most participants disagreed with the notion that antiseizure medications cause harm, with 97% disagreeing that people should stop treatment occasionally and 92.6% disagreeing that antiseizure medications do more harm than good. The mean score for harm was 7.84 (SD = 1.76), with scores ranging from 4 to 17. While there was no significant difference between cases and controls in terms of beliefs about harm, with no controlss scoring above the midpoint and only 5 cases scoring above the midpoint, these results suggest little belief in harm from antiseizure medications among the study participants.\u003c/p\u003e\n\u003ch2\u003e\u003cstrong\u003e4.5 Antiseizure drug adherance (\u003c/strong\u003e\u003cstrong\u003eMARS\u003c/strong\u003e\u003cstrong\u003e) score characteristics of study participants\u003c/strong\u003e\u003c/h2\u003e\n\u003cp\u003eThe table 5. compares medication adherence between cases (uncontrolled seizure) and controls (controlled seizure) based on various behavioral and attitudinal questions about antiseizure medication. \u0026nbsp;The overall mean adherence score for all participants was 7.82 (SD = 1.71), with scores ranging from 1 to 10. The adherence status revealed that 22 cases (32.4%) were non-adherent, whereas 7 controls (5.2%) were non-adherent. The odds ratio for non-adherence was 8.81 (95% CI: 3.53–21.99, p = 0.000), indicating a significantly higher likelihood of non-adherence among cases with uncontrolled seizure. A higher percentage of cases reported forgetting to take their medication at various intervals. For instance, 73.53% of cases had ever forgotten to take their medication, compared to 48.5% of controls. Over the past 12 months, 61.76% of cases forgot, while only 9.55% of controls did. In the past 4 weeks, 29.41% of cases missed doses, compared to only 2.2% of controls. Carelessness and Stopping Medication: Cases were also more likely to be careless about taking their medication (19.12%) compared to controls (1.47%). Similarly, 26.47% of cases reported stopping their medication when feeling better, whereas only 0.74% of controls did. Additionally, 20.59% of cases stopped medication when feeling worse, compared to just 1.47% of controls. In terms of taking medication only when feeling sick, 1.47% of cases and 0.74% of controls answered affirmatively. When asked if it felt unnatural for their mind and body to be controlled by medication, 30.9% of cases and 17.7% of controls agreed. Regarding cognitive effects, 44.1% of cases and 45.6% of controls reported that their thoughts were clearer on medication. significant number of participants, both cases (95.6%) and controls (94.9%), agreed that staying on medication helped prevent illness. In terms of side effects, 19.1% of cases felt like a \"zombie\" on medication, compared to only 7.4% of controls. Additionally, 63.2% of cases reported feeling tired and sluggish on medication, compared to 31.6% of controls.\u003c/p\u003e\n\u003ch2\u003e\u003cstrong\u003e4.6 Medication regimen \u0026nbsp; in the last 12 months\u003c/strong\u003e\u003c/h2\u003e\n\u003cp\u003emedication regimens over the past 12 months revealed notable differences between cases (uncontrolled seizures) and controls (controlled seizures). Monotherapy with phenobarbitone (PHB) was more common among controls (n=44) than cases (n=7), suggesting its relative effectiveness in seizure control for some patients. Similarly, valproate (VPA) and carbamazepine (CBM) monotherapies were also more prevalent among controls than cases. In contrast, polytherapy—especially combinations involving PHB and VPAwas more frequently observed in the uncontrolled seizure group. For instance, the combination of PHB + VPA was the most common regimen among cases (n=16), followed by PHB + CBM (n=7) and PHB + PHT + VPA (n=5), which appeared exclusively in the uncontrolled group. This trend suggests that patients with uncontrolled seizures were more likely to be on multiple medications, possibly reflecting more severe or treatment-resistant epilepsy. \u0026nbsp;\u003c/p\u003e\n\u003ch2\u003e\u003cstrong\u003e4.7 Factor associated with uncontrolled seizure and ASM adherence\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003ein a\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003emultivariate\u003c/strong\u003e \u003cstrong\u003elogistic regression model\u003c/strong\u003e\u003c/h2\u003e\n\u003cp\u003eNon-adherence to medication was strongly associated with uncontrolled seizures. Participants who were non-adherent had an odds ratio (OR) of 8.81 (p \u0026lt; 0.000) for uncontrolled seizures(cases), which decreased to(AOR= 4.67, 95% CI:1.42-15.36, p =0.011) after adjusting for other variables, highlighting the critical role of Non adherence in seizure control .Monthly or more frequent alcohol consumption was associated with increased odds of cases. However, after adjusting for other factors, this relationship became less pronounced, with no statistically significant effect. History of smoking but not active smokers was a significant predictor of uncontrolled seizures. Those who had history of smkiong had a much higher likelihood of experiencing uncontrolled seizures (OR = 6.14, p = 0.001), and this remained significant even after adjusting for other factors (AOR = 7.63, 95% CI: 1.73-33, p = 0.007). Having more than five seizures before starting medication was initially associated with an increased likelihood of uncontrolled seizures (OR = 2.01, p =0.028), but this association lost significance after adjustment, suggesting other factors may be more influential. Participants on polytherapy (multiple medications) were more likely to have uncontrolled seizures than those on monotherapy (single medication), both before (OR = 3.25, p \u0026lt; 0.000) and after adjustment (AOR = 3.07, \u0026nbsp;1.36-6.94, p = 0.007). Regular follow-up care significantly reduced the odds of uncontrolled seizures (OR = 0.13, p = 0.003), although this effect was not maintained after adjusting for other factors. Experiencing adverse effects from medications was strongly associated with uncontrolled seizures (OR = 3.15, p = 0.00), but this association was no longer significant after adjustment. Beliefs about medication, such as concerns about overuse and necessity, influenced seizure control. A negative overall belief about medication was strongly associated with uncontrolled seizures (OR = 8.72, p = 0.000), and this effect remained significant after adjusting for other variables (AOR = 7.75, 95% CI: 1.9-30.82 p p = 0.004).\u003c/p\u003e"},{"header":"5. Discussion","content":"\u003cp\u003eThis study identified several key factors associated with uncontrolled seizures. Non-adherence to antiseizure medications emerged as a major contributor to poor seizure control. Cigarette smoking and being on polytherapy, rather than monotherapy, were also linked to higher likelihood of uncontrolled seizures. Additionally, participants who held negative beliefs about their medications were more likely to have uncontrolled seizures. In contrast, other factors such as alcohol use, presence of comorbidities, frequency of seizures before treatment, adverse effects, treatment beliefs (necessity, concerns, overuse), and regular follow-up did not show a meaningful association with seizure control after adjusting for other variables.\u003c/p\u003e \u003cp\u003eNotably, Non-adherence to ASMs showed a strong and statistically significant association with uncontrolled seizures. Participants who were non-adherent had an odds ratio OR of 8.81 for experiencing uncontrolled seizures, which remained significant even after adjusting for other variables (AOR\u0026thinsp;=\u0026thinsp;4.67 ). This finding aligns with multiple studies conducted in Ethiopia and South Africa, which similarly identified poor adherence to ASMs as a significant predictor of seizure recurrence (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan additionalcitationids=\"CR34 CR35 CR36\" citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e). For example, A study done in Gonder (\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e), reported an AOR of 9.37 for seizure recurrence among patients with poor adherence. Similarly, A study done in Southern Ethiopia (\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e), found poor medication adherence to be significantly associated with uncontrolled seizures (AOR\u0026thinsp;=\u0026thinsp;4.03). A study dne in Ayder Comprehensive specialized hospital (\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e), also reported a strong association (AOR\u0026thinsp;=\u0026thinsp;11.52), while a sudy in Mezan tepi university teaching hospital (\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e) demonstrated that both medium (AOR\u0026thinsp;=\u0026thinsp;5.4) and poor adherence (AOR\u0026thinsp;=\u0026thinsp;8.16) were significantly linked to poor seizure control.\u003c/p\u003e \u003cp\u003eBeliefs about medication, such as necessity, concerns, overuse and harm belief about ASM, influenced seizure control. A negative overall belief about medication was strongly associated with uncontrolled seizures (OR\u0026thinsp;=\u0026thinsp;8.72), and this effect remained significant after adjusting for other variables (AOR\u0026thinsp;=\u0026thinsp;7.75) which is similar with study done here and other countries. (\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e)\u003c/p\u003e \u003cp\u003eSimilarly, substance use particularly a history of cigarette smoking, even if not current was associated with poor seizure control (AOR\u0026thinsp;=\u0026thinsp;7.63). This finding aligns with existing research that highlights the negative impact of lifestyle factors on seizure outcomes. Although alcohol use showed an association with uncontrolled seizures in the unadjusted analysis, it was not independently significant after controlling for confounders. However, other studies have found a significant association between alcohol use and uncontrolled seizures.(\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e)\u003c/p\u003e \u003cp\u003eComorbidities were associated with uncontrolled seizures in the unadjusted analysis, this relationship did not remain statistically significant after adjusting for confounding variables. In contrast, other studies have reported a strong association between comorbid condition and uncontrolled seizure(\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e). In our study, this discrepancy may be partly explained by underreporting, as some participants initially stated they had no comorbidities, but were later found to have additional illnesses, especially mental health conditions, upon reviewing patients data.\u003c/p\u003e \u003cp\u003eThe odds of uncontrolled seizures was 3 fold higher in epileptic patients on 2 or more ASMs (polytherapy) as compared with those on single ASMs (AOR\u0026thinsp;=\u0026thinsp;3.07). This finding was supported by studies done in the United Kingdom (UK), Saudi Arabia, and Ethiopia which showed taking two or more ASMs was a predictor of uncontrolled seizure.(\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e) The plausible explanation could be that patients on dual or polytherapy might have more pill burden, more drug-related side effects, and more financial expenses which predispose to poor ASM adherence. Polypharmacy causes drug\u0026ndash;drug interactions and altered drugs metabolism. In addition, PWE on poly-therapy might have inherent intractable epilepsy, and might require other interventions. All these clinical scenarios could lead to uncontrolled seizure in epileptic patients.\u003c/p\u003e"},{"header":"6 .Strength and Limitation","content":"\u003cdiv id=\"Sec26\" class=\"Section2\"\u003e \u003ch2\u003e6.1 Strength of the study\u003c/h2\u003e \u003cp\u003eA key strength of this study lies in its use of a case-control design, which allowed for a robust comparison between patients with and without seizure control while adjusting for multiple confounding variables, such as sociodemographic factors, medication beliefs, comorbidities, and substance use. The inclusion of validated tools like the Medication Adherence Rating Scale (MARS) (\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e, \u003cspan additionalcitationids=\"CR29\" citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e) and the Beliefs about Medicines Questionnaire (BMQ) (\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e) further enhanced the reliability and validity of the findings.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec27\" class=\"Section2\"\u003e \u003ch2\u003e6.2 Limitation of the study\u003c/h2\u003e \u003cp\u003eOne limitation of this study is its reliance on self-reported measures to assess medication adherence and patient beliefs, which may be subject to recall bias and social desirability bias, potentially leading to an overestimation of adherence levels. To mitigate this limitation, the study used seizure control over a one-year period as an objective outcome measure, and by ensuring confidentiality and employing trained data collectors. Additionally, the relatively small sample size may have limited the statistical power to detect associations, particularly in the multivariable analysis.\u003c/p\u003e \u003c/div\u003e"},{"header":"7. Conclusion","content":"\u003cp\u003eThis study identified several factors associated with uncontrolled seizures among epileptic individuals on antiseizure medications (ASMs). Non-adherance to antiseizure medication (ASM), history of cigarette smoking, polytherapy, and negative beliefs about medications were significantly linked to a higher risk of uncontrolled seizures. Non-adherence was the strongest predictor, emphasizing the vital role of consistent medication use. Although alcohol use, seizure frequency before treatment, and adverse drug effects showed associations in unadjusted analysis, they were not independently significant after adjusting for confounders. Overall, these results highlight that beyond clinical treatment, patient behavior and beliefs greatly influence seizure control outcomes.\u003c/p\u003e"},{"header":"8.Recommendations","content":"\u003cp\u003eTo improve seizure control and ASM adherence, interventions should focus on enhancing patient education, addressing misconceptions about long-term medication use, and providing regular reminders and counseling. Strategies may include patient education programs, reminder systems, involvement of community health workers, and policy-level actions. Healthcare providers should also assess and address substance use, including smoking, and offer support for cessation. Given the challenges of polytherapy, treatment plans should be personalized to meet individual patient needs. Strengthening follow-up visits with structured adherence counseling, psychoeducation, and family or community engagement can help overcome behavioral and psychological barriers. Future longitudinal research is needed to examine the causal impact of these interventions on adherence, seizure control, and overall patient outcomes.\u003c/p\u003e"},{"header":"Abbreviations ","content":"\u003cp\u003e\u003cstrong\u003eACIPH\u0026nbsp;\u003c/strong\u003eAddis Continental Institute of Public Health\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAEDs\u0026nbsp;\u003c/strong\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; Anti-eEpileptic Drugs\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eASMs\u0026nbsp;\u003c/strong\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Anti -Seizure Medications\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMARS\u0026nbsp;\u003c/strong\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Medication Adherence Rating Scale (MARS)\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eBMQ\u0026nbsp;\u003c/strong\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; Belief about AntiSeizure Medication Questioner(BMQ)\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePCC\u0026nbsp;\u003c/strong\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;People-Centered Care\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePWE\u0026nbsp;\u003c/strong\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; People With Epilepsy\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eWHO\u0026nbsp;\u003c/strong\u003eWorld Health Organization\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003eAcknowledgment\u003c/p\u003e\n\u003cp\u003eI would like to thank my advisor, Prof. Yemane Berhane, for his unreserved advice and constructive comments, as well as the Addis Continental Institute of Public Health for providing me with this opportunity\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eEthical clearance \u003cstrong\u003ewas\u003c/strong\u003eobtained from the Addis Continental Institute of Public Health Research Ethics Committee before conducting the study. Permission to undertake the study \u003cstrong\u003ewas\u003c/strong\u003eobtained from hospital officials. A written informed consent \u003cstrong\u003ewas\u003c/strong\u003eobtained from each study participant. Patient privacy and confidentiality of information \u003cstrong\u003ewere\u003c/strong\u003e maintained by creating a private space for interviews, and patient names \u003cstrong\u003ewere\u003c/strong\u003eremoved from the database, which \u003cstrong\u003ewas\u003c/strong\u003e shared with others. Non-research persons did not access data. Participation \u003cstrong\u003ewas\u003c/strong\u003evoluntary, and study participants \u003cstrong\u003ecould\u003c/strong\u003e withdraw from the study at any time during the study process.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets used and analyzed during the current study are not publicly available due to ethical restriction and personal data protections but are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was self-funded. The authors received no external funding, and no funding body had any role in the study design, data collection, analysis, interpretation, or manuscript preparation.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors' contributions\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eDr. Betsadkan Kebede conceived and conducted the research and drafted the manuscript. Prof. Yemane Berhane supervised the study, provided methodological guidance. Data were collected by trained data collectors. All authors critically reviewed and approved the final manuscript.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eFisher RS, Acevedo C, Arzimanoglou A, Bogacz A, Cross JH, Elger CE, et al. ILAE Official Report: A practical clinical definition of epilepsy. Epilepsia. 2014 Apr;55(4):475\u0026ndash;82.\u003c/li\u003e\n \u003cli\u003eref 1 . 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Int J Health Sci. 2014 Sep;8(3):247\u0026ndash;55.\u003c/li\u003e\n \u003cli\u003eMohammed A, Mishore K, Tafesse T, Jambo A, Husen A, Alemu A. Seizure Remission and Its Predictors Among Epileptic Patients on Follow-Up at Public Hospitals in Eastern Ethiopia: A Retrospective Cohort Study. Int J Gen Med. 2023 Nov;Volume 16:5343\u0026ndash;54.\u003c/li\u003e\n \u003cli\u003eNasir BB, Yifru YM, Engidawork E, Gebrewold MA, Woldu MA, Berha AB. Antiepileptic Drug Treatment Outcomes and Seizure-Related Injuries Among Adult Patients with Epilepsy in a Tertiary Care Hospital in Ethiopia. Patient Relat Outcome Meas. 2020 Apr;Volume 11:119\u0026ndash;27.\u003c/li\u003e\n \u003cli\u003eShumet S, Wondie M, Ayano G, Asfaw H, Kassew T, Mesafint G. Antiepileptic Drug Adherence and Its Associated Factors among Epilepsy Patients on Follow-ups at Amanuel Mental Specialized Hospital, Ethiopia. Ethiop J Health Sci. 2022 Sep 20;32(5):913\u0026ndash;22.\u003c/li\u003e\n \u003cli\u003eTan X, Patel I, Chang J. Review of the four item Morisky Medication Adherence Scale (MMAS-4) and eight item Morisky Medication Adherence Scale (MMAS-8). Innov Pharm [Internet]. 2014 Jan 1 [cited 2025 May 26];5(3). Available from: https://pubs.lib.umn.edu/index.php/innovations/article/view/347\u003c/li\u003e\n \u003cli\u003eZewudie A, Mamo Y, Feyissa D, Yimam M, Mekonen G, Abdela A. Epilepsy Treatment Outcome and Its Predictors among Ambulatory Patients with Epilepsy at Mizan-Tepi University Teaching Hospital, Southwest Ethiopia. Neurol Res Int. 2020 Apr 8;2020:1\u0026ndash;8.\u003c/li\u003e\n \u003cli\u003eHasiso TY, Desse TA. Adherence to Treatment and Factors Affecting Adherence of Epileptic Patients at Yirgalem General Hospital, Southern Ethiopia: A Prospective Cross-Sectional Study. Romigi A, editor. PLOS ONE. 2016 Sep 29;11(9):e0163040.\u003c/li\u003e\n \u003cli\u003eBelayneh Z, Mekuriaw B. A systematic review and meta-analysis of anti-epileptic medication non-adherence among people with epilepsy in Ethiopia. Arch Public Health. 2020 Dec;78(1):23.\u003c/li\u003e\n \u003cli\u003eChapman SCE, Horne R, Chater A, Hukins D, Smithson WH. Patients\u0026rsquo; perspectives on antiepileptic medication: Relationships between beliefs about medicines and adherence among patients with epilepsy in UK primary care. Epilepsy Behav. 2014 Feb;31:312\u0026ndash;20.\u003c/li\u003e\n \u003cli\u003eEgenasi C, Steinberg W, Raubenheimer J. Beliefs about medication, medication adherence and seizure control among adult epilepsy patients in Kimberley, South Africa. South Afr Fam Pract. 2015 Sep 3;57(5):326\u0026ndash;32.\u003c/li\u003e\n \u003cli\u003eKariuki SM. Electroencephalographic features of convulsive epilepsy in Africa: A multicentre study of prevalence, pattern and associated factors.\u003c/li\u003e\n \u003cli\u003eNiriayo YL, Mamo A, Gidey K, Demoz GT. Medication Belief and Adherence among Patients with Epilepsy. Behav Neurol. 2019 Apr 23;2019:1\u0026ndash;7.\u003c/li\u003e\n \u003cli\u003eZena D, Tadesse A, Bekele N, Yaregal S, Sualih N, Worku E. Seizure control and its associated factors among epileptic patients at Neurology Clinic, University of Gondar hospital, Northwest Ethiopia. SAGE Open Med. 2022 Jan;10:20503121221100612.\u003c/li\u003e\n \u003cli\u003eBhalla D, Lotfalinezhad E, Amini F, Delbari A, Fadaye-Vatan R, Saii V, et al. Medication Beliefs and Adherence to Antiseizure Medications. Di Lazzaro V, editor. Neurol Res Int. 2020 Oct 23;2020:1\u0026ndash;9.\u003c/li\u003e\n \u003cli\u003eDilles T, Mortelmans L, Loots E, Sabbe K, Feyen H, Wauters M, et al. People-centered care and patients\u0026rsquo; beliefs about medicines and adherence: A cross-sectional study. Heliyon. 2023 May;9(5):e15795.\u003c/li\u003e\n \u003cli\u003eWei L, Champman S, Li X, Li X, Li S, Chen R, et al. Beliefs about medicines and non-adherence in patients with stroke, diabetes mellitus and rheumatoid arthritis: a cross-sectional study in China. BMJ Open. 2017 Oct;7(10):e017293.\u003c/li\u003e\n \u003cli\u003eNiriayo YL, Mamo A, Kassa TD, Asgedom SW, Atey TM, Gidey K, et al. Treatment outcome and associated factors among patients with epilepsy. Sci Rep. 2018 Nov 26;8(1):17354.\u003c/li\u003e\n \u003cli\u003eVerma A, K K, Kumar A. Relationships Between Beliefs about Medication, Seizure Control and Adherence to Antiepileptic Drugs Among People with Epilepsy. Arch Clin Med Case Rep [Internet]. 2020 [cited 2025 Apr 26];04(06). Available from: http://www.fortunejournals.com/articles/relationships-between-beliefs-about-medication-seizure-control-and-adherence-to-antiepileptic-drugs-among-people-with-epilepsy.html\u003c/li\u003e\n \u003cli\u003eFialko L, Garety PA, Kuipers E, Dunn G, Bebbington PE, Fowler D, et al. A large-scale validation study of the Medication Adherence Rating Scale (MARS). Schizophr Res. 2008;100(1-3):53-9.\u003c/li\u003e\n \u003cli\u003eOwie GO, Olotu SO, James BO. Reliability and validity of the Medication Adherence Rating Scale in a cohort of patients with schizophrenia from Nigeria. Trends Psychiatry Psychother. 2018 May 14;40(2):85\u0026ndash;92.\u003c/li\u003e\n \u003cli\u003eRoss B, Wang D, Xi C, Pan Y, Zhou L, Yang X, et al. T217. MEDICATION ADHERENCE AND ITS CORRELATES AMONG PATIENTS WITH RECURRENT SCHIZOPHRENIA: A LARGE- SCALE STUDY IN CHINA.\u003c/li\u003e\n \u003cli\u003eNakhutina L, Gonzalez JS, Margolis SA, Spada A, Grant A. Adherence to antiepileptic drugs and beliefs about medication among predominantly ethnic minority patients with epilepsy. Epilepsy Behav. 2011 Nov;22(3):584\u0026ndash;6.\u003c/li\u003e\n \u003cli\u003ePorteous T, Francis J, Bond C, Hannaford P. Temporal stability of beliefs about medicines: Implications for optimising adherence. Patient Educ Couns. 2010 May;79(2):225\u0026ndash;30.\u003c/li\u003e\n \u003cli\u003eAhmed M, Nasir M, Yalew S, Getahun F, Getahun F. Assessment of Treatment Outcome and Its Associated Factors among Adult Epileptic Patients in Public Hospitals in the Southern Ethiopia: A Multi-center Cross-sectional Study. Ethiop J Health Sci [Internet]. 2023 Apr 6 [cited 2025 Apr 26];33(2). Available from: https://www.ajol.info/index.php/ejhs/article/view/245330\u003c/li\u003e\n \u003cli\u003eNiriayo YL, Mamo A, Kassa TD, Asgedom SW, Atey TM, Gidey K, et al. Treatment outcome and associated factors among patients with epilepsy. Sci Rep. 2018 Nov 26;8(1):17354.\u003c/li\u003e\n \u003cli\u003eRawat C, Guin D, Talwar P, Grover S, Baghel R, Kushwaha S, et al. outcome in North Indian patients.\u003c/li\u003e\n \u003cli\u003eZena D, Tadesse A, Bekele N, Yaregal S, Sualih N, Worku E. Seizure control and its associated factors among epileptic patients at Neurology Clinic, University of Gondar hospital, Northwest Ethiopia. SAGE Open Med. 2022 Jan;10:20503121221100612.\u003c/li\u003e\n \u003cli\u003eZewudie A, Mamo Y, Feyissa D, Yimam M, Mekonen G, Abdela A. Epilepsy Treatment Outcome and Its Predictors among Ambulatory Patients with Epilepsy at Mizan-Tepi University Teaching Hospital, Southwest Ethiopia. Neurol Res Int. 2020 Apr 8;2020:1\u0026ndash;8.\u003c/li\u003e\n \u003cli\u003eHamdy NA, Alamgir MJ, Mohammad EGE, Khedr MH, Fazili S. Profile of Epilepsy in a Regional Hospital in Al Qassim, Saudi Arabia. Saudi Arab.\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003eTables 1 to 8 are available in the supplementary files section\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-neurology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"nurl","sideBox":"Learn more about [BMC Neurology](http://bmcneurol.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/nurl","title":"BMC Neurology","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-9281210/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9281210/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground:\u003c/strong\u003e Epilepsy remains a significant global public health concern, affecting people across all regions of the world. The burden is disproportionately higher in low-income settings, where approximately 90% of people with epilepsy reside. In these contexts, achieving optimal seizure control is often difficult due to limited treatment guidelines and challenges in tailoring therapy to individual patient needs. In Ethiopia, the proportion of patients experiencing uncontrolled seizures varies widely, ranging from 18.6% to 82.4%, with non adherence to antiseizure medications identified as a key contributing factor.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eObjective: \u003c/strong\u003eThe objective of this study was to assess the association between uncontrolled seizures and Non-adherence to antiseizure medications(ASMs).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods: \u003c/strong\u003eA hospital-based age-matched case-control study was conducted among epileptic patients at the neurologic clinic of Eka Kotebe General Hospital and Amanuel Mental Specialized Hospital. \u0026nbsp;Cases were defined as patients who reported at least one seizure episode within the last 12 months, while controls were those who had no seizure episodes during the same period from October 2024 to March 2025. A total of 68 cases and 136 controls were involved in the study, with a matching ratio of 1:2. Data was anayzed using Stata. Bivariate and multivariate logistic regression analyses were used to examine the relationship between the dependent and independent variables. Statistical significance was declared at a p-value less than 0.05.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults:\u003c/strong\u003e Non-adherance to Antiseizure medication (ASM) was significantly associated with uncontrolled seizures (AOR = 4.67, 95% CI: 1.42–15.36, p = 0.011). History of cigarette smoking was another important factor, with smokers having higher odds of uncontrolled seizures (AOR = 7.63, 95% CI: 1.73–33, p = 0.007). Patients on polytherapy were also more likely to have uncontrolled seizures compared to those on monotherapy (AOR = 3.07, 95% CI: 1.36–6.94, p = 0.007). Moreover, participants with a negative overall belief about medications (BMQ) were significantly more likely to experience uncontrolled seizures (AOR = 7.75, 95% CI: 1.9–30.82, p = 0.004).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion and Recommendations: \u003c/strong\u003eThis study found that uncontrolled seizures among individuals on antiseizure medications (ASMs) were strongly associated with non-adherence, history of cigarette smoking, polytherapy, and negative beliefs about medications, with non-adherence emerging as the most significant predictor. To enhance outcomes, the study recommends strengthening ASMs adherence through education, reminders, and counseling, addressing misconceptions about ASMs, and regularly assessing and supporting patients in reducing substance use, alongside promoting consistent clinic follow-up.\u003c/p\u003e","manuscriptTitle":"Seizure control and adherence to antiseizure medications among epileptic hospital patients in Addis Ababa, Ethiopia","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-05-15 16:07:57","doi":"10.21203/rs.3.rs-9281210/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"reviewersInvited","content":"","date":"2026-05-06T11:13:06+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-05-06T11:08:50+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2026-04-20T08:40:01+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-04-20T07:18:41+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Neurology","date":"2026-04-20T06:36:16+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-neurology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"nurl","sideBox":"Learn more about [BMC Neurology](http://bmcneurol.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/nurl","title":"BMC Neurology","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"d8271cea-d057-4230-baf9-767ad21f21fa","owner":[],"postedDate":"May 15th, 2026","published":true,"recentEditorialEvents":[{"type":"reviewersInvited","content":"11","date":"2026-05-06T11:13:06+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-05-06T11:08:50+00:00","index":"","fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-05-15T16:07:57+00:00","versionOfRecord":[],"versionCreatedAt":"2026-05-15 16:07:57","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9281210","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9281210","identity":"rs-9281210","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}