Medication adherence is the first and main determinant of treatment success. It is defined by world health organization as “the degree to which the person’s behavior corresponds to the agreed recommendations from a health care provider”. Non-adherence is a multi-factorial phenomenon that can result from five major interacting factors. These are health team and health system-related factors; patient-related factors; therapy-related factors; socio-economic factors; and condition-related factors. The prevalence of non-adherence in mental illness was found to be 40% to 60% world wide. In developing countries, the magnitude of poor adherence is expected to increase. So this study aimed to assess medication adherence status and its associated factors among psychiatric patients in Asella Referral and Teaching Hospital in Oromia, Ethiopia.
An institution-based cross-sectional study was conducted from March 18, 2022 to May 25, 2022, with a total sample of 422 patients. Medication adherence was measured by a modified version of the medication adherence rating scale in the psychiatric setting to determine treatment adherence status, and unstructured questionnaires were assessed by interviewing the patient. Additional data concerning the medication-taking behavior of the patient was collected from caregivers. Bivariate logistic regression was performed to see the association between each explanatory variable and the outcome variable. The odds ratio and 95% confidence interval were used to see the association between treatment adherence and the strength of the link.
A total of 395 study participants were interviewed, making a response rate of 93.6%. The prevalence of treatment adherence was 246(62.3%). Medication adherence show high association with lifetime alcohol use [AOR: 3.18, 95% CI:1.31–7.72] compared to those who had no alcohol use histroy, and perceived stigma [AOR (95% CI: 2.31 (1.01–5.31)] compared with those who had no perceived stigma, where as adherence show low association with having slight or superficial insight about illness [AOR (95% CI: 0.25 (0.12–0.53)] compared to those who reported cured off their illness and belief in medication [AOR: 0.36, 95% CI: 0.16–0.81)] compared to those who didn’t belief in the medication they are taking.
The prevalence of mediation adherence was found to be lower. In this study, factors such as having the slight insight or poor insight about their illness and belief in the medication decreased medication adherence, whereas having an alcohol use history in their lifetime and perceived stigma increased medication adherence. For a better health outcome, awareness creation at an insight level needs to be worked on by psychiatric professionals working on the follow-up psychiatric patients at psychiatry clinic of Assela Referral and Teaching Hospital to enable them to well adhere to their medication.
Citation: Gudeta DB, Leta K, Alemu B, Kandula UR (2023) Medication adherence and associated factors among psychiatry patients at Asella Referral and Teaching Hospital in Oromia, Ethiopia: Institution based cross sectional study. PLoS ONE 18(4): e0283829. https://doi.org/10.1371/journal.pone.0283829
Editor: Muhammad Junaid Farrukh, UCSI University, MALAYSIA
Received: October 29, 2022; Accepted: March 16, 2023; Published: April 13, 2023
Copyright: © 2023 Gudeta et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Data Availability: The data used for this manuscript are available upon request from the ethics committee of Arsi University College of Health Science and Medicine (email@example.com). Because the dataset file contains personal information, it may not be ethical to publicly deposit the data.
Funding: The Arsi University's Research and Dissemination Office (Project number: CoHS/R/0091/2021/2022) provided funding for this study. The funding sources had no input towards the planning of the study, collecting and analyzing the data, choosing to publish, or writing the report.
Competing interests: The authors have declared that no competing interests exist.
Abbreviations: ARTH, Assela Referral and Teaching Hospital; ART, Anti Retro Viral Therapy; COVD, Corona Virus Disease; ETB, Ethiopian Birr; MMI, Major Mental Illness; OPD, Outpatient Department; SPSS, Software Package for Social Science; TB, Tuberculosis; VIF, Variance inflation factor; WHO, World Health Organization
Medication adherence is the frist and main determinant of treatment success. It is defined by world health organization as “the degree to which the person’s behavior corresponds to the agreed recommendations from a health care provider”. Non-adherence to medicine is a major public health problem that is termed an "invisible epidemics”.
The prevalence of non-adherence in mental illness was found to be 40% to 60% world wide . In developing countries, the magnitude of poor adherence is expected to increase, and its impact will be very high. In Ethiopia, the prevalence of non-adherence was reported as 39.3%–55.5%, and many factors were significantly associated with treatment adherence [3, 6–9]. Non adherence to medication continues to be a significant challenge for patients suffering from mental illnesses, physicians, and the healthcare system . It is well known that many patients have difficulty in following treatment recommendations, especially with mental illness . This is due to some differences from other areas of medicine, such as chronicity with a time of exacerbation and relapse, poor insight into the illness process, patients feeling better and cognitive disturbance, and alternative treatment choices which is the traditional one [3–5]. In particular, in severe mental illnesses like schizophrenia, it is a common and critical issue that needs a solution .
Poor adherence is a multi-factorial phenomenon which can result from five major interacting factors; health team and health system related, patient related, therapy related, social /economic and clinical factors . According to some research findings poor adherence in mental illness is associated with poor social support, higher self-stigma, perceived spiritual causation of mental illness and being employed [3, 4]. Of these health system related factors may vary from country to country or even from area to area within a given country where the factors may include lack of health insurance coverage, due to different barrier to high quality health care and having lower socio economic status .
Inability to well adhere to a medication regimen may not affect only the patient, it also affect health care effectiveness. Broadly it may result in poor health, higher healthcare costs, relapse of illnesses, increase risk of suicide, increased risk of dependency, presence of inter episodic symptoms, frequent hospital admission, difficulty to return back to previous functionality, increased risk of absents and rebound effect and increase rate of mortality .
Because of the multifactorial reasons for non-adherence, also in our country, many risk factors might exist because of the difference in socio-demographic and economic factors, patient-related, health care and health system related, and clinical-related factors. By this time, people even fear going to health facilities due to the COVID-19 pandemic, so it is also the other hindering factor.
Despite the existence of solutions for treatment non-adherence and its determinants, since it is perceived as a minor health issue even if it leads to a variety of undesirable health consequences, there is a scarcity of information on the area of mental illness in our country, particularly in the Arsi Zone, Oromia region to our knowledge of searching. Therefore, we were interested in determining medication adherence status and factors associated with mental illness. The current study will have a significant contribution in that it will help to set strategies to overcome perceptual and practical barriers to adherence. Since it is an indicator of healthcare effectiveness, it can also enhance the flow of patient visits to psychiatry clinics. It involves good patient outcomes and support health policy-making issues.
Methods and materials
The study was conducted at Asella Referral and Teaching Hospital’s (ARTH) outpatient psychiatric clinic. Asella is a town in Ethiopia’s Oromia regional state, and it is the capital city of Arsi zone. It is 175 kilometers North of Addis Ababa, the country’s capital. ARTH is a well-known government institution in Asella town, and it is a teaching and tertiary level hospital that provides inpatient and outpatient health services for over 3.5 million people in Ethiopia’s North East . More than 60,000 patients got psychiatric service from this hospital. This care is given by 1 psychiatrist, 4 BSC psychiatric nurses, and 2 MSc psychiatry professionals. There is no inpatient psychiatric service in this hospital.
Study period and design
A hospital-based cross-sectional study was conducted in the psychiatric OPD of ARTH from March 18, 2022 to May 25, 2022.
Source and study population
The source population were patients who came for follow-up to take medication at Asella Referral and Teaching Hospital. All psychiatric patients who came to take their treatment during the data collection period are included in the study population.
The study included all patients aged 15 and above who came for follow-up at the psychiatric clinic and whose charts clearly indicated a diagnosis of major mental illness, who were calm and took their treatment on their second visit and on follow-up. On the other hand patients who were not able to communicate because of their illness were excluded.
The treatment adherence status of psychiatric patients, which was assessed by a validated and modified version of the medication adherence rating scale and classified as adherent or non-adherent, was a dependent variable. whereas socio-demographic and economic factors (age, gender, income, occupation, education, religion, ethnicity, area of residence, availability of social support), patient-related factors (smoking, alcohol use, other substance use, patient attitude, belief on medication, fear of stigma, level of satisfaction, and fear of COVID-19 transmission), health-system-related factors (time duration for follow-up, creation of awareness on treatment adherence, availability of medication) and clinical factors such as duration of the illness, insight level, severity of illness, side effect of medication, dosage, frequency per day) were independent variables.
- Major mental illness: mental illness with the diagnosis of major depressive disorder, schizophrenia, Bipolar disorders, brief psychotic disorder and schizophreniform
- Medication adherence status: Medication adherence was measured by modified version of medication adherence rating scale with  with a total of 8 item where item 1 to 7 have choice of Yes = 1, No = 0 whereas item number 8 have choices A to E, A = 0, B to E = 1. Those who score 8 out of 8 are termed adherents, where a score of less than 8 indicates non-adherence
- Poor adherent- score of less than 6 (0–5)
- Partially adherent–score of 6 to 7
- Adherent– 8 out of 8 score
- Psychiatry patient: patient with major mental illnesses
- Associated factor: factor that lead the patient for non-adherence
- Patients: clients 15 years old and above
Sample size estimation/determination/
The sample size was calculated using the single population proportion formula. By using the proportion of treatment non-adherence for major mental illness in concurrent cases and for associated factors (since there is no similar study in Ethiopia up to the knowledge of the investigators) of 50%, and 95% confidence level, 5% tolerable margin of error and a possible non-response rate of 10%, the final sample size was 422.
Simple randam sampling technique was used. During the data collection dates, when patients’ charts were brought to the clinic, they were checked for inclusion criteria. The charts were differentiated from new patients, then, by lottery method or randomly, we chose those who would be involved in the study. If a patient is absent while the chart is brought, another patient who fulfills the criteria is added. The patients on follow-up recorded in the record book were the sampling frame of this study.
Data collection procedure
Data was prepared in English, then it was translated in to local language, Afan Oromo and Amharic and back to English. Data was collected by the preference of patients by either of the two language from respondents. Primary data was collected from individual patients. These were structured questions where the contents were socio-demographic and economic factors; clinical-related factors; health system-related factors; and patient-related factors. In addition to this, four questions concerning unresolved reasons for not properly taking medication at family level and possible solutions they expect were developed to be gathered from care givers. For those patients who came alone, questionnaires designed to be collected from caregivers were collected by phone. Secondary data was gathered from the patient’s chart by using the already prepared checklist that contains 7 items in English. The data was collected by six psychiatric professionals. The principal and coinvestigators provided supervision during the data collection period.
Data quality assurance
Medication adherence was measured by validated and modified version of the medication adherence rating scale with internal consistency (Cronbach’s alpha) = 0.75 and reliability of 0.83) . Additionally, other questionnaires were prepared after reviewing literature in English. Then it was translated into Amharic and Afan Oromo and back to English to ensure consistency. Data collection took place by Afan Oromo and Amharic languages according to the language fluency of patients. Before starting the data collection, a pre-test of questionnaires was done on 10% of psychiatric patients attending service at Adama General Hospital to prevent cross-contamination of information, and it was performed in order to check the language clarity and consistency of the questionnaire. Corrections to words on the questionnaire that were ambiguous for respondents were made after the pre-test.
There was supervision. The questions’ completeness was checked and corrected before the patients left the mental health clinic. For uniformity and accuracy, the collected data was entered into a computer by utilizing a double data entry procedure.
Data processing and analysis
The data was cleaned for completeness, coded, entered, and analyzed using the Statistical Package for Social Science (SPSS) version 24.00. The summary of the descriptive analysis was calculated and displayed as frequency and percentage (categorical data), and mean for continuous data. Bivariate analysis was performed to see the association between the independent and the outcome variable. Multi-collinearity was checked to see if there was an association between independent variables and those with a variance inflation factor (VIF) value of 1 to 5 were taken, as they have no correlation, so they were used in the final model. Variables with a p-value of less than 0.25 in the bivariate analysis were candidate variables for multivariable analysis. To identify significant factors in the model, first the variables were filtered by using the backward LR, and then, after some variables were removed, the remaining variables were processed by the enter method. Model fitness was assessed using the Hosmer and Lemeshow test. After adjustment, an independent variable with a p value less than or equal to 0.05 was considered significantly associated with the outcome variable. It was reported using an adjusted odds ratio with a 95% confidence interval.
The Arsi University College of Health and Medical Science Ethical Review Committee granted us ethical approval. All adult participants provided verbal informed consent, and minor participants provided informed consent after receiving a detailed description of the study from their parents/legal guardians. All methods were carried out in accordance with the applicable guidelines and regulations. Patients identified as non-adherent groups were advised to properly take their medication, and family members caring for the patients were given health information.
Socio-demographic and economic factors
A total of 395 patients were interviewed, which makes a response rate of 93.6%. Two hundred twenty-nine (58%) of the respondents were females. The minimum age was 15, whereas the maximum age was 78, with a mean age of 33 and a standard deviation of +11.7. A large number of the respondents lie in the age group of 30–39, which accounts for 127 (32.2%). Most of them are Muslim in religion and Oromo in ethnicity; 235 (59.5%) and 322 (81.5%) respectively. Most were from rural areas (56.7%). Two hundred thirty-five (59.5%) of respondents said they had only learned in elementary school, while 43 (10.9%) said they had a diploma or higher. The mean income was 1110.30 Ethiopian Birr (ETB) with a standard deviation of +2065.55ETB. Almost two thirds of the respondents had no well-known income; they account for 293 (74.2%), whereas 3 (0.8%) had the maximum range of income in the group, which lies between 10,055 and 11,305 ETB. More than half of the respondents were married 206 (52.2%). Regarding the presence of an individual to remind them to take their medication, 358 (90.6%) reported that they had an individual who reminded them to take their medication (Table 1).
Patient related factors
Among the respondents, 41 (10.4%), 34 (8.6%) and 38 (9.6%) had a history of Khat, tobacco and alcohol use in their lifetimes, respectively. Other substances like cannabis and marijuana were rarely used by 12 (3%) of the study participants. In terms of patients’ belief in the medication they are taking, 354 (89.6%) believed that the medication could cure them. 264 (66.8%) of the respondents have a good understanding of the reason they took the medication. 37 (9.4%) of them reported perceived stigma, while the rest did not. During the time of the CVD-19 pandemic, only 24 (6.1%) reported fear of coming for follow up, whereas 10 (2.5%) had a history of cutting down their medication due to fear of transmission. Even iff the pandemic will continue, 388 people (98.2%) said they would keep taking their medication on follow up. Only 20 (5.1%) were unsatisfied with the service they obtained from the psychiatry OPD (Table 2).
Health system related factors
Among the study participants, 131 (33.2%) reported that there is a problem with medication accessibility in the hospital pharmacy and 145 (36.7%) of the respondents reported that the cost is expensive. Only 86 (21.8%) reported that they waited more than two hours while they came for their follow up. 263 (66.6%) and 344 (87.1%) were confirmed as they got information from professionals working in the clinic on the side effects of medication and medication adherence (Table 3).
According to the information obtained from their chart, 255 (64.6%) were diagnosed as cases of schizophrenia and taking atypical antipsychotics, 151 (38.2%) and 122 (30.9%) were on conventional antipsychotics. One hundred sixty-nine (42.8%) of respondents had slight or superficial insight about their illness, and 78 (19.7%) reported being cured of their illness. Concerning severity estimation by the patients, 271 (68.6%) reported that their illness was severe and 49 (12.4%) reported that it is mild. Thirty patients have different reports of side effects currently which was also reported by professional observation. Medical illness comorbidity accounted for 24 (6.1%) of the 27 (6.6%) with high epilepsy comorbidity (Table 4).
Information taken from caregivers to obtain additional data
All respondents were interviewed face-to-face and by phone to add additional information that may be associated with the medication-taking behavior of the respondents. Accordingly, among 395 close family members, 132 (33.4%) reported that the most common reason for not properly taking the medication was a lack of insight and hesitation as a result. For the question asked the difficult and unsolved issue by them not to properly take medication, 130 (32.9%) of care givers reported lack of insight and hesitation as a result was found the difficult and still unsolved problem, followed by care givers’ report that there is no difficult problem that accounts for 109 (27.6%). For the possible solution for proper medication taking behavior, 130 (32.9%) of caregivers reasoned that free and sufficient medication accessibility would be a possible solution, followed by strong family support at 84 (21.3%) (Table 5).
Prevalence of medication adherence status
Fig 1 indicates the prevalence of respondents’ medication adherence status at Assela Referral and Teaching Hospital in Ethiopia. Among the respondents, 149 (37.7%) were non-adherent and 246 (62.3%) of them were adherent to medication.
Factors associated with treatment adherence
Lifetime alcohol use, belief in medication, perceived stigma, and illness insight were among the variables that showed a significant association with treatment adherence. The odds of medication adherence among respondents who had a lifetime alcohol use history [AOR (95%CI); 3.18 (1.31–7.72)] were 3 times higher than their counterparts. Individuals who believed in their medication were 65% less likely to be adherent than those who did not believe in their medication [AOR (95%CI); 0.36 (0.16–0.81)]. Respondents who had perceived stigma had 2 times higher chance of adherence to their medication compared to those who had no perceived stigma [AOR (95%CI); 2.31 (1.01–5.31)]. Individuals who had slighht insight compared to those who reported currently getting a cure from their illness were less adherent [AOR (95%CI); 0.25 (0.12–0.53)]. The educational status and medication availability problems in the hospitals’ pharmacy were found insignificant in the final model. (Table 6).
The aim of this study was to assess the prevalence of treatment adherence and its associated factors. The prevalence of treatment adherence was found to be 62.3%. This prevalence is nearly similar to a study conducted in Jimma, Nigeria with a prevalence of 60.5% and 55.7% respectively [3, 9]. Where as it was high compared with studies conducted in Bahir Dar at different years of study [10–12] and systematic review and Meta-analysis summary prevalence . The possible reasons for the difference can be explained by differences in client background, time of the study and the tool used for assessing adherence to medication. There are different factors for treatment adherence according to different findings because of variation in different aspects across the world, including setting, clients’ background, tools used, and other factors [11, 13]. In the current study, factors significantly associated with treatment adherence were found to be: life-time alcohol use, perceived stigma, belief about medication, and insight about illness. In this study, lifetime alcohol use history had 3 times the odds of adherence compared to those who had no history of using alcohol in their lifetime. It contradicts a systematic review of the literature, which found substance abuse to be a significant factor in medication non-adherence among patients with various major mental illnesses [4, 14] and excessive alcohol use is related to a lower medication adherence rate . The possible reason for the difference might be due to respondents’ change in attitude toward medication taking as a result of getting help and advice from psychiatric professionals to stack on their medication. Those who had perceived stigma were 2 times more adherent compared to those who had no perceived stigma. This can be explained by the respondents’ inner motivation to be cured of their illness so that people cannot stigmatize them. Belief about medication was the other factor which showed a significant association in which clients who believed in their medication were less adherent compared to those who had no belief in their medication. This can be due to an arbitrary answer by respondents to a closed-ended question. This is contrary to the study finding in New York, which states that higher motivation for mental health treatment and recovery support was related to greater adherence [15, 16]. The difference might be due to fear of responding "I cannot believe in the medication you are giving to me." to the clinician. Some of the respondents may say yes only to prevent further questions. Concerning insight, those respondents who had slight insight and those who had no insight were less adherent to their medication than those who reported they got more cure from their illness. This is supported by studies’ findings which found that poor insight is one of the significant factors in medication non-adherence [4, 5, 9, 10, 14]. It is not consistent with the findings of study which found patients feeling better  and expectation of cure rather than continuing treatment leads for treatment non adherence .
In this study, additional data was gathered from family members who were caring for the patient to search for possible associated factors for medication non-adherence. This is due to the multifaceted factors that caused patients to deviate from their medication. So, unless care givers are included, it is impossible to solve the problem of non-adherence, which is recommended by some researchers [11, 15, 18]. Therefore, this finding part was supportive of the clients’ data. They stated that the most critical problem for not taking medication properly was a lack of insight, which accounted for 33% of the total. Still, this is the problem that most family members did not have a solution for (33%). While family members asked for possible solutions for their significant other to adhere to their medication, (40%) reported giving health information for the patient followed by free and enough medication from the hospital (33%) might help to solve the current non-adherence issue, according to the caregiver’s opinion. Generally, it is impossible to conclude that adherence can be improved without the involvement of patients and significant others in their family members .
Because this study is cross-sectional type, it cannot determine the exact cause of treatment nonadherence and it cannot indicate non adherence effects on the patients. Secondary data were extracted from patients’ charts but not assessed from the patient. Some people were simply saying yes for some of the close ended question.
The prevalence of medication adherence among people with major mental illness was not satisfactory. Factors like alcohol use, belief in medication, having perceived stigma and insight were found to be associated with medication adherence status. Alcohol use history and perceived stigma increase medication adherence, whereas having superficial insight, poor insight, and belief in medication decrease medication adherence.
Improving the medication adherence of people with major mental illness in the study area and tackling those associated factors will have a better contribution to the good outcome of patients. As a result, health care facilities, professionals, patients, and family members need to collaborate to address these problems. Awareness creation at an insight level needs to be worked on by psychiatry professionals working on follow-up of patients at ARTH psychiatry clinic to enable patients to well adhere to their medication. Deep understanding of adherence and true belief in their medication will help to increase their adherence level. Discussing patient-specific factors with the patient and significant other family members will further address the problem of adherence need to be addressed by psychiatry professionals working in this clinic.
We would like to thank the psychiatry professionals at Adama General Hospital and Asella Referral and Teaching Hospital for their assistance during data collection.
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