|Year : 2019 | Volume
| Issue : 1 | Page : 135-140
Psychosocial correlates of medication adherence in patients with depressive illness
Jyoti Prakash1, YK Yadav2, Kalpana Srivastava1, T Madhusudan3
1 Department of Psychiatry, Armed Forces Medical College, Pune, Maharashtra, India
2 Department of Psychiatry, Command Hospital, Kolkata, West Bengal, India
3 Department of Psychiatry, Command Hospital, Lucknow, Uttar Pradesh, India
|Date of Submission||29-Sep-2019|
|Date of Acceptance||13-Nov-2019|
|Date of Web Publication||11-Dec-2019|
Dr. Jyoti Prakash
Department of Psychiatry, Armed Forces Medical College, Pune
Source of Support: None, Conflict of Interest: None
| Abstract|| |
Introduction: Nonadherence to medication is common in depressive illness and the same may lead to increased risk of relapse, morbidity, burden of care, and avoidable health cost. Factors which may cause nonadherence are multiple. Methodology: A study was undertaken to appreciate the role of various psychosocial factors in adherence to various antidepressant medication in the patients of depressive disorder. One hundred and fifty patients after due consent were subjected to medico-psychosocial-structured per forma, Beck's Depression Inventory, The Belief About Medicines Questionnaire, and the Morisky Medication Adherence Scale. Results: Nonadherence to antidepressant medication in our study was 73.33%. Characteristics of the disease, disease therapies, patient-associated aspects including beliefs, and social and economic support did affect medication adherence. Conclusion: Nonadherence to medication was common in patients with depressive illness. Finding emphasizes the need to sensitize the patients about the importance of proper adherence.
Keywords: Antidepressants, depressive illness, medication adherence
|How to cite this article:|
Prakash J, Yadav Y K, Srivastava K, Madhusudan T. Psychosocial correlates of medication adherence in patients with depressive illness. Ind Psychiatry J 2019;28:135-40
Depressive illnesses are common mental health issues in young and older adults. As per the World Health Organization, around 350 million people worldwide are affected with depression, reflecting about 20% of the given population.
Prescribing medicine is integral to medical management in many long-term illnesses such as depression. However, around half of these medications are not taken as prescribed, resulting in suboptimal response to medication and failure of effective treatment. Where the prescriptions given are appropriate, the extent of nonadherence has adverse consequences, for the person in terms of lost opportunity for well-being and enhanced morbidity or mortality. For the health-care system, it results in drained resources, overuse of services, and hospitalization.
One of the significant challenges to manage depressive patients is ensuring adherence. A major dilemma in psychiatry has been to comprehend why patients do not adhere to given medication and various treatments suggested.
Nonadherence to medication is common in depressive disorder and the same may lead to increased risk of relapse, morbidity, burden of care, and avoidable health cost. Factors that may cause nonadherence are multiple and include biopsychosocial factors, attitudes about own illness, and belief about medications.
Many factors which lead to the medication adherence include sociodemography, clinical parameters, and belief/attitudes about illness. Social theory of health belief model argues that main elements which define an individual's adherence to treatment are the perception of severity and susceptibility of the illness, perceived benefits of the treatment prescribed, expected disadvantages of the treatment imparted, and individual's intent to adhere to the treatment schedule. Self-regulatory theory argues that the treatment perception and illness representations do influence the medication adherence. Very consistently noted that patient-centered psychological risk factors for medication nonadherence are lack of insight, refusal of having an illness, and poor attitude for the given medication. Negative bias toward medication and absence of a belief that a medication will avert the relapse have been found as factors toward the risk for nonadherence. Maeseneer et al. observed that belief of the individual or the family about the type of illness and the role of medicine have a huge impact on patient's adherence. Findings related to the impact of severity of symptoms on adherence are not very conclusive. In a review study of patients of psychotic illnesses, the severity of psychosis or the insight was seen to have effect on adherence; however, the interplay between significant other variables was complex.
An appreciation of these clinico-psychosocial variables which affect the medication adherence in these depressed patients will not only make us more informed of these issues but also empower us to take early remedial steps to ensure better adherence.
The aim of this study is to understand the role of various psychosocial factors in adherence to antidepressant medication in patients of depressive illness, with an overall objective to understand nature and extent of medication adherence in patients of depressive disorder and also to identify various clinical and the psychosocial correlates of medication adherence.
The study begins with an overview of the salient features of the disease in patients of various age groups. This study helped us to appreciate the nature and extent of medication adherence and its relation with different correlates in the patients of depressive disorders. This will benefit clinicians to devise suitable interventional strategies to ensure healthy adherence to medication, thereby leading a significant reduction in the morbidity.
| Methodology|| |
The study was conducted in a tertiary care multispecialty hospital. One hundred and fifty patients with the diagnosis of depressive disorder undergoing treatment were taken as part of the study. As there is a wide variance in adherence in the available literature, the prevalence of 50% was taken as proportion of nonadherence for the calculation of sample size. With the same, the sample size was taken as 132 (95% confidence interval and an absolute difference of 5%).
Patients having severe depression with suicidal or psychotic features and coexisting cognitive impairment were excluded.
The study was approved by the institutional ethical committee. Informed consent was obtained. Structured per forma was used for recording the psychosocial profile and relevant medical history. Beck's Depression Inventory (BDI) was used to measure the presence and extent of depression. The Belief about Medicines Questioners was used for understanding people's belief about medicine. Morisky Medication Adherence Scale (MMAS), which is a self-reported adherence measure scale, was administered to measure adherence.
Participants were provided with written and verbal communication about the purpose of the study, contact numbers of persons concerned, and respondent's right to discontinue the interview at any point of time they desired without affecting their treatment benefits.
Chi-square and t-tests were applied for discrete and continuous variables, respectively. Pearson's correlation was used to find a correlation, if any, between the variables.
| Results|| |
One hundred and fifty patients were registered for the data analysis. Equal number of male and female participants was included after obtaining informed written consent.
Medico-psychosocial detail is as brought out in [Table 1]. Majority of them belonged to <40 years age group. Fifty-eight percent of patients of depression had associated comorbid illness such as chronic obstructive pulmonary disease, coronary artery disease, hypertension, diabetes mellitus, andmalignancy. Maximum patients (50.66%) of our study population had a duration of illness between 1 and 5 years. Patients whose duration of disease was higher had more relapses. One hundred percent of the patients with more than 3 years of illness had relapses, among which nonadherence was the main reason. [Table 2] brings out the levels of adherence by MMAS4 and MMAs18. In Morisky Medication Adherence Scales (MMSA) (4), 49% of the patients had a medium level of adherence to prescribed medications, 27% had a high level, and 24% had low-level adherence. As per the MMSA18, 20% of the patients had a high level of adherence, and maximum number of patients (41%) had a medium level of adherence. The responses to “The Belief about medication questionnaire” are shown in [Table 3]. The table aptly highlights a lot of concerns which need to be addressed in drug-related counseling. An ANOVA test showing a significance of difference between variables is shown in [Table 4], which shows that age, onset, duration of the therapy, relapse, BDI, MMAS4, MMAS8, and compliance variables are significantly associated with adherence. The correlation among the variables is shown in [Table 5]. It suggests that the relapse in patients of depression is directly correlated with the duration of therapy and score on the BDI, MMAS4, and MMAS8. It negatively correlated with adherence to drugs. The relapse rate was higher in nonadherent patients. The duration of therapy positively correlated with all other variables except adherence, signifying that nonadherence is commoner in patients whose duration of therapy is prolonged. The BDI in our study had positive correlation with all variables except compliance proving that patients with higher BDI are less compliant. MMAS4 and MMAS8 scores positively correlated with all variables except adherence. The difference between these scores and all other variables was statistically significant. The regression table with dependent variable adherence is as shown in [Table 6]. An R2 of 1 suggests that regression line perfectly fits the given data. In our study, we got R2 value of 0.88; it shows “eighty eight percent of the variance in the response variable can be explained by the explanatory variables [Figure 1].”
|Table 2: Levels of adherence by Morisky Medication Adherence Scale 4 and Morisky Medication Adherence Scale 8|
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|Table 4: ANOVA test showing the significance of difference between variables|
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|Figure 1: Partial regression plot dependent variable: Adherence. R2 gives some information about the goodness of fit of the model. R2 coefficient of determination is the statistical yield of how well regression line approximates real data points|
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| Discussion|| |
This study has attempted to document the role of various psychosocial factors affecting adherence to treatment among patients of depressive illnesses in a psychiatric wing of a tertiary care hospital. Based on the findings available from the literature, the aim of the study was to explore the extent and nature of adherence associated with depression.
Sajatovic et al. in their study with bipolar disorder patients found that a majority of them (54.1%) were totally adherent, 24.5% partly adherent, and 21.4% were not adherent. Nonadherent patients were found to be younger, not married, or to suffering from substance use disorder. Our study concludes that a majority of the study sample belonged to the younger age group (ʀ40 years). Majority of them had a medium level of adherence (49.34%) according to the MMAS 4 scoring scale, while 24% had a low level of adherence. About 26.66% of the patients had good compliance and a high level of adherence.
Kane et al. in their research on psychotic disorders found male gender to be a risk factor among other variables. Our study had an equal number of male (75) and female (75) patients, and the prevalence of low and medium adherence was found to be higher in the male population.
The hospital-based prevalence of nonadherence to antidepressants in this study was found to be 73.33% when medium and low adherence is taken as nonadherence according to the MMAS 4 scale. This is considerably higher than the literature suggested nonadherence to depression medication which ranged from 10.0% to 60.0%. The finding needs to be replicated with similar researches in future.
| Conclusion|| |
- This study has brought out health-related issues that are typically neglected but which routinely confront health services. Nonadherence to the prescribed therapy in a clinical setting was a common problem among those people diagnosed with depression, which is characterized by the discontinuation of medicines without consulting the treating physician. The finding here emphasizes the need to sensitize patients about the importance of correct and proper drug intake
- Patient nonadherence to the prescribed medications is an important factor in the practice of psychiatry, as there is a significant correlation between the nonadherence and morbidity, while also affecting economic, social, and psychological domain significantly. Although the studies have identified risk factors for nonadherence, researchers are yet to bring out robust and consistent ways to improve a patient's adherence. Until specific guidelines are developed in this direction and are found effective, we authors here believe that a good therapeutic alliance between a patient and the therapist will remain at the crux to improve medication adherence.
- This study is a cross-sectional analysis which suggests a caution in making a causal inference with regard to the predictors for adherence. Treatment history and compliance were solely dependent on the patient's history and treatment records. In few patients, treatment history was not available
- Patients had different comorbidities with depression. It can affect their compliance and adherence according to the nature of their comorbid illness
- Different classes of antidepressants have different profiles of side effects affecting the adherence variably
The study's sample size is inadequate for application of its result to all individual psychiatric illness or the various categories of substance users be it alcohol or other drugs. The study was done at a tertiary care center, and thus, generalizing it to all persons with mental illness and substance use problems may be a bit limited.
This article is based on the Armed Forces Medical Research Committee project No. 4619/2015. The authors are extremely grateful to the Office of Director General Armed Forces Medical Services for sanctioning the project. We would be failing in our duty if we do not place on record our sincere thanks to those patients who have contributed to the data in the study.
Financial support and sponsorship
Conflicts of interest
There are no conflicts of interest.
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[Table 1], [Table 2], [Table 3], [Table 4], [Table 5], [Table 6]