Medication Adherence in Patients With MDD
Of the reviewed articles that investigated medication adherence to anti-depressant medications or concomitant with antipsychotics, anxiolytics, mood stabilizers, and psychostimulants, 34 studies used adherence measurement methods and 10 studies did not report prevalence of adherence.
Descriptions of data collection methods are presented in Table D (available in the online version of this article). Of 34 studies that measured medication adherence, 23 (67.6%) studies used self-report, nine (26.5%) used pharmacy refill and claims databases, and two (5.9%) used pill count. The rate of adherence as assessed using self-report, claims/refill databases, pill count, and health provider's report (self-report per patient files) ranged from 10.6% to 85.4% (Abegaz et al., 2017; Alekhya et al., 2015; Al-Jumah, Ahmad Hassali, & AlQhatani, 2014; Al-Jumah et al., 2014; Aljumah & Hassali, 2015; Baeza-Velasco et al., 2019; Bhat et al., 2018; Burnett-Zeigler et al., 2014; Chatterjee et al., 2017; De las Cuevas et al., 2014a,b; Endale Gurmu et al., 2014; Isa et al., 2018; Klein et al., 2017; Lu et al., 2016; Lucca et al., 2015; Mert et al., 2015; Novick et al., 2015; Serrano et al., 2014; Sirey et al., 2017; Taleban et al., 2016; Vannachavee et al., 2016), 10% to 62.9% (Bushnell et al., 2016; Green et al., 2017; Grover et al., 2018; Holvast et al., 2019; Klang et al., 2015; LeBlanc et al., 2015; Mert et al., 2015; Yau et al., 2014; Zhang et al., 2016), 45% (Hammonds et al., 2015; Pradeep et al., 2014), and 69.2% (Mert et al., 2015; Novick et al., 2015), respectively. This wide range of adherence rates could be due to variations among studies in terms of data collection methods, including measurement tools and period of data collection.
Twenty-three studies used standardized and structured data collection tools and structured interviews to measure adherence. Five (21.7%) studies used the Morisky Medication Adherence Scale-8 items (MMAS) (Abegaz et al., 2017; Al-Jumah, Ahmad Hassali, & AlQhatani, 2014; Al-Jumah et al., 2014; Aljumah & Hassali, 2015; Chatterjee et al., 2017), four (17.4%) studies used the four-item Morisky Green Levine Medication Adherence Scale (MGLS) (De las Cuevas et al., 2014a,b; Klein et al., 2017; Lu et al., 2016), and four (17.4%) studies used the Medication Adherence Rating Scale (MARS) (Baeza-Velasco et al., 2019; Endale Gurmu et al., 2014; Lucca et al., 2015; Taleban et al., 2016).
Nine studies used electronic data records (pharmacy or medical claims databases) to measure medication adherence using different measures, including the percentage of days covered (PDC), medicine possession ratio (MPR), prescription fill, and missing days. The PDC is the ratio of the number of days the patient is covered by the medication in a period to the total number of days in the period. LeBlanc et al. (2015) considered 80% the cutoff between adherence and nonadherence. The MPR is the number of days in which doses are dispersed divided by the total number of days between the first and last doses. This ratio is dichotomized into >80%, which is considered adherent, and ≤80%, which is considered nonadherent as reported by Holvast et al. (2019), whereas Slabbert et al. (2015) reported that patients are considered adherent if MPR is between >80% and ≤110%.
Regarding prescription fill and missing days, nonadherence is considered discontinuing the medication before the 180 days after the index refill date (Bushnell et al., 2016). Other studies defined adherence as the proportion of compliance during the first 24 weeks from prescription fill (Klang et al., 2015). Yau et al. (2014) measured adherence as filled prescriptions for medications with no lapses of more than 15 days within 6 months after the start of treatment. On the other hand, two studies used pill count by calculating the number of pills taken divided by the expected number of pills taken during the study period and multiplying it by 100 (Hammonds et al., 2015). Another study calculated adherence as the total number of weeks participants took medication (Pradeep et al., 2014).
Factors Affecting Medication Adherence
Several factors contribute to patients' lack of adherence. Most literature reports the following five factors of adherence from the WHO: (a) socioeconomic, (b) health care provider/system, (c) illness, (d) medication, and (e) patient related (Gast & Mathes, 2019; Sabaté, 2003). Later studies added to the aforementioned list of factors to include family/caregiver and other resource factors (Kane et al., 2013). Hung (2014) identified the following factors to be associated with nonadherence to antidepressant treatment: sociodemographic, clinical features of depression, comorbidities, pharmacological, attitudes toward antidepressants, previous experiences of antidepressant treatment, patient– provider relationship, and genetics.
Although there is some overlap in factors affecting medication adherence, most studies relied on those of the WHO. Therefore, we used these five factors in the current scoping review to extract the factors from included studies. Factors that could contribute to medication adherence among patients diagnosed with MDD are summarized and presented in Table E (available in the online version of this article). Of 37 included studies, 27 studies investigated factors that influence medication adherence. The following section will explore commonly reported factors associated with medication adherence.
Factors affecting toward medication adherence (n=27)
Socioeconomic Factors. Language and literacy have been associated with medication adherence level (Green et al., 2017). Using different self-report assessment methods, medication adherence was related significantly to income (Lu et al., 2016; Lucca et al., 2015) and level of education (De las Cuevas et al., 2014a; Lucca et al., 2015). Regarding living conditions, Yau et al. (2014) noted that type of accommodation was associated with noncontinuous use of antidepressant medications, particularly in patients with low socioeconomic status who live in public housing. Endale Gurmu et al. (2014) reported that patients residing in rural areas had a higher risk of nonadherence. Patients' occupation is also associated with medication adherence. Patients working in service and farming industries reported significantly higher adherence rates compared to patients working in business industries and those of housewives and students (Shrestha Manandhar et al., 2017).
Lack of support is also a factor for nonadherence (Grover et al., 2018; Lucca et al., 2015). Studies conducted in different contexts reported that lack of support from family members, spouses, and friends was found to be a barrier, ranging from delaying initiation of medication to continuation of medication (Ho et al., 2017; Srimongkon et al., 2018). In addition, Ho et al. (2017) and Vargas et al. (2015) noted that sociocultural stigma influences adherence. In instances where depression is considered a negative personal characteristic and sign of madness, this view has contributed to the ostracization and alienation of patients with MDD. Moreover, religion and cultural beliefs have been reported as barriers to medication adherence (Ho et al., 2017).
Health Care Provider/System–Related Factors. Accessibility to health care services, poor access to health care locations, long clinic wait times, limited time with a psychiatric provider, and lack of accessible appropriate material have been found to influence medication adherence (Abegaz et al., 2017; Green et al., 2017; Grover et al., 2018; Ho et al., 2017). Patients who travel long distances to a psychiatric clinic are five times more nonadherent to medication compared to patients who live a short distance from the clinic (Abegaz et al., 2017). Ho et al. (2017) reported that patients who have experienced long clinic wait times and lack transportation to health care settings had lower rates of medication adherence. Limited access to different formats of informational materials in psychiatric clinics also influences medication adherence due to lack of verbal and written instructions and information, use of different languages in instructions and information, and inappropriate formats for patients with physical disabilities (e.g., hearing and visual impairment) (Green et al., 2017). Furthermore, the limited time of psychiatric follow-up visits affects adherence to medication (Green et al., 2017).
Seeing different psychiatrists and multiple prescribers at every clinic visit affects patients' confidence and trust toward providers, which later affected their medication-taking behavior (Ho et al., 2017). Nonavailability of psychiatrists during follow up was another reason for nonadherence (Lucca et al., 2015). In addition, patients' satisfaction level with psychiatrists is also related to medication adherence (Alekhya et al., 2015). The frequency of follow-up visits to psychiatric clinics was also found to affect medication adherence (Alekhya et al., 2015; Ho et al., 2017; Mert et al., 2015). Less clinic visits related significantly to a low level of medication adherence (Al-Jumah et al., 2014; Yau et al., 2014).
Ho et al. (2017) reported that poor communication between patients and providers could impede medication adherence. In addition, inadequate information on medications and disorders and health care provider guidance were related to low adherence levels (Green et al., 2017; Lucca et al., 2015; Srimongkon et al., 2018). Despite appropriate information and guidance, access to medication in facilities is more related to availability, which increases adherence rate (Endale Gurmu et al., 2014; Ho et al., 2017; Lucca et al., 2015; Srimongkon et al., 2018).
Illness-Related Factors. Acute onset of illness associated with early withdrawal was experienced in patients with MDD (Grover et al., 2018). Earlier diagnosis of MDD minimized medication's noncontinuous behaviors (Yau et al., 2014). A short duration of illness signified high rates of adherence in one study (Al-Jumah et al., 2014). Alekhya et al. (2015) noted a correlation between patients who experienced illness for >1 year and low adherence. Similarly, risk of medication nonadherence in patients who have been diagnosed with MDD for more than 2 years was found to be high (Abegaz et al., 2017). Furthermore, adherence to medication is influenced by symptoms and severity of the disorder. Lucca et al. (2015) demonstrated that patients reported forgetfulness, no improvement, and deterioration of conditions as factors influencing medication adherence. Similarly, other studies showed that somatic symptoms of MDD are associated with early treatment dropout (Grover et al., 2018). Furthermore, nonadherence is associated with high physical pain (Baeza-Velasco et al., 2019). In addition, in patients with a history of childhood maltreatment, adherence levels were lower (Baeza-Velasco et al., 2019). De las Cuevas et al. (2014a) found that patients with severe depression demonstrated medication nonadherence. However, the opposite association between adherence and depression severity demonstrated that less severe depression was significantly correlated with higher medication adherence rates (Al-Jumah et al., 2014; Baeza-Velasco et al., 2019). In another study, recurring episodes of depression had a significant impact on medication adherence, indicating a positive relationship to increased medication adherence (Lu et al., 2016).
Number of psychiatric hospitalizations also influences medication adherence, with Baeza-Velasco et al. (2019) concluding that more psychiatric hospitalizations are associated with high levels of nonadherence. In addition, comorbid physical illnesses, alcohol dependence, illicit drug use, and concomitant psychiatric illness negatively interfered with medication adherence in patients with MDD (Abegaz et al., 2017; Alekhya et al., 2015; Grover et al., 2018; Ho et al., 2017; Srimongkon et al., 2018). On the contrary, patients with comorbid anxiety exhibited higher medication adherence (Lu et al., 2016). Patients with a family history of depression were also found to be nonadherent (Alekhya et al., 2015). In patients with suicidal ideation and attempts, poor adherence was substantially increased (Alekhya et al., 2015; Baeza-Velasco et al., 2019). Cross-sectional studies of patients with bipolar disorder, schizophrenia, schizoaffective disorder, depression, and other psychiatric disorders showed that the diagnosis had a significant negative effect on medication adherence (Endale Gurmu et al., 2014; Mert et al., 2015).
Medication-Related Factors. According to recent studies, complex treatment regimens impair adherence significantly. Alekhya et al. (2015) found that polypharmacy has a significant impact on adherence; most patients do not adhere to a multiple drug regimen. In addition, patients with comorbidities discontinue medications due to pill burden (Ho et al., 2017). Moreover, previous studies stated that adverse reactions are associated with level of medication adherence (Alekhya et al., 2015; Bhat et al., 2018; Endale Gurmu et al., 2014; Grover et al., 2018; Green et al., 2017; Srimongkon et al., 2018; Vannachavee et al., 2016; Yau et al., 2014). In addition, nonadherence is related to the severity and amount of adverse effects (De las Cuevas et al., 2014a). Ho et al. (2017) reported that patients stop taking medications due to side effects. In other studies, patients with MDD stated that the most common reason for nonadherence was adverse reactions to medications (Lucca et al., 2015; Mert et al., 2015; Shrestha Manandhar et al., 2017).
The duration of treatment can also affect medication adherence. Studies using MPR reported that duration of treatment is statistically and clinically correlated with adherence (Slabbert et al., 2015). However, Lucca et al. (2015) noted that although patients continued to receive treatment during the first 3 months, they also reported a significant rate of medication nonadherence. A qualitative study concluded concerns about the long-term effects of antidepressant medications have a negative effect on implementation of therapy and medication adherence (Srimongkon et al., 2018). Endale Gurmu et al. (2014) reported increases in treatment duration resulted in increased nonadherence. Inconvenient dose regimen may also affect medication adherence (Srimongkon et al., 2018). In other studies, the cost of medication was a factor for nonadherence (Lucca et al., 2015) and correlated substantially with nonadherence (Shrestha Manandhar et al., 2017). Studies that assessed adherence to a prescribed class of medication reported that the type of active ingredients consumed, or formulations, significantly related to level of adherence (Lucca et al., 2015; Slabbert et al., 2015). Discontinuing medication was found to be associated with perception of ineffective response (Novick et al., 2015).
Patient-Related Factors. Patient factors associated with medication adherence represent sociodemographic (e.g., age, gender, race, marital status), psychological (e.g., beliefs, attitudes, satisfaction, knowledge, psychological reactance, locus of control, self-stigma, self-motivation, insight, self-management), and physical (cognitive and behavioral; e.g., forgetfulness, personal obligation, carelessness, confusion) factors.
Age is considered a predictor of adherence to prescribed medications. Adherence to antidepressant medication was assessed in two community mental health centers located on Tenerife Island, Spain, indicating the likelihood of medication adherence for older patients was low (De las Cuevas et al., 2014b). A study comparing level of adherence reported lower adherence levels for patients age >60 years than patients age 18 to 40 years (Slabbert et al., 2015). In contrast, other studies reported older patients had higher adherence rates than younger patients (Al-Jumah et al., 2014; Endale Gurmu et al., 2014). In addition, young age is significantly associated with medication discontinuation (Yau et al., 2014).
Gender is a factor in the discontinuation of medications among patients with MDD, with female patients showing higher levels than male patients (Yau et al., 2014). In addition, male gender was also found to be associated with lack of adherence (Al-Jumah et al., 2014). Race/gender is also associated with adherence. Across four race/gender subgroups (African American women, African American men, White women, and White men), White women had higher rates of adherence (3.1 times) than African American women (Burnett-Zeigler et al., 2014). Marital status also exhibited significant differences in level of medication adherence. According to Baeza-Velasco et al. (2019), high rates of adherence have been found among those who have partners.
Patients' beliefs also influence medication-taking behavior. Believing in the need for medication is positively associated with medication adherence (Green et al., 2017), whereas concerns regarding harmfulness and overuse are related to medication nonadherence (Al-Jumah et al., 2014; Bhat et al., 2018; Chatterjee et al., 2017; Green et al., 2017; Vannachavee et al., 2016). The belief that psychiatric medications are considered harmful has been associated with higher rates of nonadherence (De las Cuevas et al., 2014a). Non-adherent patients displayed a higher degree of concern regarding potential adverse effects of medications, such as dependence, side effects, and accumulation effects (De las Cuevas et al., 2014a). In another study, beliefs that medication does not relieve symptoms and increases the severity of the disease, in addition to denial of one's psychiatric illness, have been reported as reasons for interrupting treatment plans (Endale Gurmu et al., 2014; Grover et al., 2018).
Necessity beliefs were significant predictors of high antidepressant medication adherence. Patients believe that antidepressant medication may protect against exacerbation of depression, thus their mental health status is dependent on adherence (Lu et al., 2016). However, concerns of long-term consequences, being heavily dependent on medication, patients' perception of mastery on medication (i.e., perception of being controlled by the medication), and their perception of life stability may negatively impact their beliefs regarding antidepressant medications (Lu et al., 2016). Srimongkon et al. (2018) reported that patients' beliefs in medication efficacy had a positive influence on adherence, whereas therapeutic side effects had a negative influence on adherence. Qualitative interviews of the experiences of MDD in Latino outpatients concluded that patients had concerns regarding medications and depression that may have been perceived as obstacles to treatment and medication adherence (Vargas et al., 2015).
Concerns regarding fear of dependence on antidepressant medications, physical ramifications of taking antidepressant medications, risk of deteriorating mental health, potential hazardous dosages, irrepressible adverse effects (Vargas et al., 2015), and alternative therapies also impact antidepressant medication adherence (Endale Gurmu et al., 2014; Vargas et al., 2015).
Regarding attitude toward medication, positive attitude is related to adherence (Baeza-Velasco et al., 2019; De las Cuevas et al., 2014a; Green et al., 2017; Serrano et al., 2014), and negative attitude is related to nonadherence (Ho et al., 2017). In addition, low level of adherence to antidepressant medication is associated with low treatment satisfaction (Al-Jumah et al., 2014). Medication adherence can also be influenced by a negative emotional reaction to regulations or recommendations of medication use that affect freedom and autonomy, and beliefs regarding the control over one's health. Psychological reactance and chance external locus of control are positively associated with medication adherence. More reactant patients are less adherent and more externalized, whereas patients who depend on their providers have higher levels of adherence (De las Cuevas et al., 2014b).
Self-stigma also affects medication adherence (Vargas et al., 2015). Self-stigma regarding depression, denial of one's disorder, and nonacceptance of the disorder are major reasons for discontinuing medication (Mert et al., 2015; Srimongkon et al., 2018; Yau et al., 2014). Patients who experience severe depressive symptoms but want to feel better are motivated to adhere to medications. According to Srimongkon et al. (2018), self-motivation and self-management contribute to an increase in medication adherence; however, lack of insight may influence adherence negatively (Ho et al., 2017; Lucca et al., 2015). Moreover, patients revealed that forgetfulness negatively affects medication adherence (Endale Gurmu et al., 2014; Ho et al., 2017; Shrestha Manandhar et al., 2017). Patients' personal characteristics, such as carelessness, confusion (Lucca et al., 2015; Shrestha Manandhar et al., 2017), and being busy (Endale Gurmu et al., 2014), as well as obligations, such as traveling to work and/or health care agencies, negatively influence medication adherence.
Intervention Strategies for Improving Medication Adherence
Ten of the 37 included studies evaluated the effectiveness of various interventions to improve medication adherence among patients with MDD (Table F, available in the online version of this article), ranging from single element interventions to multi-element interventions. These interventions have been categorized into monitored feedback (adherence and disease), reminders, education and information, counseling (cognitive, behavioral interventions), and multifaceted interventions. Multifaceted interventions were defined as interventions including two or more components, such as education with monitored feedback and cognitive education with counseling (Cochrane Effective Practice and Organization of Care Review Group [EPOC], 2002).
Interventions Based on Monitored Feedback. The use of pharmacy management and community health care services has been shown to positively affect medication adherence (Bhat et al., 2018; Klang et al., 2015; Pradeep et al., 2014). Pharmacist-led, multidisciplinary telemonitoring provided early intervention for patients following antidepressant medication initiation or up-titration to enhance adherence, relieve adverse effects, and minimize suicide risks through education and information and monitored feedback (adherence and disease) (Bhat et al., 2018). Klang et al. (2015) compared community pharmacist management, which used education and information, reminders, and monitored feedback approaches, with treatment as usual to measure treatment adherence after 1 and 6 months. Adherence rate was higher among patients who received community pharmacist management (Klang et al., 2015). In a study that investigated enhanced care home visits using education and information and monitored feedback compared to treatment as usual, higher rates of treatment completion and medication adherence were noted for the intervention group (Pradeep et al., 2014). However, there was no significant difference in outcomes of depression severity at 6-month follow up (Pradeep et al., 2014).
Interventions Based on Reminder Systems. Use of an electronic medication reminder application through a smart-phone increased adherence to antidepressant medications in a sample of college students (Hammonds et al., 2015).
Education and Information Interventions. Information is conveyed in a variety of formats, including verbal, written, or audiovisual. These interventions are designed to educate patients to promote medication adherence by sufficiently describing the way to take medication, discussing any reluctance to take medication, and discussing patients' beliefs and knowledge about their condition and treatment (Aljumah & Hassali, 2015; LeBlanc et al., 2015). These interventions focus on patients, context, and the health care system, adopting patient-centered care and shared decision-making principles (Aljumah & Hassali, 2015; LeBlanc et al., 2015). Providing information about antidepressant medications through pharmacist-led interventions significantly improves medication adherence, treatment satisfaction, general overuse beliefs, and specific beliefs. However, in one study, the severity of depression and health-related quality of life did not differ between intervention and control groups at 6 months (Aljumah & Hassali, 2015). In addition, other studies used depression medication choice as a novel shared decision-making approach compared to usual care and found no differences in medication adherence, depression control, and encounter duration (LeBlanc et al., 2015).
Cognitive-Behavioral Counseling Interventions. Cognitive-behavioral therapy (CBT) has been proven effective in improving self-concept, pessimistic worldview, negative thoughts, and medication adherence (Nieuwlaat et al., 2014). Taleban et al. (2016) used a novel approach to cognitive-behavioral interventions through bibliotherapy (booklet) and booklet associated with text messaging. The study sample was allocated to three groups: control, booklet, and text messaging. Data were collected three times: before the intervention, immediately after the intervention, and 3 months after the intervention. Medication adherence was insignificant within each group at different times; however, the interactive effect of groups was significant (Taleban et al., 2016).
Multifaceted Intervention. A single element approach has limited effectiveness on medication adherence because the factors determining adherence interact and potentiate each other's influence (Nieuwlaat et al., 2014; Sabaté, 2003). Evidence supports a multifaceted approach is the most effective, as it uses more than one factor and more than one strategy (Isa et al., 2018; Sirey et al., 2017; Vannachavee et al., 2016). Examples include the treatment initiation and participation (TIP) program, drug adherence enhancement program, and psychoeducation with basic CBT strategies (Isa et al., 2018; Sirey et al., 2017; Vannachavee et al., 2016). Multifaceted approaches significantly improved level of knowledge of depression and attitudes toward medication adherence, as well as decreased depressive symptoms compared with treatment as usual (Isa et al., 2018; Sirey et al., 2017; Vannachavee et al., 2016).