“Why Am I Not Taking Medications?” Barriers and Facilitators of Diabetes Medication Adherence Across Different Health Literacy Levels

Abstract

Medication adherence is important for diabetes management. Better knowledge of how patient factors relate to medication adherence allows us to develop more tailored interventions. We explore patients’ perceptions of the barriers to and facilitators of medication adherence across different levels of health literacy. Semi-structured interviews with 23 participants with type 2 diabetes (T2D) were completed, and direct content analysis identified the facilitators of and the barriers to medication adherence through the lens of the Health Literacy Pathway model. Linking medication-taking to daily routine and focusing on the internal locus of control are imperative approaches to fostering self-efficacy of medication use. Understanding patients’ life experiences and clarifying medication misinformation help patients address their concerns with medications. Lowering the cost of medications and simplifying therapy regimens can alleviate participants’ perceived barriers to medication-taking. In this study, we explore medication adherence from the experience of people with T2D and can inform tailored interventions to improve medication adherence.

Keywords

content analysis diabetes health literacy medication adherence qualitative United States of America North America

Introduction

Diabetes is a complex and demanding disease that affects 10.5% of the U.S. adult population in 2018 (Centers for Disease Control and Prevention, 2020). By 2050, the prevalence of population with diabetes is estimated to reach 12.0% with a projection of 48.3 million people diagnosed with diabetes (Narayan et al., 2006). In particular, type 2 diabetes (T2D) incurs tremendous health costs associated with various complications due to poor diabetes control (American Diabetes Association, 2018). In 2017, the total estimated national cost of diagnosed diabetes was US$327 billion, and approximately US$1 of US$7 health care dollars in the United States was spent on caring for people with diagnosed diabetes, including treating diabetes and its complications (Presley et al., 2018). However, health care professionals in the United States still face increasing challenges for diabetes care in spite of the advancement in diagnosis technology and medication treatment. Less than 50% of people with T2D achieve desired glycemic goal recommended by the American Diabetes Association (Ali et al., 2012).

Strict medication adherence to antidiabetic medications is one of the most effective strategies to achieve optimal glucose control; yet, people with T2D have an adherence rate of 31% (World Health Organization, 2003), one of the lowest medication adherence rates among people with chronic illnesses (Donnan et al., 2002). As such, understanding the reasons for medication nonadherence is a logical first step to devising effective interventions (Mayberry et al., 2013). For example, the cost of medical care and complexity of medication regimens (e.g., multiple dosing, high pill burden, taking injectable medications) are two therapy-related reasons frequently cited for nonadherence (Gellad et al., 2011). In addition, people of certain sociodemographic backgrounds have shown a higher rate of nonadherence in T2D, such as people of younger age, lower education level, lower income, and racial/ethnic minority (Curkendall et al., 2013; Kirkman et al., 2015). Even with personalized interventions targeting patients of specific sociodemographic backgrounds to improve patients’ medication adherence (e.g., more access to medication, provision of printed and digital materials, and supply of medication reminders; Pousinho et al., 2016; Presley et al., 2018), improvement in adherence rates is smaller than expected. In fact, a meta-analysis of trials on interventions revealed an increase in adherence ranged from 4% to 11% (Peterson et al., 2003). One of the reasons for the slow progress may be a lack of comprehensive theoretical models to explain nonadherence and guide potentially successful interventions (Costa et al., 2015).

The Health Literacy Pathway (HLP) Model (Paasche-Orlow & Wolf, 2007) is a promising theoretical model to consider in this study because health literacy is critical for optimal medication adherence (Bailey et al., 2014). Health literacy is an individual’s ability to obtain, navigate, and understand the basic health information necessary to make an appropriate health-related decision (McCormack et al., 2010). The HLP posits that health literacy may influence individual communication and psychosocial factors (e.g., health beliefs, self-efficacy, motivation, and perceived barrier) and then change one’s health behaviors (Paasche-Orlow & Wolf, 2007). Similarly, in a systematic review on how medication adherence is shaped by salient individual-level determinants, Bailey et al. (2014) found that health literacy indirectly influences medication adherence via its direct impact on individuals’ communication ability and psychosocial factors, such as individual beliefs in or attitudes toward medications, self-efficacy of medication use, and social support. Both frameworks proposed by Paasche-Orlow and Wolf (2007) and Bailey et al. (2014) advocate for future studies to investigate the detailed contexts of these individual-level factors that could be tailored to clinical practice.

Following Bailey et al. (2014) and the HLP model (Paasche-Orlow & Wolf, 2007), in the present study, we focus on the role of health literacy vis-à-vis medication adherence, communication, and psychosocial factors relevant to medication adherence. However, few studies detail the contexts of medication nonadherence that occurs due to the changes in patient–provider communication and psychosocial factors across different levels of health literacy. For example, health care providers may follow a protocol when communicating with patients; however, they may need more training on how to address patients’ health literacy, tailor the protocol accordingly in clinic visits with a stringent time constraint, and work to improve medication adherence (Marcum et al., 2013). Challenges of addressing health literacy and medication adherence simultaneously may compromise the ability of health care providers to offer pertinent and personalized care. In addition, self-efficacy, a psychosocial factor defined as individuals’ belief in their capacity to perform given tasks and attain desired goals (Bodenheimer et al., 2002), is one of the important prerequisites for behavioral change and considered a major determinant of medication adherence (Huang, Shiyanbola, & Chan, 2018). As such, a better understanding of salient individual communication and psychosocial factors will provide health care professionals with more insights into the interplay between health literacy and medication adherence. Given medication adherence is affected by a variety of patient factors, there is a need to understand from patients what their barriers and facilitators are to capture what could be missed with just quantitative measures alone. In turn, practitioners will be better at pinpointing critical mechanisms, leading to medication adherence, and devising necessary interventions accordingly.

The purpose of this study was to explore patients’ perceptions of the barriers to and facilitators of medication adherence with different levels of health literacy. In this study, a facilitator was operationally defined as any situational or individual factor identified by study participants that improves adherence to the diabetes medications as prescribed. A barrier was any situational or individual factor identified by study participants that hinders adherence to the diabetes medications as prescribed. This qualitative study using direct content analysis further extends our understanding of medication adherence of people with T2D (Elo & Kyngas, 2008).

Method

Study Design

This study was the qualitative part of a mixed-methods study using an explanatory sequential design (Ivankova et al., 2006). We first used a survey to identify salient patient factors associated with diabetes medication adherence across different health literacy levels via quantitative analyses (Huang et al., 2020), followed by a qualitative study with semi-structured interviews. This cross-sectional study was conducted by a pragmatic, descriptive, qualitative approach (Kim et al., 2017; Savin-Baden & Major, 2013), which focuses on the exploration of how individuals make decisions within an actual real-world situation, to summarize patients’ perspectives of communication and psychosocial factors related to medication adherence. Medication adherence could be influenced by a myriad of factors (Bailey et al., 2014; Paasche-Orlow & Wolf, 2007), and it may be difficult to comprehensively measure or describe specific factors in detail by using quantitative methods alone. Therefore, it is appropriate to apply a pragmatic qualitative approach to describe what and how people with diabetes handle medication problems in diabetes management (Savin-Baden & Major, 2013). All authors in this study had research training and health care backgrounds in pharmacy or nursing, and therefore understood the importance of medication for diabetes management.

Sampling and Recruitment

This study was part of a larger research project that focused on the medication adherence of people with T2D, which was conducted at a family medicine clinic in a Midwestern state. Study participants were at least 20 years old, diagnosed with T2D, presently being prescribed to take at least one diabetes medication by mouth daily, and able to read and speak in English. For the qualitative interviews, there is no rigid rule of how large the sample size should be (Malterud et al., 2016). A sample size of 15 to 30 is sufficient for a content analysis approach (Francis et al., 2010). A total of 205 participants completed the screening survey in the quantitative study. Hence, we approached 36 of these participants and 23 (63.9%) agreed and completed the interview.

We applied a purposive maximum variation sampling to recruit participants for interviews based on their levels of health literacy and medication adherence and sociodemographics (i.e., age, gender, and race). Based on their Newest Vital Sign score, participants were divided into inadequate health literacy (i.e., scoring 3 or lower) and adequate health literacy (i.e., scoring 4 or higher; Huang, Shiyanbola, Smith, Chan, 2018; Weiss et al., 2005). Also, based on the Adherence to Refills and Medications Scale for Diabetes score, participants were classified as high-adherent when their total subscore of medication-taking was 28 and low-adherent when they scored less than 28 (Mayberry et al., 2013). Consequently, all participants fell into one of four distinct groups: (a) inadequate health literacy and high medication adherence (n = 5), (b) adequate health literacy and high medication adherence (n = 5), (c) inadequate health literacy and low medication adherence (n = 6), or (d) adequate health literacy and low medication adherence (n = 7).

Data Collection

To best understand participants’ experience of taking medications for diabetes management, face-to-face, semi-structured interviews were conducted for each participant from February to May 2019. Following the HLP model, these interview questions were created and focused on the factors that link health literacy to medication adherence at the individual and interpersonal levels, including (a) self-efficacy, (b) motivation, (c) perceived barriers, and (d) patient–provider communication. These questions (Online Appendix 1) were revised by three professionals with expertise in health literacy, qualitative methodology, and medication adherence to ensure high relevance of the questions to the research aims.

The researcher asked potential participants if they wanted to join the interviews after completing the screening survey and built rapport by providing clear information about the role of the participants and their importance for this study. The researcher saw the participants once for survey collection before they partook in interviews. The participants were not familiar with the researcher prior to the survey data collection. For those who agreed and consented to participate, the interview was scheduled at 1 hour before the participant’s next clinic visit or any time convenient for the participants. Each semi-structured interview took place in a private room on the research site, and the researcher audio-recorded each interview and took written notes. To generate richer information, the interviewees were asked probing questions and allowed to add any information they deemed fit. The median length of interview was 46 (range = 22–70) minutes. In addition to interviews, we collected participants’ sociodemographic background (e.g., age, gender, race, education, and income) and clinical characteristics (e.g., A1C for glycemic control) information.

Data Analysis

Interviews were audio-recorded with an encrypted audio recorder and transcribed verbatim by a University-approved business company that specializes in interview transcription. The researcher verified each interview transcript against its corresponding audio recording. Direct content analysis was employed in interview analysis, of which the process included the following steps: (a) initially reading the transcripts for 3 times to achieve immersion; (b) reading the data line by line to capture key thoughts; and (c) coding and organizing the themes and categories in accordance with the mapping of the constructs guided by the HLP model (Hsieh & Shannon, 2005).

There were two stages of the coding process. First, the researcher assigned the data chunks to generate main codes, and then used both descriptive coding and in vivo coding (Miles et al., 2014). In the first-cycle coding, we summarized and condensed large amounts of data into a fewer number of analytic units. In the second stage, pattern coding was used to group these units into a fewer number of themes aligned with categories that were chosen at the outset from the HLP model.

We coded all 23 transcripts using the technique of investigator triangulation to develop an overall coding taxonomy (Archibald, 2016). Two researchers independently coded all transcripts and came to consensus on each code and interpretation to ensure the findings were grounded in the texts. To display the data in a clear way, a data accounting log was used to show participants’ sociodemographic and clinical data across groups. A content-analytic summary table was created to show the factors related to medication adherence from participants’ perspectives. MAXQDA 12 was used to help organize and categorize the themes.

Ethics

The study was approved by the Health Sciences Institutional Review Board of the University of Wisconsin–Madison (2018-1083). During the recruitment process, the study was explained by a printed study information sheet and a face-to-face interaction between participants and the researcher. Signed written informed consent was required from each participant who had agreed to participate, before the start of each interview. Each participant was given an incentive of US$20 cash after completing the interview.

Results

Background Characteristics of Study Participants

Twenty-three patients agreed and completed the interviews. As more diverse opinions emerged during the interviews of participants with low medication adherence, we recruited more participants in the low-adherent clusters to capture more information of how they managed medications for diabetes care. The sample was composed of 12 females (52%) and 11 males (48%), with the age range of 40 to 78 years old. Online Appendix 2 describes the sociodemographic and clinical characteristics of the participants.

Content Analysis

Guided by the HLP model, factors related to barriers and facilitators of medication adherence were coded into four categories: (a) self-efficacy, (b) communication, (c) motivation, and (d) other perceived barriers. Table 1 lists the specific themes emerging under each category. The themes identified as barriers or facilitators that may influence medication adherence are explained with direct verbatim quotes for further clarification.

Table 1.

Qualitative Themes and Subthemes of Barriers and Facilitators of Medication Adherence.

Category	Facilitators	Barriers
Self-efficacy	• Feeling of being able to control medications for diabetes management on their own	• Feeling of overwhelmingly controlled by medications for diabetes management
Self-efficacy	• Integration of medication-taking into life routine	• Situational influences impede the integration of medication-taking into routine
Communication	• Rapport between patients and providers served as perceived support for diabetes management	• Lack of trust in providers
Motivation	• Life experiences strengthen the perceived need of medications for diabetes management (1) Belief in the effectiveness of treatment	• Life experiences diminish the role of medications for diabetes management (1) Belief in better effectiveness of alternative approaches to diabetes management than medications (2) Prioritizing the use of oral medications instead of injectable medications
		• Concerns about medication safety
		• Confusion over the role of medications for diabetes management
Other barriers		• Individuals’ negative emotion• Limited access to medicationsComplex diabetes regimen

Category 1: Self-Efficacy of Medication Use

Feeling of being able to control medications for diabetes enhances self-efficacy of medication use

Most of the participants felt they could take medications and practice diabetes self-management on their own regardless of their levels of health literacy and medication adherence. Some participants mentioned that they were equipped with full physical skills (e.g., manual dexterity), so it was easy to take medications on their own. In addition, a few participants explained that they had enough knowledge to tell whether their diabetes was under control, so they were able to adjust their medication dose by themselves. The sense of being able to administer or adjust medications independently may have developed participants’ self-efficacy of medication use:

I have manual dexterity. I can give myself my shot, and it’s easy to take those, the diabetes, the oral medicine that I take. It’s very convenient. It’s not hard to do.

Well, with the insulin, you have control of how much insulin goes into your body. So they’ve at least taught me to be able to read my blood sugars, so that I can adjust on my own.

From participants’ point of view, treatments involving simple regimens helped them build more internal controls for taking medications as prescribed. Some participants thought they could take all their medications at once with reminders because they had a less frequent dosing schedule. Some participants mentioned they can take medications as prescribed since they took fewer pills:

I don’t have to do the fast-acting, pre-meal insulin, so it’s easy for me to just take all my meds at one time. I don’t have to remember any other time.

I don’t have a problem taking it as prescribed. I only have to take it one time a day, and that’s it. It’s just one pill. I don’t know how I can take it wrong. There’s no problem. I have this day planner where all my medications are in, and I just go day to day.

In particular, participants with adequate health literacy said clear medication instructions on the bottle helped foster more confidence in taking the medications as prescribed. If they had questions related to taking their medications, referring to the information on the medication bottles helped them manage the medications as instructed by providers:

I’ve got the highest confidence. The label instructions are very clear. And I set out all my medications for the following day, I set out at night when I take my final daily doses before I go to sleep, so everything is ready to go in the morning, and there is no question.

Feeling of overwhelmingly controlled by medications for diabetes management decreases self-efficacy of medication use

Some low-adherent participants with adequate health literacy mentioned that they would like to adjust diet and excise for diabetes management rather than be externally controlled by medications. The feeling that their diabetes management was overly controlled by the medication prevented some participants from taking their medications as prescribed. They thought they were not allowed to fully control their health due to a lack of autonomy in their diabetes care:

I don’t want to be led around by a pill, and far as a concern right now, that’s what’s happening. I am not in control of my health, which I can’t be in control of. A medication is.

Integration of medication-taking into life routine fosters self-efficacy of medication use

The majority of participants highlighted the importance of the integration of medication-taking into daily routine so they do not forget to take medications. Such intention was an internal cue for taking the medications on a regular basis among all participants. In addition, keeping medications at a particular spot that was easily seen was reported as an external cue for medication adherence by most participants. The visibility of medications reminded participants of taking medications at the right time:

[Taking medications] is part of my daily routine now. It’s like getting up taking a shower or brushing your teeth. It’s part of my life. It’s what I got to do.

I keep [medications] right beside me. They are always there, and so as a reminder, it’s time to take medication.

High-adherent participants reported using more external cues to strengthen their confidence in taking their medication as prescribed. Some of them divided their medications in a weekly pillbox or certain containers so they did not miss a dose due to forgetfulness. Also, this approach helped them track medication-taking. In particular, participants with adequate health literacy navigated and used various available resources to reinforce their self-efficacy for taking medications regularly. Some participants asked pharmacists for prefill services that organized their medications into prepackaged doses. Other participants set an alarm on electronic devices to remind themselves of medication-taking. Using multiple approaches provided high-adherent participants an easy way to manage medication-taking:

My medication is set up in a med box provided by the university pharmacy so my medication is distributed to me in little packets, four packets a day. So morning, noon, with my evening meal, and then at bedtime. It’s very easy for me to follow that.

Situational influences impede the integration of medication-taking into routine, resulting in less self-efficacy of medication use

Several low-adherent participants expressed that they had difficulties in taking medications as a part of daily routine. Some of them mentioned that it was hard to take medications at regular time when their work schedule was irregular. A few of them said they sometimes missed the dose, especially the night one, when they fell asleep. For some participants who had to take medications in accordance with the time for meal, they skipped medications when the time for meals and medications mismatched. In addition, some participants reported that they did not have a habit of taking their medication when being away from home, resulting in medication nonadherence:

It’s kind of hard to keep up with your medication on a routine basis at the certain time when you’ve got to be at work at the irregular hours when you’re supposed to take your medication.

I just do [not take the medication] on purpose because if I, you got to eat before you take it. And I’m used to drinking coffee before I can even eat anything. So then I’ll deliberately forget [to take the medication] there.

Category 2: Patient–Provider Communication

Rapport between patients and providers served as perceived support for diabetes management

The communication between patients and providers was considered important for participants’ decision-making regarding medication adherence. Most participants indicated that providers respected their opinions in diabetes management, and that empowered them to be more involved in their diabetes management via starting more conversations and providing rationales for their treatment. This engaged bilateral communication helped participants develop rapport with their providers and perceive more social support for their diabetes management. The good patient–provider relationship made patients more informed of their treatment and motivated them to take medications persistently:

[The doctor] obviously encourages me to keep up the good work, so to speak. Because my results had been good, and he basically encourages me not to back off, that whatever I’m doing is working, and so continue to do it. He’s also very responsive to any questions that I may have.

Lack of trust in providers risks the relationship between patients and providers

A number of low-adherent participants mentioned that a poor patient–provider communication sabotaged their relationship with providers. Some participants felt that their providers did not listen to patients but forced them to follow the providers’ orders instead. As a result, participants thought that their providers did not care about their health. That is, they perceived excessive paternalism from their providers:

[My doctor] doesn’t want to listen. That’s why I told her, I tried to explain to her that [the medication] wasn’t working for me. But at first, she didn’t understand, and this is, she, I just talked to her like nine days ago . . . So it’s a matter of, we don’t communicate . . . Then I just say, well, crap, she doesn’t care. Then obviously, [taking medications] can’t be that important for me to do.

Other participants indicated that their providers did not seem to engage them in the conversation because their providers kept providing the same information over and over again without new information:

I don’t think that they could talk to me about anything any different, because I’ve been diabetic for so long that what they tell me is stuff that I already know. It may be boring. I’m fairly intelligent. I read, so I know it’s not anything the doctors are saying or doing.

Category 3: Motivation for Medication Adherence

Life experiences strengthen or diminish the necessity belief about medications for diabetes management

The necessity belief about medications and three subthemes were identified as influencing factors of how participants perceived the role of medications for diabetes management. Life experience from oneself or other important referents (i.e., families, friends, peers) was described as an important factor that affected participants’ beliefs about medications. One subtheme was the belief in the effectiveness of treatment: The fear of diabetes-related complications was mentioned by a majority of participants, especially after learning about other individuals’ experiences of managing diabetes. All of the participants agreed that medication was essential for diabetes management because it helped regulate blood sugar and improve health. They wanted to stay healthy to achieve goals in their life and did not want to suffer from miserable consequences encountered by their family members. Some participants believed that staying healthy left them more time with their family and helped avoid being a burden for the family:

When you see it happening, you have a tendency to be a little more diligent to avoid it happening to you. My husband died from kidney failure, and so you kind of are wary of, you’re going to follow the directions and the medications, what can help resolve the problem a little.

Some participants referred to their own experiences to describe how they felt that the medication was necessary for their diabetes management. They perceived that there were direct benefits of glucose control when they followed providers’ instructions to take medications regularly:

I definitely need metformin now because, if I didn’t take metformin, I’m sure my blood sugar level would go up very quickly. I think that’s dangerous, so I’m taking that very seriously, as a major health issue.

The second subtheme was the belief in the better effectiveness of alternative approaches to diabetes management than medications. Diet, exercise, and medication were the three most frequent alternatives discussed by participants. All of the high-adherent participants ranked medication as high priority for diabetes management. However, the majority of the low-adherent participants considered alternative approaches (e.g., diet adjustment or exercise training) more effective in diabetes management than medications:

The number one thing would be just staying healthy and eating right. You got to eat right. Exercise plays a good part of it, but you have to eat right. You have to eat all the right kind of foods and fruits and vegetables and stuff like that. Stay away from junk and sweets and stuff like that.

Those who favored alternative approaches to diabetes management did not perceive that medication improved diabetes control based on their past experiences. Some of the participants shared that they perceived more immediate benefits of diabetes management by controlling their diet rather than taking medications:

Over the last few years I’ve been on [the medication], and now I just stopped taking [the medication] because I don’t feel like [the medication] was doing any good for me. I don’t feel like it’s improving my health, so why keep taking it?

Some of the participants mentioned that their family members’ or friends’ experiences regarding diabetes management shaped their perceived role of medications. Some participants shared that medications do not improve diabetes effectively but may bring damages to the body. In particular, a few participants described that their friends with diabetes stayed healthy by relying on herbals alone without any pills:

I’ve been having this discussion with my friend, and he keeps telling me if I just change my way of eating and eliminate things, certain things from my diet, then I would make a difference.

Concerns about medication safety impede motivation for taking medications

Regardless of the level of health literacy and medication adherence, participants across all four clusters mentioned that they were concerned with side effects (e.g., gastrointestinal upset, hypoglycemia) of the medication they used. Some participants shared that they formed their concern beliefs based on their past experiences with a few side effects from the medication they used:

I’m still concerned about [the side effect of the medication]. I’m not comfortable, the fact that I did develop kidney disease, I am not comfortable with that. Because I know what can happen, and there again, I been through the mill.

In addition, those with low medication adherence, especially with inadequate health literacy, reported more concerns about medications. They were worried about the consequences of the long-term use of current medications:

I have been on metformin a long term. So how is it affecting my body? Any kind of side effects, what it do damage to any of my organs down through the years.

A number of participants indicated that their concerns with medication safety were derived from their past experiences of taking medications, and that influenced their decision regarding taking medications as prescribed. Sometimes they cut back the medication dose or stopped taking medications to avert the side effects without informing their providers:

[The doctor] had me taking two of them pills. I cut back to one, it just, got sick off of them. My stomach got so upset all the time. I got the diarrhea, and I just felt better after I cut it off, and I left it at one . . . I did cut it off by myself without the doctors being told.

Although high-adherent participants had concerns with medications, they said that asking doctors for help relieved their concerns. In particular, participants with adequate health literacy reported that they looked up online information to cope with their concerns if doctors were unavailable:

I won’t know until I talk to my doctor. Or I can just go online and look it up, but I’ll talk to my doctor about it.

Confusion about the role of medications hinders the motivation for medication-taking

Lacking an awareness of the role of medications was identified as a barrier to medication adherence among the participants with low medication adherence. Most of them doubted the effectiveness of medication. Those with inadequate health literacy mentioned that they were confused with information from health care professionals and were short of knowledge of diabetes itself:

I went in for a colonoscopy, and [the specialist] said check with your doctor to see if you should take your medication or not take your medication. [My doctor] always taught me, it’s all very important to take your medication, and then you go in for a certain test like that, and they tell you, don’t eat for 12, 16 hours. Don’t take your medication. I kind of get confused on if it’s so important to take, then why am I not taking it?

While those with adequate health literacy were able to navigate relevant information at hand, they also had difficulties handling conflicting information from their self-research and health care providers:

But some of this medication, I don’t know. I keep hearing things, you know, that is, that the side effects can trigger this and that. So I’m like, why should I take this if is it going to help me, or is it going to harm me? It’s a 50/50 chance. But doctor said you need it. But then research said, doctors don’t want to tell you this because of this. If you take this, then this happens. I’m like, oh, boy.

Participants wanted to be well and were able to tell if they were healthy based on their subjective assessment of how they felt in the present moment. A number of participants reported that medication was unable to cure diabetes but brought side effects, so they sometimes stopped taking their diabetes medication for a while when they felt better or asymptomatic:

I know the medication is not to cure, it’s to maintain. I don’t expect it to cure me if I take my medication. I’ve been taking it for a long time, and over the years, I think it has progressively, my health has progressively gotten worse. It hasn’t gotten any better by taking the medication . . . There are times when I’m going on vacation or something in the summer, and I’ll have felt really good, and so I feel I don’t need to take my medication every day. And so I won’t take it and then after about a couple weeks or so.

Category 4: Other Perceived Barriers to Medication Adherence

Negative emotion hampers medication adherence

A few participants with low medication adherence perceived negative emotions as a barrier to taking medications as prescribed. They were tired of being sick and taking medications for a long time:

I just be tired of taking medication. I am tired of being sick. It’s been years, I guess it would be considered depression then because I do that. But, I don’t really think I’m depressed or anything like that.

Limited access to medications hinders medication adherence

A large proportion of the participants with low medication adherence indicated that the high cost of medications, especially the injectable medication not covered by the insurance, was a significant barrier to medication adherence. Due to the restricted access to medications, some participants reported they stopped taking medications or cut back the dosage of medication. One of the participants with adequate health literacy said he went online and looked for resources regarding insulin-sharing:

I stopped because the medication was too expensive, and I couldn’t get it. Not too long ago, I had switched insurances, and in between the insurance, I couldn’t, the medication was too high, because they said I wasn’t covered.

You do go online and read about all the people that have diabetes, people that are out there are insulin sharing. They don’t use a whole bottle, so they pass what’s left on to somebody else who can’t afford it. That’s a big one. People who take less of a dose than they’re supposed to because they need to make it last longer until they can afford it again, that type of situation.

Complex diabetes regimen impedes medication adherence

A number of participants with low medication adherence described the complex diabetes regimen as a common barrier to medication adherence. The complexity was composed of the type, frequency, quantity, and size of the medication. They mentioned that the injectable medications were hard to handle. From their perspective, a frequent medication schedule, too many pills, and the large size of the medication made it difficult for them to take medications as prescribed:

Poking myself. My belly has become so hard, it’s just tough from all over the years of giving myself shots in the belly. So that’s the hardest part, finding a place on my belly to give another shot.

It’s not easy for me to take a medication repeatedly during the day.

Discussion

This study identifies key differences in facilitators and barriers to medication adherence in terms of psychosocial and communication factors using theory-driven methods. Facilitators of medication adherence included feeling in control of diabetes management, successful integration of medication-taking into routine, perceived support between patients and providers, and prior experiences reinforcing medication importance. Barriers to medication adherence comprised feeling overwhelming control by diabetes management, situational influences rendering medication-taking as routine, lack of trust in providers, prior experiences diminishing the role of medications for diabetes management, concerns, and confusion about diabetes medications.

Participants in the adherence clusters more commonly perceived themselves as confident in taking their medication and were more likely to do so. Participants with stronger self-efficacy tended to use various strategies to make medication-taking as part of daily routine so they had fewer problems with taking medications as prescribed. High-adherent participants were good at matching their medication schedule with daily routine by using pillboxes and specific containers for medication management, setting an alarm for medication use, and keeping medications in visible places. These basic approaches to medication adherence are able to be carried out without advanced technology or other personnel. In addition, those with adequate health literacy tended to facilitate medication-taking by making use of digital devices as reminders and asking pharmacy service for medication management (e.g., prefilled medication box and cardboard packing of medications). While low-adherent participants also used some of the aforementioned strategies as high-adherent participants did, the same strategies did not work equally well when more perceived situational influences occurred. In particular, those with inadequate health literacy had more difficulties in dealing with situational influences. Thus, the application of diverse strategies fosters the development of self-efficacy of medication use, which in turn facilitates medication adherence.

One explanation for these findings is that the perceived locus of control differs between the clusters with low and high medication adherence. Locus of control is the extent to which individuals believe that they have control over the outcome of events directly by their own (internal control), as opposed to be determined by external forces beyond their control (external control; Hong et al., 2006). All participants were found equipped with internal control of medication because they demonstrated an ability to manage their medications on their own. However, low-adherent participants also expressed a low sense of autonomy and did not want to be overly controlled by medications. It is thus evident that for these participants, the locus of control overshadows self-efficacy. A stronger sense of internal control could foster competence in medication use; conversely, a high level of external control could not. This is in line with the review by West et al. (2018), who found that medication adherence is positively associated with an internal locus of control but negatively with an external locus of control in patients with chronic illnesses.

Making medication-taking a daily routine is a predecessor for a heightened self-efficacy. In a clinical environment, health care providers can assess patients’ self-efficacy of medication use to identify their obstacles to taking medication by using short measurement tools or checklists. As a result, health care providers can adjust interventions to increase patients’ self-efficacy based on the level of health literacy and locus of control. For instance, those who attribute their medication nonadherence to outside influences may indicate a sense of external locus of control. Health care support with more communication and detailed information about integrating medication into routine could strengthen patients’ motivation to take medications.

Most participants in the adherent clusters indicated the rapport between patients and providers motivated their diabetes management. Providers’ respect for patients’ opinions can empower patients to be more engaged in diabetes management. Participants with inadequate health literacy perceived more support as providers invited them to engage diabetes management. In addition, participants with adequate health literacy reported that they were motivated for medication-taking as they were well informed of how medications worked for improved health outcomes. However, participants of low-adherent clusters indicated providers only persuade them to take medications without explanation or empathy. This finding appears to be consistent with the principles of Information–Motivation–Behavioral Skills Model, which suggests that patient–provider communication directly predicts the extent to which a patient adheres to the self-care behaviors recommended by the provider, including medication adherence (Gao et al., 2013). The communication between a patient and a health care provider is another important factor affecting a patient’s medication adherence (Bauer et al., 2014). Peimani et al. (2018) found that a higher perceived quality of patient–provider communication among people with T2D is associated with improved adherence to diabetes medications. As a result, tailored communication of diabetes management accounting for patients’ health literacy (e.g., using plain languages or chunking information) should be applied to diabetes care to develop better patient–provider relationship (Shiyanbola et al., 2019).

Participants indicated their life experiences shaped their perceptions of the medication for diabetes management. Participants in the adherent clusters mentioned that prior exposure to diabetes prepared them to understand the role of the medication for diabetes, to take diabetes seriously, and to take medications as prescribed. Their experiences of how their friends or families coped with diabetes appeared to impact their belief in the effectiveness of treatment. In accordance with social cognitive theory, patients learned vicariously about diabetes from family members and formulated their beliefs and behaviors (Bandura, 1989). These experiences also served as key turning points in motivating or discouraging patients to adhere to their diabetes medications. Our findings resonated with principles of the Health Belief Model and the Transtheoretical Model, which indicated that how individuals’ processes of change depend on how they perceive disease (Prochaska & Velicer, 1997; Strecher et al., 1997). Health care professionals may use these life events to trigger patients to self-reflect or reassess the severity and seriousness of diabetes, ultimately motivating them to modify their health beliefs about medications.

Low-adherent participants reported more concerns about their medication than high-adherent participants. Those with inadequate health literacy had few ideas about how to deal with their concerns, so they sometimes stopped taking medications based on life experiences from themselves or other important referents. While those with adequate health literacy sought more information to relieve their concerns about medications, conflicting information from self-search and providers confused their decision-making regarding medication-taking. As such, while this additional information should alleviate unnecessary concerns, conflicting information from different resources can be detrimental to persistent medication adherence. It is plausible that the confirmation bias influences patients’ decision-making of medication use. Confirmation bias refers to one’s tendency to selectively expose himself or herself to cherry-pick information that confirms one’s preexisting beliefs or ideas, which were more prevalent among people with adequate health literacy (Meppelink et al., 2019; Nickerson, 1998). The ability to seek relevant information turns out to be a double-edged sword. Although patients are able to gather more information to enrich their understanding of the medication, they may fall into a confirmation bias when the providers are not available to clarify misinformation (Champlin et al., 2017). These findings suggest that addressing concern beliefs about medication use may be a focus of intervention for low-adherent patients with inadequate health literacy. Reconciliation of information from different sources will benefit the decision-making process for low-adherent patients with adequate health literacy.

This study had some strengths. The researcher earned participants’ trust through providing clear information of the study process and highlighting participants’ impacts on the practice of diabetes care. The established working relationship between the researcher and participants is integral to the quality of this study. As a result, participants tended to disclose their thoughts that reflected their experiences relevant to study interests. The researchers have health care backgrounds and that helped researchers develop probing questions tapping into participants’ medication-taking. In addition, two researchers independently analyzed interviews and made a consensus via iterative discussion, ensuring the truthfulness of analyses and capturing themes applicable to clinical practice. We portrayed researcher reflexivity at three stages (i.e., pre-research, data collection, and data analysis) suggested by Finlay (2002) to balance our self-knowledge without becoming overemotional (Rae & Green, 2016). The training and background of the three researchers engaged in the study, along with a thoughtful study process, minimized possible researcher biases from subjective prejudice.

Despite the strengths of the study design, findings need to be interpreted with an awareness of its limitations. Participants were recruited from a single medical center where a majority of the participants were White and well educated. There may be local differences in barriers or facilitators of medication adherence, as many of the barriers and facilitators assessed are related to social contexts and availability of information and resources. As such, findings should be considered exploratory in nature. We suggest future researchers focus on more diverse patient populations (e.g., nonnative English-speaking patients) to explore whether the themes identified in the present study remain applicable. Future studies could apply a pragmatic qualitative approach with multi-informant design to assure that the data collection procedures and process indeed capture the relationship in a holistic perspective. For example, interviewing providers on their communication experience with patients could provide useful information about future interventions aiming to improve the quality of patient–provider communication and as a result improve their adherence to medication.

Conclusion

The findings underline the complexity of medication adherence and the intertwined patient factors to perform this behavior. This study depicts various types of barriers that are common and can be adapted for patient care when individual-level barrier assessment is not feasible. The findings further highlight the need to address patients’ psychosocial factors and patient–provider communication after accounting for their health literacy levels improve patients’ medication adherence.

Supplemental Material

6_Appendix – Supplemental material for “Why Am I Not Taking Medications?” Barriers and Facilitators of Diabetes Medication Adherence Across Different Health Literacy Levels

Supplemental material, 6_Appendix for “Why Am I Not Taking Medications?” Barriers and Facilitators of Diabetes Medication Adherence Across Different Health Literacy Levels by Yen-Ming Huang, Kristen E. Pecanac and Olayinka O. Shiyanbola in Qualitative Health Research

Footnotes

Acknowledgements

The authors would like to thank Anya Beric, Ayomi Nwaka, and Stephanie Benton for their help with the data collection process. We would also like to acknowledge the participating medicine clinic and clinic staff for their assistance with recruitment and overall support during this study. Portions of this work were presented as a poster at the International Conference on Communication in Healthcare & Health Literacy Annual Research Conference, San Diego on October 27, 2019.

Declaration of Conflicting Interests

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

Funding

The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: The study was supported by the Sonderegger Research Center Dissertator Award and the Joseph Wiederholt Fellowship.

ORCID iD

Yen-Ming Huang

Supplemental Material

Supplemental Material for this article is available online at . Please enter the article’s DOI, located at the top right hand corner of this article in the search bar, and click on the file folder icon to view.

Author Biographies

Yen-Ming Huang is an assistant professor in College of Pharmacy and Allied Health Professions at South Dakota State University, and an adjunct lecturer in Graduate Institute of Clinical Pharmacy at National Taiwan University. His research interests lie in medication adherence of people with chronic illnesses, with a specific focus on the way health literacy and psychosocial factors influence patients’ medication-taking.

Kristen E. Pecanac is an assistant professor at the University of Wisconsin-Madison, School of Nursing. Her research involves interactions among health care providers, patients and family members when making decisions related to treatment.

Olayinka O. Shiyanbola is an associate professor in the Social and Administrative Sciences Division at the School of Pharmacy, University of Wisconsin-Madison. Her research interests include health literacy, medication adherence, and health equity among underserved populations.

References

Ali

M. K.

McKeever Bullard

Imperatore

Barker

Gregg

E. W.

(2012). Characteristics associated with poor glycemic control among adults with self-reported diagnosed diabetes—National Health and Nutrition Examination Survey, United States, 2007-2010. MMWR Morbidity and Mortality Weekly Report: Supplement, 61(2), 32–37.

American Diabetes Association. (2018). Economic costs of diabetes in the U.S. in 2017. Diabetes Care, 41(5), 917–928. https://doi.org/10.2337/dci18-0007

Archibald

M. M.

(2016). Investigator triangulation: A collaborative strategy with potential for mixed methods research. Journal of Mixed Methods Research, 10(3), 228–250. https://doi.org/10.1177/1558689815570092

Bailey

S. C.

Brega

A. G.

Crutchfield

T. M.

Elasy

Herr

Kaphingst

Karter

A. J.

Moreland-Russell

Osborn

C. Y.

Pignone

(2014). Update on health literacy and diabetes. The Diabetes Educator, 40(5), 581–604. https://doi.org/10.1177/0145721714540220

Bandura

(1989). Human agency in social cognitive theory. American Psychologist, 44(9), 1175–1184. https://doi.org/10.1037/0003-066X.44.9.1175

Bauer

A. M.

Parker

M. M.

Schillinger

Katon

Adler

Adams

A. S.

Moffet

H. H.

Karter

A. J.

(2014). Associations between antidepressant adherence and shared decision-making, patient-provider trust, and communication among adults with diabetes: Diabetes study of Northern California (DISTANCE). Journal of General Internal Medicine, 29(8), 1139–1147. https://doi.org/10.1007/s11606-014-2845-6

Bodenheimer

Lorig

Holman

Grumbach

(2002). Patient self-management of chronic disease in primary care. Journal of the American Medical Association, 288(19), 2469–2475. https://doi.org/10.1001/jama.288.19.2469

Centers for Disease Control and Prevention. (2020). National diabetes statistics report, 2020. U.S. Department of Health and Human Services.

Champlin

Mackert

Glowacki

E. M.

Donovan

E. E.

(2017). Toward a better understanding of patient health literacy: A focus on the skills patients need to find health information. Qualitative Health Research, 27(8), 1160–1176. https://doi.org/10.1177/1049732316646355

10.

Costa

Giardini

Savin

Menditto

Lehane

Laosa

Pecorelli

Monaco

Marengoni

(2015). Interventional tools to improve medication adherence: Review of literature. Patient Preference and Adherence, 9, 1303–1314. https://doi.org/10.2147/PPA.S87551

11.

Curkendall

S. M.

Thomas

Bell

K. F.

Juneau

P. L.

Weiss

A. J.

(2013). Predictors of medication adherence in patients with type 2 diabetes mellitus. Current Medical Research and Opinion, 29(10), 1275–1286. https://doi.org/10.1185/03007995.2013.821056

12.

Donnan

P. T.

MacDonald

T. M.

Morris

A. D.

(2002). Adherence to prescribed oral hypoglycaemic medication in a population of patients with Type 2 diabetes: A retrospective cohort study. Diabetic Medicine, 19(4), 279–284. https://doi.org/10.1046/j.1464-5491.2002.00689.x

13.

Elo

Kyngas

(2008). The qualitative content analysis process. Journal of Advanced Nursing, 62(1), 107–115. https://doi.org/10.1111/j.1365-2648.2007.04569.x

14.

Finlay

(2002). “Outing” the researcher: The provenance, process, and practice of reflexivity. Qualitative Health Research, 12(4), 531–545. https://doi.org/10.1177/104973202129120052

15.

Francis

J. J.

Johnston

Robertson

Glidewell

Entwistle

Eccles

M. P.

Grimshaw

J. M.

(2010). What is an adequate sample size? Operationalising data saturation for theory-based interview studies. Psychology and Health, 25(10), 1229–1245. https://doi.org/10.1080/08870440903194015

16.

Gao

Wang

Zhu

(2013). Validation of an information–motivation–behavioral skills model of self-care among Chinese adults with type 2 diabetes. BMC Public Health, 13(1), Article 100. https://doi.org/10.1186/1471-2458-13-100

17.

Gellad

W. F.

Grenard

J. L.

Marcum

Z. A.

(2011). A systematic review of barriers to medication adherence in the elderly: Looking beyond cost and regimen complexity. The American Journal of Geriatric Pharmacotherapy, 9(1), 11–23. https://doi.org/10.1016/j.amjopharm.2011.02.004

18.

Hong

T. B.

Oddone

E. Z.

Dudley

T. K.

Bosworth

H. B.

(2006). Medication barriers and anti-hypertensive medication adherence: The moderating role of locus of control. Psychology, Health & Medicine, 11(1), 20–28. https://doi.org/10.1080/14786430500228580

19.

Hsieh

H.-F.

Shannon

S. E.

(2005). Three approaches to qualitative content analysis. Qualitative Health Research, 15(9), 1277–1288. https://doi.org/10.1177/1049732305276687

20.

Huang

Y. M.

Shiyanbola

O. O.

Chan

H. Y.

(2018). A path model linking health literacy, medication self-efficacy, medication adherence, and glycemic control. Patient Education and Counseling, 101(11), 1906–1913. https://doi.org/10.1016/j.pec.2018.06.010

21.

Huang

Y. M.

Shiyanbola

O. O.

Chan

H. Y.

Smith

P. D.

(2020). Patient factors associated with diabetes medication adherence at different health literacy levels: A cross-sectional study at a family medicine clinic. Postgraduate Medicine, 132(4), 328–336. https://doi.org/10.1080/00325481.2020.1749499

22.

Huang

Y. M.

Shiyanbola

O. O.

Smith

P. D.

Chan

H. Y.

(2018). Quick screen of patients’ numeracy and document literacy skills: The factor structure of the Newest Vital Sign. Patient Preference and Adherence, 12, 853–859. https://doi.org/10.2147/PPA.S165994

23.

Ivankova

N. V.

Creswell

J. W.

Stick

S. L.

(2006). Using mixed-methods sequential explanatory design: From theory to practice. Field Methods, 18(1), 3–20. https://doi.org/10.1177/1525822X05282260

24.

Kim

Sefcik

J. S.

Bradway

(2017). Characteristics of qualitative descriptive studies: A systematic review. Research in Nursing & Health, 40(1), 23–42. https://doi.org/10.1002/nur.21768

25.

Kirkman

M. S.

Rowan-Martin

M. T.

Levin

Fonseca

V. A.

Schmittdiel

J. A.

Herman

W. H.

Aubert

R. E.

(2015). Determinants of adherence to diabetes medications: Findings from a large pharmacy claims database. Diabetes Care, 38(4), 604–609. https://doi.org/10.2337/dc14-2098

26.

Malterud

Siersma

V. D.

Guassora

A. D.

(2016). Sample size in qualitative interview studies: Guided by information power. Qualitative Health Research, 26(13), 1753–1760. https://doi.org/10.1177/1049732315617444

27.

Marcum

Z. A.

Sevick

M. A.

Handler

S. M.

(2013). Medication nonadherence: A diagnosable and treatable medical condition. Journal of the American Medical Association, 309(20), 2105–2106. https://doi.org/10.1001/jama.2013.4638

28.

Mayberry

L. S.

Gonzalez

J. S.

Wallston

K. A.

Kripalani

Osborn

C. Y.

(2013). The ARMS-D out performs the SDSCA, but both are reliable, valid, and predict glycemic control. Diabetes Research and Clinical Practice, 102(2), 96–104. https://doi.org/10.1016/j.diabres.2013.09.010

29.

McCormack

Bann

Squiers

Berkman

N. D.

Squire

Schillinger

Ohene-Frempong

Hibbard

(2010). Measuring health literacy: A pilot study of a new skills-based instrument. Journal of Health Communication, 15(Suppl. 2), 51–71. https://doi.org/10.1080/10810730.2010.499987

30.

Meppelink

C. S.

Smit

E. G.

Fransen

M. L.

Diviani

(2019). “I was right about vaccination”: Confirmation bias and health literacy in online health information seeking. Journal of Health Communication, 24(2), 129–140. https://doi.org/10.1080/10810730.2019.1583701

31.

Miles

M. B.

Huberman

A. M.

Saldaña

(2014). Qualitative data analysis: A methods sourcebook (3rd ed.). SAGE.

32.

Narayan

K. M.

Boyle

J. P.

Geiss

L. S.

Saaddine

J. B.

Thompson

T. J.

(2006). Impact of recent increase in incidence on future diabetes burden: U.S., 2005-2050. Diabetes Care, 29(9), 2114–2116. https://doi.org/10.2337/dc06-1136

33.

Nickerson

R. S.

(1998). Confirmation bias: A ubiquitous phenomenon in many guises. Review of General Psychology, 2(2), 175–220. https://doi.org/10.1037/1089-2680.2.2.175

34.

Paasche-Orlow

M. K.

Wolf

M. S.

(2007). The causal pathways linking health literacy to health outcomes. American Journal of Health Behavior, 31(1), S19–S26. https://doi.org/10.5555/ajhb.2007.31.supp.S19

35.

Peimani

Nasli-Esfahani

Sadeghi

(2018). Patients’ perceptions of patient-provider communication and diabetes care: A systematic review of quantitative and qualitative studies. Chronic Illness,16(1), 3–12. https://doi.org/10.1177/1742395318782378

36.

Peterson

A. M.

Takiya

Finley

(2003). Meta-analysis of trials of interventions to improve medication adherence. American Journal of Health-System Pharmacy, 60(7), 657–665. https://doi.org/10.1093/ajhp/60.7.657

37.

Pousinho

Morgado

Falcao

Alves

(2016). Pharmacist interventions in the management of type 2 diabetes mellitus: A systematic review of randomized controlled trials. Journal of Managed Care & Specialty Pharmacy, 22(5), 493–515. https://doi.org/10.18553/jmcp.2016.22.5.493

38.

Presley

Groot

Pavlova

(2018). Pharmacy-led interventions to improve medication adherence among adults with diabetes: A systematic review and meta-analysis. Research in Social and Administrative Pharmacy, 15(9), 1057–1067. https://doi.org/10.1016/j.sapharm.2018.09.021

39.

Prochaska

J. O.

Velicer

W. F.

(1997). The transtheoretical model of health behavior change. American Journal of Health Promotion, 12(1), 38–48. https://doi.org/10.4278/0890-1171-12.1.38

40.

Rae

Green

(2016). Portraying reflexivity in health services research. Qualitative Health Research, 26(11), 1543–1549. https://doi.org/10.1177/1049732316634046

41.

Savin-Baden

Major

C.-H.

(2013). Qualitative research: The essential guide to theory and practice. Routledge.

42.

Shiyanbola

O. O.

Walbrandt Pigarelli

D. L.

Unni

E. J.

Smith

P. D.

Maurer

M. A.

Huang

Y. M.

(2019). Design and rationale of a mixed methods randomized control trial: ADdressing Health literacy, bEliefs, adheRence and self-Efficacy (ADHERE) program to improve diabetes outcomes. Contemporary Clinical Trials Communications, 14, 100326. https://doi.org/10.1016/j.conctc.2019.100326

43.

Strecher

V. J.

Champion

V. L.

Rosenstock

I. M.

(1997). The health belief model and health behavior. In Gochman

D. S.

(Ed.), Handbook of health behavior research 1: Personal and social determinants (pp. 71–91). Plenum Press.

44.

Weiss

B. D.

Mays

M. Z.

Martz

Castro

K. M.

DeWalt

D. A.

Pignone

M. P.

Mockbee

Hale

F. A.

(2005). Quick assessment of literacy in primary care: The newest vital sign. The Annals of Family Medicine, 3(6), 514–522. https://10.1370/afm.405

45.

West

L. M.

Borg Theuma

Cordina

(2018). Health locus of control: Its relationship with medication adherence and medication wastage. Research in Social and Administrative Pharmacy, 14(11), 1015–1019. https://doi.org/10.1016/j.sapharm.2017.12.003

46.

World Health Organization. (2003). Adherence to long-term therapies: Evidence for action.

Supplementary Material

Please find the following supplemental material available below.

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

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

0.00 MB

0.12 MB