Adherence and Communication
Abstract and Keywords
Patient adherence (sometimes referred to as patient compliance) is the extent to which a patient’s health behavior corresponds with the agreed-upon recommendations of the healthcare provider. The term patient compliance is generally synonymous with adherence but suggests that the patient played a more passive role in the healthcare professional’s prescription of treatment, whereas the term adherence suggests that the patient and healthcare professional have come to an agreement on the regimen through a collaborative, shared decision-making process. Another term related to the concept of adherence is persistence (i.e., taking a medication for the recommended duration). Some patients are purposefully or intentionally nonadherent, whereas others are unintentionally nonadherent due to forgetfulness or poor understanding of the regimen. Patients may be intentionally nonadherent because of a belief that the costs of the regimen outweigh the benefits, for example. Nonadherence behaviors in medication taking include never filling a prescription, taking too much or too little medication, or taking a medication at incorrect time intervals. Patient adherence is relevant not only in medication-taking behaviors, but also in health behaviors such as following a specific dietary regimen, maintaining an exercise program, attending follow-up appointments, getting recommended screenings or immunizations, and smoking cessation, among others.
A number of factors predict patient adherence to treatment, but the relationship between provider-patient communication and adherence to treatment will be stressed. Focusing on recent research, the article examines the concept of patient adherence, describes how provider-patient communication can enhance patient adherence, explains what elements of communication are relevant for adherence, and illustrates how interventions to improve communication can improve adherence.
Overview of Adherence: History, Measurement, and Outcomes
The terms patient adherence and patient compliance were first reported in published studies in 1966 (Davis, 1966; Wilson, 1966). In 1979, R. Brian Haynes proposed the following now commonly accepted definition of adherence: “the extent to which a person’s behavior (in terms of taking medications, following diets, or executing lifestyle changes) coincides with medical advice” (Haynes & Sackett, 1979, pp. 1–2). Since that time, thousands of studies on the topic of adherence have been published, involving scholars from medicine, epidemiology, psychology, nursing, and public health, among other disciplines. Efforts to synthesize and systematically review the adherence literature have been undertaken by M. Robin DiMatteo, who has published multiple meta-analyses of predictors of adherence including a seminal meta-analytic review of the corpus of adherence literature (DiMatteo, 2004b). Another key author in this field is Haynes, who conducted one of the first systematic reviews of the literature on interventions to improve patient adherence (Haynes, Ackloo, Sahota, McDonald, & Yao, 2008). Extensive research has also focused on interventions to improve adherence, and it is recognized that no one intervention will work to improve the adherence of all patients (Martin, Williams, Haskard, & DiMatteo, 2005).
Rates of nonadherence vary depending on disease, regimen, patient population, and other factors, but on average, rates of nonadherence range from 25 to 50% (DiMatteo, 2004b; Sabaté, 2003). Nonadherence rates tend to be higher with regimens associated with lifestyle changes, such as beginning an exercise regimen after leading a sedentary life or making major changes to one’s dietary habits. Other factors affect rates of adherence, including category of illness (i.e., acute vs. chronic), with higher rates of adherence in acute illness compared to chronic illness (DiMatteo, 2004b). Adherence rates can drop over time in many diseases. Regimen characteristics also affect rates of adherence, as patients are more adherent with simpler regimens, as demonstrated in a meta-analysis of adherence to antihypertensive medications (Iskedjian et al., 2002). Across eight studies, once daily dosing regimens were associated with higher adherence rates than twice or multiple daily dosing schedules. Another meta-analysis of two studies found that higher medication complexity (measured using the validated Medication Regimen Complexity Index) was associated with greater medication nonadherence (Alves-Conceição et al., 2020). When a regimen is more complex and requires greater adjustment to one’s lifestyle, adherence tends to suffer. Furthermore, adverse side effects associated with a medication can predict adherence levels, as experience of troublesome side effects can cause a patient not to take medication as prescribed.
There are serious health consequences of nonadherence. When patients do not adhere to recommended treatment, they can experience poorer health outcomes, such as continuation or worsening of symptoms or progression of their disease. Specifically, a meta-analysis of 63 studies examining adherence and outcomes of treatment across diseases revealed the odds of a positive health outcome were almost three times higher if a patient was adherent to treatment (DiMatteo, Giordani, Lepper, & Croghan, 2002). A meta-analysis of the relationship between medication adherence and mortality across 21 studies demonstrated that patients with good adherence to medication had about half the risk of death of those individuals with poor adherence (Simpson et al., 2006). Examples from individual studies and in specific diseases abound. For instance, diabetes patients who are nonadherent to medication have higher HbA1c levels as well as greater risk of hospitalization and death from all causes (Ho et al., 2006). In HIV, patients who have medication adherence of 95% or more experience a host of better outcomes, including a greater number of CD4 cells, reduced likelihood of virologic failure, fewer days of hospitalization, and lower risk of opportunistic infections or death (Paterson et al., 2000).
In addition to the health outcomes of nonadherence, there are financial ramifications, including unused prescriptions, wasted time in medical visits, and unnecessary hospitalizations; some estimates of these costs due to nonadherence have been as high as $300 billion per year (DiMatteo, 2004b). In the years since those data were collected such costs have likely increased. Nonadherence also affects healthcare providers, whose ultimate goal is to help their patients heal and achieve better health. When patients are nonadherent, a trusting relationship between a patient and his or her healthcare provider may suffer, as providers are frustrated and challenged.
Healthcare professionals frequently underestimate patient adherence; thus, it is particularly important to measure adherence accurately. Measurement methods are often categorized into either direct or indirect methods; there is unfortunately no “gold standard” measure of adherence, as all measures have both advantages and drawbacks (Osterberg & Blaschke, 2005). Direct measures include directly observing the patient taking medication and measurement of levels of medicine or metabolite in blood. Direct observation is difficult in everyday practice, and physiological measures are invasive. Indirect methods include self-report, pill count, pharmacy refill records, and electronic monitoring. The most frequently used and affordable method of measurement is self-report, although bias is possible with this form of measurement. With pill counts, patients can dispose of pills before they are counted, and pharmacy refill records do not indicate whether a patient has actually ingested a medication. Electronic monitoring involving automatic indicators of the time and date pill bottles were opened can be quite accurate but also extremely expensive. Ultimately, the use of multiple measures of adherence is recommended to current researchers in the field to improve accuracy.
Predictors of Adherence
One challenge in understanding and intervening to promote patient adherence is the myriad factors that predict adherence behavior, which differ from patient to patient. Researchers have organized the predictors of adherence into three main categories: patient-related factors, provider-patient interaction factors, and healthcare system factors (Osterberg & Blaschke, 2005). Demographic characteristics or patient personality traits have not been shown to be consistently predictive of adherence. Patient-related factors that are predictive of adherence include mental health (i.e., depressed patients have greater levels of nonadherence to treatment; Grenard et al., 2011) and social support (i.e., patients with lower levels of social support, including a more distant family, are less adherent to treatment DiMatteo, 2004a). Other patient factors related to adherence are beliefs and attitudes; when a patient does not believe in the efficacy of the regimen or believes the risks outweigh the benefits, his or her adherence is lower (Wong, 2009). Patient cognitive factors are also related to adherence. For example, a common barrier to adherence for patients is forgetfulness, as patients struggle to remember to consistently take their medication. Additionally, if patients do not understand how to take a medication or related requirements, such as substances they must avoid while taking the medication, they may be more likely to be nonadherent.
Healthcare system factors related to adherence include costs of medications, access to medical care, and insurance status. For example, if access to appointments is poor, patients may struggle to attend required follow-up appointments. Patients who face significant out-of-pocket costs for their medication may take less medication or not fill their prescriptions on schedule because of the financial barriers.
Finally, provider-related factors and those related to the interaction between the provider and patient can predict adherence. Interpersonal factors such as provider communication skills, provision of information about the regimen and its efficacy, empathy, encouragement of patient question-asking, trust, and a participatory style of communication, among others, can predict adherence. The provider’s ability to anticipate and assist the patient in overcoming practical barriers can also predict adherence. More detailed examples of studies describing these interactional aspects will be presented.
Provider-Patient Communication and Adherence
Many of the studies cited here report qualitative rather than quantitative research. The former provide richer data but preclude the drawing of statistical or potentially causal conclusions. The nature of the topics being discussed—communication and adherence—make research allowing conclusions about causality very difficult, in any event. The most notable exception to this is the research discussed in the section “Interventions to Improve Adherence,” which focuses upon communicative interventions and their impact on patient adherence.
Physician-patient communication is a key predictor of patient adherence to treatment, and researchers have been studying this relationship for the past several decades. A meta-analytic review of the communication-adherence link involved a review of the relevant literature between 1949 and 2008 (Zolnierek & DiMatteo, 2009). This review attempted to answer two questions: (a) Is there a positive relationship between physician communication and patient adherence across studies? (b) Can patient adherence be enhanced through communication skills training for physicians? Communication in studies was broadly coded as task-oriented or psychosocial. A total of 106 correlational studies was included in this meta-analysis; 41 studies measured task-oriented communication (e.g., ratings by patient of physician explanations or instructions, physicians’ use of collaboration), 10 measured psychosocial communication (e.g., judgments of content-filtered voice tone), and 55 measured both. It should be noted that, although communication creates trust and trust influences communication, the two concepts are not the same thing. Findings revealed that across these 106 studies, the association between physician communication and patient adherence was positive and significant (unweighted mean r = .19, p < .001). Analysis of moderator effects showed that the correlation between adherence and communication was significantly larger under the following conditions: smaller sample size, objectively rather than subjectively measured adherence, physician specialty as a pediatrician, physician training status as a resident, and when communication was assessed by someone other than the patient (e.g., neutral observers). This meta-analysis was not able to show which aspects of communication are most important for adherence, and this remains an important question to answer. However, an examination of the appendix accompanying Zolnierek and DiMatteo (2009) reveals more detail about the individual studies included in this analysis and potential insights into communicative behaviors that can promote adherence. For example, several included studies showed a positive relationship between physicians giving thorough information and clear explanations and adherence to treatment in diabetes and glaucoma (Friedman et al., 2008; Heisler, Bouknight, Hayward, Smith, & Kerr, 2002). Other included studies point to the importance of active listening and positive communication for adherence to treatment across conditions (Fassaert, van Dulmen, Schellevis, van der Jagt, & Bensing, 2008; Freemon, Negrete, Davis, & Korsch, 1971). These studies of positive communication typically look at statements of friendliness, solidarity, non-medical information, and freely offered information. Furthermore, the majority of included studies involved patients’ self-reports of physician communication rather than observational assessments of communication (i.e., videotapes or audiotapes of physician-patient interactions).
Having established the relationship between communicative behavior and patient adherence to treatment recommendations, it behooves us to more thoroughly examine the particular aspects of communication that are most directly related to adherence. The research on this issue has investigated a number of health problems, a variety of care providers, and a multitude of cultural backgrounds in patients. A key distinction that has been identified in the literature is apparent in research in which communication variables are measured through rather specific assessment compared to those that assume it is appropriate to sum or total across a variety of communication behaviors for a measure that is referred to as “more” communication. The implication is that “more” communication is meaningful, when such an assumption would be regarded as simplistic and less-than-useful by any communication expert.
The majority of studies conducted in the last several years similarly involve patient perceptions of physician communication, which may not provide the detail or nuance of observational measures. For instance, a study of adherence to adjuvant hormonal therapy for breast cancer examined the relationship between self-reported adherence to treatment at 36 months and patient perceptions of physician-centered communication (Liu, Malin, Diamant, Thind, & Maly, 2013). These authors found a strongly positive and significant relationship between self-reported hormone therapy adherence and patient-centered communication. It is notable that there was a high (nearly 90%) adherence rate in this study population.
This topic was also addressed in work by Wuensch et al. (2015). Patients in this study had been prescribed endocrine therapy, and the results of the study indicated that a very small amount of information had been shared with the women about their treatment. The side-effects of this treatment are significant and affect daily functioning but were almost completely ignored by physicians; the data indicate that these side effects were largely responsible for lack of adherence in the patients. The authors concluded that lack of communication about several aspects of the treatment by physicians were key but easily addressable determinants of adherence, as their data indicated a strong relationship between adherence and detailed answers to the women’s questions.
Adherence to adjuvant breast cancer therapy was also addressed in work by Davidson, Vogel, and Wickerham (2007). This linguistic study of oncologist-patient discussions found that the interactants did not address potential difficulties of remaining adherent with therapy in the long term. Communications about persistence were usually monologues addressing what research has shown; they were not tied directly to the patient or to the importance of persistence and adherence. The patient’s cancer was framed in the past tense, and discussions were similar to those of chronic management in preventive medicine rather than being more specifically adapted to this context. This is a potential barrier for motivating patients to stay on hormonal therapy. Although the oncologists in this study recognized that adherence to hormonal therapy is a problem, they did not feel that their patients experienced this problem. As minimal nurse interactions were observed, the importance of communication from the oncologist is especially important.
In understanding the adherence-communication relationship, it is important to consider other populations, such as patient adherence to mental health medications for psychiatric conditions. The meta-analysis described in Zolnierek and DiMatteo (2009) excluded psychiatric populations, but a review attempted to fill this gap (Thompson & McCabe, 2012). This review included 23 studies, although the authors cited “heterogeneity of methods” as a reason for not being able to conduct a proper meta-analysis. Unfortunately, only one study involved examination of the relationship between adherence and objective ratings of communication, demonstrating that patients who asked more questions were less adherent. A study examining Type II diabetes patients with a new antidepressant prescription (Bauer et al., 2014) assessed associations with several patient self-reported measures of communication (i.e., trust and shared decision-making). Several measures of adherence were examined, using physician prescribing and pharmacy dispensing information; findings revealed that patients’ perceptions of lack of shared decision-making and trust were strongly associated with multiple measures of antidepressant adherence. Another study also focused on psychiatric patients, but its emphasis was on nonverbal communication. It will be discussed in the “Nonverbal Communication” section (Cruz et al., 2013).
Pediatric populations are another special population for whom the communication-adherence relationship is less frequently studied. In one study, pediatric asthma medical visits were audiotaped, and the following elements of communication were coded: number of medication questions asked by child and whether the healthcare professional sought parent/caregiver or child input into the treatment plan (Sleath et al., 2012). Adherence was assessed using the validated, self-reported Brief Medication Questionnaire, and one notable finding was that the medical provider’s seeking of caregiver/parent input into the child’s treatment plan was associated with better adherence reported at a one-month follow-up home visit interview. As parents or caregivers are present in pediatric visits, it is necessary to assess the communication of multiple interactants in the medical visit.
Other studies have examined modifiers of the communication-adherence relationship, such as racial background of providers and patients. A study examined race discordant and concordant physician-patient interactions, measuring adherence to antihypertensive medications with the widely used Morisky Medication Adherence Scale, and surveying patients using an adaptation of an existing measure of collaborative communication (Schoenthaler, Allegrante, Chaplin, & Ogedegbe, 2012). Findings from this study indicated that African American patients in racially discordant relationships who reported more collaborative communication also reported better adherence to antihypertensive medications, whereas white physicians’ communication that was rated as non-collaborative was related to poorer adherence. With the current emphasis on reducing disparities in medical care for patients of minority or economically disadvantaged backgrounds, this study suggests the importance of paying attention to demographic factors that may change the communication-adherence relationship and also ensuring awareness of these factors in training programs and interventions to improve communication skills. Of course, race is not always a modifier of the adherence-communication relationship. Another study that investigated patient perceptions of the extent to which patients left the physician’s office with unanswered questions found that this element of communication was not related to self-reported cardiovascular disease medication adherence as a function of patient race (Zullig et al., 2015). The issue of race is also relevant to the notion of concordance as it impacts shared decision making, to be discussed in the section “Shared Decision Making.”
Providers other than physicians may communicate to promote adherence, and studies have examined other members of the patient’s healthcare team for their role in communicating to promote adherence. For instance, a study focused on improving adherence to medication after discharge for hospitalized heart disease patients involved an intervention in which pharmacists counseled patients on the importance of adherence and also attempted to work with patients to reduce their identified adherence barriers (Calvert et al., 2012). Medication refill records demonstrated a trend toward improved adherence to heart disease medications in the intervention group. The role of pharmacists in responding to emotional and informational cues in patients using inhaled corticosteroids has also been examined (Driesenaar, de Smet, van Hulten, Noordman, & van Dulman, 2016). This research indicated that pharmacists did not pick up on many of the emotional cues but that appropriate responses to cues were associated with higher self-reported adherence at follow-up. And a review of nurse-focused interventions to improve adherence after hospital discharge in older patients examined results of 14 studies. The findings indicated that medication adherence was significantly higher in eight studies in the nurse-focused intervention (e.g., counseling, education, verbal reminders) compared to a usual-care group (Verloo, Chiolero, Kiszio, Kampel, & Santschi, 2017).
As several studies on communication and adherence have focused on the very important and problematic topic of HIV treatment adherence, we now move to a more specific discussion of this body of work. Communication with pharmacists, as just noted, is also relevant to this issue.
An example of a concern of research focusing on totaling or summing communicative behaviors in relation to adherence is work on HIV patients in western Kenya that was conducted by Wachira, Middlestadt, Reece, Peng, and Braitstein (2014). Although the physician communicative behaviors were not ultimately associated with physician-patient relationships as assessed by time spent with the physician, trust in the physician, and decision-making preferences, the frequency of several physician communicative behaviors was associated with adherence and health outcomes. Across the assessed physician communication behaviors, more communication was associated with higher perceived health status. Physicians tended to talk more to healthier patients. More communication was related to higher attendance at the clinic, fewer missed appointments, and more adherence to cART (Combination Antiretroviral Therapy) medications. The Wachira et al. study assessed 11 types of communicative statements and reported the frequency of each, but the analyses ignore any potential impact of each type of statement on adherence.
A similar study of HIV patients and highly active anti-retroviral (HAART) adherence was conducted in Zambia by Sanjobo, Frich, and Fretheim (2012). They determined that lack of information and communication were barriers to adherence, with a particular focus on lack of information about how to take the medication. Patients reported that physicians would write prescriptions and just hand them to the patients with no accompanying instructions, and that no healthcare provider ever inquired about their understanding of procedures or their adherence to the treatment. Some care providers indicated that they assumed that patients would get information about their medications from the pharmacy, but this did not occur. Other research has focused on the relevance of communication between HIV patients and pharmacists (Watermeyer & Penn, 2012). Key findings from this research emphasized patient face-saving, agency, and empowerment as well as negotiating a new commitment to adherence during the discussion. The relevance of face and stigma issues is also apparent in the qualitative findings of Kedia, Dillon, and Basu (2019), which determined that HIV+ African American women’s adherence to ART treatment was sometimes negatively impacted by their perceived need to conceal their HIV status from their own children.
The research cited to this point has made evident the relevance of various interpersonal dimensions as they relate to adherence. A similar theme is apparent in the work of Laws et al. (2012) on HIV treatment focusing on what they called “whole person knowledge” (p. 893). The respondents, who reported stable relationships with their providers,
appreciated providers who knew and cared about their personal lives, who were clear and direct about instructions, and who were accessible. Most had struggled to overcome addiction, emotional turmoil, and/or denial before gaining control over their lives and becoming adherent to medications.
(Laws et al., 2012, p. 893)
What is notable about these findings is the assumption on the part of patients that their adherence was an autonomous decision on their parts rather than related to provider-patient interaction.
Earlier work on HIV and treatment adherence compared patients in San Francisco and Copenhagen (Barfod, Hecht, Rubow, & Gerstoft, 2006). The providers in this study rarely initiated the topic of adherence, feeling that it was awkward to do so if there were no signs of nonadherence. Providers quickly came to question the believability of patients’ statements of adherence, however.
Fehringer et al. (2006) also provided an interesting examination of adherence-related communication between HIV+ patients on HAART medications and care providers. Questions posed by providers were generally closed and leading. Most communication was focused on biomedical issues and avoided psychosocial concerns. Patients did indicate a desire for more open and direct communication about adherence.
Beyond HIV—Other Health Problems
In a study focusing on Dutch nurses working with inflammatory bowel disease (IBD) patients, the relationship between recall of information and adherence to instructions is made evident (Linn, van Dijk, Smith, Jansen, & van Weert, 2013). Patients remembered about half the information that was communicated to them, as evidenced through videotapes of the earlier interactions, and were adherent to that information that they remembered. This was true both in terms of immediate and delayed (three weeks) recall. The name and procedure for administration of the medication were generally recalled fairly well, but the impact of the medication on the patient’s daily life (which other research shows is essential for patients to understand), side effects, and medication intake advice were not likely to be remembered. Lower delayed recall scores and injection rather than pills as the intake procedure were associated with less self-reported adherence. Age was also related to lower adherence and recall. The question that is begged in this research, however, is characteristics of how information is communicated that makes it memorable to patients. Complexity of information, of course, is related to the ability of a patient to remember it, but there are also numerous other aspects of communication that may impact recall and are worthy of investigation. Given that the study included videotaped interactions of the nurses and patients, a much more detailed analysis could have been conducted about how the manner of communication related to self-reported adherence. As the authors also note, more adequate assessment of patient recall would be beneficial.
Focusing on a broader application of the notion of adherence is a body of research that centers on compliance with exercise regimens. One example is Horne and Tierney’s (2012) study of compliance with exercise regimens suggested for elderly South Asian patients in the United Kingdom. This systematic review of qualitative studies indicates a lack of understanding of information in the patients, coupled with a need for family help with support and translation as well as cultural beliefs that suggest inappropriateness of exercise for this population. It is likely that these findings have implications well beyond these patients and this cultural group.
Wright, Galtieri, and Fell (2014) also focused on exercise; in this study of Australian patients the emphasis was on musculoskeletal injuries and home rehabilitation exercise. The provider-patient relationship was the key predictor of adherence to the prescribed exercises, and the authors suggest an increased emphasis on provider-patient communication. The two key aspects of communication that were advocated were increased information and building trust. Again, however, no particular communicative behaviors were examined. Although the authors draw conclusions about communication, an examination of the measures indicates that no assessment method utilized in the study actually focused upon communicative behavior in the sense that a communication expert would expect.
Physical exercise is an issue that is relevant to most populations, and exercise is related to the work of Polikandrioti and Babatsikou (2013) on coronary disease patients. Echoing the themes noted previously, this bibliographic review thoroughly documents the types of information needed by coronary disease patients. The authors do not, however, examine the link between the various types of information and adherence to an exercise regimen; they instead assert such a link without data. As the other data cited within this report make clear, there is no reason to doubt this link. It would have been helpful, however, for the authors to more specifically relate certain types of information with varying levels of adherence.
Although most work on adherence focuses on compliance by the patient, the concept is also relevant to home healthcare provided to others, especially children and the elderly. The work of van Elsland et al. (2012), conducted on home healthcare providers of children with tuberculous meningitis in South Africa, helps illuminate this process. In cultures with scarce medical resources, prolonged hospitalization is not a possibility. South Africa has an unusually high rate of tuberculous meningitis. This combination leads to an increased emphasis on home care, with a concomitant increase in adherence problems. Nonadherence is more likely when healthcare providers are not able to closely monitor patients within the hospital. This group of researchers did find a tendency for doctors to persevere to ensure adequate communication of information; this was particularly notable and surprising in light of the inordinately long waiting times at the clinic that was studied. Once again, however, the study did not enable the correlation of certain communicative behaviors with increased or decreased adherence. The relationship is assumed rather than established.
The notion of caregiver/child/provider communication and the impact on compliance in children is also the core of work by Sleath et al. (2012). These children had been diagnosed with asthma, an illness for which adherence is known to be suboptimal. Adherence was assessed by caregiver or parent reports, but it was communication between the provider and the child that was a key causal variable under examination. Provider-child communication was associated with higher adherence, but the same was true of provider-parent communication. Thus, communication from providers to both the children and the caregivers increased adherence. This study, like most of the others discussed, did not break down the findings by type of communicative behavior. The findings did indicate the importance of identifying the child’s preferences in order to increase adherence, thus leading to the focus of the section “Shared Decision Making.”
Shared Decision Making
Another group of studies has taken a more dyadic focus on the provider-patient interaction by looking at how shared decision making and adherence interrelate. Building on earlier work by Bultman and Svarstad (2000), Hahn (2009) focused on adherence to antidepressant medication and shared decision making. After articulating the problem of detecting nonadherence, he then proposed a four-step strategy to spot this. This includes normalizing nonadherence rather than stigmatizing it. This is followed by a shared decision-making process in which the provider and the patient work to determine what the patient does and does not understand about the medication and enabling the patient to feel comfortable reporting accurate levels of adherence rather than trying to hide nonadherence. The provider and the patient work as a team to make decisions and monitor behavior without perceived evaluation or judgement on the part of the provider. The notion of shared decision making is also addressed in much detail in work by Herlitz, Munthe, Törnes, and Forsander (2016), which offers a model and provides examples of the relevance of self-care as it relates to person-centered care. Based on a perspective grounded in moral psychology, Herlitz et al. argue that the typical person-centered care approach may actually lower adherence because of confounds of autonomy.
The issue of race concordance between a provider and a patient may impact the likelihood of shared decision making. The interrelationships among race concordance, shared decision making or collaboration, and general concordance were investigated in the study of hypertensive patients by Schoenthaler et al. (2012). The findings were not simplistic, in that there was no overall significant relationship between adherence and provider-patient communication in race-concordant relationships. The relationships were different for Caucasian compared to African American patients. Perhaps race concordance or the lack thereof determines expectations for collaborative communication, which subsequently affects adherence? Evident in this study, however, is once again the lack of distinction among different collaborative communication behaviors. It cannot be assumed that all “collaborative” behaviors have the same outcome on adherence, apart from race concordance or other demographic matches or mismatches.
Race concordance in combination with language concordance was examined in research on cardiovascular medication adherence in diabetic patients by Traylor, Schmittdiel, Uratsu, Mangione, and Subramanian (2010). They found that race concordance was a key determinant of adherence in African American patients, but language concordance was more important for Hispanic patients. Caucasian patients were more adherent than were Hispanic, African American, or Asian participants. Other research has also found low adherence in Latino patients, especially those with low English proficiency (Guntzviller, 2013).
Specifics of Language Use
Overcoming the criticisms of lack of specificity of communicative behaviors are two studies that looked in more detail at actual language use as it relates to adherence. Focusing, as did Hahn (2009), on antidepressant adherence, Kaplan, Keeley, Engel, Emsermann, and Brody (2013) audio-recorded interactions between newly diagnosed depressed patients and their care providers. Several specific communicative behaviors on the part of each interactant were coded. On the part of the clinicians, statements of reflections, motivational interviewing-adherent statements (MIAs), global ratings of empathy, and what was labeled “motivational interviewing spirit” (Kaplan et al., 2013, p. 409) were coded. The focus of the assessment of patients’ communication was “change talk” (p. 409), which included statements from patients indicating intent to take the medication. All of the clinician behaviors except motivational interviewing spirit were significantly related to patients’ change talk. Pharmacy records were assessed to determine first whether patients filled the initial prescription, followed by estimates of adherence over the next 180 days. Although almost 89% of patients filled the first prescription, the follow-up estimates of adherence were closer to 45%. Uttering two or more statements of change talk was associated with 63% of follow-up adherence; zero or one such statements were associated with 36% of follow-up adherence. Empathy, motivational interviewing spirit, and change talk were all associated with filling the first prescription. Whereas MIAs, empathy, and reflections seemed to lead to patient change talk, the key determinants of filling the initial prescription and follow-up adherence were clinician empathy and patient change talk.
Another language-related issue is message framing as it affects adherence (Zhao, Villagran, Kreps, & McHorney, 2012). Many health-related messages may be framed from either a gain- or a loss-perspective; similarly, messages may be framed with a focus on the present or the future. Zhao et al. used two different message topics—one related to side effects and one related to the patient’s need for a medication—and found that the gain frame showed an advantage over the loss frame among future-oriented patients; for present-oriented patients, the framing effect was less relevant to intention toward adherence. This was true regardless of message topic.
Tran and Sweeny (2019) examined physicians’ language complexity using linguistic analysis in 145 audiotaped physician-patient interactions. Physicians’ usage of more complex language at a pre-surgical visit was predictive of greater self-reported patient adherence after surgery. The authors speculate that perhaps more complex language promotes patient understanding and a stronger provider-patient relationship, thereby improving adherence.
Although most of the studies reviewed to this point have focused on face-to-face communication as it relates to adherence, work by Ellington et al. (2008) examined phone conversations between callers to a poison-control line and the poison-control experts. A sample of calls was coded using Roter’s Interaction Analysis System (RIAS; Roter & Hall, 1989), which categorizes both interactants’ statements into 48 different categories. Patients were the key determinants of the direction of the conversations; patient adherence was most strongly determined by staff partnership statements.
The nonverbal aspects of the communicative process also impact adherence. Cruz et al. (2013) reported one of the few studies to look at the relationship between these two processes. They focused on depressive patients interacting with psychiatrists; they, too, used the RIAS as well as assessment of nonverbal aspects of communication. Their assessment of adherence was appointment adherence, an issue that is especially problematic for mental health professionals. They found that positive voice tone was significant in its relationship to appointment adherence. Positive voice tone was not related to appointment length or more patient-centered communication, nor were either of those variables related to adherence. It is likely that there are many other aspects of nonverbal communication that interrelate with adherence, but research has yet to provide analysis of these other dimensions.
Interventions to Improve Adherence
In light of all of these studies indicating relationships between communication and adherence, it is important to target ways in which communication interventions may improve adherence. Numerous interventions have been conducted with the goal of improving treatment adherence; unfortunately, fewer than half of published interventions have demonstrated significant improvement in adherence or patient health outcomes (Haynes et al., 2008; McDonald, Garg, & Haynes, 2002). One review categorized adherence intervention approaches as informational (e.g., providing some form of education to patients), behavioral (e.g., using reminders or fitting the regimen into the patient’s lifestyle), social (e.g., peer or family support), or a combination of these approaches (Kripalani, Yao, & Haynes, 2007).
A review of 182 randomized controlled trials of interventions to improve medication adherence reported that interventions addressing multiple barriers to adherence and personalizing the intervention to the patient tended to be the most successful (Nieuwlaat et al., 2014). These authors conducted a qualitative analysis, commenting on the heterogeneity of interventions and the issues of bias in study design and methodology in many of the studies. Accordingly, the findings suggested that some of these complex and personalized interventions involved persistent support from healthcare providers, such as counseling and patient education. A narrative review of interventions suggested that effective interventions involve clinicians engaging in the following behaviors: simplifying the regimen, working to enhance patient understanding of the regimen, addressing patient beliefs, improving provider-patient communication, and effectively measuring adherence (Atreja, Bellam, & Levy, 2005). Conn and Ruppar (2017) conducted a systematic review and meta-analysis of 771 intervention studies focused on the outcome of adherence. The authors reported numerous findings including that habit-based and behavioral change interventions were more efficacious, pharmacist-delivered interventions were more beneficial than those delivered by other health care providers, and face-to-face was the ideal mode of intervention delivery.
Rochon et al. (2011) addressed interventions with HIV+ patients. Their qualitative results indicated five constructs—cultural beliefs and language, stigma, cues to action, self-efficacy, and mood state—that may be modified by communication strategies. On the basis of these, their ongoing work involves the development of an adherence-related social marketing campaign. Responding to this essay, however, de Bruin (2012) cited data indicating more effectiveness of HIV adherence interventions than presented by Rochon et al. The relevance of cultural beliefs impacting adherence noted by Rochon et al. is also echoed in subsequent research by Jin and Acharya (2016), whose work examined those of Chinese descent living in the United States. The theme of adapting to cultural beliefs of patient groups has now become common in health communication research.
As was noted in regard to exercise regimens, adherence to dietary plans is another especially difficult problem for many patients. Focusing on this issue, Desroches, et al. (2013) conducted a systematic review of 38 randomized control studies, with a particular focus on the relation of diet to chronic disease. They found that most of the studies were poorly done and of short duration; few showed statistical differences between the intervention and control groups. Measures of adherence varied widely. Only 32 out of 123 diet adherence outcomes favored the intervention group. Those studies that reported a significant effect of an intervention in the short term rarely did so in the longer term. Studies using interventions such as group sessions, individual sessions, reminders, restrictions, and behavior change techniques were particularly ineffective. Some positive results were noted for investigations using telephone follow-ups, videos, contracts with rewards, feedback, and nutritional tools. More complex interventions including multiple manipulations were common. The Desroches et al. report is a very thorough presentation of the relevant research and will be of great interest to researchers and practitioners focusing on this topic. More recently, Hoeeg, Mortil, Hansen, Teilman, and Grabowsky (2020) provided increased evidence regarding the complexity of family-based interventions addressing adherence to obesity regimens in their study of the role of authenticity, shared-caring, negotiation, and other theoretically grounded concepts. The qualitative findings indicated that the families did not benefit from the authenticity that was offered in the intervention.
Adherence issues are also frequently problems for kidney dialysis patients. In an attempt to address this, scholars and practitioners have examined the role of narrative communications on anticipated adherence in dialysis patients. Fung’s (2019) study was perhaps the most thorough examination of this, as he looked not only at narrative but at both the additive (“I should have done . . .”) and subtractive (“I shouldn’t have . . .”) counterfactual thinking accompanying narratives. He also manipulated promoted-framed vs prevention-framed goal failure. Anticipated regret, mental simulation, attitude toward adherence, and behavioral intentions to adhere were measured. Mental simulation impacted anticipated regret, which impacted attitude toward adherence. These attitudes then subsequently impacted intended adherence.
In addition to the various types of interventions just noted, several studies have focused on technology-assisted strategies to impact or monitor adherence. In a longitudinal study of Internet reliance, medication beliefs, and adherence, Linn et al. (2019) reported that Internet use following a consultation was associated with lower adherence at the three-week point and higher levels of concern at the six-month assessment. Another useful example of the relevance of technology is evident in the work of Wu and Hommel (2014), which presents a summary of some of this research on the pediatric population with chronic diseases. The ease of eHealth and mHealth (through mobile devices) technology makes such interventions a useful option in the attempt to impact adherence, especially in a younger population that is generally comfortable with technology. Research has indicated effective applications of text messaging, smartphone applications (which allow monitoring and encouragement of adherence as well as social media networks), electronic monitors of adherence (which can also be programmed to send reminders to patients), and illness-specific devices, such as those adapted to diabetic patients. Wu and Hommel noted several relevant issues that cut across technologies as well as some that are unique to each. Their overall conclusion, however, is that eHealth and mHealth technologies are very useful for both monitoring of adherence and for encouraging adherence through reminders. These technologies show much more applicability for tailoring messages to particular patients, which is especially important for influencing adherence. Not all patients respond to any message in the same way, and the growing body of research on tailoring is particularly relevant to a focus on communication and adherence.
Tailoring was also central in the work of Blake, McMorris, Jacobson, Gasmararian, and Kripalani (2010), which focused on medication adherence in poor and underserved patients. Noting the lower literacy levels in these patients, Blake et al. developed and tested an intervention that consisted of an automated telephone call reminder system, an illustrated medication schedule tailored to each patient’s medications, and pharmacist training in clear health communication. The messages were personalized to the special needs and interests of the target population. The communication training focused on avoiding medical jargon, emphasizing a few key points, and asking patients to re-state the information in their own words to assess patient comprehension. Although the study was designed to improve adherence, actual patient adherence was not reported in the results. Pharmacists and patients did both respond positively to the intervention, however. Health literacy was also the focus of Mayo-Gamble and Mouton’s (2018) study of older African-American patients’ adherence to medication regimens. Their results indicated that lower levels of health literacy are associated with higher likelihood of forgetting to take medication and taking less medication than prescribed.
Additionally, technological interventions have been of great interest to care providers who treat patients with asthma, another area in which adherence is a notable problem. Tran, Coffman, Sumino, and Cabana’s (2014) systematic review of research on this topic found that electronic reminders were associated with greater levels of participant asthma medication adherence in comparison to those in the control group. None of the studies, however, demonstrated that the reminders were associated with changes in asthma-related quality of life or clinical asthma outcomes.
Communication Skills Training
Yet another intervention approach related to the study of communication and adherence is that body of work that focuses on training either providers or patients in communication skills. The meta-analytic review described earlier that examined the relationship between communication and adherence also examined whether patient adherence can be improved through communication skills training for physicians (Zolnierek & DiMatteo, 2009). A total of 21 studies listed patient adherence as an outcome of a physician communication skills intervention. Across these 21 studies, the effect of physician communication skills training on patient adherence was positive and significant (r = .12, p < .001), although not large. One interesting moderator analysis revealed that, when communication training was explicitly focused on patient adherence, there was a marginally significant effect of communication skills interventions on adherence. This suggests that it may be valuable in communication interventions to provide training about adherence and how to communicate about this challenge. Consistent with several of the studies noted is the work of Broers, et al. (2005), which also examined asthma. They focused on general practitioners and developed a communication training program based on behavior change counseling; this is a technique derived from motivational interviewing. Unfortunately, no adherence outcome measures were utilized in this study, but the results did indicate positive attitudes on the part of the GPs toward the approach and self-reports of use of the counseling techniques they had been taught. This is another case in which it is surprising that adherence was not assessed, as it appears to be a primary interest in the study.
Another study focused on adherence to infection control procedures during patient transfers. Ong et al.’s (2013) intervention utilized two manipulations: a pre-transfer checklist used by radiology porters to confirm a patient’s infectious status and a colored cue to highlight written infectious status information in the transfer form. Both interventions were effective, although combined they were only slightly more effective than either alone. The colored cue intervention was more acceptable to the porters than was the checklist procedure.
In an examination of management of pain, Butow and Sharpe (2013) noted that one of the problems in pain management is lack of patient adherence to treatment regimens. Their review of the relevant literature indicated several communicative interventions that may impact such adherence; all of these focused upon tailoring messages to patients’ reasons for lack of adherence. Consistent with several of the studies noted, they found that a nonjudgmental approach, allowing open exploration of patient beliefs and concerns, and use of a negotiating approach that fosters shared decision making are essential.
Lonsdale et al. (2012) described a rather interesting communication skills training program called CONNECT that is focused upon the relationship between provider skills and patient adherence. This program relates to the difficulty of compliance with exercise regimens already noted but emphasizes application to patients with chronic low back pain. Based on self-determination theory (Ryan & Deci, 2002), the communicative behaviors emphasized in the training are those related to autonomy-supportiveness from physiotherapists toward their patients. Subsequent work by these authors and their colleagues (Murray et al., 2015) indicated support for this system; communicative behaviors were assessed using the Health Care Climate Questionnaire (HCCQ), which requires raters to judge physiotherapists’ needs-supportive communication while listening to audiotaped recordings. The HCCQ involves the judgement of five types of communicative behaviors: asking, advising, agreeing, assisting, and arranging. Each of these categories also includes subcategories of statements, all of which are targeted toward certain psychological needs of the patient. There was a notable effect size difference between the intervention group and the waiting-list control group.
Hahn et al. (2010) utilized a sociolinguistic perspective to study communication skills training and detection of adherence in patients with glaucoma. The intervention used videotaped vignettes and role playing to encourage the development of patient-centered communication skills, including a four-step adherence assessment process and the use of open-ended questions in ask-tell-ask sequences. Physicians who had participated in the training asked more open-ended questions, especially about whether patients had taken medications. Both the advised ask-tell-ask sequences and discussions about adherence were significantly more common after training. Physician elicitation of adherence was also three times more likely after training. This is important in light of the findings that many physicians do not include relevant aspects of persuasive recommendations in their messages to patients (Feng, Bell, Jerant, & Kravitz, 2011).
Peterson et al. (2016) examined how provider communication skills (including communication training) predicts adherence to cervical, breast, and colorectal cancer screening. This systematic review included eight intervention studies, that varied in approach, from practice communicating with standardized patients to encouraging physicians to have brief discussion with patients regarding the value of screening. Six of the eight studies showed patients of intervention physicians were more likely to adhere to cancer screening recommendations. Focusing particularly on a population that is difficult to reach in terms of screening, those living in Appalachian communities, two studies identified barriers to screening adherence suggestions. Cohen, Wilson, Vanderpool, and Collins (2016) looked at mammogram barriers and Bachman et al. (2018) examined colorectal screening. Both provide advice for communicative strategies to help overcome the embarrassment of breast and colorectal screenings.
Patient communication training
Although most of the studies on communication skills training and adherence have focused on care providers, a small body of research has examined the impact of communication skills training in patients on adherence. Cegala, Marinelli, and Post (2000) manipulated training patients about effective communication a few days prior to their scheduled appointment through a written brochure vs. informing the patients about the relevant information in the waiting room prior to their appointment. An untrained/uninformed control group was also included. Training through the written brochure increased patient compliance more than did either of the other two conditions. Thus, patient adherence can be addressed by targeting both provider and patient behaviors.
What is clear in the research cited is that there is an essential relationship between communicative behavior and the very problematic issue of patient treatment nonadherence, and that some interventions focusing on communication can impact adherence. Those are two very important conclusions. Also notable in our assessment of this research is that communicative behaviors are too frequently inadequately assessed or addressed in this body of literature. It is fortunate that some of the studies cited within conceptualize and measure communication more adequately than do others; however, many of the studies are simplistic in their theoretical approach and operationalization. Some of the studies claim to address communication when they do not do so at all.
The same is true of the operationalization of adherence or compliance. This key outcome variable may be assessed in a multitude of ways, some of which are more useful and appropriate than are others. And terminology can vary across disciplines and in different areas of medical treatment. Several of the studies reviewed, however, do not measure adherence in any way. Relationships are assumed rather than assessed.
It will continue to be important to parse out which specific aspects of communication are most beneficial for adherence. Studies reviewed here describe the following aspects of communication as related to adherence: patient-centered communication, detailed information–giving, shared decision making, collaborative communication, open discussions, empathic communication, and positive voice tone. In light of these findings and other research showing the communicative behaviors most important to adherence, future adherence interventions related to provider-patient communication should be designed accordingly.
Two areas of research that seem especially promising in terms of communication and adherence are those approaches based on tailoring to patients or patient groups (frequently called targeting) and those newer approaches that rely on technology for reminders and monitoring. These two approaches work nicely together, but it is likely that they work best when used as supplementary to the interpersonal aspects of communication noted earlier. The work on the relation between interpersonal and mediated aspects of communication is consistent in noting the interrelationships between the two, and that the most impactful health communication uses both channels of communication (Southwell & Yzer, 2007). Indeed, personalized, targeted interventions are ideal, as each patient faces a different set of barriers to adherence; furthermore, the potential for interaction, monitoring, support, and encouragement via smartphones and other technology is great. A recent systematic review of adolescents with chronic health conditions reported beneficial effects of smartphone app or text messaging interventions on adherence in 7 of 15 studies (Badawy et al., 2017). Another systematic review examining the relationship between smartphone apps and medication adherence reported that the use of mobile apps increased medication adherence in 7 of 11 studies (Perez-Jover, Sala-Gonzalez, Guilabert, & Mira, 2019). Ongoing and future research, including studies examining long-term effectiveness and studies that also incorporate interpersonal provider-patient communication, will show the extent to which these technology-based interventions make a difference for patient adherence.
Alves-Conceição, V., Rocha, K. S. S., Silva, F. V. N., Silva, R. O. S., Cerqueira-Santos, S., Nunes, M. A. P., … de Lyra, D. P., Jr. (2020). Are clinical outcomes associated with medication regimen complexity? A systematic review and meta-analysis. Annals of Pharmacotherapy, 54(4),301–313.Find this resource:
Atreja, A., Bellam, N., & Levy, S. R. (2005). Strategies to enhance patient adherence: Making it simple. Medscape General Medicine, 7(1), 4.Find this resource:
Bachman, A. S., Cohen, E. L., Colliers, T., Hatcher, J., Crosby, R., & Vanderpool, R. (2018). Identifying communication barriers to colorectal cancer screening adherence among Appalachian Kentuckians. Health Communication, 33(10), 1284–1292.Find this resource:
Badawy, S. M., Barrerra, L., Sinno, M. G., Kaviany, S., O’Dwyer, L. C., & Kuhns, L. M. (2017). Text messaging and mobile phone apps as interventions to improve adherence in adolescents with chronic health conditions: A systematic review. JMIR mHealth and uHealth, 5(5), e66.Find this resource:
Barfod, T. S., Hecht, F. M., Rubow, C., & Gerstoft, J. (2006). Physicians’ communication with patients about adherence to HIV medication in San Francisco and Copenhagen: A qualitative study using Grounded Theory. BMC Health Services Research, 6, 154–166.Find this resource:
Bauer, A. M., Parker, M. M., Schillinger, D., Katon, W., Adler, N., Adams, A. S., … 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, 1139–1147.Find this resource:
Blake, S. C., McMorris, K., Jacobson, K. L., Gasmararian, J. A., & Kripalani, S. (2010). A qualitative evaluation of a health literacy intervention to improve medication adherence for underserved pharmacy patients. Journal of Health Care for the Poor and Underserved, 21(2), 559–567.Find this resource:
Broers, S., Smets, E., Bindels, P., Evertsz, F. B., Calff, M., & de Haes. H. (2005). Training general practitioners in behavior change counseling to improve asthma medication adherence. Patient Education and Counseling, 58(3), 279–287.Find this resource:
Bultman, D. C., & Svarstad, B. L. (2000). Effects of physician communication style on client medication beliefs and adherence with antidepressant treatment. Patient Education and Counseling, 40(2), 173–185.Find this resource:
Butow, P., & Sharpe, L. (2013). The impact of communication on adherence in pain management. Pain, 154, S101–S107.Find this resource:
Calvert, S. B., Kramer, J. M., Anstrom, K. J., Kaltenbach, L. A., Stafford, J. A., & Allen LaPointe, N. M. (2012). Patient-focused intervention to improve long-term adherence to evidence-based medications: A randomized trial. American Heart Journal, 163(4), 657–665.Find this resource:
Cegala, D., Marinelli, T., & Post, D. (2000). The effects of patient communication skills training on compliance. Archives of Family Medicine, 9(1), 57–64.Find this resource:
Cohen, E. L., Wilson, B. R., Vanderpool, R. C., & Collins, T. (2016). Identifying sociocultural barriers to mammography adherence among Appalachian Kentucky women. Health Communication, 31(1), 72–82.Find this resource:
Conn, V. S., & Ruppar, T. M. (2017). Medication adherence outcomes of 771 intervention trials: Systematic review and meta-analysis. Preventive Medicine, 99, 269–276.Find this resource:
Cruz, M., Roter, D. L., Cruz, R. F., Wieland, M., Larson, S., Cooper, L. A., & Pincus, H. A. (2013). Appointment length, psychiatrists’ communication behaviors, and medication management appointment adherence. Psychiatric Services, 64(9), 886–892.Find this resource:
Davidson, B., Vogel, V., & Wickerham, L. (2007). Oncologist-patient discussion of adjuvant hormonal therapy in breast cancer: Results of a linguistic study focusing on adherence and persistence to therapy. Journal of Supportive Oncology, 5(3), 139–143.Find this resource:
Davis, M. S. (1966). Variations in patients’ compliance with doctors’ orders: Analysis of congruence between survey responses and results of empirical investigations. Journal of Medical Education, 41(11), 1037–1048.Find this resource:
De Bruin, M. (2012). Commentary on “Communication strategies to improve HIV treatment adherence” by Rochon et al. (2011). Health Communication, 27(2), 217–218.Find this resource:
Desroches, S., Lapointe, A., Ratté, S., Gravel, K., Légaré, F., & Turcotte, S. (2013). Interventions to enhance adherence to dietary advice for preventing and managing chronic diseases in adults. Cochrane Database of Systematic Reviews, 2, CD008722.Find this resource:
DiMatteo, M. R. (2004a). Social support and patient adherence to medical treatment: A meta-analysis. Health Psychology, 23(2), 207–218.Find this resource:
DiMatteo, M. R. (2004b). Variations in patients’ adherence to medical recommendations: A quantitative review of 50 years of research. Medical Care, 42, 200–209.Find this resource:
DiMatteo, M. R., Giordani, P. J., Lepper, H. S., & Croghan, T. W. (2002). Patient adherence and medical treatment outcomes: A meta-analysis. Medical Care, 40, 794–811.Find this resource:
Driesenaar, J. A., de Smet, P., van Hulten, R., Noordman, J., & van Dulman, S. (2016). Cue-responding behaviors during pharmacy counseling visits with patients with asthma about inhaled corticosteroids: Potential relations with medication beliefs and self-reported adherence. Health Communication, 31(10), 1266–1275.Find this resource:
Ellington, L., Matwin, S., Jsasti, S., Williamson, J., Crouch, B., Caravati, M., & Dudley, W. (2008). Poison control center communication and impact on patient adherence. Clinical Toxicology, 46(2), 105–109.Find this resource:
Fassaert, T., van Dulmen, S., Schellevis, F., van der Jagt, L., & Bensing, J. (2008). Raising positive expectations helps patients with minor ailments: A cross-sectional study. BMC Family Practice, 9(1), 38.Find this resource:
Fehringer, J., Bastos, F. I., Massard, E., Maia, L., Pilotto, H. H., & Kerrigan, D. (2006). Supporting adherence to highly active antiretroviral therapy and protected sex among people living with HIV/AIDS: The role of patient–provider communication in Rio De Janeiro, Brazil. AIDS Patient Care and STDs, 20(9), 637–648.Find this resource:
Feng, B., Bell, R. A., Jerant, A. F., & Kravitz, R. L. (2011). What do doctors say when prescribing medications?: An examination of medical recommendations from a communication perspective. Health Communication, 26(3), 286–296.Find this resource:
Freemon, B., Negrete, V. F., Davis, M., & Korsch, B. (1971). Gaps in doctor-patient communication: Doctor-patient interaction analysis. Pediatric Research, 5(7), 298–311.Find this resource:
Friedman, D. S., Hahn, S. R., Gelb, L., Tan, J., Shah, S. N., Kim, E. E., . . . Quigly, H. A. (2008). Doctor-patient communication, health-related beliefs, and adherence in glaucoma results from the Glaucoma Adherence and Persistency Study. Ophthalmology, 115(8), 1320–1327.Find this resource:
Fung, T. K. F. (2019). The role of counterfactual thinking in narrative persuasion: Its impact on patients’ adherence to treatment regimen. Health Communication, 34(12), 1482–1493.Find this resource:
Grenard, J. L., Munjas, B. A., Adams, J. L., Suttorp, M., Maglione, M., McGlynn, E. A., & Gellad, W. F. (2011). Depression and medication adherence in the treatment of chronic diseases in the United States: A meta-analysis. Journal of General Internal Medicine, 26(10), 1175–1182.Find this resource:
Guntzviller, L. M. (2013). Increasing medication adherence in LEP (low-English proficiency) Latino populations: Merging speech act theory and cultural competency. In M. Lumal & J. Merrick (Eds.), Health risk communication (pp. 11–26). Hauppauge, NY: Nova Science.Find this resource:
Hahn, S. (2009). Adherence to antidepressant medication: Patient-center shared decision making communication to improve adherence. CNS Spectrums, 14(12), 6–9.Find this resource:
Hahn, S. R., Friedman, D. S., Quigley, H. A., Kotak, S., Kim, E., Onofrey, M., . . . Mardekian, J. (2010). Effect of patient-centered communication training on discussion and detection of nonadherence in glaucoma. Ophthalmology, 117(7), 1339–1347.Find this resource:
Haynes, R. B., Ackloo, E., Sahota, N., McDonald, H. P., & Yao, X. (2008). Interventions for enhancing medication adherence. Cochrane Database of Systematic Reviews, 2, CD000011.Find this resource:
Haynes, R. B., & Sackett, D. L. (1979). Compliance in health care. Baltimore, MD: Johns Hopkins University Press.Find this resource:
Heisler, M., Bouknight, R. R., Hayward, R. A., Smith, D. M., & Kerr, E. A. (2002). The relative importance of physician communication, participatory decision making, and patient understanding in diabetes self-management. Journal of General Internal Medicine, 17(4), 243–252.Find this resource:
Herlitz, A., Munthe, C., Törnes, M., & Forsander, G. (2016). The counseling, self-care, adherence approach to person-centered care and shared decision making: Moral psychology, executive autonomy, and ethics in multidimensional care decisions. Health Communication, 31(8), 964–973.Find this resource:
Ho, P. M., Rumsfeld, J. S., Masoudi, F. A., McClure, D. L., Plomondon, M. E., Steiner, J. F., & Magid, D. J. (2006). Effect of medication nonadherence on hospitalization and mortality among patients with diabetes mellitus. Archives of Internal Medicine, 166(7), 1836–1841.Find this resource:
Hoeeg, D., Mortil, A.M.A., Hansen, M.L., Teilmann, G.K., & Grabowski, D. (2020). Families’ adherence to a family-based childhood obesity intervention: A qualitative study on perceptions of communicative authenticity. Health Communication, 35(1), 110–118.Find this resource:
Horne, M., & Tierney, S. (2012). What are the barriers and facilitators to exercise and physical activity uptake and adherence among South Asian older adults: A systematic review of qualitative studies. Preventive Medicine, 55(4), 276–284.Find this resource:
Iskedjian, M., Einarson, T. R., MacKeigan, L. D., Shear, N., Addis, A., Mittmann, N., & Ilersich, A. L. (2002). Relationship between daily dose frequency and adherence to antihypertensive pharmacotherapy: Evidence from a meta-analysis. Clinical Therapeutics, 24(2), 302–316.Find this resource:
Jin, L., & Acharya, L. (2016). Cultural beliefs underlying medication adherence in people of Chinese descent in the US. Health Communication, 31, 513–521.Find this resource:
Kaplan, J. E., Keeley, R. D, Engel, M., Emsermann, C., & Brody, D. (2013). Aspects of patient and clinician language predict adherence to antidepressant medication. Journal of the American Board of Family Medicine, 26(4), 409–420.Find this resource:
Kedia, S. K., Dillon, P. J., & Basu, A. (2019). A qualitative exploration of “mother first” identity and antiretroviral adherence among African American women living with HIV in the mid-south region of the United States. Health Communication.Find this resource:
Kripalani, S., Yao, X., & Haynes, R. B. (2007). Interventions to enhance medication adherence in chronic medical conditions: A systematic review. Archives of Internal Medicine, 167(6), 540–550.Find this resource:
Laws, M. B., Rose, G. S., Bezreh, T., Beach, M. C., Taubin, T., Kogelman, L., . . . Wilson, I. B. (2012). Treatment acceptance and adherence in HIV disease: Patient identity and the perceived impact of physician–patient communication. Patient Preference and Adherence, 6, 893–903.Find this resource:
Linn, A. J., van Dijk, L., Smit, E. G., Jansen, J., & van Weert, J. C. M. (2013). May you never forget what is worth remembering: The relation between recall of medical information and medication adherence in patients with inflammatory bowel disease. Journal of Crohn’s and Colitis, 7(11), e543–e550.Find this resource:
Linn, A. J., van Weert, J. C. M., Gebeyehu, B., Sanders, R., Diviani, N., Smit, E. G., & van Dijk, L. (2019). Online information seeking behavior throughout patients’ treatment: An analysis of the impact on medication beliefs and medication adherence. Health Communication, 34(12), 1461–1468.Find this resource:
Liu, Y., Malin, J. L., Diamant, A. L., Thind, A., & Maly, R. C. (2013). Adherence to adjuvant hormone therapy in low-income women with breast cancer: The role of provider-patient communication. Breast Cancer Research and Treatment, 137(3), 829–836.Find this resource:
Lonsdale, C., Hall, A. M., Williams, G. C., McDonough, S. M., Ntoumanis, N., Murray, A., … Hurley, D. A. (2012). Communication style and exercise compliance in physiotherapy (CONNECT). A cluster randomized controlled trial to test a theory-based intervention to increase chronic low back pain patients’ adherence to physiotherapists recommendations: Study rationale, design, and methods. BMC Musculoskeletal Disorders, 13(104), 104–119.Find this resource:
Martin, L. R., Williams, S. L., Haskard, K. B., & DiMatteo, M. R. (2005). The challenge of patient adherence. Therapeutics and Clinical Risk Management, 1(3), 189–199.Find this resource:
Mayo-Gamble, T. L., & Mouton, C. (2018). Examining the association between health literacy and medication adherence among older adults. Health Communication, 33(9), 1124–1130.Find this resource:
McDonald, H. P., Garg, A. X., & Haynes, R. B. (2002). Interventions to enhance patient adherence to medication prescriptions: Scientific review. Journal of the American Medical Association, 288(22), 2868–2879.Find this resource:
Murray, A., Hall, A. M., Williams, G. C., McDonough, S. M., Ntoumanis, N., Taylor, I. M., . . . Lonsdale, C. (2015). Effect of a self-determination theory-based communication skills training program on physiotherapists’ psychological support for their patients with chronic low back pain: A randomized controlled trial. Archives of Physical Medicine and Rehabilitation, 96(5), 809–816.Find this resource:
Nieuwlaat, R., Wilczynski, N., Navarro, T., Hobson, N., Jeffery, R., Keepanasseril, A., . . . Sivaramalingam, B. (2014). Interventions for enhancing medication adherence. Cochrane Database of Systematic Reviews, 11, CD000011.Find this resource:
Ong, M.-S., Magrabi, F., Post, J., Morris, S., Westbrook, J., Wobcke, W., . . . Coiera, E. (2013). Communication interventions to improve adherence to infection control precautions: A randomised crossover trial. BMC infectious Diseases, 13(72), 72–81.Find this resource:
Osterberg, L., & Blaschke, T. (2005). Adherence to medication. New England Journal of Medicine, 353(5), 487–497.Find this resource:
Paterson, D. L., Swindells, S., Mohr, J., Brester, M., Vergis, E. N., Squier, C., . . . Singh, N. (2000). Adherence to protease inhibitor therapy and outcomes in patients with HIV infection. Annals of Internal Medicine, 133(1), 21–30.Find this resource:
Pérez-Jover, V., Sala-González, M., Guilabert, M., & Mira, J. J. (2019). Mobile apps for increasing treatment adherence: Systematic review. Journal of Medical Internet Research, 21(6), e12505Find this resource:
Peterson, E. B., Ostroff, J. S., DuHamel, K. N., D’Agostino, T. A., Hernandez, M., Canzona, M. R., & Bylund, C. L. (2016). Impact of provider-patient communication on cancer screening adherence: A systematic review. Preventive Medicine, 93, 96–105.Find this resource:
Polikandrioti, M., & Babatsikou, F. (2013). Information to coronary disease patients. Health Science Journal, 7(1), 3–10.Find this resource:
Rochon, D., Ross, C., Looney, M., Nepal, V., Price, A., & Giordano, T. (2011). Communication strategies to improve HIV treatment adherence. Health Communication, 26(5), 461–467.Find this resource:
Roter, D. L., & Hall, J. A. (1989). Studies of doctor-patient interaction. Annual Review of Public Health, 10(1), 163–180.Find this resource:
Ryan, R. M, & Deci, E. L. (2002) Overview of self-determination theory: An organismic dialectical perspective. In E. L. Deci & R. M. Ryan (Eds.), Handbook of self-determination research (pp. 1–25). Rochester, NY: University of Rochester Press.Find this resource:
Sabaté, E. (2003). Adherence to long-term therapies: Evidence for action. Geneva, Switzerland: World Health Organization.Find this resource:
Sanjobo, N., Frich, J. C., & Fretheim, A. (2012). Barriers and facilitators to patients’ adherence to antiretroviral treatment in Zambia: A qualitative study. SAHARA-J: Journal of Social Aspects of HIV/AIDS: An Open Access Journal, 5(3), 136–143.Find this resource:
Schoenthaler, A., Allegrante, J. P., Chaplin, W., & Ogedegbe, G. (2012). The effect of patient‐provider communication on medication adherence in hypertensive black patients: Does race concordance matter? Annals of Behavioral Medicine, 43(3), 372–382.Find this resource:
Simpson, S. H., Eurich, D. T., Majumdar, S. R., Padwal, R. S., Tsuyuki, R. T., Varney, J., . . . Johnson, J. A. (2006). A meta-analysis of the association between adherence to drug therapy and mortality. British Medical Journal, 333(7557), 15.Find this resource:
Sleath, B., Carpenter, D. M., Slota, C., Williams, D., Tudor, G., Yeatts, K., … Ayala, G. X. (2012). Communication during pediatric asthma visits and self-reported asthma medication adherence. Pediatrics, 130(4), 627–630.Find this resource:
Southwell, B. G., & Yzer, M. (2007). The roles of interpersonal communication in mass media campaigns. Communication Yearbook, 31(1), 420–462.Find this resource:
Thompson, L., & McCabe, R. (2012). The effect of clinician-patient alliance and communication on treatment adherence in mental health care: A systematic review. BioMed Central Psychiatry, 12(1), 87.Find this resource:
Thompson, T. L. (1984). The invisible helping hand: The role of communication in the health and social service professions. Communication Quarterly, 32(2), 148–163.Find this resource:
Tran, B. Q., & Sweeny, K. (2019). Correlates of physicians’ and patients’ language use during surgical consultations. Health Communication.Find this resource:
Tran, N., Coffman, J. M., Sumino, K., & Cabana, M. D. (2014). Patient reminder systems and asthma medication adherence: A systematic review. Journal of Asthma, 51(5), 536–543.Find this resource:
Traylor, A. H., Schmittdiel, J. A., Uratsu, C. S., Mangione, C. M., & Subramanian, U. (2010). Adherence to cardiovascular disease medications: Does patient-provider race/ethnicity and language concordance matter? Journal of General Internal Medicine, 25(11), 1172–1177.Find this resource:
van Elsland, S. L., Springer, P., Steenhuis, I. H. M., van Toorn, R., Schoeman, J. F., & van Furth, A. M. (2012). Tuberculous meningitis: Barriers to adherence in home treatment of children and caretaker perceptions. Journal of Tropical Pediatrics, 58(4), 275–279.Find this resource:
Verloo, H., Chiolero, A., Kiszio, B., Kampel, T., & Santschi, V. (2017). Nurse interventions to improve medication adherence among discharged older adults: A systematic review. Age and Ageing, 46(5), 747–754.Find this resource:
Wachira, J., Middlestadt, S., Reece, M., Peng, C.-Y. J., & Braitstein, P. (2014). Physician communication behaviors from the perspective of adult HIV patients in Kenya. International Journal for Quality in Health Care, 26(2), 190–197.Find this resource:
Watermeyer, J., & Penn, C. (2012). “Only two months destroys everything”: A case study of communication about nonadherence to anti-retroviral therapy in a South African HIV pharmacy context. Health Communication, 27(6), 602–611.Find this resource:
Wilson, M. A. (1966). The influence of the diet prescription and the educational approach on patient adherence to sodium restricted intake. Medical Times, 94(12), 1514–1522.Find this resource:
Wong, N. (2009). Investigating the effects of cancer risk and efficacy perceptions on cancer prevention adherence and intentions. Health Communication, 24(2), 95–105.Find this resource:
Wright, B. J., Galtieri, M. J., & Fell, M. (2014). Non-adherence to prescribed home rehabilitation exercises for musculoskeletal injuries: The role of the patient-practitioner relationship. Journal of Rehabilitative Medicine, 46(2), 153–158.Find this resource:
Wu, Y. P. & Hommel, K. A. (2014). Using technology to assess and promote adherence to medical regimens in pediatric chronic illness. The Journal of Pediatrics, 164(4), 922–927.Find this resource:
Wuensch, P., Hahne, A., Haidinger, R., Meibler, K., Tenter, B., Stoll, C., . . . Huebner, J. (2015). Discontinuation and non-adherence to endocrine therapy in breast cancer patients: Is lack of communication the decisive factor? Journal of Cancer Research and Clinical Oncology, 141(1), 55–60.Find this resource:
Zhao, X., Villagran, M., Kreps, G., & McHorney, C. (2012). Gain versus loss framing in adherence-promoting communication targeting patients with chronic diseases: The moderating effect of individual time perspective. Health Communication, 27(1), 75–85.Find this resource:
Zolnierek, K. B. H., & DiMatteo, M. R. (2009). Physician communication and patient adherence to treatment: A meta-analysis. Medical Care, 47(8) 826–834.Find this resource:
Zullig, L. L., Shaw, R. J., Shah, B. R., Peterson, E. D., Lindquist, J. H., Crowley, M. J.,. . . Bosworth, H. B. (2015). Patient-provider communication, self-reported medication adherence, and race in a post-myocardial infarction population. Patient Preference and Adherence, 9, 311–318.Find this resource: