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Supporting Adherence to Medicines for Long-Term Conditions: A Perceptions and Practicalities Approach Based on an Extended Common-Sense Model Rob Horne, Vanessa Cooper, Vari Wileman, and Amy Chan
by Hogrefe
Special Issue: Adjustment to Chronic Illness Original Articles and Reviews
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A Perceptions and Practicalities Approach Based on an Extended Common-Sense Model
Rob Horne, Vanessa Cooper, Vari Wileman, and Amy Chan
Centre of Behavioral Medicine, Department of Practice and Policy, UCL School of Pharmacy, London, UK
Abstract: Pharmaceutical prescriptions are core to the treatment of most chronic illnesses, yet only half are taken as prescribed. Despite the high costs of nonadherence to individuals and society, effective adherence-promoting interventions are elusive. This is partly due to the sheer complicity of the issue. There are numerous determinants of adherence, both internal to the patient (intrinsic) and external (extrinsic, e.g., environmental or health system-related factors). Also, the relative importance of these determinants varies between individuals and even within the same individual over time and across treatments, presenting a challenge for intervention design. One complication is that interventions can target several levels: (1) patient (e.g., enhancing motivation and/or ability to adhere), (2) patient-provider interactions (e.g., improving communication and the prescribing process), and (3) the healthcare system (e.g., providing the opportunity to access medication through regulatory approval and co-payment schemes). Here, we focus on level 1: the patient. Although environmental factors are important, the effect of an intervention designed to change them will depend on how they impact on the individual. We describe the Perceptions and Practicalities Approach (PAPA), a pragmatic framework positing that adherence/nonadherence is essentially a produce of individual motivation and ability. Adherence interventions, targeted at any level, will therefore be more effective if tailored to address the perceptions and practicalities underpinning individual motivation and ability. We discuss how PAPA can be operationalized, including the application of theoretical models of illness and treatment representation (Necessity-Concerns Framework and Leventhal’s Common-Sense Model) to address salient adherence-related perceptions.
Keywords: adherence, Perceptions and Practicalities Approach (PAPA), Necessity-Concerns Framework (NCF), interventions, Common-Sense Model (CSM)
Nonadherence to Medication in Chronic Illness: The Need for More Effective Interventions
The prescription of a medicine is one of the most common interventions in developed health economies (Kantor, Rehm, Haas, Chan, & Giovannucci, 2015) and is essential to the treatment of most chronic illnesses (Simpson et al., 2006). However, treatment adherence rates are highly variable, ranging from 0% to over 100% (Nieuwlaat et al., 2014), depending on the condition, therapy, and methods used to measure adherence. The World Health Organization (WHO) estimates that, on average, only half of prescriptions for long-term conditions are taken as advised (Sabaté, 2003). If the prescription was appropriate, this may represent a lost opportunity for health gain and increased financial costs resulting from unnecessary escalations of treatment (DiMatteo, Giordani, Lepper, & Croghan,
2002; Sabaté, 2003). The complex comorbidities that accompany many long-term conditions, with their associated polypharmacy and complicated medication regimes, further exacerbate the problem of nonadherence (Murray & Kroenke, 2001). Despite the costs of nonadherence to individuals and society, effective adherence-promoting interventions remain elusive. A series of systematic reviews have examined the efficacy of medication adherence interventions. These began with a review of 13 randomized controlled trials (RCTs) in 1996 (Haynes, McKibbon, & Kanani, 1996) and culminated in a recent Cochrane review which included 46,962 participants in 182 published RCTs across 24 conditions (Nieuwlaat et al., 2014). Although the number of RCTs investigating interventions has increased substantially in the last two decades, the findings have changed little. Each systematic review has concluded that while adherence can be improved, most interventions have limited effectiveness (Nieuwlaat et al., 2014).
Adherence is difficult to quantify. Adherence measures vary across studies, making comparisons difficult, and measures differ in accuracy and reliability (Farmer, 1999; Horne & Clatworthy, 2010). Moreover, three stages in the medication-taking process can be delineated: initiation, execution, and persistence (Vrijens et al., 2012). Different assessment methods may be more applicable for one stage than another (e.g., prescription collection rates may be better at identifying non-persistence than nonadherence relating to poor execution), with each method having its own strengths and weaknesses (Farmer, 1999), yet accurate adherence monitoring is key for intervention development.
A further limitation of the current literature is that few interventions are described in sufficient detail to explain why some worked and others did not, or to reliably identify the active components of effective interventions (Hoffmann et al., 2014; Horne et al., 2005).
The Need for a Pragmatic Framework for Adherence Support
A key challenge for the development of adherencepromoting interventions is the sheer complexity of the issue (Nieuwlaat et al., 2014). There are numerous determinants of adherence, both internal to the patient (intrinsic) and external (extrinsic, e.g., environmental or health systemrelated factors). Also, the relative importance of these determinants varies between individuals and even within the same individual over time and across treatments, presenting a challenge for intervention design. One complication is that interventions can target several levels: (1) patient (e.g., enhancing motivation and/or ability to adhere), (2) patient-provider interactions (e.g., improving communication and the prescribing process), and (3) the healthcare system (e.g., providing the opportunity to access medication through regulatory approval and co-payment schemes; Horne et al., 2005) (Figure 1). In 2009 and 2016, National Institute for Health and Care Excellence (NICE) published guideline CG76 Medicines adherence: involving patients in decisions about prescribed medicines and supporting adherence. After a detailed review, NICE concluded that was no definitive gold standard intervention and that much could be done to improve the quality of support delivered to individuals. The development of their pragmatic guidelines drew on a review of compliance adherence and concordance in medicine taking, commissioned by the UK National Institute for Health Research (NIHR) (Horne et al., 2005) which had applied the Perceptions and Practicalities Approach (PAPA) as a framework
2019 Hogrefe Publishing Healthcare System Policy & Practice
Patient-Provider Interactions
Patient INTERVENTIONS
Figure 1. Adherence interventions “lollipop” –multi-level targets for intervention (Horne et al., 2005).
for understanding nonadherence form the patients’ perspectives and for apprising adherence interventions. The NICE guidelines recommended the application of the PAPA advocating that addressing nonadherence should start with “an exploration of patients’ perspectives of medicines and the reasons why they may not want or are unable to use them and that to understand adherence to treatment we need to consider the perceptual factors (e.g., beliefs and preferences) that influence motivation to start and continue with treatment, as well as the practical factors that influence patients’ ability to adhere to the agreed treatment” (Nunes et al., 2009, p. 5). In this paper, we outline the key feature of the PAPA. We will argue that to understand and address adherence, we should start with the patient and question how the treatment and, any interventions to support its use, impacts on their motivation and ability to follow the agreed treatment recommendations. Healthcare professionals have a duty to help patients make informed decisions about treatment and use appropriately prescribed medicines to best effect (Horne & Weinman, 2004). The NICE guidelines embody this principle stating that addressing nonadherence is not about getting patients to take more medicines per se. Rather, it starts with an exploration of patients’ perspectives of medicines and the reasons why they may not want or are unable to use them.
We will review research investigating patient perceptions of medication with particular emphasis on “commonsense” representations of medication, and the illnesses they are prescribed for. We will suggest theoretical frameworks for conceptualizing the beliefs about medication (Necessity-Concerns Framework) and illness (Leventhal’s components of illness representation) that are likely to be particularly salient for adherence/nonadherence and discuss how they can be applied in an extended CommonSense Model.
PAPA (Horne, 2001; Horne et al., 2005) offers a simple framework to guide the development and appraisal of adherence-promoting interventions. It attempts to specify the “minimum ingredients” of adherence support targeted to the needs of the patient. The PAPA focuses on how the individual interacts with their treatment and derives from the basic premise that two key attributes that are considered essential for adherence: motivation and ability. It presumes that, although a wide variety of intrinsic factors (e.g., depression and anxiety; DiMatteo, Lepper, & Croghan, 2000) and extrinsic factors (e.g., environmental opportunities and constraints) are relevant, their effect on adherence is likely to manifest through enhanced or reduced motivation and/or ability.
It is widely recognized that nonadherence may be both intentional (e.g., when we decide not to take the treatment or to take it in a way which differs from recommendations) and/or unintentional (e.g., when we want to follow the recommendations but are prevented from doing so by barriers that are beyond our control). If we begin with the individual, the minimum requirement for explaining variation in adherence/nonadherence is the interaction between two factors: motivation and ability (Horne et al., 2005). Motivation may arise from conscious decision-making processes but also more instinctive, intuitive processes (Kahneman, 2011). Likewise, a range of factors influence ability (e.g., knowledge and physical capability to administer the dosage form on time) (Horne et al., 2005; Piette, Heisler, Horne, & Alexander, 2006). These two aspects of motivation and ability, which are driven by intentional and unintentional processes, form the fundamental basis of the PAPA framework (Figure 2). The division between intentional and unintentional processes may be blurred, with degree of overlap between motivation and ability represented in Figure 2 by the overlapping circles. For example, we may be more inclined to forget to take a medicine that we perceive to be unimportant than one that we perceive to be essential. Likewise, the provision of training on the best technique for administration of asthma medication via an inhaler was more effective in those who were more motivated to practice the technique (Ovchinikova, Smith, & Bosnic-Anticevich, 2011). Moreover, an intervention designed to improve patients’ ability to adhere by simplifying the regimen (and making it easier to take) might also increase motivation.
The concepts of motivation and ability leading to action (in this case, action to take a medication) need not precede one another in succession. While in most cases, increasing motivation and/or ability can lead to an increase in action, in some cases, beginning the action itself (i.e., taking the medication) can lead to increases in motivation or ability. For example, if a patient feels better after taking the medication, this may lead to increased motivation to continue to take the treatment.
The value in the intentional–unintentional, motivation–ability constructs is not in the fact that these are completely distinct and separate categories. Rather, it is in presenting a basic aide-memoir of the fundamental ingredients of adherence support. If we are designing or evaluating an intervention to change behavior, a basic starting point is to consider the recipient of the interventions and question whether it addresses both perceptions and practicalities and motivation and ability. The PAPA framework is therefore not intended as comprehensive theory. There are clearly many other factors that need to be considered if we are trying to map the antecedents of adherence and nonadherence. Rather, the two overlapping circles suggest the “core” components of adherence support. This might serve as a foundation for more comprehensive modeling of determinants as discussed previously (Horne, 2006; Horne et al., 2005) and later in this paper.
Opportunity and Triggers
Motivation and ability, which are usually thought of as intrinsic qualities, may also be influenced by extrinsic factors that make the behavior possible or prompt it. This was recognized in the “Opportunity” construct proposed by Ölander and Thøgersen in their motivation–opportunity–abilities (MOA) model (Thøgersen, 1995) and by Michie and colleagues in their COM-B model, where the behavioral determinants are labeled motivation, opportunity, and capability (Michie, van Stralen, & West, 2011). Similarly, in Fogg’s behavioral model, the importance of external prompts or calls to action, such as the sounding of an alarm, is emphasized (Fogg, 2009). Fogg replaces the more generic opportunity construct proposed by Ölander and Thøgersen, with “Triggers” in the Fogg Behavioral Model (FBM) which incorporates motivation, ability, and triggers (Fogg, 2009). There is clearly considerable overlap between these constructs (Jackson, Eliasson, Barber, & Weinman, 2014). Providing treatment opportunities (e.g., by making a medicine available or providing free access to it) might also enhance motivation, if the treatment is valued by the patient (Taira, Wong, Frech-Tamas, & Chung, 2006). Triggers may be external or internal and influence both motivation and ability to adhere. External triggers such as a text reminder
Intentional processes
Unintentional processes
MOTIVATION ABILITY
e.g. Beliefs, emotions, and preferences Perceptions
e.g. Capability and resource limitations Practicalities
Figure 2. Perceptions and Practicalities Approach (PAPA): motivation and ability as core intrinsic attributes for adherence.
could improve ability to take the treatment on time and motivate behavior to do so (Petrie, Perry, Broadbent, & Weinman, 2012). Conversely, an unwanted reminder might reduce our motivation to adhere if we are irritated by it (Mannheimer et al., 2006). Internal triggers such as symptom experiences might motivate adherence if the individual believes taking the medication will help relieve the symptoms (Figure 3). Interventions to support adherence, especially to longterm treatments, are likely to be effective if they impact on both the specific perceptions (e.g., beliefs and emotions) and practicalities (e.g., capacity, resources, and opportunities) affecting the individual’s motivation and ability to start and continue with treatment (Horne et al., 2005). Both perceptions and practicalities can be moderated by external opportunities and triggers. However, a fundamental requirement of patient-centered adherence support is that it considers both the perceptions and practicalities linked to individual motivation and ability to start and continue with the agreed treatment plan.
Addressing motivation and ability through perceptions and practicalities may also a prerequisite to the formation of a (healthy) habit where taking medication becomes part of the patient’s routine. In this respect, we might envisage a logical flow of motivation–ability–habit. Before describing the PAPA approach to adherence support, it is important to consider perceptions that are central to PAPA. Interventions that attend to the practicalities of adherence (e.g., by making the medicine readily available or by providing prompts or reminders) are unlikely to be effective if the patient has already made an intentional decision not to take their prescribed medication because of their beliefs. Understanding how we make decisions about treatments is key to the PAPA adherence framework.
From Overarching Frameworks to Specific Content
2019 Hogrefe Publishing Triggers [e.g. External / Internal cues / Prompts to action]
Intentional processes
Unintentional processes
MOTIVATION ABILITY
e.g. Beliefs, emotions, and preferences Perceptions
e.g. Capability and resource limitations Practicalities
Opportunity
E[e.g. Access to treatment through prescription / co-payments etc.]
Figure 3. Perceptions and Practicalities incorporating Triggers and Opportunity.
Ruppar, & Chan, 2016; Holmes, Hughes, & Morrison, 2014). Most theories share the common assumption that the motivation to engage in and maintain health-related behaviors arises from beliefs that influence the interpretation of information and experiences and guide behavior (Conner & Norman, 1996; Horne & Weinman, 1998b). The capacity of theoretical models to explain variance in adherence and other behaviors is, however, determined by the validity of the model and whether it contains the right constructs. It is also influenced by the way in which the constructs are operationalized. In social cognition models, the antecedents of behavior are specified at the process level (e.g., attitudes inform intentions, which influence behavior; Ajzen, 1991). When theoretical models are used to develop interventions, they are likely to be more effective if they specify content (e.g., the beliefs that contribute to the positive or negative evaluations that constitute the attitude toward the behavior) as well as process (Marteau, Dieppe, Foy, Kinmonth, & Schneiderman, 2006; Noar & Zimmerman, 2005; Painter, Borba, Hynes, Mays, & Glanz, 2008). This is recognized within Leventhal’s Common-Sense Model of self-regulation (CSM) where the content, as well as the process of illness representations, is specified (Leventhal et al., 1992). However, theoretical models of behavior are likely to be more explanatory when their content becomes more specific to the behavior in question (Francis, O’Connor, & Curran, 2012). Although representations of coping procedures (e.g., taking treatment in response to an illness threat) are implicit within Leventhal’s CSM, a more explicit consideration of perceptions of treatment is necessary when the model is applied to adherence (Aujla et al., 2016; Horne, 2003). A consideration of how we evaluate prescribed treatments and how these evaluations relate to the self-regulation of illness is central to the PAPA framework.
Making Decisions About Taking Medicines: The Necessity-Concerns Framework
Studies of adherence to prescribed medicines consistently link nonadherence to patients’ treatment beliefs, and in particular, how necessary the patient believes their medicine to be for their illness (necessity beliefs) relative to how concerned they are about taking it (concerns) (Horne et al., 2013). Necessity beliefs might be thought of as the answer to two questions: “How much do I need this treatment to achieve a goal that’s important to me?” and “How much can I get away without it?”. Perceived necessity is not a form of efficacy belief: We might believe that a treatment will be effective but not that we need it. We might have a low necessity belief even if we understand the scientific evidence for the potential benefits of treatment. This might occur because we do not “value” that particular benefit or perceive it be important enough to overcome our concerns about taking the medicine. For example, we may understand that inhaled cortico steroids are effective for reducing inflammation in the airways in asthma, but we may not believe we need to take it every day, even when we feel well, as our necessity belieffor the treatment is low. Concerns: There is a commonality in the types of concerns that patients report about prescription medicines. One obvious source of concern is the experience of symptoms as medication “side effects” and the disruptive effects of medication on daily living, but this is not the whole picture (Cooper et al., 2015). Many patients receiving regular medication who have not experienced adverse effects are still worried about possible problems in the future. These concerns often arise from the belief that regular use can lead to dependence or that the medication will accumulate within the body and lead to long-term harmful effects (Horne, Weinman, & Hankins, 1999). Another common concern is that regular use of medication now will make it less effective in the future (Horne, Parham, Driscoll, & Robinson, 2009). These core concerns seem to be fairly generic and relevant across a range of disease states and cultures, and they are typically endorsed by over a third of participants (Chapman et al., 2015; Clatworthy et al., 2009; Horne, 2001; Horne et al., 1999, 2009). Medication concerns are evaluative summations of representations of the threat posed by medication. In common with illness representations, they have a cognitive and emotional dimension (Leventhal et al., 1998). Cognitive representations of treatment threat are likely to share a similar structure to illness representations (Horne & Weinman, 1998a). Representations of these risks (and benefits) of medication comprise beliefs about the timeline
for onset and duration of effects, their likely consequences and the potential for control or cure (Leventhal et al., 1998). Unpleasant symptoms may also be (correctly or incorrectly) labeled as side effects of the medication and the expectation of medication side effects may initiate a search for confirmatory symptoms (Heller, Chapman, & Horne, 2015; Nestoriuc, Orav, Liang, Horne, & Barsky, 2010). Meaning of Medication and Sense of Self: Concerns also relate to the meaning that being on regular medication has for the individual and their sense of self. Taking a daily treatment may be an unwelcome reminder of an illness that has a negative impact on how people see themselves or perceive they are seen by others. In these circumstances, nonadherence might be seen as an implicit strategy for minimizing the impact on their sense of self (Cooper et al., 2002; Horne, 2003). Determining the necessity of a treatment may also be influenced by notions of self. There has been disappointingly little research in this area, but perceptions that one can resist the progress of disease by drawing on sources of “inner strength,” or by keeping a “positive outlook” emerged as reasons for deciding not to start clinically indicated antiretroviral treatments in interviews with human immunodeficiency virus (HIV) positive men (Cooper et al., 2002).
Balancing Necessity Against Concerns: The Necessity-Concerns Differential
Necessity beliefs and concerns can be assessed using the validated Beliefs about Medicines Questionnaire (BMQ; Horne et al., 1999). A recent meta-analysis of 94 peerreviewed studies applying the BMQ in 23 long-term conditions across 18 countries showed that adherence to medication prescribed for long-term conditions was often related to necessity beliefs and concerns (Horne et al., 2013). These seem to influence adherence separately and in combination, although in some studies one or other of the constructs had a predominant influence on adherence (Horne et al., 2013). This research suggests that many patients have a necessity-concerns dilemma in treatment decisions. Medication can be perceived as a “double-edged sword” in which the potential benefit is compromised by the tendency to harm. For some, the dilemma is made more acute by the belief that efficacy and toxicity appear to go hand in hand and more effective medicines implicitly have more severe side effects (Leventhal, Easterling, Coons, Luchterhand, & Love, 1986). A simple necessity-concerns differential (NCD) in which the BMQ concerns scale is subtracted from the BMQ necessity scale provides a crude indicator of the relative
importance of needs and concerns. However, as necessityconcerns are not complete opposites, an approach using polynomial regression has been suggested to provide a better picture of the relationships between beliefs and adherence than a simple NCD score (Phillips, Diefenbach, Kronish, Negron, & Horowitz, 2014). Despite the methodological limitations of this approach, a recent meta-analysis showed that NCD scores (which were normally distributed) were more strongly correlated with reported adherence than necessity beliefs or concerns considered in isolation (mean effect size correlations [95% CI]: necessity beliefs: 0.17 [0.14, 0.20]; concerns 0.18 [0.21, 0.15]; NCD 0.24 [0.18, 0.30]; Foot, La Caze, Gujral, & Cottrell, 2016; Horne et al., 1999). This indicates that patients who attained higher scores on the concerns scale than on the necessity scale were significantly less adherent.
These effects might operate through explicit and implicit processes. In some situations, nonadherence could be the result of a deliberate strategy to minimize harm by taking less medication. Alternatively, it might simply reflect the fact that patients who do not perceive their medication to be important are more likely to forget to take it. The impact of perceptions of treatment on adherence will also be influenced by beliefs about adherence, such as the importance of strict adherence to achieve the desired outcome (Siegel, Schrimshaw, & Raveis, 2000). have more negative views about pharmaceutical medicines and vaccines, and be more reluctant to take medication or receive vaccines (Horne et al., 2013). Taken together, these sets of beliefs about medicines and about self in relation to medicines can be thought of as “pharmaceutical schema,” or in other words, how individuals structure their ideas about pharmaceuticals.
Negative pharmaceutical schema are linked to wider concerns about science, medicine, and technology within Western cultures (Calnan, Montaner, & Horne, 2005; Green et al., 2013). There is some evidence that general beliefs about medicines may vary across cultural and ethnic groups within the United Kingdom (Horne et al., 2004). However, variation within groups is likely to be greater than between groups (Horne et al., 2004). Negative pharmaceutical schema are associated with greater concerns that specific medication will result in harm and with greater doubts about the personal need to take it (Chapman, Horne, Chater, Hukins, & Smithson, 2014; Horne et al., 2009). They influence the way in which information about the potential benefits and harms of a specific treatment are processed. In experimental studies, people with more negative pharmaceutical schema are more likely to think that symptoms are caused by the drug (i.e., attribute symptoms as side effects; Heller et al., 2015) and less likely to recall side effects correctly (Heller, Chapman, & Horne, 2017).
Representations of specific medicines are influenced by more general beliefs (social representations) about medicines as a class of treatment (Horne et al., 1999). Many people are suspicious of pharmaceuticals, perceiving them to be fundamentally harmful, addictive substances that should not be taken for long periods of time, and which tend to be overprescribed by doctors (Horne et al., 1999). Moreover, the dangerous aspects of medication are often linked to their “chemical”/”unnatural” origins and to suspicions about the pharmaceutical industry (Britten, 1994; Horne et al., 1999; Pound et al., 2005). Negative views about medicines in general are often related to a broader “world-view,” characterized by suspicion of chemicals in food and the environment (Gupta & Horne, 2001) and the perception that complementary therapies (e.g., homeopathy/herbalism) are more “natural” and therefore safer than medicines (Green, Horne, & Shephard, 2013; Horne et al., 1999). Moreover, people vary in their perceptions of personal sensitivity to their effects of medicines, with many believing that they are more sensitive than other people to the effects of medicines. People with this view tend to
We suggest a symbiotic relationship between the NecessityConcerns Framework (NCF) and Leventhal’s CommonSense Model of self-regulation (CSM) in explaining variations in treatment uptake and adherence. The CSM helps us to understand the process by which treatment perceptions influence adherence, and how the content of illness representations relates to these treatment representations. Equally, treatment perceptions and the NCF can be used to extend the explanatory power of the CSM in relation to treatment adherence (Horne et al., 2009). Figure 4 shows how the Necessity-Concerns Framework can be incorporated into Leventhal’s CSM, producing an extended model (e-CSM).
We can differentiate two stages in how we arrive at our views about our need for a treatment. First, we must believe that the condition warrants treatment. Here, we try to achieve a “common-sense fit” between our concept of the
Contextual factors e.g. self-efficacy, social and cultural norms, personality
2 Specific and General representations of treatment e.g. Necessity beliefs, Concerns about prescribed medication (Specific) Pharmaceutical schema (General)
1
Health Threat e.g. symptom experiences or medical diagnosis
1 3
Illness Representation 4
Coping Procedure (action taken) e.g. adherence / nonadherence
Emotional response to illness
3 Coping Procedure
4
2 Emotional response to treatment e.g. worry, fear, anxiety, depression 5
Appraisal
Appraisal
5 1. Symptom experiences/information trigger
treatment perceptions, depending on attribution of cause e.g. illness attribution reinforces treatment necessity; attribution to side-effects reinforces concerns (Copper et al., 2009).
2. Parallel processing of cognitive and emotional representations of treatment e.g. Having to take this treatment worries me” (Horne et al., 1999).
3. Illness perceptions and treatment beliefs have an internal logic as the individual strives for commonsense coherence. For example patients who perceived their illness to be a cyclical problem (linked to symptom experiences) rather than a chronic disease perceive fewer consequences, and were more likely to doubt the necessity for their treatment (Horne & Weinman, 2002; Horne et al., 2009).
4. Treatment perceptions influence adherence.
Adherence and non-adherence are both types of coping procedures (e.g. Horne & Weinman, 1999, Horne et al., 2013).
5. The outcome of adherence/non-adherence is appraised with subsequent reinforcement or change in treatment representations e.g. I omitted doses of my medication because I feel better (Horne et al., 2007).
Figure 4. Treatment representations extending Leventhal’s Common-Sense Model of Self-regulation (e-CSM).
problem (the illness) and the solution (the treatment). If we think the illness requires treatment, we then judge the relative necessity of different treatment options. These necessity evaluations are influenced by a range of factors including our illness prototypes and stereotypes (Horne & Clatworthy, 2010), pharmaceutical schema, past experiences of ourselves and others, social and cultural norms, and information we receive from various sources (Chapman et al., 2015). The way we evaluate the treatment is also affected by the symptoms we experience when we first perceive a threat to health (symptom perceptions). These symptoms can later influence our illness representations (i.e., how we make sense of, and understand, the illness –illness consequences and timeline). These, and other aspects of the e-CSM as applied to treatment, are discussed below.
Symptom Perceptions –Perceived Health Threat Initial perceptions of treatment necessity and subsequent treatment appraisals are influenced by our symptom experiences and expectations. Symptoms may stimulate medication use by acting as a reminder or by reinforcing beliefs about its necessity. Conversely, the absence of symptoms might lead to the interpretation that the condition is more benign than it actually is and lead to doubts about the need for treatment (Halm, Mora, & Leventhal, 2006). Moreover, symptoms can lead to concerns if patients interpret the symptoms as side effects (Cooper, Gellaitry, Hankins, Fisher, & Horne, 2009) or, alternatively, as evidence that the medication is not working (Leventhal et al., 1986). For example, in study of HIV positive individuals starting on antiretroviral treatment, patients who had a lack of improvement in their
symptoms they attributed to HIV or to the medication had lower adherence (Cooper et al., 2009).
Illness Consequences and Timeline Symptom experiences inform representations of illness timeline and illness consequences, as well as perceptions of treatment necessity (Horne & Weinman, 2002). Many patients do not perceive a common-sense fit here. For example, patients who perceived their asthma to be a cyclical rather than a chronic disease were more likely to doubt the necessity of their preventer inhaler and not use it sufficiently (Horne & Weinman, 2002). Messages about treatment necessity are likely to be more convincing if they take account of the individual’s representation of their illness.
Causal Attributions Perceptions of necessity for different treatment options may be influenced by beliefs about the cause of the illness. Changing lifestyle behaviors, such as stress or diet, may be perceived to be more necessary than taking medication if the person believes that stress or diet causes the illness. For example, in a systematic review that pooled together qualitative research around patient perspectives of hypertension and drug adherence, many thought that hypertension was caused by stress; therefore, treatment was not needed when they did not feel stressed (Marshall, Wolfe, & McKevitt, 2012).
Control/Cure Individuals have different types of beliefs about illness control. The relationships between treatment beliefs and
External (environmental) factors e.g. - Opportunities - Triggers - Information - Communication (e.g. healthcare professionals, friends etc.) - Cultural influences - Health policy - Social support - Media - Resources - Views of significant others - Social norms - Financial reasons - Medication costs
Internal factors
Appraisal: assessment and interpretation of outcomes relative to expectations
Perceptions of illness Perception and Symptom interpretation Beliefs about specific prescribed medicines e.g. - Necessity beliefs - Concerns Intention to take medication
Perceptions of self in relation to illness - Personal resilience to illness - Self-efficacy - Perceived control Social representations of medicines
Perceptions of self in relation to treatment - Personal sensitivity to medication - Self-efficacy - Perceived control Ability e.g. - Memory - Dexterity - Knowledge - Organisation
Affect/mood e.g. anxiety, depression
Figure 5. Perceptions and Practicalities Approach –a detailed conceptual map of adherence. Adherence
beliefs about illness control are specific to the type of control belief. For example, necessity beliefs are positively correlated with beliefs that the illness will be controlled by treatment (a form of efficacy belief), but not with other types of control beliefs (e.g., chance/fate or personal control over illness) (Horne & Weinman, 2002). This relationship between illness control beliefs and treatment necessity beliefs depends on the perception that the particular treatment is appropriate (i.e., makes sense to the patient).
Cognitive and emotional aspects of treatment representations are processed in parallel. Beliefs that taking medication will result in unpleasant side effects may be a source of anxiety and worry. In some situations, such as the prescription of chemotherapy or radical surgery, people may fear the treatment more than the illness. In a series of interviews with 31 women, some stated that they would rather have the cancer than have to cope with the side effects of treatment, with one stating “I felt so horrible I said to my husband these tablets are making me feel so ill I think I’d rather take the risk with cancer than feel miserable, unhappy, fat” (Cahir et al., 2015, p. 3125). External factors influencing perceptual and practical barriers to adherence Figure 5 shows the interplay between internal and external factors impacting on adherence. Perceptual and
practical barriers to adherence (internal factors) are influenced by external (environmental) factors, such as the quality of communication with healthcare professionals (Chapman et al., 2015; Jang & Bakken, 2017), the availability of social support (Jang & Bakken, 2017), and cultural factors such as religious beliefs (Spiers, Smith, Poliquin, Anderson, & Horne, 2016; Figure 4). Internal contextual factors such as depression may also impact on adherence by accentuating perceptual and practical barriers (DiMatteo et al., 2000). For example, depression has been associated with greater concerns about medicines (Salgado et al., 2017), greater symptom burden (Leonhart et al., 2016), lower self-efficacy (Hilliard, Eakin, Borrelli, Green, & Riekert, 2015), and more negative illness perceptions (Nahlén Bose, Elfström, Björling, Persson, & Saboonchi, 2016). Depression may also reduce the person’s ability to organize and implement adherence schedules and routines, thereby increasing practical barriers.
The Perceptions and Practicalities Approach to Supporting Informed Adherence
For interventions to be adopted in clinical practice, they need to be simple, clear, and require minimal effort to implement into practice (Flottorp et al., 2013). Research investigating
patients’ perceptions of illness treatment suggests that treatment beliefs (necessity-concerns) may be salient for adherence. We have suggested a pragmatic framework for medication beliefs and the importance of illness representations, as described in Leventhal’s Common-Sense Model, in influencing evaluations of treatment necessity and concerns. We can apply this framework to operationalize some of the salient perceptions relating to adherence within a simple motivation–ability structure. Here, we outline a 3-step PAPA to supporting informed adherence.
Taking a “No-Blame” Approach to Facilitate Informed Adherence
Adherence interventions should support informed treatment choices and help avoid choices that are based on misconceptions and misplaced concerns, such as not using preventer medication as the patient does not feel any difference after taking the inhaler (Horne et al., 2005). One way of determining whether informed choice has been achieved is to check whether the individual can demonstrate knowledge of relevant information about the treatment, then act according to their beliefs (Michie, Dormandy, & Marteau, 2003). This can be extended to a concept described as informed adherence –where “informing” goes beyond the provision of information to consider the individual’s perceptions of the illness and treatment (Horne & Weinman, 2004). Treatment recommendations should be presented in a way that considers the patient’s beliefs and seeks to address any incompatibilities between these beliefs and the evidence-based recommendations (Horne & Clatworthy, 2010). A no-blame approach is essential to encourage an honest an open discussion where the patient feels able to report nonadherence and express doubts and concerns about the treatment that many patients are reluctant to report (Nunes et al., 2009).
(1) Necessity beliefs: Communicate a rationale for the personal necessity of treatment that addresses the implicit question “Why do I need to follow this treatment to achieve a goal that is important to me.” This should demonstrate a common-sense fit with the patient’s beliefs about the illness and consider symptom expectations and experiences as specified in the e-CSM above (Figure 4). (2) Concerns: Elicit and address concerns and outstanding information needs. Provide support with side effect management if indicated and address low self-efficacy beliefs relating to adherence
(3) Practicalities: Make the treatment as easy and convenient to use as possible and help the patient to overcome the intention-behavior gap and support the formation of a treatment habit.
Perceptual and practical barriers to adherence can be addressed using appropriate behavior change techniques (BCTs; Michie, Johnston, Francis, Hardeman, & Eccles, 2008) as illustrated by the examples shown in Table 1.
Perceptions
Cognitive behavioral therapy (CBT) and motivational interviewing (MI) are effective techniques for challenging unhelpful beliefs and increasing motivation, respectively (Beck & Dozois, 2011; Miller & Rollnick, 2002). Less intensive educational interventions have also proved effective in modifying beliefs about medicines (Clifford, Barber, Elliott, Hartley, & Horne, 2006; Magadza, Radloff, & Srinivas, 2009) including individually tailored text messages targeting individual patient’s beliefs based on the e-CSM (Petrie et al., 2012) and “active visualization” –a technique designed to enable patients to visualize the biological processes involved in treatment (Perera, Thomas, Moore, Faasse, & Petrie, 2014).
Practicalities
Practical barriers to adherence, such as forgetting, are often the primary target of adherence interventions. Numerous studies have evaluated the efficacy of audiovisual reminders, short-term message service (SMS) messages, and pager messages, with varying degrees of success (Vervloet et al., 2012). Simplifying the regimen and reducing unnecessary polypharmacy is also of key importance, particularly in patients with complex comorbidities. Simplifying the regimen generally improves the ability to adhere (Ingersoll & Cohen, 2008) by making the treatment less intrusive (Cooper et al., 2010) and as easy and convenient as possible (Cooper et al., 2010). Reorganizing multiple medicines into dispensing boxes, and providing home delivery of medicines free of charge (Zillich et al., 2012) increases adherence in the short term, presumably by facilitating access to medicines and reducing treatment complexity. These approaches should be tailored to the specific adherence barriers facing the patient as providing unwanted reminders may be detrimental to adherence (Mannheimer et al., 2006). Linking the behavior to specific environmental cues to encourage habit formation may be effective. However, this is may then be susceptible to changes in the environment or routine such as when on holiday
Behavior change technique Example
Examples of techniques for addressing perceptual barriers Problem-solving Identify barriers to medication-taking and discuss possible ways to overcome them Re-attribution Explore alternative explanations for nonspecific symptoms that the patient attributes to treatment side effects Information about health consequences Provide information about how missing doses can affect disease control if the patient has doubts about the need for adherence Salience of consequences Use pictures or animations to show what happens to the levels of medication in the body when medication is missed Pros and cons Elicit and evaluate the potential advantages and disadvantages to taking medication regularly Framing/reframing If the patient perceives their medication as an unnatural chemical provide an alternative view of medication as supporting natural processes within the body
Examples of techniques for addressing practical barriers
Prompts (Triggers) and Cues Using reminders e.g., text messages or reminders from family members/carers
Habit formation Establishing a routine around medication-taking, for example by taking treatment with breakfast each morning Action planning –Intention implementations Formulate a plan for medication-taking, including plans for taking medicines when away from home Self-monitoring Provide calendar or diary for the patient to use to record doses taken and identify patterns
Social support Identify friends or family members to remind patient to take their medication Adding objects to the environment Provide a dosette box or blister pack to help organize medication Anchoring to established habits Suggest that the patient keeps their medication close to the bedside or next to their toothbrush
(Lally & Gardner, 2013). Implementation intentions can be used to link behaviors to specific environmental cues (Gollwitzer, 1993).
Tailoring to Individual Needs and Preferences
Evidence suggests that interventions which are tailored to the individual’s needs and preferences, and influence the way the individual interacts with the treatment, are more likely to be effective (Gatwood et al., 2016; Hugtenburg, Timmers, Elders, Vervloet, & van Dijk, 2013; Kassavou & Sutton, 2017, 2018; Lewis et al., 2013). A recent multivariable meta-regression analysis demonstrated that tailored interventions explained the largest variance in adherence effect sizes (β = 1.100, p = .008) (Kassavou & Sutton, 2018). Theory-based interventions also appear to be more effective (Marteau et al., 2006; Noar & Zimmerman, 2005; Painter et al., 2008). A recent meta-analysis reporting on theory- or model-linked adherence interventions reported an overall effect size of 0.3 for the intervention versus control groups (Conn et al., 2016), an effect size which, while modest in size, is larger than that reported with simple reminder or adherence feedback interventions (which report effects sizes of approximately 0.1) (Demonceau et al., 2013; Fenerty, West, Davis, Kaplan, & Feldman, 2012).
Tailoring can be achieved through identifying and addressing each patient’s perceptual and practical barriers to adherence, for example, by using validated questionnaires such as the Beliefs about Medicines Questionnaire (Horne et al., 1999), the brief Illness Perceptions Questionnaire (Broadbent, Petrie, Main, & Weinman, 2006) to elicit each patient’s perceptual barriers to adherence (Clifford et al., 2006; Perera et al., 2014). Questionnaires can also be used to identify practical barriers to adherence (Chapman et al., 2015; Clifford et al., 2006). Intervention components can then be tailored to address only those barriers that are experienced by the patient.
Beyond the content of the intervention, it is important that the delivery channel (e.g., healthcare professional, text, apps, etc.) is optimized for the individual. It is important to consider the wider context in which the intervention will be adopted (Tucker et al., 2017). This can be achieved by involving members of the target population in the development and testing of interventions (Yardley, Morrison, Bradbury, & Muller, 2015). It is likely that the efficacy of adherence support increases as more elements of the PAPA are utilized. Some improvement in adherence might occur with practical support but these are likely to be enhanced if the intervention also addresses perceptions. To increase effectiveness, the intervention should be tailored to address the specific perceptions and practicalities influencing motivation and
ability for the individual and then reviewed at intervals over the course of a long-term condition.
Conclusion
The Perceptions and Practicalities Approach (PAPA) provides a simple framework for understanding nonadherence and developing interventions to support optimal adherence to appropriate treatments. Research conducted across long-term conditions and in different sociodemographic groups shows that nonadherence is underpinned by intrinsic factors of motivation and ability, moderated by extrinsic factors such as opportunity and triggers. The PAPA considers the complex cognitive processes underlying decisions about whether to take and adhere to treatment, as well as the practical factors influencing ability. This simple approach can guide the development of pragmatic adherence interventions by eliciting and addressing the specific perceptions and practical barriers influencing each patient’s motivation and ability to take their medicine as prescribed, thus bringing us one step closer to addressing the challenge of improving adherence in chronic illness.
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History Received June 7, 2017 Revision received May 15, 2018 Accepted May 24, 2018 Published online February 11, 2019
Funding Rob Horne reports personal fees from AbbVie, Amgen, Biogen, Idec, Gilead Sciences, GlaxoSmithKline, personal fees from Janssen, Pfizer, Roche, Shire Pharmaceuticals, MSD, Astellas, Astrazeneca, DRSU, Novartis, Universitätsklinikum Hamburg-Eppendorf, and is the cofounds of Spoonful of Sugar Ltd, a UCL-spin out company specializing in medicines adherence. Rob Horne and Vari Wileman are supported by the National Institute for Health Research (NIHR) Collaboration for Leadership in Applied Health Research and Care (CLAHRC) North Thames at Bart’s Health NHS Trust. The views expressed are those of the author(s) and not necessarily those of the NHS, the NIHR, or the Department of Health. Amy Chan reports speaker fees from Novartis and has received an educational grant and consultancy fees from Janssen-Cilag. She was the recipient of the Medicines New Zealand 2015 award and is a freelance consultant for Spoonful of Sugar Ltd.All other authors have nothing to disclose.
Rob Horne Centre for Behavioral Medicine UCL School of Pharmacy University College London London WC1H 9HR United Kingdom r.horne@ucl.ac.uk
Rob Horne is Professor of Behavioural Medicine at University College London. His research focuses on the role of psychological and behavioral factors in explaining variation in response to treatment. His current interests center on the development of interventions to support engagement with essential treatments and on optimizing the nonspecific effects (placebo and nocebo components) of medicines. A key focus is on understanding patient and public representations of illness and treatment and how representations influence self-regulation in illness and treatment outcomes.
Vanessa Cooper (PhD) is a Chartered Health Psychologist at University College London. She has 15 years of experience at the forefront of research into medicines-related behavior. Vanessa has expertise in a wide range of methodologies including qualitative and quantitative approaches, systematic reviews, and meta-analyses. She is experienced in the application of Experience-Based Co-Design to develop patient-centered approaches to healthcare delivery and in the development of interventions to support patient engagement with treatment.
Vari Wileman (PhD) is a postdoctoral researcher at the University College London, Centre of Behavioural Medicine, School of Pharmacy. Vari experienced in applying psychological methods to the study of behavior relevant to health, illness, and health care. Her particular interest lies in psychological factors associated with treatment nonadherence and acceptance in long-term conditions and has specific knowledge of developing psychological theorybased interventions and in conducting and evaluating psychological intervention randomized controlled trials.
Amy Chan (PhD) is a postdoctoral researcher at the University College London, Centre of Behavioural Medicine, School of Pharmacy. Amy has led on several research projects in the area of adherence and chronic disease, and digital adherence support interventions. She has a particular interest and expertise in understanding medicines-related behaviors –particularly around medication adherence in long-term conditions. Amy has provided consultancy to medical research organizations, nongovernmental organizations, and pharmaceutical companies and has been involved in developing patient-centric programs in a variety of healthcare settings.
