Heuristics and decision-making: what are the effects on adherence for patients with cardiovascular disease

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Cardiovascular

Cardiovascular

Heuristics and decision-making: what are the effects on adherence for patients with cardiovascular disease?

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Key messages:

  • The human mind has evolved to make decisions and draw the most plausible conclusions regardless of the quality of available information
  • The decision-making process is influenced by heuristics, or cognitive “short-cuts”, which can have a significant impact on adherence when relevant information is limited 
  • Understanding heuristics can therefore significantly help us understand patients’ adherence and assist them in taking their medication as prescribed

As described in the previous articles in this series, << Two systems of thought: why “rational” people make “irrational” choices >>,  the mind has two systems of thinking: System 1 and System 2. The first is immediate and spontaneous. The second is reflective and conscious, but requires cognitive efforts and is thus used less frequently. System 1, our immediate, impulsive reaction, is responsible for 95% of all the decisions we make. It is driven by heuristics (i.e. cognitive short-cuts), which make it faster, less taxing, and (unfortunately) subject to error.  This article will describe some of these heuristics. 


People make decisions even when all the relevant information is unavailable

According to the latest findings from behavioral science, the human mind is “set” to react to the environment in which it lives as best it can in the moment while expending the least mental effort possible. This process is run by System 1, which pops up automatically and effortlessly. However, in many cases, the information that comes from the environment is only partial or even irrelevant to making a completely rational decision. This rapid response system is very useful when we immediately need to get out of harm’s way, but in many cases, the immediately available information is incomplete or irrelevant to the issue at hand. Even in these situations when relevant information is limited, System 1 continues to draw conclusions and make decisions, largely automatically. In order to do so, System 1 uses mental proxies based on experience and previous learnings. These are adapted to the situation and used, within the confines of cognitive “shortcuts”, or heuristics. These heuristics significantly influence attitudes and behaviors, including patient adherence. 


Patients process information and behave according to a narrative understanding 

Daniel Kahneman described the mind as a “machine for jumping to conclusions”. According to Kahneman, evolution has led us to develop a “narrative” understanding of our environment based on available data. The amount and the quality of the data are irrelevant to System 1, which will choose the easiest cognitive conclusion possible1 according to the existing narrative. For example, suppose a hypertension patient is asked the following question: “Do you want Dr. Brown to be your main doctor for your heart problem? He studied medicine at the best university in the country and has successfully managed more than 10 000 patients during his career.” The patient’s quick System 1 answer to this question likely will be “yes”, but it will be based only on partial information. For example, what if the continuation of the statement on Dr. Brown were “he is an accomplished oncologist”?  These conclusions result from the heuristics inherent to System 1. 

Similarly, consider the question: “Is Dr. Brown nice to his patients?”. The initial reaction is somehow different compared to the question: “Is Dr. Brown mean to his patients”? Finding the most accurate answer to these questions would require analysis by System 2 of relevant information, which may be unavailable. In this case, System 1 tends to seek data that would confirm the immediate belief. This heuristic is referred to by Kahneman as confirmation bias, which can lead to exaggerated emotional coherence, known as the halo effect. For example, a patient is very likely to assess the clinical skill of his physician as a function of the doctor’s interpersonal skills, because the patient is familiar with interpersonal skills and may know nothing about the technical aspects of medicine. Likewise, the halo effect might have a very strong influence on the patient’s adherence, as a poor relationship with the doctor is one of the major drivers of non-adherence.2 Therefore, a patient who likes the prescribing doctor is more likely to be adherent than a patient who dislikes his doctor.


Understanding patient adherence behavior requires an understanding of these cognitive heuristics

Understanding these heuristics or “Rules of Thumb”, can allow a prescriber to better understand how people make their judgements regarding their medication adherence and in which way these judgements are biased. In addition to confirmation bias and the halo effect, already discussed, these heuristics include:

  • The Anchoring heuristic – This heuristic is a tendency to make decisions with respect to a reference point. Consider the following experiment: three groups of people are asked how much they would be willing to donate to a charity, but via the following questions:

    o How much would you consider giving to charity,
       for example $5?
    o How much would you consider giving to charity? (no anchor)
    o How much would you consider giving to charity,
       for example$400?

The results of this experiment were that people were willing to give respectively $20 when anchored at $5; they were willing to give $64 with no anchor, and they were willing to give $143 when $400 was mentioned.1 The participants were strongly influenced by the mentioning of an initial amount. This heuristic is often used in negotiation but can be readily applied in healthcare. In a recent study in dermatology for a drug injected once a month, a group of patients (i.e. the intervention group) was asked to rank their desire to take a daily injection for psoriasis.  This was used as an anchor, as patients were then asked if they would be willing to take a monthly injection. The result showed that the patients anchored to daily injection were more willing to start a monthly injection treatment when compared to the control group, which received no anchoring (median score 7,5 to 2)3. This rationale may be applied to cardiovascular disease treatment to improve adherence, since patients may be more likely to be adherent if they are informed about standard treatment practices (e.g. are given an anchor point). 

  • The Availability (salience) heuristic – We assess probability of an outcome not on the basis of an understanding of the actual probability, but rather by the degree to which it is easy to imagine a given outcome. For example, someone who has recently seen images of an earthquake in a movie may be more likely to overestimate the probability of an earthquake occurring as compared to someone who hasn’t seen those images. This heuristic implies that the person who has seen the earthquake on the screen will be keener to buy earthquake insurance. However, it also implies that once the memory of the earthquake disappears, the effect on their purchasing behavior will disappear as well.1 The same principle can be applied to adherence in cardiovascular disease: a patient who has recently been diagnosed with heart failure is likely to be more adherent to a treatment, but his adherence would decrease over time as the symptoms diminish. A recent study of patients with HIV showed that the percentage of patients with mean adherence rates of 90 % or greater increases from 31.1 to 48.3 % for those who recently received positive feedback (salient information) about the HIV medication from other patients4.
  • Representativeness – This heuristic also contributes to our perceived likelihood of an event. It is often associated with stereotypes that people might have about others. For example, consider someone with a master’s degree in anthropology, who is passionate about environmental protection, a devoted feminist, and politically on the left. Which of these two occupations is more likely for this person: working in an environmental charity or an accountant? The representativeness bias would lead you to imagine the environmental charity as the first choice, as this is how System 1 imagines her. However, there are far more accountants than employees of environmental charities, regardless of their opinions.  Simple math indicates that it is more likely this person is an accountant. Similarly, people tend to develop ideas about how people in certain roles should behave. A farmer, for example, might be seen as hard-working, outdoorsy, and tough. A librarian, on the other hand, might be viewed as being quiet, organized, and reserved5.
    This heuristic could be very useful in our understanding of adherence. In a study on pain management in arthritis, researchers provided conflicting information to the patients on whether the arthritis medication should be taken with or without food. Several patients chose to take the drug with food because it is standard practice to take arthritis treatment with food6. Taking the medication with food appeared to be representative for these patients. 
  • Loss aversion / endowment – People generally feel worse about losing something than happy when they earn the same thing. For example, losing $100 is typically more painful in intensity than is the joy of being given $100. Richard Thaler provides the example of a group of students who were split in two sub-groups. One sub-group received a mug with the university insignia and the other did not. After that, each student was asked at which price they would consider buying or selling the mug, respectively. The sellers of the mug valued it twice as much as the buyers. How can this heuristic be exploited in the case of adherence?  Keep in mind that when people give up something, they are hurt more than the joy they experience when acquiring it1.  As such, a healthcare professional can stress that every time medication is taken, or the patient engages in positive behavior, such as exercise, they are gaining in health and by abandoning such behaviors they will be losing the advances they’ve made.
  • Optimism / Over-optimism – People tend to think that they assess a situation and act better than the others (i.e. roughly speaking, most people believe that they are above average)1. In his famous book, “Nudge”, Richard Thaler provides the example of people starting their own small business being asked two questions: 1. “What is the rate of success for business similar to yours?” And, 2. “What are your chances for success?” On average, people responded “50%” to the first question and “90%” when asked about their own chances of success. This bias might be responsible for misconceptions that doctors might have of their patients’ adherence: while they may acknowledge that adherence is a problem, they are often quite confident that their patients are adherent7.  A recent study showed that overly-optimistic patients with HIV (i.e. those who believe that they will do better than other patients in the clinic) are less likely to achieve the desired adherence rates when compared to other patients by about 10%4. Physicians should keep in mind that patients’ self-assessment of their adherence cannot always be relied on for accuracy.

Heuristics drive decisions and behavior, including attitudes towards and adherence to treatments for chronic diseases such as cardiovascular disease. A thorough understanding of these heuristics is informative for physicians, hospital authorities and HCPs to improve adherence. Future articles will discuss other behavioral theories and corresponding interventions for improving patient adherence. 

References
1. Kahneman, “Thinking Fast and Slow”, “Machine for jumping to conclusions, Section: What you see is all there is”, 2011
2. Charitini Stavropoulou “Non-adherence to medication and doctor–patient relationship: Evidence from a European survey”, Patient Education and Counseling, Volume 83, Issue 1, April 2011, Pages 7-13, https://doi.org/10.1016/j.pec.2010.04.039
3. Elias Oussedik, BSc1; Leah A. Cardwell, MD1; Nupur U. Patel, MS, An Anchoring-Based Intervention to Increase Patient Willingness to Use Injectable Medication in Psoriasis, September 2017 (https://jamanetwork.com/journals/jamadermatology/fullarticle/2629993)
4. Sebastian Linnemay and Chad Stecher, Behavioral Economics Matters for HIV Research: The Impact of Behavioral Biases on Adherence to Antiretrovirals (ARVs), doi: 10.1007/s10461-015-1076-0 (https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4720130/)
5. Kendra Cherry, Representativeness Heuristic and Our Judgments Representativeness heuristic affects judgments but can lead to errors, 2019, (https://www.verywellmind.com/representativeness-heuristic-2795805)
6. Emily Elstad , MPH,Delesha M. Carpenter , PhD,Robert F. Devellis , PhD &Susan J. Blalock, Patient decision making in the face of conflicting medication information, 2012 (https://doi.org/10.3402/qhw.v7i0.18523)
7. M. Robin DiMatteo,Kelly B. Haskard-Zolnierek &Leslie R. Martin, Improving patient adherence: a three-factor model to guide practice, 2011 (https://doi.org/10.1080/17437199.2010.537592)


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