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Central Nervous System

Heuristics and decision-making: What are the effects on adherence for patients with vertigo?

  • 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 shortcuts, which can have a significant effect on adherence when relevant information is limited.
  • Understanding heuristics can significantly help us understand patients’ adherence and assist them with taking their medication as prescribed.

As described in the articles, Two systems of thought: Why “rational” people make “irrational” choices,  the mind has two systems of thinking: System 1 and System 2. System 1 is immediate and spontaneous; System 2 is reflective and conscious but requires cognitive effort and is used less frequently. System 1, governing our immediate, impulsive reaction, is responsible for 95% of the decisions we make. It is driven by heuristics, i.e. cognitive short-cuts, which make it faster, less taxing, and more prone to error.  This article describes some of the heuristics that have important implications for patient behavior,1 including adherence.  

People make decisions even when relevant information is unavailable

According to the latest behavioral science findings, the human mind reacts to its environment as best it can in the moment while expending the least mental effort possible. This process is run by System 1 and functions automatically and effortlessly. In many cases, however, the information that comes from the environment is only partial and may be irrelevant to making rational decision. System 1 generates a rapid response, which is very useful when we need to immediately get out of harm’s way, but in many cases, the immediately available information is insufficient to the issue at hand. Even in situations where relevant information is limited, System 1 continues to draw conclusions and make decisions using mental proxies based on experience and previous learnings.  These cognitive shortcuts, or heuristics, significantly influence attitudes and behaviors,1 including adherence. 

Patients process information and behave according to a narrative understanding 

Daniel Kahneman described the mind as a “machine for jumping to conclusions.”1 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 generate the easiest cognitive conclusion possible1 according to the existing narrative. For example, suppose a patient with Meniere’s disease is asked the following question: “Do you want Dr. Brown to be your doctor? He studied medicine at the best university in the country and 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. If Dr. Brown’s extensive experience is limited to oncology, the patient’s decision might be quite different, but the heuristics inherent to System 1 led to the patient’s prompt but ill-informed decision.1 

Similarly, consider the question, “Is Dr. Brown nice to his patients?” The initial reaction is different compared to the question, “Is Dr. Brown mean to his patients?” Finding the most accurate answer to these questions would require a System 2 analysis of relevant information that may be unavailable. Instead, System 1 tends to seek data that would confirm the immediate belief. This heuristic is referred to by Kahneman as the confirmation bias, which can lead to exaggerated emotional coherence, known as the halo effect.1 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; a poor relationship with the doctor is one of the major drivers of non-adherence.2 Therefore, a patient who likes his prescribing doctor is more likely to be adherent than a patient who dislikes his doctor.

Understanding patient adherence behavior requires an understanding of cognitive heuristics

Understanding heuristics or “Rules of Thumb,” can help physicians better understand how patients make judgments regarding their medication. In addition to confirmation bias and the halo effect already discussed, relevant heuristics include:

  • Anchoring – This heuristic is a tendency to make decisions with respect to a reference point.1 Consider the following experiment: three groups of people are asked how much they would be willing to donate to a charity with the following questions:
    • How much would you consider giving to charity, for example $5?
    • How much would you consider giving to charity? (no anchor)
    • 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; $64 with no anchor; and they gave $143 when $400 was mentioned.1 The participants were strongly influenced by the initial amount proposed. This heuristic is often used in negotiation but can be readily applied in healthcare. In a recent dermatology study for a monthly injectable treatment, a group of patients, i.e. the intervention group, was asked to rank their desire to take a daily injection for psoriasis. The incorporation of “daily” was used as an anchor, as patients were then asked if they would be willing to take a monthly injection. The result showed that patients anchored with the suggestion of daily injections were more than three times more likely willing to start a monthly injection treatment when compared to the control group that received no anchoring.3 This rationale may be applied to vertigo-linked disease (e.g., Meniere’s disease) treatments to improve adherence; since patients informed about standard treatment practices, i.e. are given an anchor point, may be more likely to be adherent to new therapies.

  • Availability (Salience) – People assess the probability of an outcome based on the ease with which they can imagine a given outcome rather the actual probability of 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. This heuristic implies that a person who has visualized or experienced an earthquake will be keener to buy earthquake insurance. However, it also implies that once the memory of the earthquake disappears, the effect on purchasing behavior will disappear as well.1 The same principle can be applied to adherence in vertigo-linked disease treatment: A patient who has recently had vertigo is likely to be more adherent to a treatment, but his adherence would decrease over time as symptoms and the memory of symptoms diminishes. 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 patients.4 
  • Representativeness – This heuristic also contributes to our perceived likelihood of an event, and it is often associated with stereotypes. For example, consider someone with a Master’s degree in anthropology who is passionate about environmental protection, a devoted feminist, and politically left-leaning. Of these two occupations, which would be presumed more likely for this person: working in an environmental charity or an accountant? Representativeness bias, a function of System 1, would suggest environmental charity worker as the first choice. However, there are far more accountants than employees of environmental charities, and statistics indicate that it is more likely this person is an accountant. Similarly, stereotypes inform expectations about how people in certain roles should behave. A farmer, for example, might be expected to be hard-working, outdoorsy, and tough, while the expectation for a librarian would be someone quiet, organized, and reserved.5  This heuristic could be particularly useful in our understanding of adherence. For example, in a study on pain management in arthritis, researchers provided conflicting information to patients on whether an arthritis medication should be taken with or without food. Several patients chose to take the drug with food because they perceived it as standard (representative) practice for them to take arthritis treatment with food.6 
  • Loss Aversion/Endowment – People generally feel worse about losing something than happy when they earn the same thing.1 For example, losing $100 is typically more painful in intensity than is the joy of being given $100. Richard Thaler uses 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 what price they would consider buying (or selling) the mug. The sellers of the mug valued it twice as much as the buyers. How can this heuristic be exploited in the case of adherence?  A physician can stress that every time medication is taken or the patient engages in positive behavior such as exercise, they are improving their health, and by abandoning such behaviors, they will be lose or detract from the progress they’ve made.
  • Optimism/Over-optimism – People tend to think that their assessment of a situation and subsequent actions are better than the others; roughly speaking, most people believe that they are above average.1 In his book, Nudge, Richard Thaler provides an example where people starting their own small businesses are asked two questions: 1. “What is the rate of success for businesses 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. A similar bias may be responsible for misconceptions that doctors have about their patients’ adherence: While they may acknowledge that adherence is a problem, they may be over-confident that their patients are among the adherent.7  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 about 10% less likely to achieve the desired adherence rates when compared to other patients.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 attitude and adherence to treatments for chronic diseases such as vertigo-linked disease. A thorough understanding of these heuristics is informative for physicians, hospital authorities, and practitioners to positively influence patient behavior.1 Future articles will discuss other behavioral theories and corresponding interventions for improving patient adherence. 

References

  1. Daniel Kahneman (2011). Thinking Fast and Slow. New York: Farrar, Straus, and Giroux. 
  2. Charitini Stavropoulou (2011). “Non-adherence to medication and doctor–patient relationship: Evidence from a European survey,” Patient Education and Counseling, (83):1, pp. 7–13. https://doi.org/10.1016/j.pec.2010.04.039
  3. Elias Oussedik, Leah A. Cardwell, & Nupur U. Patel (2017). “An anchoring-based intervention to increase patient willingness to use injectable medication in psoriasis,” JAMA Dermatology, (153):9, pp. 932–934. https://doi:10.1001/jamadermatol.2017.1271
  4. Sebastian Linnemayr & Chad Stecher (2015). “Behavioral economics matters for HIV research: The impact of behavioral biases on adherence to antiretrovirals (ARVs),” AIDS & Behavior, (19):11, pp. 2069–2075. https://doi: 10.1007/s10461-015-1076-0  
  5. Kendra Cherry (2019). “Representativeness heuristic and our judgments: Representativeness heuristic affects judgments but can lead to errors,” VeryWell Mind. https://www.verywellmind.com/representativeness-heuristic-2795805
  6. Emily Elstad, Delesha M. Carpenter, Robert F. Devellis, & Susan J. Blalock (2012). “Patient decision making in the face of conflicting medication information, International Journal of Qualitative Studies on Health and Well-being, (7):1, Article 18523. https://doi.org/10.3402/qhw.v7i0.18523
  7. M. Robin DiMatteo, Kelly B. Haskard-Zolnierek, & Leslie R. Martin (2011). “Improving patient adherence: A three-factor model to guide practice,” Health Psychology Review, (6):1, pp. 74–91. https://doi.org/10.1080/17437199.2010.537592