Behavioral Economics Matters for HIV Research: The Impact of Behavioral Biases on Adherence to Antiretrovirals (ARVs)

Abstract Behavioral economics (BE) has been used to study a number of health behaviors such as smoking and drug use, but there is little knowledge of how these insights relate to HIV prevention and care. We present novel evidence on the prevalence of the common behavioral decision-making errors of present-bias, overoptimism, and information salience among 155 Ugandan HIV patients, and analyze their association with subsequent medication adherence. 36 % of study participants are classified as present-biased, 21 % as overoptimistic, and 34 % as having salient HIV information. Patients displaying present-bias were 13 % points (p = 0.006) less likely to have adherence rates above 90 %, overoptimistic clients were 9 % points (p = 0.04) less likely, and those not having salient HIV information were 17 % points (p\0.001) less likely. These findings indicate that BE may be used to screen for future adherence problems and to better design and target interventions addressing these behavioral biases and the associated suboptimal adherence

The Importance of BE Biases for Chronic Health Behaviors We focus on three key behavioral biases that have been found to influence health behaviors for other chronic conditions [9] and that we hypothesize may also be important to components of ARV adherence:

Present-Bias A key behavioral bias is present-bias, which is the tendency of people to give into current temptation at the price of beneficial future outcomes [16]. For example, a seminal article by Benartzi found that people tend to delay the decision to save (e.g., to forego current consumption in exchange for future benefits) to a tomorrow that—when turning into today—is again pushed off [17]. Chronic HIV care management requires a similar decision, as health is conditional on daily pill-taking with immediate costs such as social stigma, side-effects, and financial costs. The benefits of optimal ARV adherence that include a healthier and longer life, on the other hand, manifest only in the distant future. We therefore hypothesize that patients displaying present-bias will display lower adherence, as they overly discount the future benefits of adherence and may see their actions guided mainly by its daily costs.
Overoptimism Being overly confident in one’s ability to stick to a planned behavior has been found to have important negative consequences for a wide range of behaviors [18]. For ARV adherence, this bias may manifest itself as patients not taking appropriate steps to assure their taking the medicine on time or not taking it at all; for example, most patients in our sample set phone alarms that subsequently prove insufficient to assure optimal adherence. We hypothesize that patients displaying overoptimism will show lower

Information Salience Behavioral economists have found that people act on the information that first comes to mind rather than on all the relevant information available [18]. This can lead to people being guided by relatively recent experiences, or those that were experienced by friends and that were particularly memorable. For example, people tend to buy earthquake insurance following an earthquake in their area, even though this occurrence does not change the underlying probability of an earthquake occurring [20]. We argue that HIV as a health threat may not be very salient (e.g., on top of their minds) for people living with HIV, in particular for those who have been on ARV for a number of years as is the case for the sample described below. Such patients often enjoy good health and no longer experience health improvements from taking their medication, therefore the benefits of ARV may become relatively invisible/less salient over time, leading them to fail to perceive adhering to the pill regimen as a priority. We expect that for patients who have received positive feedback on the ARV medication’s health benefits from peers at the HIV clinic this information is salient, leading to higher adherence.

Methods The data for this article come from the Rewarding Adherence Program (RAP) that uses variable rewards to improve ARV adherence and retention in care. The program attempts to reduce present-bias and increase information salience by providing small prizes allocated by a drawing at each clinic visit conditional on keeping scheduled clinic appointments (treatment group 1) and high ARV adherence measured by MEMS caps (treatment group 2). The study was implemented as a small randomized controlled trial (RCT) with about 50 participants in each of the two treatment groups and the control group, which received standard clinical care and answered the survey but did not take part in the prize drawings. RAP is currently being implemented at Mildmay Uganda, an NGO in the capital Kampala. At the time of enrollment into the RAP program, patients completed a baseline survey before being informed of their randomized treatment assignment and before they were exposed to the intervention. This survey consisted of 11 different modules measuring a variety of characteristics such as patient demographics, household characteristics, or community environment. BE biases were also collected as part of this baseline survey as described below, and form the basis for the analysis in this paper.

Eligible participants (18 years of age or older, taking ARVs for at least 2 years, having adherence problems (either self-reported or otherwise indicated in the medical records data) in the last 6 months, willing to follow and able to understand the study procedures) were asked to provide written consent in their preferred language (English or Luganda) that included the survey data collection and use of MEMS caps. RAP was approved by the HSPC Board at RAND (2012-0372), the IRB review board at Mildmay, and the Uganda National Science Counsel (UNCST).

Measurement of BE Biases
Present-Bias

The survey used the common method of asking clients to make a choice between hypothetical rewards that varied in size depending on the delay of payment [21]. The survey question stated: ‘‘Imagine you can win a lottery prize and have to choose between receiving 50,000 USh tomorrow, or 75,000 USh in one year. Which would you choose?’’. Respondents who chose the immediate reward rather than the more distant, larger reward were subsequently classified as present-biased. This method has been validated across many cultural settings [6], and this particular question was designed for a similarly, resource-poor environment [22]. Overoptimism

Respondents were asked to report the likelihood of forgetting at least one dose in the next month based on a four point Likert-type scale, and to make the same judgment about the likelihood of other clients at the clinic to measure overplacement. As displaying adherence problems in the 6 months preceding the survey was one of the enrollment criteria for the RAP intervention, we expected study participants to realize that on average they are likely to display lower adherence than most other clinic patients. Patients therefore were classified as overconfident if they assigned themselves a lower likelihood of forgetting pill doses relative to the other clients in the clinic.

Information Salience

Patients were asked whether they know people who have benefited from ARVs (as a reminder of the benefits of ARVs), and whether they have a close friend or family member who has died from AIDS (which would make the serious consequences of non-adherence more salient). We do not report results for the latter measure as the large majority of the sample (over 90 %) responded in the af- firmative, indicating the generalized nature of the HIV epidemic in Uganda.

Adherence Measures
Participants at baseline were provided with a MEMS cap that electronically records the date and time a pill bottle is opened, and were instructed to bring it with them for each clinic or study visit, at which point the adherence data were abstracted. Such an objective measure of adherence has been found to give a more accurate picture of adherence compared with self-reports that are easily manipulated and often overstated [23]. Objectively measuring adherence is particularly important in the current study where eligibility for participating in the prize drawing is conditional on high adherence (treatment group 2). Adherence so measured may differ from actual adherence if participants do not consistently use the caps, which we tried to control for by adjusting the measured adherence by self-reported pocketing or taking of medication from sources other than the MEMS cap. A second possible source of error in this measure is if people open the MEMS cap but do not actually swallow the pill. This would typically occur if people are trying to ‘game the system’. While we cannot control for this possibility, we can largely abstract from this problem for the control group and intervention group 1 as their eligibility in the lottery was not conditional on adherence but only on timely clinic visits.

MEMS data from the first 4 months of study participation are used to calculate the adherence outcome variable; we exclude the first month where we observe significantly higher adherence for all participants that is likely due to the novelty of being part of the study and focus our analysis on months two through four when we hypothesize that the novelty of using a MEMS cap would have worn off. Our main outcome variable is the fraction of clients displaying mean adherence of at least 90 %, where mean adherence is calculated as (# of actual bottle openings/# of prescribed bottle openings). While current regimens seem to be less forgiving than older ones [24], high and consistent adherence is certainly more conducive to viral suppression, and we therefore think that such a cut-off level is justified. Moreover, recent research has shown high risks for the development of disease resistant strains and advanced disease progression at mean adherence rates below 90 %

Patients who more heavily weigh the immediate costs of pill-taking than its future benefits are 13.4 % points less likely to attain mean adherence rates of at least 90 % (p = 0.006).

Overoptimism Participants who report being ‘very likely’ to fully adhere in the next month are 13.4 % points more likely to have mean adherence rates equal or above 90 % (p = 0.07). The 20.7 % of patients who believe that they are more likely to show optimal adherence relative to others (i.e. those displaying overplacement), have an 9.4 % points lower chance to display 90 % adherence (p = 0.11).

Information Salience 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 about the HIV medication from other patients (p = 0.001).

This paper presents first empirical evidence that BE can shed new light on ARV adherence behaviours

The finding that BE biases are common and are associated with subsequent ARV adherence supports the view of BE as a novel and low-cost way to screen for people in HIV care who are likely to show suboptimal adherence. We therefore encourage future research on the topic of BE biases and their impact on adherence using larger samples, using studies with the sole purpose of investigating the role of biases (i.e. not measuring biases as part of an intervention study), utilizing refined survey tools to detect biases, and using experiments in controlled settings to gain further insights.