HIV Cure Research: Risks Patients Expressed Willingness to Accept.

Despite doing well on antiretroviral therapy, many people living with HIV have expressed a willingness to accept substantial risks for an HIV cure. To date, few studies have assessed the specific quantitative maximal risk that future participants might take; probed whether, according to future participants, the risk can be offset by the benefits; and examined whether taking substantial risk is a reasonable decision. In this qualitative study, we interviewed 22 people living with HIV and used standard gamble methodology to assess the maximum chance of death a person would risk for an HIV cure. We probed participants' reasoning behind their risk-taking responses. Conventional inductive content analysis was used to categorize key themes regarding decision-making. We found that some people would be willing to risk even death for an HIV cure, and some of their reasons were plausible and went far beyond the health-related utility of an HIV cure. We contend that people's expressed willingness to take substantial risk for an HIV cure should not be dismissed out of hand.

Regulating impact on bystanders in clinical trials: An unsettled frontier.

This article informally reviews key research ethics guidelines and regulations, academic scholarship, and research studies and finds wide variety in how they consider risk to bystanders in medical research (namely, non-participants whom studies nevertheless place at risk). Some of these key sources give no or very little consideration to bystanders, while others offer them the utmost protection (greater than they offer study participants). This unsettled frontier would benefit from a deeper investigation of the ethics of protecting research bystanders.

The Need to Track Payment Incentives to Participate in HIV Research.

Providing incentives is an accepted and common practice in human subjects research, including clinical HIV research. While we know that financial incentives among similar studies can greatly vary, surprisingly little research exists on how to determine when such incentives are excessive or constitute an "undue inducement." Multiple factors, such as risks and benefits, study procedures, study budget, historical precedent, recommendations from institutional review boards, advice from other investigators, and local regulations may influence decisions about appropriate incentives, but little empirical data exist about what incentives are offered to potential research participants. Rules for acceptable gifts, services, and compensation should consider study location and population, but without a clearer understanding of currently offered incentives and how these practices match up to ethical beliefs of appropriateness, we continue to follow perceived trends without critical assessment. Here, we present one potential approach to explore the impact of financial incentives on biomedical HIV research and to further clarify undue inducement: the development of a framework to support ethical decision-making about payment to participate. This framework is based on input from people living with HIV, biomedical HIV researchers, ethicists, former study participants, and IRB members and includes a database that allows for tracking payment practices.

Ethical issues in HIV remission trials.

PURPOSE OF REVIEW: Several promising experimental pathways exist for long-term control of HIV in the absence of antiretroviral therapy (HIV 'remission') and are now being tested in early clinical studies. These studies can be invasive and pose a host of distinctive risks to participants, as well as to nonparticipants, especially to participants' fetuses, and sexual partners. RECENT FINDINGS: Ethical analyses of these studies have mainly focused on the risks to study participants. They recommend, and some investigators implement, procedures to mitigate risks for participants or to offset them with direct, indirect, and nonmedical benefits. They also suggest ways to keep participants' consent highly voluntary and informed. Rarely do ethicists propose keeping the social value of studies high. Of these recommended responses, only the latter, rarer proposals help address the risk to nonparticipants, as would some novel ways to address that risk. SUMMARY: HIV remission studies pose a number of ethical dilemmas. Many current investigative approaches put the participant at significant risk, but well established guidelines exist for mitigating this risk. Ethical issues that are not being fully addressed include risk to nonparticipants and the need to consider the societal value of studies, for example, their prospective impact on the global HIV burden. VIDEO ABSTRACT.

Animated randomness, avatars, movement, and personalization in risk graphics.

BACKGROUND: Risk communication involves conveying two inherently difficult concepts about the nature of risk: the underlying random distribution of outcomes and how a population-based proportion applies to an individual. OBJECTIVE: The objective of this study was to test whether 4 design factors in icon arrays-animated random dispersal of risk events, avatars to represent an individual, personalization (operationalized as choosing the avatar's color), and a moving avatar-might help convey randomness and how a given risk applies to an individual, thereby better aligning risk perceptions with risk estimates. METHODS: A diverse sample of 3630 adults with no previous heart disease or stroke completed an online nested factorial experiment in which they entered personal health data into a risk calculator that estimated 10-year risk of cardiovascular disease based on a robust and validated model. We randomly assigned them to view their results in 1 of 10 risk graphics that used different combinations of the 4 design factors. We measured participants' risk perceptions as our primary outcome, as well as behavioral intentions and recall of the risk estimate. We also assessed subjective numeracy, whether or not participants knew anyone who had died of cardiovascular causes, and whether or not they knew their blood pressure and cholesterol as potential moderators. RESULTS: Animated randomness was associated with better alignment between risk estimates and risk perceptions (F1,3576=6.12, P=.01); however, it also led to lower scores on healthy lifestyle intentions (F1,3572=11.1, P<.001). Using an avatar increased risk perceptions overall (F1,3576=4.61, P=.03) and most significantly increased risk perceptions among those who did not know a particular person who had experienced the grave outcomes of cardiovascular disease (F1,3576=5.88, P=.02). Using an avatar also better aligned actual risk estimates with intentions to see a doctor (F1,3556=6.38, P=.01). No design factors had main effects on recall, but animated randomness was associated with better recall for those at lower risk and worse recall for those at higher risk (F1,3544=7.06, P=.01). CONCLUSIONS: Animated randomness may help people better understand the random nature of risk. However, in the context of cardiovascular risk, such understanding may result in lower healthy lifestyle intentions. Therefore, whether or not to display randomness may depend on whether one's goal is to persuade or to inform. Avatars show promise for helping people grasp how population-based statistics map to an individual case.

Blocks, ovals, or people? Icon type affects risk perceptions and recall of pictographs.

BACKGROUND: Research has demonstrated that icon arrays (also called "pictographs") are an effective method of communicating risk statistics and appear particularly useful to less numerate and less graphically literate people. Yet research is very limited regarding whether icon type affects how people interpret and remember these graphs. METHODS: 1502 people age 35-75 from a demographically diverse online panel completed a cardiovascular risk calculator based on Framingham data using their actual age, weight, and other health data. Participants received their risk estimate in an icon array graphic that used 1 of 6 types of icons: rectangular blocks, filled ovals, smile/frown faces, an outline of a person's head and shoulders, male/female "restroom" person icons (gender matched), or actual head-and-shoulder photographs of people of varied races (gender matched). In each icon array, blue icons represented cardiovascular events and gray icons represented those who would not experience an event. We measured perceived risk magnitude, approximate recall, and opinions about the icon arrays, as well as subjective numeracy and an abbreviated measure of graphical literacy. RESULTS: Risk recall was significantly higher with more anthropomorphic icons (restroom icons, head outlines, and photos) than with other icon types, and participants rated restroom icons as most preferred. However, while restroom icons resulted in the highest correlations between perceived and actual risk among more numerate/graphically literate participants, they performed no better than other icon types among less numerate/graphically literate participants. CONCLUSIONS: Icon type influences both risk perceptions and risk recall, with restroom icons in particular resulting in improved outcomes. However, optimal icon types may depend on numeracy and/or graphical literacy skills.

Belief in numbers: When and why women disbelieve tailored breast cancer risk statistics.

OBJECTIVE: To examine when and why women disbelieve tailored information about their risk of developing breast cancer. METHODS: 690 women participated in an online program to learn about medications that can reduce the risk of breast cancer. The program presented tailored information about each woman's personal breast cancer risk. Half of women were told how their risk numbers were calculated, whereas the rest were not. Later, they were asked whether they believed that the program was personalized, and whether they believed their risk numbers. If a woman did not believe her risk numbers, she was asked to explain why. RESULTS: Beliefs that the program was personalized were enhanced by explaining the risk calculation methods in more detail. Nonetheless, nearly 20% of women did not believe their personalized risk numbers. The most common reason for rejecting the risk estimate was a belief that it did not fully account for personal and family history. CONCLUSIONS: The benefits of tailored risk statistics may be attenuated by a tendency for people to be skeptical that these risk estimates apply to them personally. PRACTICE IMPLICATIONS: Decision aids may provide risk information that is not accepted by patients, but addressing the patients' personal circumstances may lead to greater acceptance.