The contemporary ubiquity of notions of risk has been well-documented across literatures, including anthropology. Mary Douglas has noted that the ways in which people understand this central concept has changed and shifted (Douglas and Wildavsky 1982
; Douglas 1985
; Douglas 1990
). Risk was initially a value-neutral construct reflecting raw probability that became associated with consequences then increasingly connoting only adverse consequences. For example, the socket of the lamp on my desk reads: WARNING, Risk of Fire, Use Only Type A, 150 Watt Lamp(s) Maximum. In the clinical domain, risk refers mainly to possible morbidity or mortality, “adverse events” or side-effects, and is also used as a marker of attributes as in “risk factors.”
That risk has become an almost ubiquitous notion is not to say that there is agreement or specificity within this common-sense
construct. Past studies have sought to ascertain how lay people translate verbal descriptors of probability -- always, usually, likely, less common, occasionally, small chance, rare, never: terms commonly used in clinical conversation and written communication -- into numerical quantities. On examination, we find that patients do not agree about the numerical meaning of such words and, in fact, each word elicits a wide range of interpretations (Sutherland, Lockwood et al. 1991
). Perception of risk is also subject to bias that results from heuristic thinking. First, heuristics are pragmatic cognitive short-cuts formed on the basis of past experience, or in the case of cancer, the prior absence of a cancer experience in an individual's life (Finucane, Alhakami et al. 2000
). Second, cancer is perceived as a catastrophic hazard, a condition that is difficult for an individual to estimate accurately and that triggers our cognitive efforts to cope by asserting a sense of control over this uncertain possibility (Kahneman, Slovic et al. 1982
). Thus, fear of cancer can produce a range of reactions in different people, ranging from outright denial to action-oriented compensation like care-seeking, or improved adherence or compliance (Consedine, Magai et al. 2004
; Carpenter 2005
). What is not clear is how earlier awareness (that creates fear) acts to prime sensitivity to risk. Proximity to such a vivid hazard, however, such as cases of cancer in family, friends or co-workers, may impact that sense of perceived risk. Proximity increases salience and would impact awareness as an earlier exposure. And indeed, some studies indicate that having a female relative with breast cancer reduces nearly two-fold the likelihood of respondents to estimate themselves at lower risk than other women (Facione 2002). This type of finding becomes increasingly important in light of the range of lay knowledge and attitudes about familial (inherited) cancer, both actual and perceived.
For example, in the course of fieldwork in an unrelated pilot study into the cancer care delivery system in North Texas, I recently encountered a middle-aged man that I'll call Jorge.ii
Jorge had no personal experience of serious disease, but lived with a complicated history of minor ailments that he seemed to manage well despite depending on relatives to compensate for continuously unstable employment. When he talked with me at the bus stop outside of the county hospital, Jorge was mulling over a clinician's comment about colorectal cancer screening.
Jorge: well, I used to think you can't worry about something you can't do nothing about…. But my brother-in-law, he had cancer. They told him last year. He died, you know…. They treated it [with chemo] but it moved fast…. I don't know; it's all a mystery to me.
Over the few exchanges we had, I learned that Jorge was worried because he had not thought about something as serious as cancer before. He juggled a lot of other concerns that were more pressing. But the conversation with his clinician about routine colorectal screening had become a source of worry because Jorge's brother-in-law had been diagnosed with lung cancer the prior year. Though recognizing these were somehow different diseases, Jorge perceives now perceives cancer to be more salient in a way it had not been before – again, suggesting the availability heuristic (Kahneman and Tversky 1973
). The offer to screen re-personalized an awareness of cancer risk made proximate by the death of his in-law.
Perceived risk is strongly affected by proximity in the case of purported “cancer clusters”, though in this instance, operating at the level of community. The persistent belief in “cancer clusters” demonstrates how the uptake of risk information depends on the social context in which the information is communicated. Perceived cases draw attention to a locale and beg for a common explanation, but the public often disregards disease heterogeneity, how common many cancers are, and often do not understand the effects of random chance and correlative factors as well as the retrospective nature of cluster identification (Benowitz 2008
). Similarly, when notions of risk are propagated through simple percentage point estimates (e.g. 7% risk) without additional explanation of how such a number was generated, public health recommendations and programs concentrate the locus of risk at the level of the individual cum decision-maker. This not only obscures the multi-causal complexity of carcinogenesis, it renders opaque the broader context through which risk information is filtered.
Earlier studies have raised the possibility that there are context effects, for example, variation in the clinical setting, or indeed in certain types of medical conditions, that influence how both lay individuals and physicians assign numerical meaning to verbal descriptors (Mapes 1979
; Sutherland, Lockwood et al. 1991
). The point of thinking about the meaning that people ascribe to notions of risk is to improve our grasp of how such understandings shape what people do with respect to preventing cancer. The concept of “risk factors” most commonly presupposes a differentiation (who has them, who doesn't) between who is at risk, which is short-hand for a comparative assessment of defined groups of individuals. In this sense, risk depends on probabilities that are only possible because they are derived from collectives, or populations (Spasoff and McDowell 1987
; Hayes 1992
). Let us consider how, then, an individual applies information to make sense of “risk of cancer” that might shape decisions to engage in preventive screening.
Cancer registries permit an epidemiology that produces excellent population risk estimates, and the surveying and statistical calculations secure generalizability. However, at an individual level, inference is still founded on correlation not causation in determining the risk of a particular mail-carrier, whom we'll call Ms. Angeline, for developing colorectal cancer. Most people have difficulty contending with the uncertainty implicit in concepts of risk and the numerical meaning of risk estimates. A cancer event in the life of Ms. Angeline is still actually dichotomous: either she develops dysplasia or she does not.iii
In this lies the crux of the problem when we engage individuals through risk estimation models. Objective probability does not apply to an individual thinking about risk for a single event. Objective probability only emerges from repeatable events, either in time (by a single individual) or a space (across a population of such individuals) – people do not necessarily understand this in these terms but we see that they reflect this problem when they correctly explain a 10% risk of cancer as “one in ten” but also wonder whether or not they are “one of those ten people” (Han, Lehman et al. 2009
). Lay people were very willing to engage second-order risk, a dual understanding of risk. For example, in our focus group discussion, Angeline understood an estimate to express both the proportion of an event offering in a given population (frequentist) and a degree of confidence about the future occurrence of an event (Bayesian):
Q: Why do you think that's low, Angeline?
Angeline: It's low; I don't know how to explain it. But 9% of 100 would be 9 people out of 100; so you would be one of the 9 possibly. But I don't know the answer. That's why I said it appears to me that you have a slight chance.
The earlier example of the salience dynamic exemplified by Jorge's new concern reacting to his brother-in-law's death is further complicated by findings from a research team in Bristol conducted among first-degree relatives suggesting that families to explain away risk even within a family history of cancer with appeals to lifestyle differences and other behavioral traits (Sanders, Campbell et al. 2003
). Thus, though familial proximity can create salience that influences the availability heuristic, additional defense mechanisms can encourage exception-seeking that our focus groups suggest accompanies lay people's cognitive efforts to interpret numerical estimates. Angeline's comments, then, are not only about conceptualizing probability but that interpretation may also be interacting with how a given probability relates to an individual. For example, Owen explains:
Owen: It's a matter of getting so much data that you don't have to, that it automatically breaks down. Jones is a 67-year-old, you know, black male who stopped smoking 10 years ago. Well, there were thousands of other 67-year-old black males who live next door to Dave who stopped smoking 10 years ago. There are enough of them in the sample, if there are enough of them in the sampling, you come up with stats where I don't think you have to worry about being so narrow, where I think on the contrary it has been so wide that it automatically limits to that particular type person, that particular individual. He's got these characteristics. History shows everybody of that same type over the last 50 years that we have records, of those 9% developed colon cancer. …. It's not just demographics, it's the number of demographics. Just make it narrow so that you make sure I'm in this group, and don't include a bunch of people who have nothing to do with my life. I don't do that [lifestyle behavior], I don't do that [lifestyle behavior], I don't do that [lifestyle behavior].
Most people don't see risk as a neutral statistical statement but think of risk as indicating danger and emotional threat. To most of us, cancer risk is not about mathematical probability but is about concrete, if not immediately tangible, risk factors. Thus, in many cases, the possibility (risk) of something happening (outcome) derives some of its meaning from whether or not there is anything Jorge or Ms. Angeline can do about it. That is, assessment depends on whether the risk factor is modifiable like diet or exercise, or non-modifiable like particular family history or, perhaps, race. As we saw in our focus groups, the salience of a proffered risk estimate depends on the relevance of the explanatory model that Ms. Angeline understands produced that estimate. If she determines she shares risk factors with that model, that is, if she perceives the source of risk as similar to actual factors active in her world, then the risk estimate gains significance. Put another way, if she imagines the “population” used to model the estimate as having things in common with her, Angeline is more likely to perceive the estimate as “true” (Han, Lehman et al. 2009
Anthropologists and sociologists have thought a great deal about the sick role (Parsons 1951), the emergence of a patient identity and, increasingly, its relation to notions of risk and susceptibility. Some scholars have proposed that the idea of being “at risk” creates an intermediate identity between healthy and sick, that is the not-yet-sick or not-yet-patient. When we think about the role of disease surveillance in the lived experience of people trying to understand their personal relationship to cancer risk, we have to recognize the dynamic between individual psychological and affective perception of cognitive notions of risk and the ways in which that inchoate risk has very concrete implications for individual behaviors and social systems of care (Joseph, Burke et al. 2009
). In our own studies, similarly, we saw respondents like Owen deploying contextual variables in his efforts to volunteer exceptions that might exempt them from the hypothetical risk estimate proffered to lay focus groups (Han, Klein et al. 2009
; Han, Lehman et al. 2009
). Similarly, Fred and Mike argue about the relative applicability of the estimate based on a population that might or might not be like him, as follows:
Facilitator: This is your [estimate], this isn't everybody's. This is yours.
Fred: No, no, no, no. Because this study is going to give a percentage of people over 50. I'm one of those. So that's not me.
Mike: Yes, it is.
Fred: Yeah, it is to a degree, but my mindset is that it's not me because I escaped that, from other tests. I've had tests. I know I fall within that range. I am within that range, I'm in that population that is capable of having it.
Taken together, such data reminds us that risk information is rarely taken up as value-neutral objective truth, but rather risk information is deeply subjective, interiorized against a pre-existing sense of self. This might range from broad psychological characteristics like the general way in which we perceive newness or change as threat, or how we process any new information to roles shaped by social positionality: “I am a caretaker not someone people take care of”; “I am the decider, I need to act and lead”; “I'm not sure; my wife makes these kinds of decisions”(Washington, Burke et al. 2009
). These phrases are loose colloquialisms but we might think further about how social expectations set up behavioral character conditions. The introduction of new risk information then either aligns with that conditioned response or ruptures it.
A study in Britain serves as a good example for elucidating this dynamic in the context of the health care delivery system. The study examined individuals who had been referred to a British regional cancer genetics service to receive a risk assessment by either their general practitioner or a secondary care physician (Scott, Prior et al. 2005
). In Britain, the result of the risk assessment serves a triage function: only “high” and some “moderate” risk individuals go on to gain face-to-face consultations with clinical geneticists and possibly additional screening services.
As Scott and colleagues argue, the cancer genetics testing service seems to serve as a mediating agent between the anticipation of becoming-patients and the expectation of attention and services from the healthcare system. Their more challenging observation, however, is that those individuals who suspected themselves as being at high risk for inheritable cancer prior to clinical assessment are dissatisfied, almost disappointed, upon learning that their estimate revealed them to be at only low or moderate risk. The researchers interpret this to reflect the individual's efforts to redefine herself within the purview of the healthcare system. They suggest the dissatisfaction is a result of the common desire to assert control in the face of uncertainty/new information, in that addressing perceived risk of heritable cancer creates the expected claim on perceptual resources to address that risk. The notion of being “at risk” is received against a pre-existing expectation, the authors argue, that it would be, in effect, helpful to be “at risk” because that would elicit special attention in the form of referral to a specialist. Thus, the risk of cancer itself is also interpreted through a larger, pre-existing framework in which British people recognize their need to advocate for care within the bureaucracy of NHS or to increase personal vigilance to compensate for a system that doesn't perceive their risk as warranted. Moreover, the technological imperative is increasingly acculturated – not only are risk estimates available but health and medical care services are now often re-organized to support the application of risk estimation, as cost-benefit data is used to rationalize available services, whether or not any individual actually chooses to act on this new risk information (Aronowitz 2009
Larger structural differences like the nature of health systems, then, also contribute to the social context within which an individual is exposed to risk information. In the absence of organized structured universal system, as in the US, screening falls in a social realm of “choice” where screening policy takes the form of recommendations to physicians and may influence insurance reimbursement designs. Of course, a screening procedure for cancer is not given involuntarily in either societal setting but universal systems routinize education thus affecting awareness, as well as increasing access and uptake generally than more market-driven situations.
The different ways that “risk” is perceived or interpreted highlight the significance of lay theorizing about both cause and effect. As we think about surveillance as a structural vehicle that instantiates ideas about risk in policy, it is all the more crucial to recognize that “risk” is not an independent construct but a perceptual process by which we interpret information through already-operating understandings of our life-world. We actively form the meanings of abstractions like risk through our standing priorities and our broader moral geographies, both informed by the emotional valence we attribute to them (Moscovici 1984
). In this way, health information about risk is caught up in pre-existing frameworks of good/bad, danger/safety or clean/dirty and the other various layers of contrast and opposition a society uses to organize our mental schema (Douglas 2002
; Pasick, Barker et al. 2009
To further develop the contribution of affect or emotion to how people relate to risk information would engage a much larger literature than is possible here (Halpern and Little 2008
). Suffice to set out a broad continuum of possible cognitive sets. If Ms. Angeline were facing “news” of her risk of cancer, she might hold an unwavering conviction that she would develop the disease, making her unresponsive to appreciating downsides of screening (finding a polyp or dysplasia requiring a treatment regimen) etc. Such unwavering conviction in the outcome can be contrasted with a fixation on the good outcome, without any understanding of the likelihood of that outcome. What is often easily framed as optimism is, phenomenologically, a much more complex and idiosyncratic amalgam of hope, fear, denial (Van Ness 2001
). Each of these tangents is refracted through implications Ms. Angeline has drawn from the initial presentation of the risk construct, say, at her annual check-up with her primary care physician.
Clearly, this complexity is a function of compartmentalization, if you will -- selective “spotlighting on the theatre stage” of individual awareness. Generally, compartmentalizing is a useful coping mechanism that enables an individual to get on with daily functioning in an environment of constant flux and shifting information by imposing an algorithm that lets him parse the flow of sensory data down to actionable units. It is not clear, in this sense, whether people's emotions actually incapacitate their ability to understand risk/evidence (prevention) or actively help them avoid understanding (protection, as in denial) or actively re-align their values such that understanding is irrelevant because another issue takes precedence (pre-emption) (see also (Halpern and Arnold 2008
). In any case, risk information is mediated by this set of mental mechanisms that may well be automatic but which nonetheless depend on the particular situation of a given individual at the time that risk information is introduced. However, to the extent that all three response constructs (prevention, protection, pre-emption) engage aspects of uncertain futures and accompanying notions of risk, this complexity can inform how we think through the dynamic relationship between individual risk perception, future uncertainty, and population-level screening for cancer.