Health Risk Appraisal Research Paper

These various reasons suggest that it is important to understand how risk perceptions are formed, how accurate they are, and how they influence decisions and behavior. Furthermore, as research continues to identify new risks and ‘risk factors’ (attributes of individuals or environments that alter a person’s likelihood of harm), the need grows to explain this information clearly so that individuals can make better decisions about their health. Such education about risk is the goal of the specialty called ‘risk communication.’

2. Defining ‘Risk’ And ‘Risk Perceptions’

Before pursuing this topic it should be mentioned that the term ‘risk’ is used in several different ways. Sometimes ‘risk’ is used synonymously with the word ‘hazard’, denoting a specific undesirable outcome. In this sense, cancer, the common cold, and automobile accidents are all ‘risks.’ ‘Risk’ is also used as a synonym for ‘probability’, referring to the probability (or likelihood) of the undesirable outcome. Thus, one can speak of the risk that a person will develop cancer. ‘Risk’ is frequently used in still another way, as a synonym for ‘danger’ or ‘threat’ (for example, ‘How risky is smoking?’). The term ‘risk perceptions’, then, is a general term that refers to the various beliefs that people hold about health and safety hazards.

3. How Do People Think About Risk?

3.1 Dimensions Of Hazards

Hazards have many dimensions. According to classical theories of decision-making, the key attributes of a hazard are the probability that it will occur and the severity of the undesirable consequences should it occur.

Pioneering research by Lichtenstein et al. (1978) demonstrated that laypeople are also influenced by hazard attributes that are not so obviously important. When scientists are asked about the riskiness of different illnesses and technologies, their judgments strongly reflect the number of people who die annually from each one, thus reflecting both seriousness (deaths) and likelihood (number of events in a particular population). Lay judgments are only moderately related to the number of fatalities. In addition, laypeople respond to whether the risk is familiar or unfamiliar, manufactured or natural, voluntary or involuntary, and other factors. Summarizing the many attributes that influence risk perceptions, researchers have suggested that lay judgments of risk reflect two main dimensions, the extent to which the hazard is perceived to be known or unknown and the extent to which it is dreaded or not (Slovic 1987).

Leventhal and colleagues suggest that each person copes with illness threats in accord with their own ‘common sense’ model of that illness. These models involve five attributes: the identity of the risk, its time-course (e.g., chronic vs. acute), its consequences, its causes, and its potential cure or control (Leventhal et al. 1992).

The preceding perspectives emphasize various hazard attributes. Another approach emphasizes the interconnections among the hazard properties. Beliefs about the cause of an illness, its prevalence, routes of exposure, and personal risk are all important, but it is also important to know how they are related to one another. Misunderstandings about the causes and prevalence of hazard, for example, may result in misperceptions about the likelihood of victimization. These different aspects of knowledge and belief are viewed as a ‘mental model’ that describes both the separate pieces and the connections between these pieces (Bostrom et al. 1992).

3.2 Hazard Probabilities

Much attention has been given to how people think about hazard probabilities. (Apparently researchers think that hazard severity is a simpler issue, for this topic has received little attention.) Although proportions (e.g., ‘0.25’), percentages (e.g., ‘25 percent’), and odds (e.g., ‘1 in 4’) are the units used by scientists to measure probability, there is abundant evidence that laypeople have great difficulty understanding and using such information. For instance, people sometimes give a higher probability to the likelihood of dying of breast cancer than to the likelihood of developing breast cancer. Thus, the ability to recite the correct percentage, rate, or odds should not be used as the criterion to decide whether people truly understand the probability. Except for percentages given in weather forecasts, the public is rarely exposed to probability statistics, so it is not surprising that many people find numerical information about hazard probabilities unhelpful.

Some evidence indicates that people find verbal designations of probability (e.g., ‘small chance of happening’) to be easier to use and to better reflect their own views than numerical risk measures (Diefenbach and Weinstein 1993), but people vary greatly in the numbers they associate with particular verbal labels, making the conversion of numbers to words highly subjective. Expressions of probability in terms of odds (e.g., 1 in 50 chance) are especially disliked by laypeople.

Because it seems impossible to navigate an uncertain world without forming estimates of the likelihood that particular events will occur, we tend to assume that people must form and encode judgments of hazard probabilities. In fact, it is possible that people rarely do encode such information. Instead they may generate risk judgments from past experiences and from their own implicit theories as needed. It is also possible that people store in memory only very crude probability information (e.g., no chance, small chance, large chance, certain) and never use the finer distinctions that concern scientists and policy makers.

Because social comparison is a central feature of human existence, in everyday life people may find it more natural to make decisions on the basis of risk comparisons than on beliefs about absolute probability (the likelihood that an event will occur). Thus, a woman’s interest in preventing heart disease may depend less on her beliefs about her absolute likelihood of a heart attack (e.g., 40 percent chance) than on her belief that her risk is greater than the risk of her friends. She may also compare one risk (e.g., heart disease) with another (e.g., cancer).

4. Goals Of Risk Perceptions

Obviously, accurate risk perceptions can help people make appropriate decisions about actions to avoid illness or injury. However, accuracy is only one of the goals guiding people as they formulate their risk judgments (Kunda 1990). Risk perception is not an unbiased appraisal of information, but an attempt to seek the most comforting view of one’s personal vulnerability that fits within the bounds of the evidence. Beliefs about our vulnerability to harm can lead to positive or negative emotions (pleasure about successfully avoiding harm; anxiety about potential illness or disability). Perceptions of vulnerability can also affect our feelings of self-esteem. Since we want to believe that we are intelligent, competent, and foresighted, to admit that our actions place us at greater risk than our peers would be a threat to our self-esteem. Thus, minimizing negative affect and maximizing self-esteem are also goals of risk perceptions, and these goals may be at variance with the goal to be accurate.

5. Optimistic Bias

This bias in risk perceptions is revealed especially clearly when people are asked to compare their risks with the risk of the rest of the population. Whatever they may believe about the risk of others, they tend to believe that their own risk is less (Weinstein 1987). For example, when people are asked how their risk of a particular illness compares with the risk of others of the same age and sex, many claim to have below average risk and few admit to having above average risk. Across a variety of hazards, it is typical to find 40–70 percent of a group asserting below average risk; another 30–50 percent saying that their risk is average; and less than 10 percent acknowledging that their risk is above average. Obviously, this distribution cannot be correct. The ‘average’ person has, by definition, an ‘average’ risk. So when the people who claim below average risk greatly outnumber those who say their risk is higher than average, implying that the average person is below average in risk, something must be wrong with their risk judgments.

Optimistic bias is not just denial, a blanket defense against anxiety. If it were, we would expect to find the greatest optimism among hazards, such as cancer, that generate the most fear. The amount of optimistic bias (that is, the extent to which people claiming below average risk outnumber those who say their risk is above average) does vary from hazard to hazard (Weinstein 1987), but it is not related to the severity of the hazard. Instead it is greatest for events that are believed to be preventable by individual action and events with which people have little personal experience. Bias is especially great if people think that vulnerability appears early, leading them to conclude that if they have not experienced the problem so far, they are free from risk.

The belief that we are less at risk than others is apparently reassuring, since people resist attempts to correct their misperceptions. Most interventions designed to eliminate bias in comparative risk judgments—for example, having people think of the ways in which the negative event could happen or think of the precautions that they have not taken—have proved unsuccessful (Weinstein and Klein 1995).

It may appear obvious that underestimating risk will expose people to unnecessary harm. However, a different view of this issue, known by the label ‘positive illusions,’ suggests that optimistic biases are really adaptive (Taylor and Brown, 1988). It points out that people who are overly optimistic about their ability to fight off the AIDS virus, for example, may be encouraged to maintain a healthy lifestyle and to bear with burdensome treatments. Thus, even if the perception of resistance is false, it may support other actions that are themselves beneficial. Although definitive evidence is lacking, it seems likely that underestimations of personal vulnerability decrease interest in prevention, especially when people see themselves as members of a group that does not need to be concerned about the risk, but optimism about surviving a life-threatening illness can help patients avoid depression and hopelessness (Wood et al. 1985).

6. Effects Of Risk Perceptions On Health-Related Behaviors

Perceived probability and/or perceived severity occupy an important role in nearly all theories that are used to explain the health-related behavior of individuals. The literature on health behavior generally supports the idea that increases in perceived risk increase precautionary behavior (Janz and Becker 1984), but there are also numerous instances in which risk perceptions and behavior turn out to be unrelated.

This should not be surprising. There are many factors other than risk perceptions that influence behavior, and people who think that they have a high risk may nevertheless doubt their ability to carry out precautions or the efficacy of the precautions. In addition, most health behavior studies have used correlational research designs, which are problematic for examining risk perception–risk behavior linkages. Finally, as mentioned earlier, experimental interventions may fail to alter peoples’ perceptions of their invulnerability.

The link between perceptions and action may depend on the type of action. Precautions that prevent a health problem from occurring (such as vaccinations) should reduce both perceived risk and worry about that risk. In contrast, being tested for the presence of an existing health problem (as in cancer screening) offers the immediate potential of extremely distressing information, especially if the problem is difficult to treat, so high perceived risk may be associated with high fear. The links between risk perceptions and different types of action still need to be elucidated.

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