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Perceived Susceptibility


Perceived susceptibility, also called perceived vulnerability, refers to one's perception of the risk or the chances of contracting a health disease or condition (Witte, 1992). It also can include estimates of resusceptibility and susceptibility to illness in general (Rosenstock, Strecher, & Becker, 1994).

Perceived susceptibility is a central concept in several fear appeals health information processing models, including the Health Belief Model (Becker, 1974; Rosenstock, 1974; Rosenstock, Strecher, & Becker, 1994), parallel response model (Leventhal, 1970), Protection Motivation Theory (Rogers, 1975, 1983) and the Extended Parallel Process Model (Witte, 1992, 1998).

Perceived susceptibility combined with perceived severity combine to form a perceived threat (Witte, 1992), which may influence how people process health information and how motivated they are to engage in a particular behavior. Susceptibility information can be a feature within a health message (e.g., Ronis, 1992) usually in the form of percentages or odds of contracting some illness or condition. More frequently, susceptibility is measured as a person's perception of the likelihood of developing an illness.

In Protection Motivation Theory (PMT, Rogers, 1983) susceptibility is part of a first appraisal (threat) after exposure to a fear appeal message. If perceived susceptibility and perceived severity are judged to be high, then a person will engage in a second appraisal (coping) by appraising both self and response efficacy. If both efficacy appraisals are judged to be sufficiently high, then a person will be motivated to reduce the threat (by adopting message recommendations). If one or both of the efficacy appraisals are unsatisfactorily high, then the individual will be motivated to reduce the fear [within the message] by different strategies such as message derogation and message avoidance.

The literature on measuring susceptibility suggests two conceptual supplements or options. The first suggests a researcher specify an adaptive or risk behavior in conjunction with the susceptibility measure. For example, Ronis (1992) included behavioral anchors in his measures (If you smoked, how likely do you think it is that you will get lung cancer). The second suggests using behavioral indicators for grouping purposes. Several studies (e.g., Gunther, Bolt, Borzekowski, Liebhart, & Dillard, 2006; Unger, Cruz, Schuster, Flora, & Johnson, 2001) measured "smoking status" as a way to assess a person's susceptibility to smoking. This second approach is conceptually distinct from "perceived susceptibility" because it measures behavior rather than relying on a person's judgment about the odds of developing a disease. Some examples of each type of measure are offered below.

Suggested Measures

A simple, adaptable, and short index was created by Witte, Cameron, McKeon, & Berkowitz (1996). The generic nature of the items in the index may reduce its predictive utility within a particular disease or behavioral context. In this study, Witte et al. administered the scale as part of a Risk Behavior Diagnosis Scale to 179 college students about genital warts. They obtained a Cronbach's α = .85.

  1. I am at risk of getting (health threat).
  2. I am at risk of getting (health threat).
  3. It is possible that I will contract (health threat).

The researchers used 5-point scales anchored by strongly agree to strongly disagree.

Champion (1984) developed a 6-item index to assess perceived susceptibility of breast cancer (Cronbach's α = .78). Although the following scale is multidimensional, it is moderately reliable as a single index. Please note this scale includes an item (#5) that measures anxiety about getting breast cancer rather than the chances/possibility/likelihood of contracting it. The scale adds a prediction (#6). Based on the factor loadings Champion obtained, it is possible that the reliability of the index would increase if items 5 and/or 6 were eliminated, but this is an unresolved empirical question.

  1. My chances of getting breast cancer are great.
  2. My physical health makes it more likely that I will get breast cancer.
  3. I feel that my chances of getting breast cancer in the future are good.
  4. There is a good possibility that I will get breast cancer.
  5. I worry a lot about getting breast cancer.
  6. Within the next year I will get breast cancer.

The researchers used 5-point scales anchored by strongly agree to strongly disagree.

Greene, Rubin, Hale, & Walters (1996) measured perceived susceptibility with three items specifically designed for an HIV/AIDS context (Cronbach's α = .73) on a Likert-type scale (not reported).

  1. I worry that I might catch AIDS.
  2. AIDS is a big concern to me.
  3. AIDS is not as big a problem as the media suggests (reverse coded).

Ronis (1992) noted that it is important to consider conditional susceptibility versus unconditional susceptibility. Unconditional susceptibility is reflected in items that do not anchor the perception with a behavior, such as the examples above. Conditional susceptibility includes in the measure a conditional behavior of the form, "If you did X, how likely do you think you would get Y?" For example, the perceived susceptibility of developing lung cancer for a person who does not smoke is probably lower than a person who smokes. However, perceived susceptibility of a non-smoker would likely increase if the measure included smoking as a conditional behavior, and could be measured along the lines of, "If you smoked, how likely do you think it is that you would get lung cancer?" In the case of gum disease, Ronis argued it is important to distinguish between how susceptible to a disease a person thinks he or she would be if the same person was or was not able to take preventive actions. Items below could be measured on a 5-point scale anchored by "very unlikely" to "very likely".

Unconditional (α = .86)

  1. How likely do you think it is that you will develop gum disease during the next year?
  2. How likely do you think it is that you will develop gum disease during the next five years?

Conditional A (α = .93)

  1. If you brush and floss your teeth daily, how likely do you think it is that you will develop gum disease during the next year?
  2. If you brush and floss your teeth daily, how likely do you think it is that you will develop gum disease during the next five years?

Conditional B (α = .89)

  1. If you brush your teeth daily, but do not floss daily, how likely do you think it is that you will develop gum disease during the next year?"
  2. If you brush your teeth daily, but do not floss daily, how likely do you think it is that you will develop gum disease during the next five years?

Please note the Conditional A measure includes two preventative behaviors and the Conditional B measure includes only one. These represent an experimental manipulation and illustrate different ways perceived susceptibility has been measured.

Rationale for Selection

These items were chosen because they represent a wide range of contexts in which perceived susceptibility has been reliably measured. They provide a flavor of the types of items that are typically used in current research, and they can be adapted to a particular health context under study.


Alphas for perceived susceptibility tend to have a broad range in the literature depending on the unique context of a study and the particular health threat considered. The items selected as examples here have a range (e.g., .73 to .93).

Use of Measure (with examples)

Rimal & Morrison (2006) measured perceived susceptibility by asking participants the extent to which 15 risk events were likely to occur. Responses were recorded on a 7-point scale, ranging from "much below average" to "much above average." Susceptibility indexes were then calculated as the average of responses to the 15 health events (not reported; Cronbach's α = .86 for perceived susceptibility of risk events on self). They found participants self-assigned the lowest susceptibility ratings, followed by greater ratings to a similar referent, and the greatest ratings to a negative referent.

Umphrey (2003) measured perceived susceptibility for testicular cancer with items that were adapted from Banks et al. (1995). The index consisted of the average of three 5-point Likert items anchored by "strongly agree" and "strongly disagree": 1) It is likely that I will get testicular cancer, 2) It is possible that I will contract testicular cancer, and 3) I am highly susceptible to testicular cancer. The pre-test alpha was .69; the post-test alpha was .72. Umphrey found loss frame messages produced greater testicular cancer perceived susceptibility than gain frame messages.

Green & Brinn (2003) assessed perceived susceptibility to skin cancer and sun damage with an eight-item index (only two items reported, α = .74). They found perceived susceptibility to skin cancer varied as a function of the type of evidence provided in messages (statistical vs. narrative).

Several scholars adopted or adapted a susceptibility to smoking index based on measures developed and tested by Pierce and his colleagues (Pierce, Choi, & Gilpin, 1996; Pierce, Choi, Gilpin, Farkas, & Berry, 1998). For example, Gunther, Bolt, Borzekowski, Liebhart, & Dillard (2006) measured smoking susceptibility with a scale based on Pierce et al.'s classification scheme. They surveyed 818 sixth- and seventh graders in two Wisconsin middle schools and classified participants into four levels: nonsusceptible never-smokers, susceptible never-smokers, experimenters, and established smokers. They found perceived peer smoking prevalence, exposure to pro-smoking media content, and attitudes about smoking positively predicted smoking susceptibility.

Miller et al. (2006) assessed susceptibility to smoking with two measures of a participant's resolve not to smoke. Their items came from the four-item scheme developed by Pierce, et al. (1996, 1998): 1) Do you think you might smoke a cigarette soon? and 2) If one of your best friends offered you a cigarette, do you think you might smoke it? Both items were measured on a 4-point response scale anchored by 1 (definitely yes) and 4 (definitely no), and included "refused" and "don't know" options. Participants were classified as nonsusceptible if they responded "definitely no" on both items; otherwise, they were classified as susceptible. Miller et al. obtained a Cronbach's alpha of 0.88 for these two items. The found increased psychological reactance was significantly associated with increased susceptibility.

Ungar et al. (2001) grouped respondents into four stages of smoking initiation: never smokers, susceptible, experimenters, and established smokers. Although their classification scheme is similar to one described by Pierce et al. (1994), Ungar et. al. created separate categories for the respondents who had ever tried smoking (experimenters and established smokers) and those who had not (never smokers and susceptible). They found perceived pervasiveness of pro-tobacco marketing was highest among established smokers and was the lowest for susceptibles. The never smokers and experimenters were in between.

Range of Items Used

The range of items varies substantially in the literature. Several studies use single-item measures to index perceived susceptibility. For example, Dutta and Feng (2007) asked respondents, "How often do you worry about getting cancer?" Responses were measured on a 4-point scale, with 1 representing "rarely or never" and 4 representing "all the time."

In contrast, Weinstein (2000) assessed the perceived susceptibility of 201 events, each with a single 10-point rating scale anchored by "no chance" to "certain to happen" for events such as allergies to bananas, skin cancer, etc. Roberto, Zimmerman, Carlyle, Abner, Cupp, & Hansen (2007) measured perceived susceptibility toward pregnancy, STDs, and HIV were each measured with one 5-point Likert-type item, such as "What would you say your chances of getting the AIDS virus are?" Champion's (1984) index on perceived susceptibility of getting breast cancer was the most extensive found (6 items) that focused on a single health threat.

Additional Commentary

While the ability of perceived susceptibility to predict health behaviors seem to result in mixed findings, Rosenstock, Strecher, & Becker (1994) explain the methods used to measure perceived susceptibility may be a key reason. Rosenstock note some measures include a behavioral "anchor" -- where respondents are asked about their perceived likelihood of contracting a certain illness if they behave in a particular way. For example, responses of the perceived susceptibility of non-smokers to contract lung cancer would likely be much lower than if respondents were asked about their likelihood to contract lung disease if they smoked.

Instead, Ronis (1992) and others (e.g., Halpern-Felsher, Millstein, Ellen, Adler, Tschann, & Biehl, 2001; Gerrard & Luus, 1995) suggest perceived susceptibility measures include conditional behaviors-either action or inaction. For instance, Ronis found perceived benefits and behavior were more accurately predicted by conditional than by unconditional measures of health threats (both perceived susceptibility and perceived severity), especially in survey data about flossing and gum disease. The unconditional susceptibility measure had little predictive value on behavior. These findings parallel and extend those from Ronis and Harel's (1989) study of breast cancer screening behaviors.


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