Tài liệu tâm lý học sức khỏe: Các hành vi nguy cơ sức khỏe

44 Subjective Risk and Health Protective Behavior: Cancer Screening and Cancer Prevention Leona S Aiken Mary A Gerend Arizona State University Kristina M Jackson University of Missouri This chapter explores the role of perceived risk in health protective behavior Cancer serves as the context of the presentation; the discussion employs the literature on cancer screening and prevention to highlight theory and findings on the perception of risk in relation to health behavior The origins of perceived risk, its role in health behavior models, and the linkages between perceived risk and behavior are explored In models of health behavior, perceived risk for disease is the motivational engine for health protective action This chapter is intended to serve two purposes: to provide both a broad picture of the literature on risk perception in health psychology and to characterize research on perceived risk for cancer as a putative determinant of cancer screening and preventive behavior CHAPTER OVERVIEW The chapter first addresses the role of perceived susceptibility in models of health behavior It then turns to perceived risk as a construct, its measurement, its observed relation to objective risk for cancer, and its determinants It next explores the relation of perceived susceptibility and cancer distress to cancer screening and cancer preventive behavior Here it considers not only the susceptibility-behavior link, but also explores other variables that may moderate or even mitigate the impact of perceived susceptibility on specific cancer protective behaviors The chapter then considers interventions to increase screening and preventive behavior that involve the perceived susceptibility construct The emphasis is on the use of mediational analysis to assess the direct and indirect impact of perceived susceptibility on screening and preventive behavior Finally, it explores a number of issues that arise in consideration of how perceived susceptibility impacts health protective behavior CANCER PREVALENCE Cancer is a feared disease of high prevalence By age 59, over 8% of men and 9% of women will have developed an invasive cancer; from birth to death, these percentages rise to 47% of men and 38% of women (Landis, Murray, Bolden, & Wingo, 1998) Cancer is the second leading cause of death (23% of all deaths) behind heart disease (32%) among adults in the United States In all, 1.23 million new cases of cancer and over 564,800 cancer deaths are expected in the United States in 1998 (Landis et al., 1998) SCREENING AND PREVENTIVE RECOMMENDATIONS The public is inundated with information about cancer and with recommendations for cancer screening and prevention -727As of 1998, the American Cancer Society recommended extensive cancer screening (American Cancer Society, 1998) Screening recommendations include an annual mammogram for women age 40 and older; colon and rectal screening with fecal occult blood test (FOBT) annually, plus flexible sigmoidoscopy every years for men and women over age 50; annual prostate-specific antigen (PSA) blood test and digital rectal examination (DRE) for men age 50 and older; annual pelvic examinations for all women age 18 and older, with annual Pap tests until at least three negative Pap tests have been achieved, and then less frequent Pap tests; and endometrial screening for women at high risk for uterine cancer (American Cancer Society, 1998) Regular self-examinations are also recommended, including skin self-examination (American Academy of Dermatology, 1994; National Cancer Institute, 1995), breast self-examination (BSE) for all women beginning at age 20 (American Cancer Society, 1998), and testicular selfexamination for men (National Cancer Institute, 1992) (See also the screening recommendations of the U.S Preventive Services Task Force, 1996.) Beyond screening are recommendations for cancer prevention through lifestyle modification, including skin protection (American Cancer Society, 1997b) and diet (American Cancer Society, 1996) SCREENING UTILIZATION IN THE UNITED STATES According to the National Health Interview Surveys of 1987, 1992, and 1994, a population-based national survey of 40,000 households (American Cancer Society, 1997a; National Center for Health Statistics, 1996), the percentage of women age 50 and over who have had a mammogram in the past years rose from 25% to 56% between 1987 and 1994 These rates were similar for Black and Hispanic women (56% and 50%, respectively, in 1994, up from 19% and 18%, respectively, in 1987), although rates lagged for low income women (38% in 1994) and those with less than a high school education (42%) Rates for Pap test utilization (within the past years) achieved 77% in 1994 (74% for Hispanic women), again lagging behind for low education women (62%) As of 1992, about a third of the population had had one of three colorectal screening tests, DRE within the past year, FOBT within the past years, or a sigmoidoscopy at least once OPENLY AIRED CANCER DEBATES Epidemiological findings make the news, and the public hears a relentless array, often contradictory, of associations between behaviors and cancer (Taubes, 1995) Medical debates about the efficacy of screening for mortality reduction are publicly aired (Aiken, Jackson, & Lapin, 1998) The debate on the efficacy of mammography screening for women under age 50 raged in the public media for most of this decade (Aiken et al., 1998) Prostate screening currently is occasioning considerable debate, along the lines of the previous mammography debate (Albertsen, 1996; E S Wolfe & W W Wolfe, 1997) Increasingly, laypersons are asked by their physicians to decide whether they wish to be screened, with the argument that patient choice must be preserved (Woolf & Lawrence, 1997) Issues concerning appropriate screening are aired against a backdrop of economic constraints posed by the health care industry CLASSES OF CANCER PROTECTIVE BEHAVIORS For the exploration of perceived risk and behavior, cancer protective behaviors must be divided into two broad categories- screening for early detection versus prevention Screening behaviors may further be divided into those that are medically based (e.g., mammography) versus those that involve self- examination (e.g., BSE) This distinction is important because the barriers to screening are expected to be very different for the two categories These barriers may interact with or obscure the role of perceived risk A similar argument can be made for specific preventive behaviors Although the discussion draws on literature on a variety of cancers, medically based screening is exemplified with mammography, self-screening with BSE, and preventive behavior with skin protection PERCEIVED RISK IN MODELS OF HEALTH BEHAVIOR This section is devoted to an overview of the role of perceived risk in models of health protective behavior Health psychology is rich in models of the putative determinants of health protective behavior At the core of essentially all these models is the concept of perceived risk-the extent to which individuals believe that they are subject to a health threat (Becker, 1990; Gerrard, Gibbons, & Bushman, 1996; Kowalewski, Henson, & Longshore, 1997; van der Pligt, 1998; Weinstein, 1993) Health psychology draws on a theoretically based literature in risk perception and its determinants (Kahneman & Tversky, 1973; Kasperson et al., 1988; Slavic, 1987; Tversky & Kahneman, 1974) Formal models of risk (Kasperson et al., 1988) postulate that risk is a joint function of the probability of occurrence of a negative event, and the magnitude of its consequences; risk is the product of these factors Literature applying perceptions of risk to health behavior is less precise The term perceived risk, as well as the terms perceived susceptibility and perceived vulnerability are used interchangeably for measures of the subjective likelihood of contracting a disease, absent any consideration of severity Consistent with application in health, the terms perceived risk, used here to refer to subjective estimates of the likelihood of personally contracting a disease, and not the combination of likelihood and consequences Perceived severity is used here to refer to perceptions of disease consequences independent of likelihood According to Weinstein (1993), models of health behavior assume that the motivation for health protective behavior stems from anticipation of some negative health outcome coupled with hope of avoiding the outcome Anticipation of a negative outcome involves foremost the perception that one is -728personally susceptible to some disease; for strong health motivation to be achieved, this perception must be coupled with the anticipation that the disease consequences are severe (Weinstein, 1993) Our particular interest in this chapter is the linkage of perceived susceptibility to health protective behavior A theoretical context for this linkage is provided by consideration of the way in which perceived susceptibility is used in models of health protective behavior Three widely applicable models of health behavior, the health belief model (HBM; Becker $I Maiman, 1975; Rosenstock, 1966; 1974a, 1974b, 1990), protection motivation theory (PMT; Prentice-Dunn & Rogers, 1986; Rogers, 1975,1983), and the precaution adoption process model (PAPM; Weinstein, 1988) employ the perceived susceptibility construct as a driving force in health protective behavior Perceived risk appears as well in the transtheoretical model of change (TTM; Prochaska, DiClemente, & Norcross, 1992), and the recently proposed cognitive-social health information processing (C-SHIP) model (S M Miller, Shoda, & Hurley, 1996) Perceived risk is also implicit in the theory of reasoned action (TRA; Ajzen & Fishbein, 1980; Fishbein & Ajzen, 1975) and its extension, the theory of planned behavior (Ajzen, 1991), as well as subjective expected utility theory (Ronis, 1992; Weinstein, 1993), as they are applied to health behavior Although perceived susceptibility is consistently cast as the motivating engine for health protective behavior, the specific role of perceived susceptibility and assumptions about how it combines with other constructs vary in informative ways across models A brief characterization of the role of the perceived susceptibility construct in several well-established models of health behavior and the newer C-SHIP model is provided A characterization of the complete health models is beyond the scope of this chapter; Conner and Norman (1996); Glanz, Lewis, and Rimer (1990); Weinstein (1993); and Weinstein, Rothman, and Sutton (1998) provided explications of these and other models; Conner and Norman (1996) provided extensive reviews of literature employing these models as well Curry and Emmons (1994) provided a thorough summary of applications of the HBM, TRA, and the TTM to breast cancer screening Perceived Susceptibility as Motivator: Health Belief Model The health belief model (HBM) traces its origins to problems encountered in the U.S Public Health Service nearly half a century ago-problems of failures of usymptomatic individuals to undergo screening tests or to engage in preventive health behaviors (Rosenstock, 1966, 1974a; 1990) Ironically, the health belief model is still being applied to the same issues, which are abundant in the area of cancer prevention and early detection The HBM states that individuals will undertake a health action to the extent that they believe themselves to be susceptible to a health threat (perceivedsusceptibilio), believe that the consequences of the disease are serious berceived severity or seriousness), believe that the proposed health action will offer protection against the health threat (perceived benefits), and believe that barriers to performing the health action can be overcome (perceived barriers) Finally, individuals must receive some trigger, or cue, in order to act (cue to action) Interestingly, in current interventions to increase cancer screening, a reminder letter (a cue to action) is a common component (e.g., Bastani, Marcus, Maxwell, Das, & Y an, 1994) Physicians' recommendations for screening have been conceptualized as a cue to action as well (Fox, Siu, & Stein, 1994) Perceived susceptibility is, in a sense, the centerpiece of the HBM There are two aspects to perceived susceptibility: the individuals' belief that contracting a disease is a realistic possibility for themselves, and the individuals' belief that they may have the disease in the complete absence of symptoms (Rosenstock, 1990) Failure to utilize cancer screening tests may be attributed to a lack of belief that pathology can exist in the absence of symptoms (Rosenstock, 1990) Perceived susceptibility and perceived severity combine to form perceived threat, a determinant of the likelihood of adopting a health action; this combination closely reflects the formal definition of risk (Kasperson et al., 1988) provided earlier The HBM is silent on the nature of the combinatorial rules for the constructs; in most applications of the health belief model, simple additive effects of the constructs have been explored., The interplay of perceived threat with perceived benefits is important for cancer screening, in that high risk individuals, although they perceive heightened vulnerability, may avoid seeking screening if they believe that cancer treatment cannot save them (e.g., Lerman & M D Schwartz, 1993, for breast cancer; M D Schwartz, Lerman, Daly, et al., 1995, for ovarian cancer) Ronis (1992) suggested a combinatorial rule for HBM constructs in which perceived susceptibility and severity are necessary precursors to the perception of benefits of health action, a characterization on which we draw in our later discussion of interventions The health belief model has made sustained contributions as a heuristic for the study of psychosocial correlates of preventive health behavior (See reviews by Harrison, Mullen, & Green, 1992; Janz & Becker, 1984; and Sheeran & Abraham, 1996.) Typically, the perceived barriers construct has been the strongest correlate of lack of protective behavior, whereas perceived susceptibility has typically exhibited low to moderate positive correlations with protective behavior Whereas perceived susceptibility is expected to combine with perceived severity to motivate health protective behavior, perceived severity by itself rarely correlates with preventive behavior or screening behavior (Janz 8z Becker, 1984; Harrison et al., 1992) This is certainly true for cancer research: Perceived severity has failed to show predictive utility and has not been amenable to change via intervention, as cancer apparently is seen as uniformly serious (Champion, 1994; Curry & Emmons, 1994; Rimer, 1990; but see Ronis & Harel, 1989, for an exception) Researchers often forgo the measurement of perceived severity in characterizing the HBM for cancerrelated behavior (e.g., Hyman, Baker, Ephraim, Moadel, & Philip, 1994; Vernon, Myers, & Tilley, 1997) Thus, perceived susceptibility by itself, rather than the combination of susceptibility -729and severity, is de facto characterized as the motivating force for cancer protective behavior Fear Amusing Comnmn;cat;on, Percehed Susceptibiky, and Behavior: Protection Motivation Theory Perceived susceptibility also plays a central role as a motivator of health protective behavior in PMT, a model that arose from consideration of the impact of fear arousing communication on the adoption of health protective behavior (Beck & Frankel, 198 1; Rogers, 1975) As in the HBM, perceptions of susceptibility and severity that resulted from fear communications were expected to combine with perceptions of the existence of an effective health protective behavior to arouse protection mot&- tion, which in turn led to intentions to adopt the protective health behavior (Rogers, 1975) In the revised form of PMT (Rogers, 1983; Prentice-Dunn & Rogers, 1986), a special motivating role for perceived susceptibility coupled with perceived severity was provided, that of lowering the probability of a maladaptive response (e.g., delay in seeking treatment for suspected cancer symptoms, persistence in behaviors that put one at increased cancer risk) Rippetoe and Rogers (1987) applied PMT to an experimental investigation of breast selfexamination How Perceptions of Susceptibility Accrue: The Precaution Adoption Process Model Models of health behavior assume that in order for perceived susceptibility to act as a motivational force, perceptions of susceptibility must be personal (i.e., individuals must feel that they, themselves, are vulnerable) Weinstein (1988) proposed the precaution adoption process (PAPM) as a stage model of the adoption of health behavior In general, stage models (Weinstein et al., 1998) characterize individuals as falling into a series of ordered categories with regard to adoption of a health behavior In PAPM, these stages move from lack of awareness of the health issue (Stage I) through health behavior maintenance (Stage 7) Consistent with this stage structure, beliefs about perceived susceptibility are assumed to develop in a series of cumulative stages First, individuals are assumed to become aware of a health hazard (awareness), then to believe in the likelihood of the hazard for others (general susceptibility), and finally to acknowledge their own personal vulnerability (personal susceptibility) Personal susceptibility is assumed to be critical in the decision to take precautionary action (Weinstein et al., 1998) Assessment of discrepancies between general susceptibility versus personal susceptibility has uncovered optimistic biases (Weinstein, 1980) about people's vulnerability; these biases are discussed later The PAPM has been applied to home testing for radon gas, which is an environmental cancer threat (Weinstein & Sandman, 1992) The Growth of Perceived Suscept&&y and the Process of Adopting Health Behaviors: Transtheoretical Model of Change The TTM, as the PAPM, is a stage model of health behavior adoption (Prochaska et al., 1992) Progress through the first two stages is hypothesized to be driven by the growth of awareness of perceived susceptibility from precontemplation, of vulnerability to a health threat, to contemplation, in which there is an awareness of one's own vulnerability to a health threat but no commitment to health action Although the transtheoretical model was initially applied to smoking cessation as a cancer preventive action, the model has now been applied to cancer screening as well For example, Lipkus, Rimer, and Strigo (1996), Rakowski et al (1992), and Siegler, Feaganes, and Rimer (1995) applied this model to mammography screening Cognitive-Social Health Information Processing The C-SHIP model (S M Miller et al., 1996) is a comprehensive model of the genesis and maintenance of health-protective behavior, initially expounded in the context of the complex sustained behavior of breast self-examination (BSE) The model considers five classes of determinants of health behavior that incorporate both cognitions and affect Among these, two classes address issues of perceived susceptibility: health-relevant encodings, including health risks and vulnerabilities, plus attentional strategies for gathering versus avoiding health relevant information; and health beliefs and expectancies, including how vulnerabilities, such as genetic predisposition, impact subjective likelihood of disease development The model specifies how information about objective risk and resultant perceptions of susceptibility interact with emotions associated with receiving health information, with health goals, and with self-regulation in producing health behaviors That the model addresses the interplay of emotion with cognitions about people's vulnerability is important for an understanding of cancer screening behavior among high risk individuals; this issue is discussed later Perceived Susceptibility as a Predisposing Factor in Complex Hybrid Models of Health Behavior Adoption Within this decade, a number of authors have proposed extensive integrative frameworks of the putative determinants of health protective behavior, which have been employed in the design of interventions to increase health behavior Four such frameworks are summarized in Curry and Emmons (1994) Each framework specifies a complex causal chain of variables that ultimately leads to health behavior Most important for our consideration is the fact that perceived susceptibility is included as a predisposing factor for health behavior adoption early in the causal chain, a factor that may facilitate overcoming barriers to the health protective behavior (McBride, Curry, Taplin, Anderman, & Grothaus, 1993) and lead to receptiveness to health promotion interventions (the PRECEDE-PROCEED model of Green & Kreuter, 199 1) -730- Summary: Perceived Susceptibility as a Predisposing Factor for Health Behavior Adoption Not surprisingly, models of health behavior have matured and increased in complexity Early models have been augmented with new variables, for example, the addition of self-efficacy for health behavior to both the HBM (Rosenstock, Strecher, & Becker, 1988) and PMT (Rogers, 1983) New stage models have viewed health behavior adoption as dynamic, in part driven by perceived susceptibility The interplay of susceptibility cognitions with emotion has been elucidated Hybrid models have incorporated a complex network of environmental and medical system variables along with individual cognitions, including perceived susceptibility The evolution of these models has clarified the role of perceived susceptibility as a potentially powerful predisposing factor at the outset of the process of adoption of health behaviors, a factor that motivates this process of adoption Drawing on this evolution of health behavior models, we conceptualize perceived susceptibility to disease as a distal construct in a mediational chain of constructs that eventuates in protective health behavior PERCEIVED SUSCEPTIBILITY: MEASUREMENT AND DETERMINANTS This section first considers approaches to the measurement of perceived susceptibility It then reviews comparisons of objective risk for cancer with subjective risk, raising the question of whether individuals overestimate or underestimate their cancer risk relative to objective risk Finally, it explores the putative determinants of perceived susceptibility, drawing on both a broad literature on determinants of risk, and a cancer-specific literature Measurement of Perceived Susceptibility Alternative approaches to the measurement of perceived susceptibility lead to varying pictures of personal perceptions of risk for developing cancer Two broad classes of measures are absolute measures, in which personal ratings are made without reference to any outside group, and comparative measures, in which personal perceived susceptibility is compared to susceptibility in some normative group (Weinstein 8z Klein, 1996) Absolute Measures Rating Scales Among absolute measures, typical rating scales ask individuals for Likert scale judgments of their likelihood of developing cancer-for example, “What you think are the chances that you personally will get breast cancer someday” (5-point scale; Bastani, Marcus, & Hollatz-Brown, 1991) These are the most commonly used measures of perceived susceptibility, employed both in studies of the psychosocial correlates of health protective behavior and in evaluations of interventions Numerical Estimates Numerical estimates of the chance of contracting cancer are also taken as absolute indicators of perceived susceptibility-for example, “Risk of developing breast cancer in the next 10 years” (c I%, l–5%, 640%, l–20% or > 20%; Dolan, Lee, & McDermott, 1997) Perceived risk has also been measured with rate judgments -for example, “the number of women out of 1000 whom you think would develop breast cancer in the next 10 years” (Black, Nease, 8z Tosteson, 1995; see also L M Schwartz, Woloshin, Black, & Welch, 1997) Such measures have enjoyed relatively limited application, most often in studies comparing perceived to objective risk Comparative Risk Direct cumparative risk is measured with some form of the following question: “What you believe are your chances of getting (disease) compared to other (men/women) your own age?', with typical responses of “a lot lower, somewhat lower, about the same, somewhat higher, and a lot higher.” This measure has been applied to cancer in general (Kreuter & Strecher, 1995); lung cancer, skin cancer, and cancer in general (Weinstein, 1987); breast cancer (e.g., Aiken, Fenaughty, West, Johnson, & Luckett, 1995); and colorectal cancer (e.g., Blalock, DeVellis, comparative risk is assessed by having individuals rate the perceived likelihood of developing the disease for themselves and for others on separate scales; the difference between these two ratings reflects comparative risk (Weinstein & Klein, 1996) Measure of comparative risk are sometimes used in combination with absolute rating scales in the formation of multi-item susceptibility measures However, the two most common applications of comparative risk items have been in research on optimistic bias (e.g., Weinstein, 1980) and in studies of individual attributions of risk (e.g., Aiken et al., 1995) Direct comparative risk items provide risk estimates only in relation to others; thus, the specification of the comparison group is critical An individual who felt quite vulnerable to a disease, when measured on an absolute rating scale, might nonetheless feel less at risk than more unfortunate others (Klein & Weinstein, 1997), yielding a comparative rating of relatively low comparative risk Perceived Susceptibility Versus Cancer Worry and Cancer Distress Perceived susceptibility has been distinguished from more emotional aspects of vulnerability in studies of cancer-related health behaviors, consistent with the C-SHIP model Items such as “Thinking about breast cancer makes me feel upset and frightened” (McCaul, Schroeder, & Reid, 1996) have been used to characterize cancer worry, as distinct from perceived susceptibility Sjiiberg versus perceived risk reflect emotional versus cognitive reactions to threat, respectively The two variables are weakly correlated (e.g., r =.20; McCaul et al., 1996) and form independent factors in the measurement of predictors of colorectal cancer screening adherence (Vernon et al., 1997) In addition -731to worry, fear of cancer and cancer treatment (Berman & Wandersman, 1992; Salazar & de Moor, 1995), cancer anxiety (Gram & Slenker, 1992), and morbid concern about breast cancer (Irwig et al., 1991) also have been included in research A growing literature on breast and ovarian cancer screening among high risk women (e.g., Audrain et al., 1998; M D Schwartz, Taylor, et al., 1999) has employed such measures of cancerspecific distress Perceived Vulnerability to Cancer and Objective Risk Comparisons of Objective and Subjective Risk A number of approaches have been taken to the comparison of objective with subjective risk for cancer Objective risk measures are of two types First are rates of risk in thepopulcation (e.g., the percent of women in the population ever contracting breast cancer) Second are risk estimates derived for specific individuals, based on their particular status on known risk factors; derivation of these latter estimates employs epidemiological models of risk Subjective measures are numerical estimates of risk, or rating scale measures of absolute or comparative risk Population Estimates When determined from actual versus estimated population rates, community samples overestimate their probability of developing and dying of cancer (e.g., Helzlsouer, Ford, Hayward, Midzenski, & Perry, 1994, for cancer in general; Ward, Hughes, Hirst, & Winchester, 1997, for prostate cancer) Epidemiological Estimates and Individual Assessments Individuals' risk estimates based on epidemiological models have been compared with their own subjective numerical risk estimates The Gail model (Gail et al., 1989), a five-factor epidemiological model of breast cancer risk among Caucasian women, predicts risk for breast cancer among women who obtain annual mammograms Risk factors include number of first-degree relatives (mother or sisters) with breast cancer, age at menarche, age at first live birth, number of previous biopsies and chronological age Using this model, Black et al (1995) and Dolan et al (1997) found that women grossly overestimate their chances of developing breast cancer, for example, by a factor of 20 in women under age 50 (Black et al., 1995) Subjective and objective estimates correlate moderately (for example, r =.46 for breast cancer in a sample of women under age 50; Siegler et al., 1995) Those at heightened cancer risk due to their being first- degree relatives (FDRs) of individuals with cancer also overestimate their personal risk More than 60% of FDRs greatly overestimated their lifetime risk of breast cancer as compared to Gail estimates (Lerman et al., 1995) Among FIN&, specific Gail model risk components were found to be unrelated to numerical ratings (0%100%) of the chance of getting breast cancer someday (Daly et al., 1996) Comparative Risk Ratings Versus Epidemiological Estimates A number of investigations have compared an epidemiological estimate of risk with a direct measure of comparative risk Such studies provide a very different picture of the relation of objective to subjective risk, depending on the disease Individuals are optimistic (i.e., underestimate their risk) for heart attack within the next 10 years (Avis, Smith, & McKinlay, 1989; Kreuter & Strecher, 1995), but overestimate their risk of cancer in this time frame, with almost half of individuals showing pessimistic bias (Kreuter & Strecher, 1995) Comparative Risk and Unrealistic Optimism While people overestimate their absolute risk of contracting cancer, studies of comparative risk suggest that individuals exhibit unrealistic optimism or optimistic bias (Weinstein, 1980, 1987; Weinstein 8z Klein, 1996); that is, they believe they are less likely to contract specific cancers than are others their own age This bias has been demonstrated for breast cancer (Aiken et al., 1995), skin cancer (A J Miller, Ashton, McHoskey, & Gimbel, 1990), and colorectal cancer (Blalock et al., 1990; Lipkus, Rimer, Lyna, et al., 1996), as well as brain cancer, leukaemia, and lung cancer (Lek & Bishop, 1995) In contrast, comparative judgments of “cancer in general” not yield optimistic bias (Weinstein, 1980, 1984), even when “cancer in general” and specific cancers are rated by the same sample (Weinstein, 1982, 1987) FDRs of women with breast cancer accurately estimate their comparative risk as high when asked to compare their risk to women without a family history of breast cancer (Audrain et al., 1995; Lerman, Kash, & Stefanek, 1994) However, when asked to compare their risk to others their own age, with family history unspecified, a substantial portion of FDRs incorrectly rate their risk as lower than average (Aiken et al., 1995; Blalock et al., 1990) Whereas much effort has been made to untangle the sources of optimistic bias and risk perceptions in general, the behavioral implications of the optimistic bias for protective behavior are unclear (van der Pligt, 1998; Weinstein & Klein, 1996), and have not been addressed in the context of cancer Van der Pligt (1996) argued that comparative risk appraisal may not be a determinant of health behavior and does not contribute to the prediction of health behavior beyond perceived vulnerability Determinants of Perceived Risk for Cancer Two literatures inform the question of the determinants of perceived risk for cancer The first, cancer-specific literature examines individuals' rationales for their ratings of their own risk of cancer relative to others their own age, following a methodology first employed by Weinstein (1984) The second is a broader literature on the determinants of risk Determinants of Comparative Risk for Cancer Weinstein (1984) coded the reasons generated by individuals for their comparative risk judgments into five categories: -732actions and behavior patterns, heredity, physiology or physical attributes, environment, and psychological attributes For cancer in general, breast cancer (Aiken et al., 1995; Lipkus, Rimer, & Strigo, 1996; Salazar, 1994), and colorectal cancer (Blalock et al., 1990; Lipkus, Rimer, Lyna, et al., 1996), personal lifestyle-related actions were seen as decreasing risk (e.g., proper diet, exercise) For lung cancer, personal actions (smoking) were seen as increasing risk (Lek & Bishop, 1995) Across cancers, attributions for heredity were that the absence of disease in the family reduced risk below average In contrast, women who believed their risk to be above average for breast cancer mentioned heredity most often as the determining factor (Aiken et al., 1995; McCaul & O'Donnell, 1998; Savage & Clarke, 1996) Of interest is that FDRs of colorectal cancer patients rarely mentioned heredity as increasing their risk, even after they had been informed they were at increased risk due to their sibling's cancer (Blalock et al., 1990) These results taken together suggest that individuals believe they have some control over whether they get cancer through their own actions However, there is lack of understanding of the role of heredity in cancer Absence of family history is viewed as highly protective, even though most cancers are not associated with family history At the same time, a family history of cancer may not lead to perceptions of increased risk General Determinants of Perceived Risk Van der Pligt (1996,1998) summarized an extensive literature on the determinants of perceived risk Classes of determinants include cognitive heuristics, disease characteristics, personal motivations, and personality and information- processing strategies (Gerend, 1998) (See Fischhoff, Bostrom, & Quadrel, 1993, for a discussion of risk perception and communication.) Cognitive Heuristics Individuals rely on cognitive heuristics in estimating uncertain events (Kahneman & Tversky, 1973; Tversky & Kahneman, 1973,1974), and these heuristics may underlie inaccurate perceptions of risk in the health domain The availability heuristic (Tversky & Kahneman, 1973) indicates that individuals base frequency estimates on the salience of the event in question, or the ease with which the event comes to mind Personal experience with other individuals who have cancer (Wardle, 1995), coupled with the extensive media coverage of cancer, may contribute to the observed overestimates of cancer risk (Slavic, Fischhoff, & Lichtenstein, 1979; van der Pligt, 1998) The representativeness heuristic (Kahneman & Tversky, 1973) indicates that individuals base likelihood estimates for a hypothetical event (e.g., a personal diagnosis of breast cancer) on their similarity to events with comparable characteristics (e.g., the individual's similarity to others diagnosed with breast cancer) Characteristics of the Health Threat Bias in perceptions of comparative risk has been hypothesized to depend on disease characteristics (Weinstein, 1984,1987; Weinstein & Klein, 1996) Harris (1996) and Weinstein (1987) provided support for a direct relation between the perceived controllability or preventability of a disease and optimistic bias concerning risk; that is, the more controllable or preventable a disease was perceived to be, the greater the optimistic bias Evidence of a relation of optimistic bias with disease heritability is lacking (Weinstein, 1982) The “absentlexempt” principle (e.g., “If I haven't gotten the disease by now, I won't get it”; Weinstein, 1987) is associated with lower perceived risk with increasing age (e.g., Aiken, West, Woodward, & Reno, 1994, for breast cancer), although cancer incidence increases with age, Maintenance of Self-Esteem Optimistic biases for perceived personal risk have in part been attributed to a motivation to protect oneself from feelings of distress or anxiety about future negative events (e.g., Perloff, 1983) This protection may accrue from downward social comparisons, that is, comparisons of one's own risk with the risk of others who are actually more vulnerable (Klein, 1996; Klein & Weinstein, 1997; Perloff & Fetzer, 1986) Personality Characteristics and Modes of Information Processing A variety of personality dimensions have been associated with perceived risk Among them are monitoring blunting (M D Schwartz, Lerman, S Miller, Daly, & Masny, 1995), psychological defense (Dziokonski & Weber, 1977; Paulhus, Fridhandler, & Hayes, 1997), anxiety (MacLeod, Williams, & Berekian, 1991), and neuroticism (Darvill & Johnson, 1991) This may explain linkages noted between personality factors and breast screening behavior (Siegler et al., 1995) reviewed by Siegler and Costa (1994) PERCEIVED SUSCEPTIBILITY AND CANCER RELATED BEHAVIOR This section considers the relations of perceived susceptibility to both screening for early detection of cancer and cancer preventive behavior A critical issue for health psychology is the implication of perceptions of susceptibility for protective behavior As we have already indicated, we conceptualize perceived susceptibility to disease as a distal construct in a mediational chain of constructs that eventuates in health behavior Relations of perceived susceptibility to behavior are likely to be complex, to be mediated, moderated, or nullified by other determinants of the particular behavior in question, determinants that are explored in the discussion of perceived susceptibility and protective behavior Given space limitations, this chapter does not provide a comprehensive review, but it does reference and summarize existing reviews and highlight important themes (see RoyakSchaler, Stanton, & Danoff-Burg, 1997, for related work) Perceived Susceptibility, Distress, and Screening Accuracy of Self-Report of Screening Behavior Studies of screening behavior often rely on self-report of screening Several reports suggest approximately 95% accuracy -733for self-reports of having had a mammogram when compared to clinic records (Aiken, West, Woodward, Reno, & Reynolds, 1994; Degnan et al., 1992; Etzi, Lane, & Grimson, 1994; King, Rimer, Track, Balshem, & Engstrom, 1990; Rimer et al., 1992) Correct recollection of whether a mammogram occurred within the past year or years appears somewhat lower (73% accuracy; Degnan et al., 1992) Self-report accuracy is lower for screening tests that occur during the course of physician examination, for example, 61% verification of Pap smears against laboratory records (Bowman, SansonFisher, & Redman, 1997), and very low verification rates for digital rectal examination (DRE) and fecal occult blood test (FOBT) against medical charts (Lipkus, Rimer, Lyna et al., 1996) Finally, self-reports of breast selfexamination (BSE) may overestimate actual performance (Alagna, Morokoff, Bevett, & Reddy, 1987) Perceived Susceptibility and Mammography Screening McCaul, Branstetter, Schroeder, and Glasgow (1996) provided an extensive meta-analysis of the relation between breast cancer risk and mammography screening The weighted average correlation between family history and screening was r =.27, with only one article reporting a nonsignificant negative correlation For perceived vulnerability and screening, the average weighted correlation was a somewhat lower, r =.16, with a stronger relationship evidenced in cross-sectional (r =.19) than in prospective designs (I =.lO) Higher screening likelihood was noted among women who had breast problems, r =.30 Worry about breast cancer was positively associated with screening, r =.14 The positive relation of perceived susceptibility to screening has been confirmed in more recent studies (Cole, Bryant, McDermott, Sorrell, & Flynn, 1997; Lauver, Nabholz, Scott, & Tak, 1997; Lipkus, Rimer, & Strigo, 1996) Perceived susceptibility is not a proxy for family history, and predicts screening compliance above and beyond family history (Aiken, West, Woodward, & Reno, 1994) As we have argued, the relation of perceived susceptibility to screening has been found to be moderated by other psychosocial variables Aiken, West, Woodward, and Reno (1994) found that susceptibility related to compliance with mammography screening only when perceived barriers to screening were low; under high perceived barriers, no such relation was observed Medical System and Demographic Determinants of Screening ***domain provides documentation of medical system determinants of the use of medically based cancer screening tests The impact of health care coverage (e.g., Potosky, Breen, Graubard, & Parsons, 1998) and, moreover, continuity of care, (e.g., O'Malley, Mandelblatt, Gold, Cagney, & Kerner, 1997), have been documented This literature further reflects the impact of demographic variables on screening utilization, among them race (e.g., Frazier, Jiles, & Mayberry, 1996; Paskett, Rushing, D'Agostino, & Tatum, 1997; Pearlman, Rakowski, Ehrich, & Clark, 1996), acculturation among minority women (Kaplan et al., 1996), and age (Caplan & Haynes, 1996; M E Costanza, 1992) in interaction with race (Fox & Roetzheim, 1994) These variables set limits on the impact of psychosocial variables on screening utilization Perceived Susceptibility and Breast Self-Exumination (BSE) Evaluation of the relation of perceived vulnerability to BSE performance takes into account not only the frequency of BSE performance relative to the recommended monthly schedule (American Cancer Society, 1998), but also the adequacy of BSE performance (see review by Zapka & Mamon, 1986) S M Miller et al (1996), Savage and Clarke (1996), and Aiken et al (1995) all pointed out the mixture of positive and null results for the relation of perceived vulnerability to BSE frequency When relations of vulnerability to BSE frequency are found, they are modest, ranging from 14 to.25 (S M Miller et al., 1996) The balanced mix of positive and null results yields a lower average correlation across studies Interestingly, perceived susceptibility relates to thoroughness and accuracy of BSE performance (Fletcher, Morgan, O'Malley, Earp, & Degnan, 1989; Wyper, 1990) However, across studies, the perceived barriers construct (including such factors as large breast size, difficulty of performing BSE, lack of expertise in BSE; Salazar, 1994) dominates as the strongest predictor of BSE frequency within the HBM framework, with correlations approaching -.5 (Wyper, 1990) Strong barriers may override perceptions of susceptibility in influencing performance versus nonperformance of BSE Self-Eficucy and Screening As would be expected for a self-screening behavior, self- efficacy or self-confidence in the ability to adequately perform BSE is correlated strongly with BSE frequency (e.g., Alagna et al., 1987; Champion,' 1991; Rutledge & Davis, 1988; Sortet & Banks, 1997; see reviews by S M Miller et al., 1996, and Salazar, 1994) This relation has been found both retrospectively and prospectively Similarly, the importance of self-efficacy has also been demonstrated for testicular self-examination (Brubaker & Wickersham, 1990) Few, Worry, Cancer Distress, and Screening Behavior In both the general population and in FDRs of individuals with cancer, fear of cancer, worry about cancer, and cancer distress have been associated with both insufficient and excessive screening, thus providing a plethora of conflicting results across studies General Population McCaul and colleagues (McCaul, Reid, Rathge, & Martinson, 1996; McCaul, Schroeder, & Reid, 1996) found a positive relation of breast cancer worry to mammography screening in the general population, as did Ward et al (1997) for prostate cancer However, -734in an inner-city population, an inverted U-shaped relation was observed: Moderate worry about breast cancer was associated with greater attendance at a first mammography screening than was either extreme (Sutton, Bickler, Sancho-Aldridge, & Saidi, 1994) The same inverted U-shaped relation was observed between BSE frequency and breast cancer worries (Lerman et al., 1991) Among older low income Mexican American women, fear of and fatalism about cancer were associated with lower Pap smear rates (Suarez, Roche, Nichols, & Simpson, 1997) Worry appears to serve as a barrier to mammography among African American women (Friedmanet al., 1995) Again in a sample with a substantial inner-city component, Bastani et al (1994) reported a strong negative association between fear of finding breast cancer and screening This brief sampling of articles suggests possible demographic differences in the relation of emotional aspects of cancer threat on screening, with cancer worry adversely affecting screening among inner-city, low income, and minority individuals; these findings, however, are not universal High Risk Individuals A conflicting pattern of results is also observed for high risk individuals, FDRs of individuals with cancer Ovarian cancer worries among FDRs have been positively associated with screening (M D Schwartz, Lerman, Daly, et al., 1995) In contrast, high breast cancer distress (i.e., extreme worry, intrusive thoughts about breast cancer) among FDRs is associated with reduced screening (Lerman et al., 1993; see also Kash, Holland, Halper, & D G Miller, 1992; Lerman et al., 1994), although the opposite has also been found (Stefanek & Wilcox, 1991) Interestingly, distress has been associated with either excessive or insufficient BSE (Epstein et al., 1997; Lerman et al., 1994) Cancer distress among FDRs of women with breast and ovarian cancer is associated with high perceived risk of cancer and low perceived control over cancer development (Audrain et al., in press) Conflicting Findings and the Elusive Inverted U-Shaped Function In the now classic fear communication literature, Janis and Feshbach (1953) argued that fear served as a positive motivator for protective behavior up to some critical level of fear Above that critical fear level, avoidance of the threat was expected to replace protective behavior, yielding an inverted Ushaped relation between level of fear and behavior Resolving Conflicting Findings Lerman and M D Schwartz (1993) used the notion of an inverted U-shaped relation to highlight an important issue in resolving conflicting literature on the relations of worry and distress to cancer screening- the range and level of distress represented among participants in any individual study If it is assumed for a moment that an inverted U-shaped relation of distress to screening exists, then all relations (positive, inverted U, negative, or no relation) are possible as segments of the distress continuum are sampled The resolution of conflicting study out comes may lie in the segment of the distress continuum represented in any study The McCaul, Reid, et al (1996) meta-analysis showed only monotonic increasing relations of both susceptibility and cancer worry to behavior However, the meta-analysis did not include articles in which avoidance of screening by FDRs of breast cancer victims was associated with high cancer distress, discussed further later (e.g., Kash et al., 1992; Lerman et al., 1994) In samples from the general population- samples such as those of McCaul, Reid, et al (1996)-it is possible that there are insufficient very high distress cases for a curvilinear relation to be manifested and/or detected statistically Distress Versus Perceived Susceptibility Support for the inverted U-shaped relation is found when emotional distress and not the more cognitive assessment of perceived susceptibility serves as the predictor of cancer screening behavior Perhaps the inverted U-shaped relation of risk to behavior has been sought in the wrong variable, that is, in perceived susceptibility rather than cancer distress (See Hailey, 199 1, for consideration of an inverted U-shaped relation of distress to screening among FDRs of women with breast cancer.) Modifying Perceived Susceptibility and Cancer Distress Through Training High Risk Women As already described, FDRs of women with cancer typically exhibit excessive perceived risk and associated high cancer distress, apparently leading to failure to follow screening recommendations (i.e., either excessive or insufficient screening) and even to requests for prophylactic surgery (Lerman et al., 1995) Interventions to reduce perceived susceptibility among FDRs have sometimes been successful (Alexander, Ross, Sumner, Nease, & Littenberg, 1995) However, women with high cancer distress benefit less from such susceptibility focused interventions, suggesting that both cancer distress and inaccurate perceptions of risk must be simultaneously addressed (Lerman et al., 1995) Reductions in cancer distress have been achieved through individual counseling (Lerman et al., 1996; Schwartz, Lerman, et al., 1998) An important issue is whether clarifying that perceived risk is overestimated will lead to underutilization of mammography screening (M D Schwartz, Rimer, Daly, Sands, & Lerman, 1998) General Population The extent to which subjective risk estimates can be made more accurate through intervention has also been explored in the general population (Weinstein & Klein, 1995), where perceived risk typically exceeds objective risk Kreuter and Strecher (1995) reported increased accuracy in perceived risk (i.e., decreased perceived risk) for cancer in the general population following an educational intervention Lipkus, Biradavolu, Fenn, Keller, and Rimer (1998) explored strategies for increasing accuracy of risk perceptions for cancer -735Repeated Screening An important question is whether screening behaviors are sustained over time among asymptomatic women Ronis, Yates, and Kirscht (1989) argued that the factors that lead to initiation of a behavior not sustain the behavior, and that habits, rather than attitudinal variables, determine repeated behavior Similar arguments were made by S M Miller et al (1996) in the context of BSE performance Correlations of perceived susceptibility with repeated mammography screening are not reliably observed, with positive associations noted by Lerman, Rimer, Track, Balshem, and Engstrom (1990) and Fenaughty, Aiken, and West (1993), but no association noted by Marshall (1994), Cockbum, Schofield, White, Hill, and Russell (1997), and Orton et al (199 1) Anxiety about mammography appears to be negatively related to repeated screening (Lerman et al., 1990) Medical System and Demographic Determinants of Repeated Screening A host of demographic and medical system variables relate to repeated screening, just as with mammography compliance taken at any single point in time Younger age, physician recommendation, having had regular clinical breast examinations by a physician, and family breast cancer history are positively associated with repeated mammography screening (Hitchcock, Steckevicz, & Thompson, 1995; Lerman et al., 1990; Zapka, Stoddard, Maul, & Costanza, 199 1) Failure of asymptomatic women to return for a second mammogram at a regular interval is associated with negative experiences with the initial mammogram, among them pain, embarrassment, and unpleasant interaction with clinic staff (Marshall, 1994; Orton et al., 1991) Again, it appears that many variables operate on repeated screening that weaken the potential impact of perceptions of susceptibility Sequelue of Abnormal Screening Tests and Discovery of Symptoms Two related literatures highlight the reciprocal nature between screening and perceived vulnerability and cancer distress The first literature, which addresses the impact of abnormal screening tests on psychological functioning, was reviewed by Paskett and Rimer (1995) This literature shows clear negative psychological effects of abnormal Pap smear and mammography test results, including heightened cancer distress, with varying levels of follow-up screening (from 20% to 95% across studies) The second literature, on delay in seeking treatment following the selfidentification of a possible cancer symptom (e.g., a breast lump), was reviewed by Facione (1993) This literature characterizes the myriad fears engendered by discovery of cancer symptoms and their association with delay in seeking treatment Preventive Behavior: Sun Protection Although the focus is primarily on screening, this section touches on cancer prevention, with a consideration of perceived vulnerability as a correlate of sun protection The incidence of deadly melanoma has risen 4% per year since 1973 Skin protection through limiting sun exposure and sunscreen use is recommended (American Cancer Society, 1998) (However, there is now significant controversy as to the efficacy of sunscreen for protection against melanoma; Facelmann & Wu, 1998) Sun protection against skin cancer poses four related issues First, because intensive sun exposure between age 10 and 24 is associated with melanoma development (Holman et al., 1986), adolescents must adopt sun protection Second, sun exposure early in life is associated with much later development of skin cancer, thus raising the issue for health psychology of how to induce behavior change against distal risk Third, normative influences play heavily in tanning: A suntan is perceived as healthy (e.g., Hill et al., 1992; Mermelstein & Riesenberg, 1992) and attractive (A J Miller et al., 1990) Fourth, parents must play an active role in their children's skin protection (Rodrigue, 1996) Objective risk based on skin type (Fitzpatrick, 1988) is associated with perceived susceptibility to skin cancer (Clarke, Williams, & Arthey, 1997; Jackson, 1997; Webb, Friedman, Lute, Weinberg, & Cooper, 1996) Arthey and Clarke (1995) provided a review of the psychological literature on suntanning and sun protection Positive associations between perceived susceptibility and sun protection have been noted among high school students (Mermelstein & Riesenberg, 1992; Wichstrom, 1994), university students (Cody & Lee, 1990), the general U.S population (Hall, May, Lew, Koh, & Nadel, 1997), and parents protecting their children (Lescano & Rodrigue, 1997), but such relations are not uniformly observed In fact, a negative relation has been found between sun protection and perceived risk among individuals with chronically high sun exposure (Carmel, Shani, & Rosenberg, 1996) Elevated perceptions of susceptibility in this case appear to result from past high risk behavior A similar relation has been observed in the HIV/AIDS literature; those who have engaged in high risk sexual behavior subsequently report high perceived vulnerability to HIV/AIDS (Gerrard et al., 1996) Manipulations of perceived susceptibility in interventions have resulted in increased intentions for sun protection (e.g., Cody & Lee, 1990; Mahler, Fitzpatrick, Parker, & Lapin, 1997) Normative Influences Normative influences (Pratt & Borland, 1994; Wichstrom, 1994), particularly for appearance (A J Miller et al., 1990), have shown reliable relations with sun tanning versus sun protective behavior, particularly among adolescents Self-presentation (impression management) may well lead to health risks (Leary, Tchividjian, & Kraxberger, 1994); suntanning exemplifies this phenomenon Recent interventions (e.g., Jones & Leary, 1994; Prentice-Dunn, Jones, & Floyd, 1997) also highlight the impact of appearance concerns These powerful normative influences, which are much less often considered in relation to screening behaviors such as mammography (but see Montano & Taplin, 1991), highlight the unique forces, in addition to perceived vulnerability, that influence particular cancer- specific behaviors -736- INTERVENTIONS TO INCREASE SCREENING This section addresses interventions to increase cancer screening, and, more specifically, attempts to link manipulations of perceived susceptibility to increased screening Experimental interventions provide the vehicle for untangling the causal impact of putative determinants such as perceived vulnerability on cancer protective behavior The use of mediational analysis to assess the extent of direct and indirect impact of manipulations of perceived susceptibility on screening outcomes is also highlighed Comprehensive summaries of interventions to increase cancer screening have been provided by Rimer (1994) for mammography screening and by Snell and Buck (1996) for breast, cervical, and colorectal cancer From the perspective of health psychology, theory-based interventions that employ models such as the HBM to design program components are most of interest, because they permit the linking of changes in constructs in the model (e.g., perceived susceptibility) to changes in screening behaviors A number of mammography screening interventions have included components designed to increase perceived vulnerability to breast cancer (Aiken, West, Woodward, Reno, & Reynolds, 1994; Champion, 1994; Curry, Taplin, Anderman, Barlow, & McBride, 1993; Rimer et al., 1992; Skinner, Strecher, & Hospers, 1994; Zapka et al., 1993) In some studies, the perceived susceptibility component was only one small part of a large complex intervention, and no attempt was made to establish a direct linkage from this component to behavioral outcomes (Champion, 1994; Rimer et al., 1992; Zapka et al., 1993) In contrast, Curry et al (1993) showed that providing tailored personal objective risk information to FDRs of breast cancer victims increased screening; Skinner et al (1994) showed a similar impact of tailored messages in a community sample Mediational Analysis of Intervention Impacts Aiken, West, Woodward, Reno, and Reynolds (1994) implemented an HBMbased mammography intervention, with individual program components that targeted each of the four HBM constructs: perceived susceptibility, severity, benefits, and barriers Mediational analysis, a statistical procedure that establishes linkages among chains of variables, was used to test the linkages from an intervention through intermediate mediators (the HBM components) to mammography compliance (West & Aiken, 1997) This mediational analysis is presented here because of our strong conviction (West & Aiken, 1997) that mediational analysis provides important insights into the way in which theoretical constructs influence behavior To date, mediational analysis has been used productively in both mental health and substance abuse research, as well as in several areas of basic psychological research Requirements for Mediational Analysis In order to test the theory of an intervention through mediational analysis, the following are required: a specified theoretical model on which the program will be built, a measurement instrument that provides distinct measures of each construct in the model that will serve as a mediator, a translation of each construct of the model into a distinct component of the intervention, assessment of postintervention levels on each of the constructs targeted in the model in an experimental versus control group (with adequate statistical control of pretest levels), and measurement of the outcome West and Aiken (1997) summarized the conditions that must be met in order to demonstrate that a putative mediator (here, perceived susceptibility) produced change in the outcome (here, mammography screening), as specified by Judd and Kenny (1981), Baron and Kenny (1986), and MacKinnon (1994) The Mediational Role of Susceptibility in Intervention In the intervention, the HBM was amended by assessing intentions for screening at immediate posttest as well as actual compliance months following the intervention Mediational paths were established from perceived susceptibility and perceived benefits to intentions, as was a strong link from intentions to subsequent screening The role of perceived susceptibility in the causal chain from intervention through compliance is of interest here The model of the impact of HBM constructs on outcomes is illustrated in Fig 44.1 It differs from typical characterizations of the HBM in that the four HBM constructs are not treated as coequal predictors of outcome Rather, following Ronis (1992), a model was specified in which perceived susceptibility and perceived severity were antecedents of perceived benefits, under the assumption that a woman would not perceive the benefits of mammography screening unless she felt threatened (perceived susceptibility plus severity) by breast cancer Again following Ronis (1992), it was specified that the effect of perceived susceptibility on outcome would be mediated through perceived benefits, that is, that the effect of susceptibility would be an indirect effect through benefits, in the following causal sequence: Intervention → Susceptibility → Benefits → Intentions This mediational chain was confirmed In addition, a direct path from susceptibility to intentions was confirmed, that is, Intervention → Susceptibility → Intentions The size of the indirect effect of susceptibility, over and above the direct effect, was substantial The full details of the mediational analysis, including explorations of possible roles for perceived susceptibility, are provided in West and Aiken (1997) What is critical here is a conception of perceived susceptibility at the outset of a causal chain that flows through other constructs Examining only the direct effects of susceptibility on intentions or behavior may obscure the role of perceived susceptibility in the behavioral compliance process, potentially leading to underestimates of the total effect of perceived susceptibility on behavior Some research on screening and preventive behavior omits considerations of perceived susceptibility and examines variables that are conceptually downstream of perceived susceptibility -737FIG 44.1 Mediational analysis of the impact of a health belief model (HBM) based intervention on compliance with mammography screening recommendations The indirect mediational path from intervention to perceived susceptibility through perceived benefits to intentions for screening illustrates how perceived susceptibility serves as an apparent precursor to benefits in the HBM For paths, *p