The Functions of Affect in Health Communications and in

ORIGINAL ARTICLE

The Functions of Affect in HealthCommunications and in the Construction ofHealth Preferences

Ellen Peters1, Isaac Lipkus2, & Michael A. Diefenbach3

1 Decision Research, Eugene, OR 97401

2 Duke University Medical Center, Cancer Prevention, Detection and Control Program, Durham, NC 27701

3 Mount Sinai School of Medicine, Department of Urology, New York, NY 10029

We examine potential roles of 4 functions of affect in health communication and the

construction of health preferences. The roles of these 4 functions (affect as information,

as a spotlight, as a motivator, and as common currency) are illustrated in the area of

cancer screening and treatment decision making. We demonstrate that experienced

affect influences information processes, judgments, and decisions. We relate the func-

tions to a self-regulation approach and examine factors that may influence the weight

of cognitive versus affective processing of information. Affect’s role in health communi-

cation is likely to be nuanced, and it deserves careful empirical study of its effects on

patients’ well-being.

doi:10.1111/j.1460-2466.2006.00287.x

A major theme that emerges from judgment and decision-making research is that we

frequently do not know our own ‘‘true’’ values in decisions (e.g., how much we valuea treatment option or better patient/physician communication). Rather, when askedto form a judgment or to make a decision, we often appear to construct our values

and preferences ‘‘on-the-spot’’ using cues from the decision situation and our owninternal reactions (Payne, Bettman, & Schkade, 1999; Slovic, 1995). This kind of on

the spot value judgment can have significant implications for a person’s well-being,such as when cancer patients are asked to make treatment decisions. In health

communications, the goal of communication efforts is often informed choice; deci-sions should be based on patients’ ‘‘accurate’’ understanding of the facts and be

consistent with patient values (Briss et al., 2004; Edwards, Unigwe, Elwyn, & Hood,2003; Frosch, Kaplan, & Felitti, 2001; Parascandola, Hawkins, & Danis, 2002). Forexample, a man who elects to be screened for prostate cancer by having a prostate-

specific antigen test should understand and weigh the potential positive and negativeoutcomes of the test (e.g., a possible cancer diagnosis, anxiety while waiting for the

Corresponding author: Ellen Peters; e-mail: [email protected].

Journal of Communication ISSN 0021-9916

S140 Journal of Communication 56 (2006) S140–S162 ª 2006 International Communication Association

results, the possible need to undergo additional tests such as a biopsy related to anabnormal finding that proves not to be cancer) with the likelihood of each outcome.

However, although the goal of informed choice is an excellent one, it may not attendadequately to the possibility that value judgments and preferences of patients are

malleable and are sometimes constructed on the spot. As a result, informed choicemay be a less realistic ideal in some situations (e.g., when how information is pre-sented as opposed to what information is presented exerts a significant impact on

choices). In other medical situations, the goal of health communication is to per-suade (e.g., a 14-year-old vulnerable to smoking should be persuaded not to initiate

smoking). With this goal, communicators are attempting to harness the power ofconstructed values and preferences.

We examine the roles of affect and the affect heuristic in health communicationand the construction of health preferences. This study extends earlier work on the

affect heuristic by examining four functions of affect in the construction process. Wefirst review the four functions developed by Peters (in press) and illustrate theseprocesses with examples relating to cancer screening and treatment. Research dem-

onstrates that affect experienced in the moment, whether the result of consideringa decision option or from an unrelated source, influences concurrent cognitions,

information processes, judgments, and decisions. Subsequently, we relate the func-tions to a self-regulation approach to health threats that includes both affective and

cognitive components. Finally, we examine factors that may influence the weight ofmore cognitive versus more affective processing of health information.

What are the functions of affect in the process of constructing

judgments and decisions?

Recent research has developed and tested theories of judgment and decision making

that incorporate affect as a key component in a process of constructing values andpreferences (Lichtenstein & Slovic, in press). Within these theories, integral affect

refers to positive and negative feelings1 about a stimulus that are generally based onprior experiences and thoughts and are experienced while considering the stimulus,

whereas incidental affect is positive and negative feelings such as mood states that areindependent of a stimulus but can be misattributed to it or can influence decision

processes. Together, they are used to predict and explain a wide variety of judgmentsand decisions ranging from choices among jelly beans to life satisfaction and valu-ation of human lives (Kahneman, Schkade, & Sunstein, 1998; Schwarz & Clore, 1983;

Slovic, Finucane, Peters, & MacGregor, 2002).Mild incidental affect and integral affect are ubiquitous in everyday life. Imagine

finding a quarter on the sidewalk (a mild positive mood state is induced; there maybe a ‘‘carryover’’ of incidental affect that colors your next decision even though the

feelings are not normatively relevant to the decision) or considering whether you willhave a bowl of oatmeal or a chocolate croissant for breakfast (mild positive and

negative affect are experienced; these are termed integral affect because they are part

E. Peters et al. The Functions of Affect

Journal of Communication 56 (2006) S140–S162 ª 2006 International Communication Association S141

of the decision maker’s internal representation of the decision options). Feelingsexperienced in the cancer context can be more extreme. For example, a breast cancer

survivor may experience a euphoric mood state when told that she is in remission ora 65-year-old man with prostate cancer may use integral affect toward his options of

watchful waiting and surgery to guide his treatment choice. Whether mild or strong,these feelings can impact the processing of information and, thus, what is judged ordecided. Research has begun to delineate the various ways that affect alters infor-

mation processing.In this study, we argue that affect has four separable roles important to health

communication and decision-making processes. First, as suggested above, affect canact as information. Second, it can act as a spotlight focusing our attention on different

information—numerical cues or risks versus benefits, for example—depending onthe extent of our affect. Third, affect can motivate action or the processing of infor-

mation. Finally, affect may serve as a common currency in judgments and decisions,allowing us to compare more effectively the values of very different decision optionsor information (e.g., compare apples to oranges). These functions are not mutually

exclusive, and we consider their interrelations after introducing all four functions.We will focus primarily on valence (positive and negative) feelings because this

evaluation has been found essential to meaning by researchers studying such diversephenomena as language, attitudes, and the behavior of persons with brain lesions

(see, e.g., Damasio, 1994; Osgood, Suci, & Tannenbaum, 1957). Consideration ofhow discrete emotion states impact preferences and when valence versus discrete

emotions alter preferences are also important questions but are outside the scope ofthis study (Lerner & Tiedens, in press; Peters, Burraston, & Mertz, 2004).

Affect as information

One of the most comprehensive theoretical accounts of the role of affect and emo-

tion in decision making was presented by the neurologist, Antonio Damasio (1994).In seeking to determine ‘‘what in the brain allows humans to behave rationally,’’

Damasio argued that a lifetime of learning leads decision options and attributes tobecome ‘‘marked’’ by positive and negative feelings linked directly or indirectly to

somatic or bodily states. When a negative somatic marker is linked to an outcome, itacts as information by sounding an alarm that warns us away from that choice. When

a positive marker is associated with the outcome, we are drawn toward that option.By consulting and being guided by these feelings, Damasio claims that we makebetter quality and more efficient decisions. Without these feelings, information in

a decision lacks meaning and the resulting choice suffers.The affect heuristic built upon these and other ideas to suggest that affect may

serve as a cue for many important judgments including probability judgments(Slovic et al., 2002). Zajonc (1980) proposed that affective reactions to stimuli are

often the earliest reactions. Under the affect heuristic model, affect can be experi-enced first upon consideration of a familiar technology or it can be the result of

further processing of information (LeDoux, 1996; Peters, Vastfjall, et al., 2006). In

The Functions of Affect E. Peters et al.


either event, the affect then acts as information guiding decisions and judgmentssuch as risk and benefit perceptions. The affect heuristic is substantially similar to

models of ‘‘risk as feelings’’ and ‘‘mood as information’’ (Loewenstein, Weber, Hsee,& Welch, 2001; Schwarz & Clore, 2003) and shares much in common with dual

process theories, such as those by Epstein (1994) and Leventhal (e.g., Cameron &Leventhal, 2003; Leventhal, 1970; Leventhal, Diefenbach, & Leventhal, 1992).

Whereas some theories focus exclusively on the use of mood states (incidental

affect) in judgments (Forgas, 19952; Schwarz & Clore, 2003), use of the affect heu-ristic is characterized by reliance on feelings attributed to an option or stimulus and

experienced while considering it in judgments and decisions. Alhakami and Slovic(1994) proposed that the strength of positive or negative affect associated with an

activity (and experienced while considering that activity) guided perceptions of itsrisks and benefits. Thus, judgments about a technology such as a new medical

treatment would be based not only on what people think about the treatment butalso on how they feel about it. If feelings toward a technology are favorable, decisionmakers are moved toward judging its risks as low and its benefits as high; if their

feelings are more negative, they tend to judge the opposite—high risk and lowbenefit. For example, virtual colonoscopy is currently under much scrutiny for the

detection of colon cancer. Individuals with positive affect toward this technology(the affect may be due to prior learning that it is not invasive or it is less embarrass-

ing) may interpret new information about risks and benefits in ways that are con-sistent with their affect (i.e., perceive it as low risk and high benefit).

In some situations, decision options are unfamiliar to the decision maker andfocused communication efforts may be able to assist the individual. In these cases,

providing individuals with ‘‘affective cues’’ may help provide meaning to the infor-mation presented. For example, Peters, Slovic, & Hibbard (2004) were interested inthe processes by which decision makers might bring meaning to unfamiliar, dry, cold

facts about health plan quality. In a series of studies, they influenced the interpre-tation and comprehension of numerical information about health plan attributes by

providing affective cues that can be used easily to evaluate the overall goodness orbadness of a health plan. For example, in one of the studies, older adult participants

were presented with identical attribute information (quality of care and membersatisfaction) about two health plans. The information was presented in bar chart

format with the actual score displayed to the right of the bar chart (see Figure 1). Theinformation for half of the subjects was supplemented by the addition of affectivecategories (i.e., the category lines plus affective labels that placed the health plans into

categories of poor, fair, good, or excellent).The attribute information was designed such that Plan A was good on both

attributes, whereas Plan B was good on quality of care but fair on member satisfac-tion. The specific scores for quality of care and member satisfaction were counter-

balanced across subjects, such that for half the subjects the average quality-of-carescores were higher, and for the other half average member satisfaction scores were

higher. They predicted and found that affective categories influenced the choices.



Specifically, older adults preferred health Plan A more often when the categories werepresent (Plan A was always in the good affective category when the affective labels

were present).In a second study, they found that choices of older adults with high deliberative

ability (high speed of processing measured in a digit symbol substitution task) wereinfluenced less by the presence versus absence of affective categories than werechoices of older adults with low deliberative ability. The results suggest that adults

with high deliberative efficiency are better able to compare information and derivemeaning from the data. However, for adults with low deliberative efficiency, affec-

tive categories appear to provide more information and influence its meaning—suggesting that affective labels may be especially useful among those who are taxed

by too much information, time pressure, or the stress of illness. Allowing individualssuch as a recently diagnosed cancer patient access to the meaning of important infor-

mation like the quality of care offered at different hospitals should help them toprocess it more deeply and make better decisions. A condition that included thecategory lines but no affective labels had no impact on choice, suggesting that cate-

gorization alone cannot explain this effect. A third study provided direct evidence ofthe affective basis of this manipulation by demonstrating that decision makers

accessed their feelings about the health plan highlighted by affective categories (e.g.,Plan A in Figure 1) faster than their thoughts in the presence but not in the absence of

0

Plan A

Plan B

61

65

59

63

0

Plan A

Plan B

Condition 1:Affective categories

Condition 2 :No affective categories

0 40 60 80 100

Plan A

Plan B

Poor Fair Good Excellent

61

65

59

63

0 40 60 80 100

Plan A

Plan B

Poor Fair Good Excellent

Quality ofcare received:

Member satisfactionwith HMO :

100

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Figure 1 Example of affective categories in health plan choice.



the manipulation. Communication techniques such as these may prove useful inimproving risk comprehension when cancer-related distress is high and objective

risks are underweighted (Lerman et al., 1995). Although testing in a real-worldenvironment is absolutely necessary, if affectively based attitudes are best modified

with affective as opposed to cognitive information (Millar & Tesser, 1989), thencancer risk communication techniques with an affective basis may promote bettercomprehension of information like objective risks that might otherwise be ignored.

The use of methods such as affective categories does call, however, for a differentemphasis in health and other communications. Instead of a focus on providing

complete and accurate information, the emphasis shifts to providing usable, mean-ingful, and accurate information that will support better choices. It brings with it

a new level of responsibility for health communicators (including physicians andother health professionals) who would need to know how patients currently respond

to information and would need to bring their expertise to bear not only on whatinformation to provide but also on how to present that information in ways thatethically support good decision making. It also requires a delicate balance between

informing patients and helping them take into account important information thatmight otherwise not enter into their decision processes. The provision of more

subjective interpretations may be difficult and be resisted by health professionalswho prefer to provide only ‘‘objective facts.’’ We hope this study helps shift the focus

on patient best interests from exposing them to information to helping them com-prehend and use that information.

Affect also acts as information in the construction of risk estimates (Johnson &Tversky, 1983; Loewenstein et al., 2001; Peters & Slovic, 1996). Peters, Slovic,

Hibbard, and Tusler (2006) linked affect to an adjustment process in fatality esti-mates. They found that decision makers asked to estimate the number of fatalities inthe United States each year from various causes of death were influenced by the

anchor provided (the actual number of deaths from a disease), a typical finding insuch studies. The decision makers also appeared to adjust away from the anchor

based on the extent of their worry about the disease under consideration; fatalityestimates were significantly higher for causes of death about which they reported

greater worry. These findings are among the first to link affect as a possiblemechanism underlying the adjustment process (see also Peters, Slovic, & Gregory,

2003). They are also consistent with cancer results. For example, in the breastcancer literature, worry is associated with perceived risk (Erblich, Bovbjerg, &Valdimarsdottir, 2000; Lipkus et al., 2000).3 Although the direction of this effect is

not entirely clear, experimental results have demonstrated that increasing incidentalnegative affect subsequently increases risk perceptions across a variety of domains

(e.g., Johnson & Tversky). A pervasive fear of cancer may underlie in part thetendency for individuals to exaggerate their cancer risk (Croyle & Lerman, 1999).

Reliance on affect as information may create communication challenges withrespect to cancer risk. Specifically, reliance on affect may result in less use of (non-

affective) numerical information, making it difficult to educate patients about their



objective risk and alleviate unnecessary cancer distress (Watson et al., 1999). In onenonhealth-related study, the presence of salient affective cues led to neglect of prob-

abilistic information (Rottenstreich & Hsee, 2001). We speculate that individuals’often strong negative affect about cancer may create insensitivity to its (often rela-

tively low) objective risk. In support of this notion, Kraus, Malmfors, and Slovic(1992) found that expert toxicologists were able to assess accurately the risk of cancerposed by different exposure levels to a toxic agent, but the average individual from

the public tended to believe that any exposure level was risky, possibly because negativefeelings about cancer created an insensitivity to varying levels of the likelihood of

cancer. If the strength of affect toward an outcome causes neglect of its likelihoodof occurrence as hypothesized, then probability neglect may be particularly strong

among patients who have stronger negative reactions to cancer initially. Anxiety inthe face of low objective risk, however, may also encourage protective behaviors to

avoid increased risk (e.g., using sunscreen to avoid skin cancer). Affect as informationthus acts as a substitute for the assessment of other specified target attributes injudgment (e.g., what is the objective risk of cancer from a toxic agent? Kahneman,

2003). Without affect, information appears to have less meaning and to be weighedless in cancer judgment and choice processes (e.g., numerical risk information).

Communication efforts should include statements that acknowledge a person’spossible emotional reactions to a threat (e.g., it is quite normal to be worried in

a situation like this) or illustrate the prevalence of the threat (e.g., prostate cancer isthe most diagnosed cancer in the United States). Another example, within the

context of genetic testing for breast cancer susceptibility, illustrates this approachfurther. To improve understanding of testing-related probabilities and decision

making, women eligible for genetic testing for BRCA1/2 are led through a structuredexercise in which they imagine receiving a positive, negative, or indeterminate result.In each case, they are asked to imagine what they would feel and what they would

think; the researcher’s goal was to identify potential maladaptive emotional andcognitive reactions that can be addressed by the genetic counselor (Diefenbach &

Hamrick, 2003). This is one of the special efforts being developed to highlight themeaning of important, but underweighted, numerical information.

Affect as a spotlight

Considerably less work has been done on the other three proposed functions ofaffect in the construction of preferences. Peters (in press) proposed that affect playsa role as a spotlight in a two-step process. First, the extent or type of affective

feelings (e.g., weak vs. strong affect or anger vs. fear) focuses the decision maker onnew information. Second, the new information (rather than the initial feelings

themselves) is used to guide the judgment or decision. Although incidental feelingshave been shown to function as a spotlight in memory and judgment (e.g., mood-

congruent biases on memory; Bower, 1981), little research has examined howintegral feelings about a target might alter what information becomes more salient

in decisions.



Nabi (2003) experimentally manipulated integral affect (anger vs. fear) towarddrunk driving. Consistent with the proposed two-step approach, this affect manip-

ulation first made some stored knowledge more accessible (e.g., reasons to be angryabout drunk driving were spotlighted), and second, the more accessible information

had a greater impact in subsequent preferences. Peters et al. (2003) found a similarspotlight effect with affect influencing the dollar values salient to buyers and sellers ofa lottery ticket. Both level of affect toward an object and the types of affect (e.g., anger

vs. fear) appear to make different cues more salient.Depending upon how people feel about an object, they may focus on different

information. The function of affect as a spotlight takes advantage of the role offeelings in directing cognitions to address the source of the feeling. Alhakami and

Slovic (1994) demonstrated that the negative correlation between perceived risk andperceived benefit is mediated by affect. For example, decision makers with positive

affect toward a radiation source (e.g., X rays) tend to perceive it as highly beneficialand low in risk; the reverse happens if decision makers have negative affect abouta radiation source (e.g., nuclear power). Although this effect has been interpreted in

terms of the role of affect as information (Slovic et al., 2002), it may be related toaffect’s role as a spotlight. The affect-as-spotlight hypothesis predicts that new ben-

efit information will be more salient for decision makers who had previously devel-oped positive feelings about a treatment or screening option. As a result, they will

spend more time looking at and will remember more of the new benefit information,whereas they spend less time looking at any new risk information and will remember

them less well. It predicts the reverse for treatment and screening options peopleevaluate negatively (e.g., less time spent considering and poorer memory for new

benefit information).Thus, current affective experiences will guide the processing of cancer commu-

nications from physicians, decision aids, the media, and other sources. For example,

in choices among screening options for colon cancer, negative feelings about contactwith one’s own fecal matter may lead decision makers to spend more time examining

its risks (lower accuracy rate) and less time examining its benefits. Knowing thismight lead to a communication strategy of increasing positive mood in order to alter

the negative feelings elicited during consideration of that option (or one could try toattenuate the negative affect elicited by making any fecal contact as abstract or

normal as possible). No studies exist to the best of our knowledge testing thesehypotheses. On a larger conceptual level, this means that we may need to tailorour communication approaches to a person’s emotions (see also Loewenstein, 2005).

Affect as a motivator of information processing and behavior

In a third role, affect appears to function as a motivator of information processingand behavior. Classical theories of emotion include, as the core of an emotion,

a readiness to act and the prompting of plans (Frijda, 1986). Although affect isgenerally a much milder experience compared to a full-blown emotion state, recent

research has demonstrated that we tend to automatically classify stimuli around us as



good or bad and that this tendency is linked to behavioral tendencies. Stimuliclassified as good elicit a tendency to approach, whereas those classified as bad elicit

avoidance tendencies (Chen & Bargh, 1999). Incidental mood states also motivatebehavior as people tend to act to maintain or attain positive mood states (Isen,

2000). In addition, there is abundant research showing that some emotions, suchas worry, have been used to motivate specific behavioral change, such as mammog-raphy screening (McCaul, Branstetter, Schroeder, & Glasgow, 1996). Diefenbach,

Miller, and Daly (1999), for example, demonstrated that worry about breast cancerpredicted mammography screening independent of perceived breast cancer risks and

trait anxiety.4 Several reviews explicate the role of fear appeals as a motivator ofbehavior change (e.g., Leventhal, 1970; Sutton, 1982; Witte, 1998).

Affect also appears to be linked to the extent of deliberative effort decisionmakers are willing to put forth in order to make the best decision (i.e., the extent

of systematic processing). Peters et al.’s (2003) studies of how people price lotterytickets were sometimes played for real money and other times were hypothetical.Although the same general effects emerged in both types of studies, real play elicited

stronger feelings about the lottery tickets. At the same time, the real-play participantsshowed more evidence of taking the effort to calculate an expected value (40% of

real-play buyers gave the expected value as their response compared to 10% ofhypothetical-play buyers). In addition, half the hypothetical-play participants

showed evidence of less effort in another way by giving the same buying price astheir earlier selling price; only 3% of real-play participants did so. Thus, real play

seemed to motivate buyers and sellers to work harder, and the motivating effect ofreal play was mediated by affect.

These findings suggest that individuals (whether patients, family members, orfriends) who have strong affect about cancer may work harder to find and processinformation about treatment or other options. Of course, Isen’s (2000) work on

decision makers motivated to maintain or attain positive moods suggests that deci-sion makers in negative moods from cancer diagnosis or other reasons may avoid

making choices if they do not believe that the work to make the choice will lead tomore positive or at least less negative moods. Thus, increased negative affect about

cancer risk may lead to coping efforts and, for example, increased genetic testingwhen the potential for controlling risk is high (e.g., breast cancer) but decreased

testing when risk reduction is not possible (e.g., Huntington’s disease; Croyle &Lerman, 1999).

An additional source of motivation from affect may come from the negative

feelings elicited by ambivalence. At times, our emotions and thoughts do not per-fectly align themselves as positive or negative. Instead, objects or tasks are evaluated

as having both positive and negative qualities. For example, smokers often haveconflicting (ambivalent) emotions and thoughts about smoking (Lipkus, Green,

Feaganes, & Sedikides, 2001; Lipkus et al., 2005). The decision to get a mammogrammay involve weighing its benefits (e.g., gaining peace of mind, being responsible for

one’s health) against its potential costs (e.g., pain, fear of finding cancer). In this



instance, ambivalence could hinder the decision to get a mammogram (Rimer et al.,2002). Thus, in situations where the targeted behavior is related to positive health

outcomes, ambivalence may be detrimental; conversely, ambivalence may serve a use-ful purpose by motivating change in unhealthy behaviors (e.g., smoking, drinking).5

We suspect that having ambivalent thoughts and feelings (Priester & Petty, 1996)may act as an important cue that triggers information search and influences decisionmaking. Specifically, because the presence of opposing positive and negative beliefs

and feelings is experienced as emotionally aversive (and a negative mood state results),the ambivalent individual is expected to engage in decisional conflict management

strategies (Weber, Baron, & Loomes, 2001). Within the framework of conflict anddecision-making models, ambivalence is assumed to trigger both problem-focused

coping (e.g., what will help me decide?) and emotion-focused coping (e.g., how do Ihandle my ambivalent feelings? Haenze, 2001; Lazarus, 1991; Luce, 1998; Luce,

Payne, & Bettman, 2001). Problem-focused coping should cause the person todevote more effort and thought to what action(s) seems appropriate (Haenze,2001; Jonas, Diehl, & Bromer, 1997; Maio, Bell, & Esses, 1996). Emotion-focused

coping should cause the person to engage in strategies to alleviate negative emotions(Haenze, 2001). In both cases, the negative mood state generated from facing difficult

trade-offs motivates action to reduce uncertainty in decisions.Strategies to reduce uncertainty may take the form of turning to friends, experts,

or other sources (e.g., written materials) to solve the dilemma. For example, a pros-tate cancer patient who is torn about which treatment, if any, to pursue may use

these sources to gain insight, help clarify values, and inform the final decision.Alternatively, the other functions of affect may become more relevant. For example,

if a prostate cancer patient feels ambivalent about a type of treatment (e.g., seedimplant), the ensuing negative mood state may act as a spotlight and cause thepatient to focus more on the risks than the benefits of this procedure. As a result,

the patient may decide against having this treatment. Ambivalence may incorporateour notions of affect as a spotlight on certain features of a treatment with the notion

of affect as a motivator of action. Future research could examine the effects ofambivalence on preferences, judgments, and decisions and on the communication

efforts that might best facilitate good decisions.

Affect as common currency

Affect is simpler in some ways than thoughts. Affect often comes in two ‘‘flavors,’’positive and negative; thoughts include more, and more complex, cost-benefit and

other trade-offs (Trafimow & Sheeran, 2004). Several theorists have suggested that,as a result, integral affect plays a role as a common currency, allowing decision

makers to compare apples to oranges (Cabanac, 1992). Montague and Berns(2002) link this notion to ‘‘neural responses in the orbitofrontal-striatal circuit which

may support the conversion of disparate types of future rewards into a kind ofinternal currency, that is, a common scale used to compare the valuation of future

behavioral acts or stimuli’’ (p. 265). By translating more complex thoughts into



simpler affective evaluations, decision makers can compare and integrate good andbad feelings rather than attempt to make sense out of a multitude of conflicting

logical reasons. This function thus is an extension of the affect-as-information func-tion into more complex decisions that require integration of information. It predicts

that affective information can be more easily and effectively integrated into judg-ments than less affective information.

In the health plan choice studies of Peters, Slovic, et al. (2004), affective catego-

ries were hypothesized to act as overt markers of affective meaning in choices. Ifcorrect, then these overt markers should help participants consider relevant infor-

mation (i.e., not considered as much when affective categories are not present) andapply that information to a complex judgment. Thus, affective categories should

influence not just the choice of a health plan, as shown in previous studies, butshould also help decision makers take into account more information and be more

sensitive to variation in information.In an initial test of this hypothesis, participants were asked to judge a series of

eight health plans one at a time on a 7-point attractiveness scale ranging from 1 =

extremely unattractive to 7 = extremely attractive. For each health plan, they receivedinformation about cost and two quality attributes presented with numerical scores

(e.g., Plan A scored 72 out of 100 points when members of the health plan rated the‘‘ease of getting referrals to see a specialist’’). The eight health plans represented a 2 3

2 3 2 design of low and high scores on each of the three attributes; eight versionswere constructed using a Latin square design. Participants who received the quality

information with affective categories (poor, fair, good, excellent) took into accountmore information and showed significantly greater sensitivity to differences in qual-

ity among plans. Thus, providing information in a more affective format appeared tohelp these judges better integrate important quality information into their judg-ments. Of course, it is also possible that these results reflect affect’s function as

a motivator of behavior. Specifically, the affective categories manipulation may haveproduced a greater affective reaction that motivated the judges to work harder and

integrate more information. These questions are empirical and deserve furtherresearch. Communicating the risks and benefits of cancer treatment and screening

options can be quite difficult due to the complexity of information. It may be thatproviding this information in a more affective format might help patients integrate

more information and thus make more informed choices.

Relations among the four functions of affect

The four functions of affect clearly are interrelated (see Figure 2). Affect, experienceddue to an incidental source or upon consideration of some stimulus, can provide

direction to cognition and be used as information and/or it can promote an auto-matic readiness to act and motivate information processing and behaviors (Oatley &

Jenkins, 1996).If affect is used as information, it can be used as a substitute for other informa-

tion in making a judgment (the direct line from affect as information to judgment)



or it can lead to the use of affect as common currency when multiple pieces of

information need to be combined. In this case, the affective information frommultiple sources will be highlighted in the integration process; less affective infor-mation may receive less weight in the judgment process because it is not as easily

integrated as the affective information. Finally, affect can be used as information toguide the selection of other information to process. This new information is high-

lighted and then used in the subsequent judgment. New affect could result from thisprocess and take on a function of its own (e.g., negative affect from a cancer diag-

nosis could lead a patient to examine the risks more than the benefits of sometreatment; if the risks are relatively small and elicit only slight negative affect, the

function of affect as common currency might take over and the combination of theoriginal affect from the diagnosis and the relatively neutral affect from the risks

might lead to overall lower negative affect toward the cancer).If affect is used as a motivator of information processing and behaviors, it could

lead simply to a health behavior of getting a mammogram, for example, or it might

lead to more deep processing of information, coping efforts (including the avoidanceof information that might lead to further distress), or communication to others.

Each of these motivated processes and behaviors could lead to new affect that thentakes on another function.

Health communication efforts often have as their goal inducing long-term pos-itive change in health-related behaviors. However, in research guided by the elabo-

ration likelihood model, sources of affect incidental to a decision option (e.g.,a mood state, the source of a message such as a famous liked person) have beenfound to evoke less systematic processing and less enduring attitude change than

Affect

Affect asinformation

Affect asspotlight

Affect ascommon currency

Judgment

Affect asmotivator

Behavior orfurtherinformationprocessing

New information

Figure 2 Hypothesized relationships among the functions of affect.



might be helpful in health communication (Petty, Barden, & Wheeler, 2002), sug-gesting that the use of affect is generally detrimental to this cause. But in most of

these cases, the judgments were not necessarily very important or personally relevant.In cases where the opposite holds (e.g., high personal relevance), emotions can evoke

the opposite response and may themselves receive greater scrutiny (Petty, DeSteno, &Rucker, 2001). We believe that integral affective sources (e.g., a cancer patient’sfeelings elicited as he considers the pros and cons of a course of treatment) may

increase the elaborations of health message recipients by directing attention, mem-ory, and judgment to address the affect-eliciting event (affect’s function as a spot-

light). The ability to process the message also may increase through the functions ofaffect as information and affect as common currency as data become meaningful

information through affect (Hsee, Loewenstein, Blount, & Bazerman, 1999); themotivation to process and the extent of processing may increase through the func-

tion of affect as a motivator. It would be useful to include a manipulation of argu-ment quality in further health communication tests of the functions of affect in orderto examine more closely the processes underlying these effects.

Functions of affect in health behavior theories

Considering different functions of affect may help in further development of health

behavior theories. Traditionally, health behavior theories have a strong cognitiveorientation, focusing on health beliefs, expectations, social norms, and goals to pre-

dict health behaviors such as decisions to quit smoking, adhere to a weight lossprogram, or obtain a colonoscopy (Janz & Becker, 1984, Fishbein & Ajzen, 2005).

The exception to this predominant cognitive orientation in health behavior theoriz-ing is the self-regulation framework (Cameron & Leventhal, 2003; Petrie & Weinman,1997) that explicitly takes into account affective reactions to a stimulus as determi-

nants of health behavior. The self-regulation framework has its origin in the parallelprocessing model (Leventhal, 1970) that hypothesizes that individuals process

external and internal stimuli (e.g., a message from their health plan to obtain a mam-mogram; detection of a lump) on both cognitive and emotional levels simulta-

neously. The self-regulation model regards the individual as a ‘‘problem solver’’who actively attempts to make sense of environmental and somatic stimuli using

both cognitive and affective processes (Leventhal et al., 1997). On the cognitiveprocessing level, a stimulus is categorized according to five cognitive attributes thatencompass the dimensions of identity (i.e., the attempt to name or label a stimulus),

timeline (i.e., acute vs. chronic), cause (e.g., genetic, accident, exposure), conse-quence (i.e., minor vs. life threatening), and controllability (remedy vs. no remedy;

Lau, Bernard, & Hartman, 1989). On the affective processing level, the stimulusevokes an affective response that interacts with the cognitive appraisal of the stimulus

(Diefenbach et al., 1999). For example, imagine a person taking a shower anddetecting a lump in the axilar region. The immediate response might be one of fear

(i.e., affective response) accompanied by the simultaneous thought that it might be



cancer (i.e., identity attribute). The cancer label might trigger related thoughts suchas, ‘‘this is serious’’ (i.e., consequence), ‘‘I have to deal with this for a long time’’ (i.e.,

timeline), ‘‘I don’t know where this comes from’’ (i.e., cause), and ‘‘there is treatmentavailable’’ (i.e., controllability). Each of these attributes can trigger specific emotions

and not all attributes might be present at the same time. Of course, this interplaybetween cognition and emotion might take a different trajectory as self-regulationtheory does not specify a fixed sequence among cognitive or emotional processing

(Brissette, Leventhal, & Leventhal, 2003). What is important, however, is that thismodel provides a framework for affective functioning within a larger context of

cognitive activity and recognizes that behavioral actions can be triggered as muchby affective reactions as by cognitive processing. To continue with the example

above, the individual might conclude to consult a physician about the lump becauseof her evaluation that it might be cancerous. However, she might also seek pro-

fessional advice because her anxiety becomes unbearable and she needs reassurance(note that high levels of worry also might be associated with avoidant behavior).

Although research has confirmed the existence of the cognitive attributes

describing a stimulus, much less research has focused on affective processing mech-anisms (Cameron & Leventhal, 2003). We argue that consideration of affect as

having multiple functions provides a promising approach to enriching health behav-ior theories. The example above suggests that the traditional self-regulation frame-

work recognizes two of the four affect functions: affect as information and affect asmotivator. The individual instantaneously categorizes the lump as ‘‘something bad’’

and experiences elevated levels of anxiety; these feelings may be used as informationto judge her cancer risk as high and may motivate her to seek professional advice

quickly about diagnosis and treatment as well as about how to cope with the feelingsthemselves. During further cognitive and affective processing, the role of affect asa spotlight might come into play. Elevated levels of worry might lead her to focus

more on potential negative interpretations and outcomes (affect-as-spotlight func-tion), possibly ignoring benign interpretations of the lump (e.g., the lump is

a bruise). Finally, across all the various internal and external information availableto the individual, the affective information (e.g., worry about the lump, relief from

a news story about a similar woman who found out her lump was not cancerous)may be integrated more and more easily than nonaffective information into ongoing

evaluations of her risk, thus providing evidence for the affect-as-common currencyfunction. This also underscores the need for a comprehensive theoretical frameworkthat attempts to integrate different areas of research.

Trade-offs between affect and deliberation

Affect and cognitions both play a role in constructing preferences. The weight of one

versus the other in judgments and choices, however, may be dictated in part bycontextual factors. One such factor might be the importance or relevance of the

decision. Clearly, choices of a life-saving treatment (e.g., what is the best cancer



therapy) versus a weekend movie differ in importance. We suspect that when deci-sions are not very important, individuals will spend little thought determining

a course of action, but rather rely on their affect as a substitute (e.g., how do I feelabout it?). At the other extreme, when the decision is important and consequential,

individuals may rely on both what they think and how they feel about the pros andcons of each option. Under these situations, individuals are often motivated to reachthe most accurate decisions; hence, we assume that these decisions will often involve

more central/systematic processing than peripheral/heuristic processing (Forgas,2000; Payne, Bettman, & Johnson, 1993). The most accurate decisions may rely on

interactions between thoughts and feelings. For example, different affective states(e.g., anxiety) can promote more in-depth systematic processing of health-relevant

information as well as prime information consistent with those mood states(Cameron, 2003; Forgas, 2000). Affect associated with an option through prior

experiences may guide decision makers to better options (e.g., somatic markers;Damasio, 1994). However, incidental feelings such as mood states also can colorthe interpretation of information and, thus, bias the direction of its evaluation in

potentially inappropriate situations (e.g., when critical life-saving treatments need tobe made). In some circumstances, individuals may become aware of the influence of

their feelings on decisions, think the influence is inappropriate, and try to correct forit by relying on strategies based on their lay theories of how feelings may influence

decisions (Petty & Wegener, 1993; Wegener & Petty, 1997). This combination ofprocesses may lead to more accurate decisions.

Other factors that may influence the weight accorded affective versus morecognitive information include decision complexity and familiarity. When a decision

is complex because the person is faced with several nondominating options (i.e., nosingle option is superior to all others on the outcomes of interest, e.g., choices amongprostate cancer treatment; Steginga & Occhipinti, 2004), too much information, or

too technical information, the person may rely most on how they feel rather than onwhat they think—perhaps because they may not trust their evaluation of the facts or

their ability to integrate multiple and competing reasons.Similarly, when the decision to be made can be equated with familiar past

experiences, the individual may rely more on how they felt about the outcome(s)obtained rather than go through the effort of evaluating the pros and cons of each

option (i.e., the affect-as-information function). For example, many individuals aged50 and older are faced with the option of which method they should use to screen forcolorectal cancer. Assuming some effort was put forth earlier thinking through

available screening options (e.g., fecal occult blood test, sigmoidoscopy, colono-scopy) and/or the person was pleased with how the procedure went (e.g., not too

embarrassing or time consuming, was painless), when faced with the same situation,he or she may simply use the affective cues attached to outcome(s) experienced to

determine which, if any, screening technique to use.Factors that interfere with a person’s ability to cognitively evaluate information

also can cause the individual to weigh affect more than cognition in choice. Shiv and



Fedorikhin (1999), for example, found that decision makers under cognitive loadwere more likely to choose an affectively pleasing chocolate cake over a fruit salad

compared to those in a no-load condition. For better or worse, cognitive load isubiquitous in life. We are surrounded by environmental noises, interference, or

distractions by others (e.g., phone calls, loud music, children, etc.), and we areplagued with busy schedules. These cognitive loads may be a particular burden tocancer patients faced, not only with their daily lives but also with the added stress and

decisions of a potentially life-threatening disease. Another related influential factorthat may tip the scale toward relying more on affect than on cognitions is time

pressure (e.g., the need to quickly choose a treatment, being faced with a busy phy-sician who has only a few minutes to provide information and answer questions).

Finucane, Alhakami, Slovic, and Johnson (2000) found that the inverse correlationbetween risks and benefits grows larger under time pressure. Their findings suggest

that the affective processes underlying perceptions of risks and benefits may weighmore when time for deliberation is low. In choices among cancer treatments, patientsmay be asked to make critical decisions immediately after diagnosis (e.g., treatment

decisions about mastectomy vs. breast-conserving procedures and type of adjuvanttreatment, if any, decisions about whether to enter a clinical trial, decisions about

whom to tell and when; Revenson & Pranikoff, 2005). Many patients may feel delay-ing a decision is not an option. As a result, they may base their final decisions on how

they feel because of the lack of perceived opportunity to reflect on the option(s).Finally, an important factor that may shape our emotional reactions, and hence

preferences, is the information presentation format, such as in the health plan choicestudies reviewed previously. A classic example is framing of information. Loss-frame

messages emphasize the negative outcomes or benefits lost by taking or not takingsome form of action; gain-frame messages emphasize positive outcomes or costsavoided by taking or not taking some form of action. The extant literature shows that

losses loom larger than gains and hence are more influential in determining decisionsand actions (Tversky & Kahneman, 1981). Thus, individuals are more likely to have

adverse emotional reactions to information presented in terms of losses than gains(e.g., medical decisions in which treatment outcomes are framed in terms of lives lost

vs. lives saved).In sum, differential weighting of cognitions and affect and affect itself are likely to

be influenced by several contextual variables, some of which have been presentedhere. Admittedly, this is not an exhaustive listing. The main point here is that theinfluence of affect on the interpretation of health communications and the construc-

tion of health preferences is itself shaped by several situational factors that need to beconsidered.

Is affect rational?

Emotion’s influence on health decisions can be overwhelming. It can cause undue

anxiety or fear, overestimation of risks (e.g., with breast cancer patients), and



avoidant choices among treatment options (e.g., avoiding a treatment with betterlong-term survival because it requires a colostomy). It can also be a distraction when

it provides information or motivation to attend to or act on emotional informationat the expense of other more important message content (e.g., a positive mammo-

gram result and the emotions that ensue may distract a woman from the informationthat only 20% of women with positive mammograms have breast cancer). Oftentimes when people consider the impact of emotion on health decisions, they think

about these kinds of negative impacts. Damasio (1994), on the other hand, arguesthat integral affect in the form of somatic markers increases the accuracy and effi-

ciency of the decision process, and its absence (e.g., in the brain-damaged patients)degrades decision performance. This view of affect likely is also true in the domain of

cancer. Affect is rational in the sense that some level of integral affect is necessary forinformation to have meaning so that decisions can be made. This ‘‘affective ratio-

nality’’ is key for health communications that have normally focused less on the roleof affect and more on deliberative means (Hibbard & Peters, 2003). Warning labelson cigarette packages in the United States, for example, focus on four statements

informing smokers about health hazards; evidence concerning these labels suggeststhat they have little influence on tobacco sales and have become invisible compared

to the more salient and colorful cigarette packages and advertising (Fischer,Krugman, Fletcher, Fox, & Rojas, 1993; Fischer, Richards, Berman, & Krugman,

1989). Survey research in Canada, however, suggests that their larger warning labelswith color pictures and 16 separate messages about specific risks of smoking create

more negative emotional reactions toward cigarettes and increase attempts toquit among smokers (Hammond, Fong, McDonald, Cameron, & Brown, 2003;

Hammond, McDonald, Fong, Brown, & Cameron, 2004).Affect’s role in health communication is likely to be nuanced; it therefore

deserves careful empirical study of its effects on patients’ well-being. Affect some-

times may help and other times hurt decision processes. Which occurs will dependon the affect elicited by the communication attempt, how affect influences the

information processing that takes place in the construction of preferences andhow that particular influence matches whatever processing will produce the best

decision for the cancer patient in that situation. In other words, the presence ofaffect does not guarantee good or bad decisions; it does guarantee that communi-

cated information will be processed in ways that are different from when it is notpresent. Understanding the latter processes presents important communicationchallenges.

Acknowledgments

This paper is based in part on the chapter ‘‘The functions of affect in the construction

of preferences’’ by E. Peters, which will appear in S. Lichtenstein & P. Slovic (Eds.),The construction of preference. New York: Cambridge University Press. Preparation of

this paper was supported in part by the National Science Foundation under grant



SES-0111941, SES-0339204, and SES-0241313. Any opinions, findings, and conclu-sions or recommendations expressed in this material are those of the authors and do

not necessarily reflect the views of the National Science Foundation.

Notes

1 Emotion theorists continue to debate the structure of emotion. Although some theorists

argue for a different rotation of emotion space (in particular, a 45� rotation that yields

the two factors of valence and arousal), we have chosen to focus on the rotation that

yields factors of positive and negative affect.

2 Forgas (1995) considered only the influence of incidental affect in judgments. The first

three functions proposed here, however, map somewhat onto his judgmental strate-

gies. First, the integral affect of this study may be present as a component of a pre-

existing evaluation and thus may be experienced and used as the information in

Forgas’ direct access strategy. In addition, the use of incidental affect as information

overlaps completely with Forgas’ heuristic strategy. Second, similar to his substantive

processing strategy, incidental or integral affect as a spotlight can influence attention,

encoding, retrieval, and associative processes. Third, although incidental affect may

not influence judgments in Forgas’ motivated processing strategy, integral affect,

through its functions as a motivator, can drive the goals and behaviors of motivated

processing.

3 At extreme levels of negative affect, it may cease to provide information into a decision

process and may instead prompt defensive processing of information. It is not clear

whether there exists a particular level of affect that will prompt this change although

Witte (1998) suggests that this ‘‘boomerang effect’’ will not occur so long as the decision

maker perceives that he or she can exert some control over the situation.

4 Some researchers have suggested that very high levels of cancer worry promote defensive

avoidance of cancer screening behaviors (e.g., Lerman et al., 1993). If correct, then the

specific behaviors motivated by affect may change depending upon the level of affect

experienced. It may be that one level of affect promotes healthy screening behaviors,

whereas an increase over some threshold produces avoidance, particularly in the absence

of a concrete action plan (Leventhal, 1970).

5 In the context where ambivalence hinders adaptive behaviors (e.g., getting a mammo-

gram), communications may target reducing ambivalence. Such approaches may reduce

the uncertainty and negative feelings associated with ambivalence, perhaps by helping

people envision and make salient the positive aspects of behavior change.

References

Alhakami, A. S., & Slovic, P. (1994). A psychological study of the inverse relationship

between perceived risk and perceived benefit. Risk Analysis, 14, 1085–1096.

Bower, G. (1981). Mood and memory. American Psychologist, 36, 129–148.

Briss, P., Rimer, B., Reilley, B., Coates, R. C., Lee, N. C., Mullen, P., et al. (2004). Promoting

informed decisions about cancer screening in communities and healthcare systems.

American Journal of Preventive Medicine, 26, 67–80.



Brissette, I., Leventhal, H., & Leventhal, E. A. (2003). Observer ratings of health and sickness:

Can other people tell us anything about our health that we don’t already know? Health

Psychology, 22, 471–478.

Cabanac, M. (1992). Pleasure: The common currency. Journal of Theoretical Biology, 155,

173–200.

Cameron, L. D. (2003). Anxiety, cognition, and responses to health threats. In L. D. Cameron

& H. Leventhal (Eds.), The self-regulation of health and illness behaviour (pp. 157–183).

London: Routledge.

Cameron, L. D., & Leventhal, H. (Eds.). (2003). The self-regulation of health and illness

behavior. London: Routledge.

Chen, M., & Bargh, J. A. (1999). Consequences of automatic evaluation: Immediate

behavioral predispositions to approach or avoid the stimulus. Personality & Social

Psychology Bulletin, 25, 215–224.

Croyle, R. T., & Lerman, C. (1999). Risk communication in genetic testing for cancer

susceptibility. Journal of the National Cancer Institute Monographs, 25, 59–66.

Damasio, A. R. (1994). Descartes’ error: Emotion, reason, and the human brain. New York:

Avon.

Diefenbach, M. A., & Hamrick, N. (2003). Self-regulation and genetic testing: Theory,

practical considerations, and interventions. In L. Cameron & H. Leventhal (Eds.),

The self-regulation of health and illness behaviour. Amsterdam: Harwood Academic.

Diefenbach, M. A., Miller, S. M., & Daly, M. (1999). Specific worry about breast cancer

predicts mammography use in women at risk for breast and ovarian cancer. Health


Edwards, A., Unigwe, S., Elwyn, G., & Hood, K. (2003). Personalized risk communication for

informed decision making about entering screening programs. The Cochrane Database of

Systemic Reviews, Issue No. 1, Art No. CD001865.

Epstein, S. (1994). Integration of the cognitive and the psychodynamic unconscious.

American Psychologist, 49, 709–724.

Erblich, J., Bovbjerg, D. H., & Valdimarsdottir, H. B. (2000). Psychological distress, health

beliefs, and frequency of breast self-examination. Journal of Behavioral Medicine, 23,

277–292.

Finucane, M. L., Alhakami, A., Slovic, P., & Johnson, S. M. (2000). The affect heuristic

in judgments of risks and benefits. Journal of Behavioral Decision Making,

13, 1–17.

Fischer, P. M., Krugman, D. M., Fletcher, J. E., Fox, R. J., & Rojas, T. H. (1993). An evaluation

of health warnings in cigarette advertisements using standard market research methods:

What does it mean to warn? Tobacco Control, 2, 279–285.

Fischer, P. M., Richards, J. W., Berman, E. F., & Krugman, D. M. (1989). Recall and eye

tracking study of adolescents viewing tobacco advertisements. Journal of the American

Medical Association, 261, 84–89.

Fishbein, M., & Ajzen, I. (2005). Theory-based change interventions: Comments on Hobbis

and Sutton. Journal of Health Psychology, 10, 27–31.

Forgas, J. P. (1995). Mood and judgment: The affect infusion model (AIM). Psychological

Bulletin, 117, 39–66.

Forgas, J. P. (2000). Feeling and thinking: The role of affect in social cognition. Cambridge, UK:

Cambridge University Press.



Frosch, D. L., Kaplan, R. M., & Felitti, V. (2001). Evaluation of two methods to facilitate

shared decision making for men considering the prostate-specific antigen test. Journal of

General Internal Medicine, 16, 391–398.

Frijda, N. H. (1986). The emotions: Studies in emotion and social interaction. New York:


Haenze, M. (2001). Ambivalence, conflict, and decision making: Attitudes and feelings in

Germany towards NATO’s military intervention in the Kosovo war. European Journal of

Social Psychology, 31, 693–706.

Hammond, D., Fong, G., McDonald, P., Cameron, R., & Brown, K. (2003). Impact of the

graphic Canadian warning labels on adult smoking behavior. Tobacco Control, 12, 391–395.

Hammond, D., McDonald, P., Fong, G., Brown, K., & Cameron, R. (2004). The impact of

cigarette warning labels and smoke-free bylaws on smoking cessation. Canadian Journal of

Public Health, 95, 201–204.

Hibbard, J. H., & Peters, E. (2003). Supporting informed consumer health care decisions:

Data presentation approaches that facilitate the use of information in choice. Annual

Review of Public Health, 24, 413–433.

Hsee, C. K., Loewenstein, G., Blount, S., & Bazerman, M. H. (1999). Preference reversals

between joint and separate evaluations of options: A review and theoretical analysis.

Psychological Bulletin, 125, 576–590.

Isen, A. M. (2000). Some perspectives on positive affect and self-regulation. Psychological

Inquiry, 11, 184–187.

Janz, N. K., & Becker, M. H. (1984). The health belief model: A decade later. Health Education

Quarterly, 11, 1–47.

Johnson, E. J., & Tversky, A. (1983). Affect, generalization, and the perception of risk. Journal

of Personality and Social Psychology, 45, 20–31.

Jonas, K., Diehl, M., & Bromer, P. (1997). Effects of attitudinal ambivalence on information

processing and attitude-intention consistency. Journal of Experimental Social Psychology,

33, 190–210.

Kahneman, D. (2003). A perspective on judgment and choice: Mapping bounded rationality.


Kahneman, D., Schkade, D., & Sunstein, C. R. (1998). Shared outrage and erratic

awards: The psychology of punitive damages. Journal of Risk and Uncertainty, 16, 49–86.

Kraus, N., Malmfors, T., & Slovic, P. (1992). Intuitive toxicology: Expert and lay judgments of

chemical risks. Risk Analysis, 12, 215–232.

Lau, R. R., Bernard, T. M., & Hartman, K. A. (1989). Further explorations of common-sense

representations of common illnesses. Health Psychology, 8, 195–219.

Lazarus, R. S. (1991). Progress on a cognitive-motivational-relational theory of emotion.


LeDoux, J. E. (1996). The emotional brain: The mysterious underpinnings of emotional life.

New York: Simon & Schuster.

Lerman, C., Daly, M., Sands, C., Balshem, A., Lustbader, E., Heggan, T., et al. (1993).

Mammography adherence and psychological distress among women at risk for breast

cancer. Journal of the National Cancer Institute, 85, 1074–1080.

Lerman, C., Lustbader, E., Rimer, B. K., Daly, M., Miller, S., Sands, C., et al. (1995). Effects of

individualized breast cancer risk counseling: A randomized trial. Journal of the National

Cancer Institute, 87, 286–292.



Lerner, J. S., & Tiedens, L. Z. (2006). Toward a model of emotion-specific influences on

judgment and decision making: Portrait of the angry decision maker. Journal of Behavioral

Decision Making, 19, 115–137.

Leventhal, H. (1970). Findings and theory in the study of fear communications. In L.

Berkowitz (Ed.), Advances in experimental social psychology (Vol. 5, pp. 119–186).

New York: Academic Press.

Leventhal, H., Benjamini, Y., Brownlee, S., Diefenbach, M. A., Leventhal, E. A., Patrick-Miller,

L., et al. (1997). Illness representations: Theoretical foundations. In K. J. Petrie & J. A.

Weinman (Eds.), Perceptions of health and illness: Current research and applications

(pp. 19–45). Amsterdam: Harwood Academic.

Leventhal, H., Diefenbach, M. A., & Leventhal, E. A. (1992). Illness cognition: Using common

sense to understand treatment adherence and affect cognition interactions. Cognitive

Therapy and Research, 16, 143–163.

Lichtenstein, S., & Slovic, P. (Eds.). (in press). The construction of preference. New York:


Lipkus, I. M., Green, J. D., Feaganes, J. R., & Sedikides, C. (2001). The relationship between

attitudinal ambivalence and desire to quit among college smokers. Journal of Applied

Social Psychology, 31, 113–133.

Lipkus, I. M., Kuchibhatla, M., McBride, C. M., Bosworth, H. B., Pollak, K. I., Siegler, I. C.,

et al. (2000). Relationships among breast cancer perceived absolute risk, comparative risk,

and worries. Cancer Epidemiology, Biomarkers & Prevention, 9, 973–975.

Lipkus, I. M., Pollak, K. I., McBride, C. M., Schwartz-Bloom, R. D., Lyna, P., & Bloom, P. S.

(2005). Assessing attitudinal ambivalence towards smoking and its association with desire

to quit among teen smokers. Psychology and Health, 20, 373–388.

Loewenstein, G. (2005). Hot-cold empathy gaps and medical decision making. Health

Psychology, 24, S49–S56.

Loewenstein, G. F., Weber, E. U., Hsee, C. K., & Welch, E. S. (2001). Risk as feelings.

Psychological Bulletin, 127, 267–286.

Luce, M. F. (1998). Choosing to avoid: Coping with negatively emotion-laden consumer

decisions. Journal of Consumer Research, 24, 409–433.

Luce, M. F., Payne, J. W., & Bettman, J. R. (2001). The impact of emotional tradeoff difficulty

in decision behavior. In E. U. Weber, J. Baron, & G. Loomes (Eds.), Conflict and tradeoffs

in decision-making (pp. 86–109). Cambridge, UK: Cambridge University Press.

Maio, G. R., Bell, D. W., & Esses, V. M. (1996). Ambivalence and persuasion: The processing

of messages of immigrant groups. Journal of Experimental Social Psychology, 32, 513–536.

McCaul, K. D., Branstetter, A. D., Schroeder, D. M., & Glasgow, R. E. (1996). What is the

relationship between breast cancer risk and mammography screening? A meta-analytic

review. Health Psychology, 15, 423–429.

Millar, M. G., & Tesser, A. (1989). The effects of affective-cognitive consistency and thought

on the attitude-behavior relation. Journal of Experimental Social Psychology, 25, 189–202.

Montague, R. P., & Berns, G. S. (2002). Neural economics and the biological substrates of

valuation. Neuron, 36, 265–284.

Nabi, R. L. (2003). Exploring the framing effects of emotion: Do discrete emotions

differentially influence information accessibility, information seeking, and policy

preference? Communication Research, 30, 224–247.

Oatley, K., & Jenkins, J. M. (1996). Understanding emotions. Oxford, UK: Blackwell.



Osgood, C. E., Suci, G. J., & Tannenbaum, P. H. (1957). The measurement of meaning.

Urbana, IL: University of Illinois.

Parascandola, M., Hawkins, J., & Danis, M. (2002). Patient autonomy and the challenge of

clinical uncertainty. Kennedy Institute of Ethics Journal, 12, 245–264.

Payne, J. W., Bettman, J. R., & Johnson, E. J. (1993). The adaptive decision maker. New York:


Payne, J. W., Bettman, J. R., & Schkade, D. A. (1999). Measuring constructed preferences:

Towards a building code. Journal of Risk and Uncertainty, 19, 243–270.

Peters, E. (in press). The functions of affect in the construction of preferences. In S.

Lichtenstein & P. Slovic (Eds.), The construction of preference. New York: Cambridge

University Press.

Peters, E., Burraston, B., & Mertz, C. K. (2004). An emotion-based model of stigma

susceptibility: Appraisals, affective reactivity, and worldviews in the generation of a stigma

response. Risk Analysis, 24, 1349–1367.

Peters, E., & Slovic, P. (1996). The role of affect and worldviews as orienting dispositions in

the perception and acceptance of nuclear power. Journal of Applied Social Psychology, 26,

1427–1453.

Peters, E., Slovic, P., & Gregory, R. (2003). The role of affect in the WTA/WTP disparity.

Journal of Behavioral Decision Making, 16, 309–330.

Peters, E., Slovic, P., & Hibbard, J. (2004). Evaluability manipulations influence the

construction of choices among health plans (Report No. 04-02). Eugene, OR: Decision

Research.

Peters, E., Slovic, P., Hibbard, J., & Tusler, M. (2006). Why worry? Perceived risk of medical

errors and willingness to act to reduce errors. Health Psychology, 25, 144–152.

Peters, E., Vastfjall, D., Slovic, P., Mertz, C. K., Mazzocco, K., & Dickert, S. (2006). Numeracy

and decision making. Psychological Science, 17, 407–413.

Petrie, K. J., & Weinman, J. A. (1997). Perceptions of health and illness: Current research and

applications. Amsterdam: Harwood Academic.

Petty, R. E., Barden, J., & Wheeler, S. C. (2002). The elaboration likelihood model of

persuasion: Health promotions that yield sustained behavioral change. In R. J.

DiClemente, R. A. Crosby, & M. Kegler (Eds.), Emerging theories in health promotion

practice and research (pp. 71–99). San Francisco: Jossey-Bass.

Petty, R. E., DeSteno, D., & Rucker, D. D. (2001). The role of affect in attitude change.

In J. P. Forgas (Ed.), Handbook of affect and social cognition (pp. 212–236). Mahwah,

NJ: Erlbaum.

Petty, R. E., & Wegener, D. T. (1993). Flexible correction processes in social judgment:

Correcting for context-induced contrast. Journal of Experimental Social Psychology,

29, 137–165.

Priester, J. R., & Petty, R. E. (1996). The gradual threshold model of ambivalence: Relating the

positive and negative bases of attitudes to subjective ambivalence. Journal of Personality

and Social Psychology, 71, 431–449.

Revenson, T. A., & Pranikoff, J. R. (2005). A contextual approach to treatment decision

making among breast cancer survivors. Health Psychology, 24, S93–S98.

Rimer, B. K., Halabi, S., Skinner, C. S., Lipkus, I. M., Strigo, T. S., Kaplan, E. B., et al. (2002).

Effects of a mammography decision-making intervention at 12 and 24 months. Preventive

Medicine, 22, 247–257.



Rottenstreich, Y., & Hsee, C. K. (2001). Money, kisses, and electric shocks: On the affective

psychology of risk. Psychological Science, 12, 185–190.

Schwarz, N., & Clore, G. L. (1983). Mood, misattribution, and judgments of well-being:

Information and directive functions of affective states. Journal of Personality and Social


Schwarz, N., & Clore, G. L. (2003). Mood as information: 20 years later. Psychological Inquiry,

14, 294–301.

Shiv, B., & Fedorikhin, A. (1999). Heart and mind in conflict: Interplay of affect and cognition

in consumer decision making. Journal of Consumer Research, 26, 278–282.

Slovic, P. (1995). The construction of preference. American Psychologist, 50, 364–371.

Slovic, P., Finucane, M. L., Peters, E., & MacGregor, D. G. (2002). The affect heuristic. In T.

Gilovich, D. Griffin, & D. Kahneman (Eds.), Heuristics and biases: The psychology of

intuitive judgment (pp. 397–420). New York: Cambridge University Press.

Steginga, S. K., & Occhipinti, S. (2004). The application of the heuristic-systematic processing

model to treatment decision making about prostate cancer. Medical Decision Making, 24,

573–583.

Sutton, S. R. (1982). Fear-arousing communications: A critical examination of theory and

research. In J. R. Eiser (Ed.), Social psychology and behavioral medicine (pp. 303–337).

London: Wiley.

Trafimow, D., & Sheeran, P. (2004). A theory about the translation of cognition into

affect and behavior. In G. Maio & G. Haddock (Eds.), Contemporary perspectives

in the psychology of attitudes: The Cardiff symposium (pp. 57–75). London: Psychology

Press.

Tversky, A., & Kahneman, D. (1981). The framing of decisions and the psychology of choice.

Science, 211, 453–458.

Watson, M., Lloyd, S., Davidson, J., Meyer, L., Eeles, R., Ebbs, S., et al. (1999). The impact of

genetic counseling on risk perception and mental health in women with a family history of

breast cancer. British Journal of Cancer, 79, 868–874.

Weber, E. U., Baron, J., & Loomes, G. (2001). Conflict and tradeoffs in decision-making.

Cambridge, UK: Cambridge University Press.

Wegener, D. T., & Petty, R. E. (1997). The flexible correction model: The role of naive

theories of bias correction. In M. P. Zanna (Ed.), Advances in experimental social

psychology (Vol. 29, pp. 141–208). New York: Academic Press.

Witte, K. (1998). Fear as motivator, fear as inhibitor: Using the extended parallel response

model to explain fear appeal success and failures. In P. A. Anderson & L. K. Guerrero

(Eds.), Handbook of communication and emotion: Research, theory, and contexts

(pp. 424–451). San Diego, CA: Academic Press.

Zajonc, R. B. (1980). Feeling and thinking: Preferences need no inferences. American

Psychologist, 35, 151–175.



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