Fear and Disgust in Consumer Behavior: An Evolutionary
Perspective
Research Master thesis, Marketing profile
University of Groningen, Faculty of Economics and Business
Abstract
On the basis of an evolutionary approach, the present research examined the hypotheses that
fear-motivated avoidance and disgust-fear-motivated avoidance can automatically activate the
disease-avoidance system and, in turn, affect consumer behavior. In Experiment 1 I shown that exposure to
disfigured faces (fear-related stimuli) determines a more positive attitude toward healthy foods,
whereas in Experiment 2 I show that exposure to dirty images (disgust-related stimuli) determines a
less positive attitude toward second hand products. Although none of these relationships are
mediated by disease avoidance activation, these results foster new theoretical development in
consumer behavior from an evolutionary perspective that can be used as a basis for further research.
Tables of Contents
1. Introduction. ... 4
2. Theoretical Framework: Disease avoidance system ... 6
2.1 Disease Avoidance and Fear... 9
2.2 Disease avoidance and disgust ... 12
3. Method ... 15
3.1 Study 1 ... 15
3.3 Study 2 ... 26
3.4 Results and Discussion ... 30
4. General Discussion ... 37
4.1 Managerial Implications ... 40
4.2 Limitations and directions for future research ... 41
References ... 45
1. Introduction.
Although the choices made by modern consumers seem to have everything to do with
contemporary culture, and little to do with human nature, more and more psychologists are
informing their research by drawing on an evolutionary perspective, which suggests modern
behavior is the result of the survival instincts developed over time by our ancestors (Schaller et al.
2006).
In particular, this emerging perspective suggests that motivational systems have been shaped by
natural selection to produce behaviors that increase reproductive fitness. To reproduce successfully,
namely to produce viable offspring and raise them to reproductive age, human beings need to
achieve many goals, including affiliation, self-protection, status, mate acquisition, mate retention,
and child rearing. Some of these goals may appear similar, but they are qualitatively distinct:
Successful attainment of each goal requires different, and sometimes opposing, cognitive and
behavioral responses. The objective of this research is to study the effects of one of these goals on
consumer behavior. In particular, I analyze how the activation of the disease avoidance system can
influence consumer attitudes, spending intentions and choices in terms of healthy foods and second
hand products.
The aforementioned deep-seated ancestral motives in fact, continue to influence much modern
behavior, although not always in obvious or conscious ways, giving rise to counterintuitive
implications especially from a consumer research perspective. For example, Griskevicius and
Kenrick (in press) presented a framework that offers a host of empirical implications for connecting
basic evolutionary psychological and behavioral processes – from attention to memory to cognition
to choice – in ways that have direct implications for theory and research in consumer behavior. In
addition, Griskevicius et al. (2009) demonstrated that an evolutionary approach can explain how
arousal-inducing contexts, such as frightening or romantic television programs, influence the
goals in men increased their willingness to spend on conspicuous luxuries but not on basic
necessities, whereas in women inducing mating goals boosted public – but not private – helping.
The mate acquisition motive was also studied in another contribution of Griskevicius et al. (2006),
where the authors explored the effects of mating motivation on creativity, discovering that romantic
motives enhanced creativity. In another contribution Griskevicius et al. (2007) examined how
self-protection and mate attraction influenced conformity. They found that a self-protective goal
increases conformity for both men and women. In contrast, the effects of a romantic goal depended
on sex, causing women to conform more to others’ preferences while engendering nonconformity in
men.
These contributions are just some examples of an emerging perspective that highlights a
different lens through which to look at motivation, distinguishing between proximate and ultimate
(ancestral) motives. While there could be innumerable proximate motives for behavior, there is a
much smaller set of ultimate evolutionary functions that this behavior might serve (Kenrick et al.
2010). Consumer research literature, like most social scientists, has typically been concerned with
proximate reasons for behavior (for instance, what people want to feel or seek to avoid feeling),
whereas an evolutionary viewpoint emphasizes that there is a deeper level of explanation rooted in
the adaptive function of behavior (Griskevicius & Kenrick, in press). Therefore, according to the
aforementioned contributions, marketing scholars are focusing their investigation on the
understanding this deeper level of motivations determining as a result, the presence of an emerging
stream of research that aims to study the implications of activating ancestral motives on modern
consumer behavior. Given the novelty of this topic further research is required to analyze in greater
depth the implications of each of the seven fundamental motives on consumer behavior. As a result,
the focus of this thesis is on the effects of the activation of disease avoidance on consumer attitudes,
evaluations and choices.
In general, each fundamental motives, as well as disease avoidance, can be activated by
(Kenrick et al. 2010). My research project aims to focus especially on threats related to disease
avoidance activation. In particular, I want to study the role of two possible threats that can result
from the activation of the disease avoidance system: threats arising from the fear of disease and
threats arising from the disgust of contagion.
Consequently my research questions are:
1. What is the effect of fear resulting from the activation of the disease avoidance system on food attitudes, food purchase intentions and food choices of customers?
2. What is the effect of disgust resulting from the activation of the disease avoidance system on
second hand product attitudes, second hand product price evaluations and second hand product choices of customers?
2. Theoretical Framework: Disease avoidance system
Biologists estimate that infectious diseases have been an important selection pressure on the
human species (Gangestad & Buss, 1993). Despite the medical and technological discoveries that
have controlled and limited many diseases over time, virus and bacteria contagion still represent a
daily threat for humans. The result of this ever-present pathogen threat has been the evolution of a
biological immune system to fight off infection, and also the evolution of a psychological “behavioral immune system” that helps humans to avoid infection through their behaviors (Schaller & Park, 2011). In this perspective, considering the ramifications of interacting with an individual
who is potentially diseased, disease avoidance activation helped people over time to readily identify
diseased individuals and actively avoid them (Park, Faulkner & Schaller, 2003). In keeping with
most evolved mechanisms, these processes have been described as occurring quickly, with very
little conscious, rational thought or deliberation (Townsend & Hamilton, 2012). Consequently,
according to Griskevicius & Kenrick (in press), it is possible to define the disease avoidance system
infections in order to preserve their health. As a result, this avoidance tendency against all sources
of pathogens and infections, is generally associated with negative emotions, such as fear, anxiety,
disgust, etc. The theoretical and research contributions of the past two decades have established
emotions as a legitimate area of scientific inquiry in the field of marketing. Extensive efforts have
been devoted to investigating the role of emotions in marketing, borrowing theories of emotions
from psychology (Huang, 2001). Most of the existing theoretical contributions distinguish between
negative and positive emotions (see for example, Izard,1977; Mehrabian & Russell, 1974; Plutchik,
1980). Whereas positive emotions generally involve a sense of pleasure resulting from a positive
event, negative emotions can result from problems with ongoing plans and failures to achieve
desired goals. They express an attempt or intention to exclude, keeping away or destroying what is
perceived as a threat (see also Stein, Liwag, & Wade, 1996). Consistent with these statements, this
thesis will focus on two particular negative emotions that can arise from disease avoidance
activation: fear and disgust. Since both disgust and fear have a dominant behavioral tendency of
avoidance (Izard, 1993), there is a considerable overlap between these two emotions. However they
present several differences. First, fear-motivated avoidance protects the person from perceived risk
in a general sense (i.e., any physical danger that might compromise his or her own health, Woody &
Teachman, 2000), whereas disgust-motivated avoidance appears to have the more specific function
of avoiding contaminations (Olatunji, Cisler, McKay, & Phillips, 2010). In addition, while fear
heightens activity in preparation for fight or flight (Phillips, Senior, Fahy, & David, 1998), disgust
involves a suspension of activity. With respect to the disease-avoidance system, the preparation for
fight associated with fear implies worry and alarm generated by a possible threat of infection,
whereas the suspension of activity associated with disgust implies the rejection (or refusal) of a
potential source of contagion. These arguments in turn imply a temporal distinction between the
two emotions, and in fact, fear precedes disgust. In particular, while fear arises as a form of caution
before being exposed to or in contact with a possible infectious source, disgust arises after being
Finally, with regard to the disease avoidance system, fear and disgust are distinguishable in
terms of certainty. Physical signals indicating an illness tend to be perceived as a threat that
prepares and motivates a person to escape from it generating fear (Izard, 1977; Townsend &
Hamilton, 2012). Consistent with its function as a reaction to threat, fear has been described as a
state of maximal uncertainty – given the precarious nature of threatening situations, the uncertainty in fear stems from the frightened person’s insecurity over what he or she should do and whether he or she will be able to escape or avoid the fear-eliciting object (Smith & Ellsworth, 1985).
Conversely, disgust has been conceptualized as “a revulsion” at the prospect of incorporation of an
offensive substance (Rozin & Fallon, 1987). This definition suggests that feelings of disgust are
related to physical contact between the disgusting object and the human body. In stark contrast to
fear, disgust has been associated with a strong sense of certainty, because a disgusted person is
certain what the problem is, knows how to deal with it, and is confident in his or her ability to do so
(Smith & Ellsworth, 1985).
Accordingly, fear of disease should be elicited by stimuli indicating threat of infection of an
uncertain nature, whereas disgust should be elicited by stimuli that clearly indicate a threat of contamination.
As a result, exposure to any physical signal indicating an abnormality (e.g., disfigured faces or
a person affected by disabilities or obesity) should affect fear-motivated avoidance, and not
disgust-motivated avoidance. This is because although people affected by disabilities are not able to infect
others, they are perceived as a possible threat of disease transmission (Faulkner et al. 2004).
However, the nature of this threat is not supported by specific reasons and therefore it is uncertain.
Conversely, the exposure to images related to dirtiness (e.g., dirty toilets or insects) should affect
disgust-motivated avoidance, and not fear-motivated avoidance. This because these images
unequivocally indicates a risk of contagion (Ryan, Oaten, Stevenson, & Case, 2012), and are
Consequently, in this research fear-avoidance will be elicited through stimuli showing physical
abnormalities (i.e., faces disfigured by a wine stain birthmark), whereas disgust-avoidance will be
elicited through stimuli showing dirtiness (i.e., dirty toilets, dirty foods, or vomit). Depending on
the triggered emotions (fear vs. disgust), the activation of disease avoidance system can lead to
interesting implications especially from a consumer research perspective. These implications will be
illustrate in the following two sections.
2.1 Disease Avoidance and Fear
Infections and disease transmission are perceived as a threat that scares people, generating fear.
The fear of contamination is the most common theme observed in obsessive-compulsive disorder
(Rasmussen & Tsuang, 1986). Recent theoretical developments have highlighted the complex,
powerful, and persistent nature of this fear (Rachman, 2004). Consequently, fear of disease creates a
series of avoiding behaviors, such as compulsive safety behaviors (i.e., excessive washing or
cleaning rituals) geared toward disinfection of the self and the environment (Rachman & Shafran,
1998), or becoming more socially avoidant, more introverted, or less tolerant for foreigners
(Mortensen, Becker, Ackerman, Neuberg, & Kenrick, 2010). Many other phenomena in the realm
of social cognition are influenced by fear of disease and by individual differences in chronic
concerns about disease transmission (Schaller & Duncan, 2007). For example, Park, Faulkner, &
Schaller (2003) demonstrated that people who feel particularly vulnerable to disease have fewer
friends with physical disabilities.
The disease avoidance system is mainly activated by cues suggesting the presence of
pathogens, skin lesions, or abnormalities (Schaller, Miller, Gervais, Yager & Chen, 2010). These
images can lead to individuals’ unconscious activation of specific avoidance behavior strategies that
For example, after seeing photographs that make germs and infections salient, people view
themselves as less extroverted and less open to new experiences (Mortensen et al. 2010). More
generally, disease avoidance activation predicts ethnocentric attitudes, antipathy toward individuals
who are obese or physically disabled, and preferences for facial characteristics associated with good
health (Faulkner et al. 2004). From these contributions it is possible to note that disease avoidance
activation generates a series of avoidance behaviors strategies. Accordingly, another possible
avoidance behavior strategy resulting from disease avoidance activation could be having a more
positive attitude toward healthy (vs. unhealthy) foods, and therefore avoiding unhealthy foods.
Healthy food is defined as any food believed to be “good for the health”, especially if high in fiber, natural vitamins, etc. Healthy foods are believed to reduce cholesterol, atherosclerosis and
risk of stroke; to help control glucose; to halt progression of osteoporosis; and to reduce the risk of
infections and cancer (source The Oxford English Dictionary).
Unhealthy food is defined as any food that is not regarded as being conducive to maintaining health. It includes fats, in particular of animal origin; “fast” foods – (low in fiber and vitamins); “junk food” (e.g., potato and corn chips, pretzels, crackers – high in salt and tropical oils); and “white sauces” (northern Italian cuisine, high in fat) (source The Oxford English Dictionary).
Researchers posit that unhealthy and healthy foods consumption, and its perceptual and sensory
drivers, has an evolutionary basis. For example, Wansink & Huckabee (2005) note that "fatty foods
helped our ancestors weather food shortages,... [and] sugar and the sweetness associated with it
helped them distinguish edible berries from poisonous ones". Furthermore, previous literature
shows that energy-dense (i.e., unhealthy) foods, while worse for long-term health, are better than
non-energy-dense foods in providing short-term energy stores, which human beings have been
hardwired to favor (Ostan et al. 2010). Consequently, from an evolutionary perspective unhealthy
foods are preferred to healthy foods.
However, the activation of fear of disease could reverse this expected effect. “Fear salience" is
event (Gore et al. 1998). A credible fear cue leads to increased threat appraisal perceptions (Witte &
Allen, 2000). This has important implications in the food domain, in that the short-term health
related costs of eating unhealthily are not always obvious (Schlosser, 2001). Thus, the use of a
credible fear cue should increase threat appraisal perceptions surrounding unhealthy eating. When
threat appraisal perceptions increase, people are more likely to adopt adaptive health protection
behaviors (Witte & Allen, 2000), and consequently the use of a fear cue should lead to positive and
adaptive healthy behavior. Thus, threat appraisal perceptions (through fear) should cause consumers
to muster more willpower to resist the natural impulsive urge to overconsume (underconsume)
unhealthy (healthy) food.
In this perspective, the disease avoidance system can be activated using the concept of
disfigurement. In fact, several authors have claimed that avoidance of people with disabilities, facial
lesions and disfigurement, among others characteristics, arises because such individuals trigger an innate disease avoidance system, which is primed to detect “disease-like” signs irrespective of their veracity (Oaten, Stevenson & Case, 2011). According to these studies the discomfort felt upon
viewing facial abnormalities may arise from a primal fear of contacting infections. Fear of
contagion arises due to the non conformity to the "normal facial standard" (without deformities)
generated by the specific abnormality (e.g., a disfigurement). This in turn generates a sense of
uncertainty about the health of the person with the disfigured face, which results in fear (and not in disgust)of contagion. As a result, subjects perceive disfigurement as a disease threat, implementing
an avoidance defense system against it. Consequently, I propose that the activation of the disease
avoidance system – and thus the fear of illness – through facial disfigurement exposure could
promote a more positive attitude, better purchase intentions, and choice of a more salutary food
option.
Therefore:
H1a: Fear of illness leads to more positive healthy food attitudes, and this relationship is mediated
H1b: Fear of illness leads to more positive healthy food purchase intentions, and this relationship is
mediated by the activation of disease avoidance.
H1c: Fear of illness leads to healthy food choice, and this relationship is mediated by the activation
of disease avoidance.
2.2 Disease avoidance and disgust
As previously mentioned, humans have a repertoire of behaviors that function to minimize
contact with pathogens. Some of these behaviors, and arguably the most important for humans in
the context of disease avoidance, are those resulting from the emotion of disgust (Curtis, Aunger,
& Rabie, 2004).
Disgust is typically experienced as a feeling of revulsion, sometimes accompanied by nausea,
along with a strong desire to withdraw from the eliciting stimulus (Rozin, Haidt & McCauley,
2000).
The proposed primary biological function of disgust is to protect the organism against disease
and contamination (Marzillier & Davey, 2004). However, some theorists have extended this basic “disease avoidance” view of the disgust response to suggest that the disgust emotion has evolved more sophisticated adaptive functions that protect not just the physical body but also the “psychological” body from contamination and harm by providing reminders of human mortality related to the threat of contamination by disgusting substances (Haidt, McCauley, & Rozin, 1994).
Viewed from this “psychological” perspective, disgust also serves to regulate behavior in social and
interpersonal contexts, affecting consumer social attitudes.
Disgust may produce specific autonomic responses, such as reduced blood pressure, heart rate
deceleration, and decreased skin conductance (Stark, Walter, Schienle, & Vaitl, 2005). A central
feature of certain cues that evoke disgust is that contact with them can result in a neutral object
Morales and Fitzsimons (2007) demonstrated the strong influence of disgust in a consumer
context. Using evidences from several studies, the authors developed a theory of product contagion,
in which disgusting products are believed to transfer offensive properties by physical contact with
other products they touch, thus influencing evaluations. The law of contagion argues that objects or
people can affect each other merely by touching; consequently, contagion happens when a source
(either a person or an object) passes some or even all of its properties to the target through touch.
Since the source is believed to transfer a contagious entity or “essence” to the target on contact, the
properties remain part of the target even after they are no longer touching (Morales & Fitzsimons,
2007). The law of contagion was first tested by Rozin, Millman, & Nemeroff (1986) in the realm of
disgust to show that these contagion beliefs are not limited to primitive cultures, but operate in
Western cultures as well. They found, for instance, that a drink touched briefly by a sterilized
cockroach became undesirable, as did a laundered shirt previously worn by a disliked person.
Because contact between objects is often how true microbial contamination occurs, a biological
view suggests that contagion beliefs have adaptive value and could have originated as a form of
protection against true physical contamination (Morales & Fitzsimons, 2007). This is in line with
Rozin and Fallon’s (1987) theory, that disgust is also elicited by physical contact with unpleasant or
unknown people. Consequently, according to the product contagion theory, another possible
response to disgust of contamination could be the avoidance of products touched by others. In fact,
Argo, Dahl & Morales (2006) demonstrated that consumers evaluate products previously touched
by other shoppers less favorably. This is because products touched by others can be perceived as
infected, carriers of germs. In addition, this perception of “infection” can in turn have interesting implications regarding the consumers’ attitude toward second hand products. In this scenario such products can be perceived as less desirable than brand new products because they are previously
used, and therefore have been touched (and "infected") by others. In a O’Reilly, Rocher, Hughes,
Goran, & Hand (1984) study, 76% of respondents indicated that they would not buy used
desirability of the second hand products was to avoid contamination. Because the original owners of
the used products remained anonymous to consumers, these feelings could not be based on
associations but instead suggest a belief that the clothing was contaminated simply because it had
been handled and owned by someone else previously.
From this perspective, the disease avoidance system can be activated using the concept of
dirtiness. Curtis & Biran (2001) defined the most common elicitors of disgust among several
different cultures. They found that substances of animal origin, poor hygiene, and bodily secretions
are perceived as disgusting, activating the disease avoidance motive. Also material that is seen to be “contaminated” or dirty, such as a stained toilet, clothes, sheets, or teeth, or rubbish on a beach, are able to generate disgust (Curtis & Biran, 2001). Disgust arises due to the deviation from the “normal standard of hygiene” generated by the dirty images which unequivocally creates a sense of revulsion, which results in turn, in disgust (and not in fear). As a result, subjects perceive stimuli
which are contaminated by others, or dirty stimuli more generally as a disease threat, implementing
an avoidance defense system against them.
Consequently, I propose that the activation of the disease avoidance system – and thus the
disgust of contagion – through exposure to dirty stimuli could promote a less positive preference in
terms of attitude, price evaluation and choice for brand new products.
Therefore:
H2a: Disgust leads to less positive attitudes toward second hand products, and this relationship is
mediated by the activation of disease avoidance.
H2b: Disgust leads to less positive price evaluation of second hand products, and this relationship is
mediated by the activation of disease avoidance.
H2c: Disgust leads to packaged product choice, and this relationship is mediated by the activation
3. Method
In order to test my hypotheses, I conducted two different lab experiments. The first experiment
tested how fear resulting from the activation of the disease avoidance system influences customers
attitudes, purchase intentions and choice of healthy (vs. unhealthy) foods, whereas the second
experiment tested how disgust resulting from the activation of the disease avoidance system
influences customers attitudes, price evaluation and choice of brand new (vs. second hand)
products. The two experiments were conceptually identical in design, but they differed in (1) the
stimuli used for eliciting fear vs. disgust, (2) the stimuli that were rated and chosen as dependent
variables (DV) (i.e., foods vs. products), and (3) the use of some specific control variables.
Specifically, in Study 1, fear was elicited following the Ryan et al. (2012) procedure, using faces
disfigured by a wine stain. Then participants rated a (pre-tested) pool of healthy vs. unhealthy foods
in terms of attitude and purchase intentions. In Study 2, disgust was elicited through International
Affective Picture System (IAPS) images related to dirtiness, and then participants rated a pool of
brand new vs. second-hand products in terms of attitude and price evaluation.
3.1 Study 1
Study 1 aimed to test three hypotheses. The first hypothesis was that exposure to disfigured
faces could promote a more positive attitude toward healthy (vs. unhealthy) foods, and this
relationship is mediated by the activation of the disease avoidance system. The second hypothesis
was that exposure to disfigured faces could promote a more positive purchase intention toward
healthy (vs. unhealthy) foods, and this relationship is mediated by the activation of the disease
avoidance system. Finally, the third hypothesis was that the exposure to disfigured faces could
promote a more healthy food choice, and this relationship is mediated by the activation of the
disease avoidance system.
Participants. The original sample was composed of 50 participants however six of them (five
not understand the study’s instructions. Consequently, the statistical analyses for Study 1 are conducted on a sample of 44 undergraduate students (17 males and 27 females), who participated in exchange for 4 Euro’s. The average age of the sample is 22.25 years (SD = 2.45), with an average weight of 68,86 kg (SD = 21,15) and an average height of 172,66 cm (SD = 11,10). In addition, only
10 of the 44 participants were following a diet. Finally, the results of the debriefing procedure
revealed that none of the 44 participants included into the analyses recognized the real purpose of
the experiment.
The study used a 2 (exposure: disfigured faces vs. control faces) x 2 (product: healthy vs.
unhealthy foods) design, with the first factor manipulated between-subjects and the second factor
within-subjects. As a result, the presence of the disfigured faces was the independent variable (IV)
that is a dummy variable equal to 1 if participants were exposed to the images, and equal to zero
otherwise. Consumer attitude, purchase intentions and consumer choice toward healthy (vs.
unhealthy) foods were the DVs.
Procedure. On arrival at the lab participants were informed that they would participate in a
series of unrelated studies. The experimenter placed each participants in a separate room with a
computer that provided all further instructions. Participants in the experimental condition were
primed with the disfigured faces, whereas participants in the control condition were primed with the
same faces but without disfigurement (the exact procedure will be explained further in the next
section). After target (vs. control) faces exposure, the disease avoidance system was measured by
asking participants to complete a task related to illnesses following the Greenberg, Pyszczynski,
Solomon, & Simon (1994) procedure.
Then, participants answered the Positive and Negative Affect Schedule (PANAS) questions (α
= .91; Watson, Clark, & Tellegen, 1988) in order to verify that participants in the experimental
condition were effectively scared by disfigured faces. After that a (fictitious) second study started
where participants were asked their attitudes toward a pool of healthy (10) and unhealthy (10) foods
= .70). This scale is composed of 15 items designed to assess either general beliefs about personal
susceptibility to infectious diseases or discomfort in situations in which the possibility of disease
transmission was salient (Duncan, Schaller & Park, 2009). After that, participants were asked about
their purchase intentions of healthy (vs. unhealthy) foods through a budget allocation task that will
be explained later.
Finally, in order to ascertain that nobody identified the real purpose of the study, participants
answered the “funneled debriefing” questions (Bargh & Chartrand, 2000) and then some
demographic questions (including gender, age and questions related to weight, stature and whether
participants were following a diet).
Subsequently, food choice was measured using the following procedure: participants were
informed that the study was completed and that in few minutes a research assistant would proceed
to pay them. Meanwhile they were offered, as a sort of additional reward, a choice between
chocolates (M&M’s) or grapes, contained in two separate transparent dispensers. The expectations
were that participants in the experimental condition would be more likely to choose grapes than
participants in the control condition. After the food choice the experimenter debriefed, paid and
thanked participants for their attendance.
Independent Variable: Exposure to disfigured faces. On the basis of Oaten et al.’s (2011)
paper, the IV was operationalized choosing six neutral faces (three of females and three of males)
each of which was modified adding a wine stain birthmark (each face is shown in the Appendix
section).
Participants in the experimental condition were exposed to the modified faces (from here on:
target faces), whereas participants in the control condition were exposed to the neutral faces (from
here on: control faces). Target (vs. control) faces were randomly shown using the following
procedure: participants were exposed to six screenshots, each showing six images, in which two of
them were identical. Each of the six screenshots contained one different target (vs. control) face
select the pair of identical (unrelated) images as quickly as possible. This task allowed participants
to have six exposures to the target vs. control faces. In order to avoid demand effect, the position of
the target (vs. control) faces and the position of the two identical unrelated images were changed for
each screenshot. Figure 1 shows one of the six screenshots used in the experimental condition.
Figure 1: One of the six screenshots used in the experimental condition
Dependent Variables.
Food Attitude was measured through three 7-point scales (where 1 = “Not at all/Very negative”
and 7 = “Very much/Very positive”). Participants were asked three questions about their attitude toward a pool of 20 (10 healthy and 10 unhealthy) pre-tested alternatives foods (“how much do you like …” “what is your attitude toward …”, “how desirable is …” ). In order to have two overall attitudinal scores, I first performed a reliability analysis for the three attitude items used for both
healthy (αHealt_Food = .89) and unhealthy food (αUnhealt_Food = .88) and then I constructed two overall
average attitudinal scores for healthy and unhealthy foods.
Food Purchase Intention was operationalized through an allocation budget task. Participants
in both conditions were informed that they had a fixed budget (i.e., 10 €) that had to be allocated
two healthy and two unhealthy (randomly selected from the pre-tested pool of healthy/unhealthy
foods). In particular, using a scenario, participants were asked for each of the five food combinations to allocate their budget (10 €) among the four foods, choosing the combination and the quantity that they liked most. Each food shown in the screenshots was assigned the same price;
in particular, the foods presented in three screenshots were priced at 1€, whereas the foods
presented in the remaining two screenshots were priced at 2 €. This allowed me to control for the
price sensitivity of participants.
The expectation was that participants in the experimental treatment preferred to allocate the
majority of their budget to healthy (vs. unhealthy) foods in comparison to the control group. Figure
2 shows one of the five screenshots used in the study.
Figure 2: One of the five budget allocation task used in Study 1
Food Choice was operationalized as following: before leaving the lab, participants were
allowed to choose (as a sort of additional reward) between chocolates (M&M’s) or grapes (black
and white) placed in two transparent containers. In particular, participants were informed that they
caould have a free snack as additional compensation for their attendance at the experiment. This
experimental treatment preferred grapes (proxy for healthy food) to chocolate (proxy for unhealthy
food) in comparison to the control group.
Mediator. Disease Avoidance Activation was operationalized following the Greenberg et al.
procedures (1994). Participants completed a set of 25 incomplete words by filling in one or more
missing letters. Participants could complete a part of these words as either neutral or illness-related
words, and the remaining words served as filler items (e.g., “Ill …” can be completed as “illness” or “illumed” or “…alad ...” can be completed as “malady” or “salads” etc.).
The Appendix section includes a complete list of all variables used in Experiment 1 plus the
results of the pre-test performed to choose the healthy vs. unhealthy foods pool.
3.2 Results and Discussion
As previously mentioned, the statistical analyses for Study 1 were conducted on a sample of 44
subjects that ensured the presence of at least 20 subjects for the experimental and control condition.
The results of the debriefing procedure revealed that none of the participants recognized that
they were exposed to disfigured faces, and therefore none recognized the real purpose of the
experiment. This enabled us to include all the 44 participants in the analyses.
Manipulation Check
In order to assess whether exposure to disfigured faces activated fear of disease, a series of
manipulation check-items using 7 point Likert statements (1 = Fully disagree, 7 = Fully agree)
(Faulkner, Schaller, Park, & Duncan, 2004). The analyses for “scary” mood showed that on average
the experimental and control conditions were statistically equivalent (MExp = 2.30 SD = 1.46, MContr
= 2.00 SD = 1.27; F(1,42) = .54, ns). This means that participants were not scared by disfigured
faces. Consequently, the manipulation was not successful. This represents a first weakness of the
study, because the experimental stimuli were not able to activate fear.
Conversely, the manipulation was successful with regard to “ashamed” and “guilty” moods at
5% and 10% respectively. In fact, participants in the experimental condition were more ashamed
(Mexp = 3.13, SD = 1.91; Mcontr = 2.10, SD = 1.45; F(1,42) = 4.04, p = .05) and guilty (Mexp = 2.17,
SD = 1.23; Mcontr = 1.52, SD = 1.12; (F(1,42) = 3.33, p = .07). This means that even though
participants were not scared, they were at least disturbed by the exposure to disfigured faces.
Apart from “guilty” and “ashamed” moods, analyses revealed that no other PANAS items
statistically affected the cognitive accessibility of disease-related words, food attitude, food
spending intention, or food choice.
PDV scale.
Analysis of variance on PDV items (F(1,44) = .72, ns) indicated that participants’ perceived
vulnerability to diseases was not affected by exposure to disfigured faces. Hence, personal
perceived vulnerability to diseases cannot account for the differences in cognitive accessibility of
disease-related words, food attitude, food spending intention, or food choice.
Disease Avoidance Activation.
An ANOVA on the number of completed disease-related words among the experimental (vs.
control) condition showed that on average the experimental and control conditions were statistically
equivalent (Mexp = 6.61, SD = 2.62, Mcontr = 7.14, SD = 2.41; F(1,42) = .49, ns). Consequently, there
was no difference between participants that were exposed to disfigured faces and participants that
Food Attitude.
In order to test the presence of a main effect between target faces exposure and healthy (vs.
unhealthy) food attitude, I conducted a 2 (exposure: target vs. control faces) x 2 (attitude: Healthy
vs. Unhealthy food) ANOVA, with the first factor manipulated between subjects and the second
factor within subjects.
In line with the predictions, the test of within-subjects effects gives a marginally significant
interaction effect between healthy food attitude and experimental (vs. control) condition (F(1,42) =
2.38, p =.06), indicating that participants exposed to disfigured faces evaluated healthy foods more
positively (MHealthyExp = 5.77, SD = .62) than participants in the control condition (MHealthyCont =
5.36, SD = .75). This implies that the exposure to faces disfigured by a wine stain birthmark was
able to influences food attitudes, but only for healthy food evaluation. In fact, the results show that
exposure to target faces did not significantly influenced unhealthy food attitude (MUnhealthyExp = 4.41,
SD = .71; MUnhealthyCont = 4.66, SD = .87; F(1,42) = 1.06, ns). Figure 3 shows the estimated marginal
means for both healthy and unhealthy food attitudes across the experimental and control condition.
From the graph it is possible to note that the difference of the mean levels between healthy and
unhealthy food attitudes is higher in the experimental condition than in the control condition. This
implies that, as expected, the exposure to disfigured faces generates a sense of discomfort that in
turn increases positive attitudes toward actions that reduce illness threat over time, promoting
therefore a long-term survival instinct, through a more positive attitude toward healthy (vs.
Figure 3: Estimated marginal means for both healthy and unhealthy food attitude across experimental and control conditions.
Consequently, although disfigured faces were not able to scare participants and to activate the
disease avoidance system, they were able to generate a sense of discomfort (embarrassment and
guilt) that generated a more positive attitude toward healthy foods.
These results allow me to state that exposure to disfigured faces leads to higher healthy food
attitudes.
Food Purchase Intentions.
With respect to the original sample of 44 participants, only 34 subjects completed the budget
allocation task (15 participants for the experimental condition and 19 for the control condition),
whereas the remaining 10 participants skipped the task not indicating any spending intentions. In
order to test the presence of a main effect between target images exposure and healthy (vs.
unhealthy) food spending intentions, I first aggregated all the spending intentions given for healthy
foods and all the spending intentions given for unhealthy foods, obtaining two overall spending
intention scores: one for healthy foods and another one for unhealthy foods.
After that a 2 (exposure: target vs. control faces) x 2 (spending intentions: healthy vs. unhealthy
food) ANOVA was performed, with the first factor manipulated between subjects and the second
factor within subjects.
Contrary to expectations, the interaction effect between the experimental (vs. control) condition
and healthy (vs. unhealthy) food spending intentions is not statistically significant (MHealthy_Food_EXP
= 26.20, SD = 4.66; MHealthy_Food_CONTR = 23.58, SD = 6.07; MUnhealthy_Food_EXP = 14.53, SD = 4.88;
MUnhealthy_Food_CONTR = 16.26, SD = 5.94; F(1,32) = 1.33, ns).
On the basis of these results it is possible to state that the exposure to disfigured faces does not
lead to greater healthy food purchase intentions.
Food Choice.
In order to test the presence of a main effect between target images exposure (IV) and food
choice (chocolates, proxy for unhealthy foods vs. grapes, proxy for healthy foods, DV), I performed
a Chi-Square Test. However, there is not statistically difference between the distribution of
chocolates vs. grapes in the experimental vs. control condition (chocolates_exp = 6; chocolates_contr =
10; grapes_exp = 17; grapes_contr = 11, χ2 = .21, ns). Therefore, it is not possible to conclude that the
exposure to the target images creates a greater tendency to choose healthy (vs. unhealthy) foods.
Mediation Analysis.
A mediation analysis (cf. Baron & Kenny, 1986; Zhao, Lynch & Chen, 2010) tested the
hypothesis that disease avoidance activation mediates the relation between IV (target faces
exposure) and the three different analyzed DVs (attitude, purchase intentions and choice of healthy
vs. unhealthy foods). However, since experimental condition did not significantly influence food
spending intentions, food choice (DVs) or disease avoidance activation, the mediation analysis will
Mediation Analysis – healthy food attitude (DV). The first regression analysis, with healthy
food attitude as the dependent variable and target faces exposure (dummy coded) as the predictor,
yielded a significant relation (β = -.30, p = .05). A second regression analysis, with the mediator
(disease avoidance activation) as the dependent variable and target faces exposure as the predictor,
showed that target faces exposure did not influence disease avoidance activation significantly (β =
.11, ns). Since there is not significant relationship between target faces exposure (predictor) and
disease avoidance activation (mediator) there is no reason to continue to test for the mediation
effect of the disease avoidance system on the relationship between target face exposure (IV) and
healthy food attitude (DV).
These findings do not support the hypothesis that disease avoidance can be induced by priming
with disfigured faces, and therefore mediate the relationship between target face exposure and
healthy food attitude.
Mediation Analysis – unhealthy food attitude (DV). Since there is not a significant
relationship between target faces exposure (predictor) and disease avoidance activation (mediator)
there is no reason to test for the mediation effect of the disease avoidance system on the relationship
between target faces exposure (IV) and unhealthy food attitude (DV). Consequently, disease
avoidance does not mediate the relationship between target faces exposure and unhealthy food
attitude.
On the basis of these results it is possible to conclude that H1 must be rejected, with the
exception of H1a that can be partially accepted. Consequently, faces disfigured by a wine stain
birthmark do not activate fear of illness and do not lead to healthy food preferences in terms of
purchase intentions and choice, but lead to healthy food preference in terms of attitude. However,
3.3 Study 2
Study 2 aimed to test three hypotheses. The first hypothesis was that the exposure to IAPS
target images could promote a less positive attitude toward second-hand (vs. brand new) products,
and this relationship is mediated by the activation of the disease avoidance system. The second
hypothesis was that the exposure to IAPS target images could promote a less positive price
evaluation of second hand (vs. brand new) products, and this relationship is mediated by the
activation of the disease avoidance system. Finally, the third hypothesis was that the exposure to
IAPS target images could promote a higher likelihood of choosing packaged products, and this
relationship is mediated by the activation of the disease avoidance system.
Participants. The original sample was composed of 55 participants, however one of them was
removed from the analyses because his answers revealed that he did not understand the study’s instructions. Consequently, the statistical analyses for Study 2 are conducted on a sample of 54
undergraduate students (26 female, 28 male; Mage = 22.15 years, SD = 3.06), who participated in
exchange for 4 Euro’s. The study used a 2 (exposure: dirty vs. control image) x 2 (product: brand new vs. second hand products) design, with the first factor manipulated between-subjects and the
second factor within-subjects. As a result, the presence of the dirty images was the IV that is a
dummy variable equal to 1 if participants were exposed to the images, and equal to zero otherwise.
Consumer attitude, price evaluation and choice of packaged (vs. unpackaged) products were the
DVs.
Procedure. On arrival at the lab participants were informed that they would participate in a
series of unrelated studies. The experimenter placed each participants in a separate room with a
computer that provided all further instructions. Using the same procedure illustrated for Study 1,
participants in the experimental condition were primed with the dirty images, whereas participants
exposure, the disease avoidance system was measured by asking participants to complete a task
related to illnesses following the Greenberg et al. (1994) procedure. Then, in order to assess their
mood and emotions, participants answered PANAS questions (α = .89; Watson et al. 1988). After
that, in order to verify that participants in the experimental condition were effectively disgusted by
IAPS target images, they answered the Brief Mood Introspection (BMIS) scale (α = .82; Mayer &
Gaschke, 1988) with the addition of two specific emotions related to nausea (i.e., disgust and
cloyed), and to four emotions (two positives and two negatives) provided by Izard (1977)
classification (that were not present in the PANAS and BMIS scales).
Next, a (fictitious) second study started where participants were asked about their attitudes
toward a pool of 10 brand new and 10 second hand products shown randomly. In order to control
for their perceived vulnerability to disease, participants completed the PDV scale (α = . 89; Duncan
et al. 2009). After that, they were asked to assign a reasonable price to each brand new and second
hand product previously shown in the attitudinal evaluation task. Then, price sensitivity of
participants (α = .69) was measured using the Lichtenstein, Netemeyer, & Burton (1990) scale.
After that, participants completed eight items of the disgust scale (α = .79) provided by Haidt,
McCauley & Rozin, 1994. Finally, in order to ascertain that nobody identified the real purpose of
the study, participants answered the “funneled debriefing” questions (Bargh & Chartrand, 2000) and
then demographic questions (gender and age). Next, product choice was measured using the
following procedure: participants were informed that the experiment was completed and that in few
minutes a research assistant would proceed to pay them. Meanwhile, they were offered free candies
as a sort of additional reward. However, participants could choose between packaged candies
(proxy for uncontaminated and therefore for a brand new product) or the same candies but
unpackaged (proxy for contaminated/touched by others and therefore for second hand product)
positioned in two separate dishes. The expectation was that participants in the experimental
condition. After the candy choice the experimenter debriefed, paid and thanked participants for their
attendance.
Independent Variable: Disgust. The IV was operationalized choosing 12 pictures from the
IAPS database, six that elicited dirtiness and six other unrelated images (each image is shown in the
Appendix). Participants in the experimental condition were randomly exposed to the dirty images
(from here on: target images), whereas participants in the control condition were randomly exposed
to the unrelated images (from here on: control images) using the same procedure previously
described for Study 1. Figure 4 shows one of the six screenshots used in the experimental
condition.
Figure 4: One of the six screenshots used in the experimental condition
Dependent Variables.
Product Attitude was measured through three 7-point scale questions (where 1 = “Not at
…”). In particular, for brand new products, 10 different products (four cooking utensils, two unisex accessories, two bedroom accessories, a bathrobe, and a towel set) were chosen and presented to
participants, whereas for second hand products the same 10 brand new products images were
presented but using an eBay framework (see Appendix for the complete list of the used images). In
order to have two overall attitudinal scores, I first performed a reliability analysis for the three attitude items used for brand new (αBrand_New = .89) and second hand products (αSecond_Hand = .89) and
then I constructed two overall average attitudinal scores for both brand new and second hand
products.
Using a scenario, participants were informed that they had to evaluate a series of products
furnished by a (fictitious) e-commerce web site that sells both brand new and second hand products,
and that they could recognize the second-hand products by the eBay framework presence.
Product Price Evaluation was operationalized by asking participants to give a reasonable price
to the same brand new (vs. second hand) products shown for the attitude measurement questions. In
particular, participants were informed that the (fictitious) e-commerce web site was interested in
knowing a possible reasonable price for their products, so participants were asked “What is in your
opinion a reasonable price (in Euros) for this product?” All the price evaluations given for brand
new products and all the price evaluations given for second hand products were then aggregated,
obtaining two overall price evaluation scores: one for brand new products, and one for second hand
products.
Again, participants were informed that the products with the eBay framework were second
hand products.
Product Choice was operationalized as following: before leaving the lab, participants were
offered a choice (as a sort of additional reward) between packaged or unpackaged candies placed in
two separate trays. In particular, participants were informed that they could have some free candies
participants in the experimental treatment would have a higher preference for packaged candies
(proxy for brand new product) than for unpackaged candies (proxy for contaminated/touched by
others, or second hand product) in comparison to participants in the control group.
Mediator: Disease Avoidance Activation was operationalized using the same procedure as
Experiment1. The Appendix section provides a complete list of all variables used in the Experiment
2 plus the brand new vs. second hand product stimuli.
3.4 Results and Discussion
As previously mentioned, the statistical analyses for Study 2 were conducted on a sample of 54
subjects, that ensured the presence of at least 20 subjects for the experimental and control
conditions.
The results of the debriefing procedure revealed that none of the participants recognized that
they were exposed to IAPS images, and therefore none recognized the real purpose of the
experiment. This enable us to include all 54 participants in the analyses.
Manipulation Check.
In order to assess whether target IAPS images exposure activated disgust of contamination, a
series of manipulation check-items using 7 point Likert statements (1 = Fully disagree, 7 = Fully
agree) were administered. More specifically, I used the two BMIS items (modified for the study purpose) “Disgusted” and “Cloyed” and the disgust scale mean. Then, I performed the analysis of variance with respect to the experimental (vs. control) condition.
The results revealed that on average there is not a statistical difference between the control and
experimental conditions with regard to the BMIS items of disgust (Mexp = 2.46, SD = 1.77; Mcontr =
1.96, SD = 1.37; F(1,52) = 1.34, ns) and cloyed (Mexp = 3.39, SD = 1.20, Mcontr = 3.42, SD = 1.03;
experimental conditions with regard to the disgust scale mean (Mexp = 4.37, SD = 1.20, Mcontr =
4.14, SD = .97; F(1,52) = .55, ns). This means that participants were not disgusted by target IAPS
images. Consequently, the manipulation was not successful, implying that participants in the
experimental condition were not significantly disgusted and disturbed by IAPS target images
exposure.
In addition, analyses revealed that none of the other BMIS items statistically affected the
cognitive accessibility of disease-related words, products attitudes, products price evaluations and
product choice.
PDV scale.
Analysis of variance on PDV items (F(1,52) = .35, ns) indicated that participants’ perceived
vulnerability to diseases was not affected by target images exposure. Hence, personal perceived
vulnerability to diseases cannot account for the differences in cognitive accessibility of
disease-related words, products attitudes, products price evaluations and product choice.
Price sensitivity scale.
In order to demonstrate that participants’ product evaluation (in terms of price) was not affected
by their price sensitivity, the analysis of variance on price sensitivity scale items with respect to the
price evaluation of brand new and second hand products was conducted. The results demonstrated
that both brand new product evaluations (F(1,52) = 1.06, ns) and second hand products evaluations
(F(1,52) = .94, ns) were not affected by respondents’ price sensitivity.
Mood.
Analysis of variance on the positive items of the PANAS (F(1,52) = .01, ns) and the negative
items of the PANAS (F(1,52) = .14, ns) indicated that participants’ mood states were not affected
accessibility of disease-related words, products attitudes, products price evaluations and product
choice.
Disease Avoidance Activation.
An ANOVA on the number of completed disease-related words in the experimental (vs.
control) condition showed that on average the experimental and control conditions were statistically
equivalent (Mexp = 6.96, SD = 2.01, Mcontr = 6.35, SD = 3.12; F(1,52) = .759, ns). Consequently,
there is no difference between participants who were exposed to target IAPS images and
participants who were exposed to control IAPS images in the disease avoidance activation.
Product Attitude.
In order to test the presence of a main effect between target IAPS images exposure and brand
new (vs. second hand) products attitude I conducted a 2 (IAPS images: target vs. control) x 2
(products attitude: brand new vs. second hand) ANOVA, with the first factor manipulated between
subjects and the second factors within subjects.
In line with the predictions, the test of within-subjects effects gives a significant interaction
effect of second hand product attitude at 5% of significance (F(1,52) = 7.11, p =.01), indicating that
participants exposed to IAPS target images evaluated second hand products less positively
(MSec_Hand_Exp = 3.06, SD = .75) than participants in the control condition (MSec_Hand_Cont = 3.47, SD =
.73). This implies that the exposure to IAPS images related to dirtiness is able to influences
products attitudes, but only for second hand product evaluation. In fact, the results show that IAPS
target images exposure did not significantly influence brand new product attitude (MBrand_New_Exp =
4.91, SD = .60; MBrand_New_Cont = 4.64, SD = .80; F(1,52) = 2.14, ns). Figure 5 shows the estimated
marginal means for both healthy and unhealthy food attitude across the experimental and control
conditions. From the graph it is possible to note that the difference of the mean levels between
brand new and second hand products attitude is higher in the experimental condition than in the
attitude toward products previously owned or touched by others is lower than to when they are
exposed to control images. The dirtiness elicited by target images is presumably transferred to
second hand products, which are perceived as contaminated and therefore less desirable.
Figure 5: Estimated marginal means for both healthy and unhealthy food attitude across the experimental and control conditions.
Consequently, although the IAPS target images were not able to disgust participants and to
activate the disease avoidance system, they were able to generate a less positive attitude toward
second hand products. This evidence suggests that the exposure to images related to dirtiness
generates a more negative attitude toward second hand products.
Product Price Evaluation.
In order to test the presence of a main effect between target IAPS images exposure and brand
new (vs. second hand) products evaluation in terms of price, I conducted a 2 (IAPS images: target
vs. control) x 2 (price evaluation: brand new vs. second hand products) ANOVA, with the first
factor manipulated between subjects and the second factor within subjects. Contrary to
expectations, the interaction effect between the experimental (vs. control) condition and second
hand products price evaluation is not statistically significant (MSecond_Hand_EXP = 6.03, SD = 3.26;
MSecond_Hand_CONTR = 7.95, SD = 3.62; MBrand_New_EXP = 17.86, SD = 8.70; MBrand_New_CONTR = 18.11,
SD = 6.50; F(1,52) = 1.079, ns).
On the basis of these results it is possible to state that the exposure to target IAPS images does
not lead to lower second hand product price evaluation.
Product Choice.
In order to test the presence of a main effect between target IAPS images exposure (IV) and
product choice (packaged candies, proxy for brand new product, vs. unpackaged candies, proxy for
second hand product; DV), I performed a Chi- Square Test. Only 48 participants accepted a candy
as an additional reward, while the remaining six refused it. The results revealed that there is no
statistically significant difference between the distribution of packaged vs. unpackaged candies in
the experimental vs. control condition (packaged_exp = 12; packaged_contr = 16; unpackaged_exp= 12;
unpackaged_contr = 8, χ
2
= 1.37, ns). Therefore, it is again not possible to conclude that the exposure
to the target IAPS images creates a greater tendency to choose packaged vs. unpackaged products.
Mediation Analysis.
A mediation analysis (cf. Baron & Kenny, 1986; Zhao et al. 2010) tested the hypothesis that
disease avoidance activation mediates the relation between IV (IAPS target images exposure) and
the three different analyzed DVs (attitude, price evaluation and choice of brand new vs. second
hand products). However, since experimental condition did not significantly influence product price
evaluation, product choice (DVs) and disease avoidance activation, the mediation analysis will be
presented only for second hand and brand new products attitude DVs.
Mediation Analysis – second hand products attitude (DV). The first regression analysis, with
coded) as the predictor, yielded a significant relation at 5% of significance (β = 1.92, p = .04). A
second regression analysis, with the mediator (disease avoidance activation) as the dependent
variable and target IAPS images exposure as the predictor, showed that target images exposure did
not influence disease avoidance activation significantly (β = -.12, ns). Since there is not a
significant relationship between target images exposure (predictor) and disease avoidance activation
(mediator) there is no reason to continue to test for the mediation effect of disease avoidance system
on the relationship between target images exposure (IV) and second hand products attitude (DV).
These findings do not support the hypothesis that disease avoidance can be induced by priming
with IAPS images, and therefore mediate the relationship between IAPS target images exposure and
second hand products attitude.
Mediation Analysis – brand new products attitude (DV). Since there is not a significant
relationship between target images exposure (predictor) and disease avoidance activation (mediator)
there is no reason to test for the mediation effect of the disease avoidance system on the relationship
between target images exposure (IV) and brand new products attitude (DV). Consequently, disease
avoidance does not mediate the relationship between target faces exposure and unhealthy food
attitude.
These findings do not support the hypothesis that disease avoidance can be induced by priming
IAPS target images, and therefore mediate the relationship between IAPS target images exposure
and brand new products attitude.
In sum, the results of the two experimental studies show that the exposure to disfigured faces
generates a more positive attitude toward healthy foods, and that exposure to IAPS images related
to dirtiness generates a less positive attitude toward second hand products. A more detailed
Table 1 Results Summary
HYPOTHESIS DESCRIPTION GRAPHICAL DESCRIPTION RESULT
H1a
H1a: Fear of illness leads to more
positive healthy food attitudes, and this relationship is mediated by the activation of disease avoidance.
Interaction Effect significant; Mediation ns
H1b
H1b: Fear of illness leads to more
positive healthy food purchase intentions, and this relationship is mediated by the activation of disease
avoidance.
Rejected
H1c
H1c: Fear of illness leads to healthy food
choice, and this relationship is mediated by the activation of disease avoidance.
Rejected
H2a
H2a: Disgust leads to less positive
attitudes toward second hand products, and this relationship is mediated by the
activation of disease avoidance.
Interaction Effect significant; Mediation ns H2b .
H2b: Disgust leads to less positive price
evaluation of second hand products,and this relationship is mediated by the
activation of disease avoidance.
Rejected
H2c
H2c: Disgust leads to packaged product
choice, and this relationship is mediated by the activation of disease avoidance.
Rejected
Fear illness Healthy
Food Att +
Dis.Avoidance
Fear illness Healthy
Food Choic +
Dis.Avoidance
+
Fear illness Healthy Food
