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The Impact of Product Name on Dieters’ and Nondieters’ Food Evaluations and Consumption

Caglar Irmak, Beth Vallen and Stefanie Rosen Robinson
Journal of Consumer Research
Vol. 38, No. 2 (August 2011), pp. 390-405
Published by: Oxford University Press
DOI: 10.1086/660044
Stable URL: http://www.jstor.org/stable/10.1086/660044
Page Count: 16
Subjects: Business Marketing & Advertising
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The Impact of Product Name on Dieters’ and Nondieters’ Food Evaluations and Consumption

Caglar Irmak,
Beth Vallen, and
Stefanie Rosen Robinson

This research explores the impact of merely altering the name of a food on dieters’ and nondieters’ evaluations of the food’s healthfulness and taste, as well as consumption. Four studies demonstrate that when a food is identified by a relatively unhealthy name (e.g., pasta), dieters perceive the item to be less healthful and less tasty than do nondieters. When the identical food is assigned a relatively healthy name (e.g., salad), however, dieting tendency has no effect on product evaluations. This effect, which results in differences in actual food consumption, is explained by nondieters’ insensitivity to food cues as well as dieters’ reliance on cues indicating a lack of healthfulness and tendency to employ heuristic information processing when evaluating foods. These findings contribute to the body of literature that explores both individual and contextual factors that influence food evaluation and consumption.

The name of a food item can provide consumers with relevant information about its nutritional value; for instance, an item identified as an apple is clearly a nutritious snack, while a cupcake is not. Yet the ambiguity inherent in the naming of some products might lead individuals to draw inferences regarding an item’s nutritional value that override other product information (e.g., ingredients, appearance, portion size). One such item, Romano’s Macaroni Grill Chicken Florentine Salad, is listed as a salad option, while it might as well be listed alongside the restaurant’s pasta entrées as it consists of orzo pasta, grilled chicken, fresh spinach, diced tomatoes, and capers and provides a diner with 900 calories and 60 grams of fat (Hungry Girl 2009). Such ambiguity is prevalent in the food industry; potato chips are marketed as “veggie chips,” milk shakes are sold as “smoothies,” and sugary drinks have been repositioned as “flavored water,” although the names of the latter item in each pair might lead a consumer to infer undue nutritional superiority over the former (Buia 2003; Consumer Reports on Health 2007; Newsweek 2003).

In the current research, we investigate the influence of merely altering the name of a food item on dieters’ and nondieters’ evaluations of its healthfulness and taste, as well as consumption. In four studies we show that when a food item is assigned a relatively healthy name (e.g., salad), dieting tendency does not affect health or taste perceptions; when the identical item (e.g., an item with the same ingredients, appearance, portion size) is assigned a relatively unhealthy name (e.g., pasta), however, dieters perceive the item to be less healthful and less tasty than do nondieters. These evaluations, in turn, affect consumption.

These effects are driven by differences in information processing based on dieting tendency. In particular, while dieters are highly susceptible to cues suggesting that particular food items should be classified as “forbidden” and, hence, should be avoided (Knight and Boland 1989), nondieters lack the motivation to limit their food consumption and, thus, are less sensitive to such cues. Moreover, dieters’ cognitive resources are preoccupied by eating and body image (Green et al. 2003; Green and Rogers 1995), rendering them more likely to rely on such cues and to engage in heuristic processing when evaluating foods than nondieters, who are free from such concerns. As such, the effect of product name and dieting tendency is mitigated for individuals who are high (vs. low) in need for cognition (Cacioppo and Petty 1982) and when individuals employ bottom-up, systematic information processing (vs. top-down, holistic processing) to evaluate foods.

This work builds on extant literature on nutrition- and taste-related inferences in several important ways. First, our findings extend prior research on perceptions of healthfulness and consumption of food items (Chandon and Wansink 2007a, 2007b; Howlett et al. 2009) by demonstrating that merely altering the name of a food item—without changing any additional information provided to consumers—can affect the inferences that certain consumers make about an item’s healthfulness. In demonstrating that dieters rely on heuristics to a greater extent than nondieters when evaluating foods, we add to recent research that demonstrates the increased susceptibility of dieters (vs. nondieters) to food-related cues that affect product evaluations and, importantly, food consumption (Scott et al. 2008). Moreover, while extant research in the consumer behavior and nutrition domains focuses primarily on the behavior of dieters, this work also provides insight into the behavior of nondieters by showing that the evaluations and consumption behavior of these individuals are not likely to be influenced by cues such as product name. Finally, building on research on the unhealthy = tasty intuition (Raghunathan, Naylor, and Hoyer 2006), we demonstrate that dieters rate products they perceive to be less healthy as less tasty, which affects consumption behavior. These contributions carry important implications for understanding consumer behavior related to food choice and consumption, as well as for food-marketing practices and public policy aimed at assisting consumers in making optimal nutrition-related decisions.

Conceptual Framework

Consumers often draw inferences about the overall healthfulness of food items, using product attribute information as cues for judgment. Nutrition information presented on food labels (Kozup, Creyer, and Burton 2003), objective meal sizes (Chandon and Wansink 2007b), nutrient content claims (e.g., “low fat”), health benefit claims (e.g., “may increase bone density”; Andrews, Netemeyer, and Burton 1998; Geyskens et al. 2007; Roe, Levy, and Derby 1999; Wansink and Chandon 2006), and brand names (Chandon and Wansink 2007a) may affect consumer evaluations of the healthfulness of foods. Moreover, prior research has shown that consumers tend to classify foods into dichotomous categories of “good” and “bad,” leading to inferences related to foods’ nutritional value (Oakes and Slotterback 2001; Rozin, Ashmore, and Markwith 1996). For example, individuals believe that snacks that tend to be seen as reputable or “good” in terms of health (e.g., raisins) promote less weight gain than disreputable or “bad” snacks (e.g., potato chips), even when they are provided with objective nutrition information indicating that both items contain the same number of calories (Oakes 2005).

The name of a food item—which is often associated with healthfulness or a lack thereof (e.g., salad is healthful; pasta is unhealthful)—is likely to act as a cue for evaluating a food’s nutritional value. Such inferences are likely to lead to diet-appropriate decisions in cases where the product name is relatively unambiguous (e.g., an apple or a cupcake) or for those product names that are regulated by the Food and Drug Administration (FDA; e.g., juice-based products, peanut spreads, and products containing certain fishes; Food and Drug Administration 2009, sec. 102). However, for more ambiguous items (e.g., an item containing both vegetables and pasta) that may be framed as more versus less healthful on the basis of the name assigned (e.g., salad vs. pasta), reliance on the name of the food—rather than information related to product attributes (e.g., calories, ingredients)—to evaluate the item’s healthfulness may result in different health perceptions depending on the “good” or “bad” category that the product name implies.

Notably, the influence of product name on food evaluations is likely to vary on the basis of individual dieting tendency. Dieters and nondieters differ in their motivation and propensity to exhibit self-control in the eating domain. While dieters strive to behave in line with self-regulatory goals related to food consumption, nondieters do not have such goals to follow (Martz, Stugis, and Gustafson 1996; Ward and Mann 2000). Given their motivation to avoid diet-unfriendly options, dieters tend to classify certain foods as “forbidden” (e.g., pasta, ice cream, potato chips, candy) and rate a greater number of foods as forbidden than do nondieters (Knight and Boland 1989). Interestingly, while dieters consider foods that are members of unhealthy categories to be more forbidden than do nondieters, these individuals do not rate foods that are members of healthy food categories as less forbidden (Francis, Stewart, and Hounsell 1997). As a result, dieters tend to focus their attention on forbidden food categories in order to avoid less healthful foods (Gonzalez and Vitousek 2004; Knight and Boland 1989; Poynor and Haws 2009).

Chronic attention to forbidden food categories is likely to lead to strong associations between unhealthy food names (e.g., pasta) and unhealthfulness in the memories of dieters. The usage of such accessible information is often automatic and effortless, thus requiring limited cognitive resources (Menon and Raghubir 2003). This is particularly important to note, given that the cognitive resources of dieters are limited compared to those of nondieters; while dieters’ resources are preoccupied by their persistent thoughts regarding eating and body shape (Green et al. 2003; Green and Rogers 1995), nondieters are free from such distraction. Along these lines, Ward and Mann (2000) demonstrate that dieters, but not nondieters, consume more food when under high (vs. low) cognitive load, indicating that monitoring eating behavior to stay in line with dietary goals uses cognitive resources. As a result, we posit that dieters are likely to rely to a greater extent than nondieters on heuristic information processing when evaluating foods. Supporting this argument, dieters have been shown to be highly susceptible to the influence of food-related cues (Carels, Konrad, and Harper 2007; Fedoroff, Polivy, and Herman 1997; Heatherton, Polivy, and Herman 1989). For instance, package and serving size (Scott et al. 2008) as well as olfactory and cognitive food cues (Jansen and van den Hout 1991) influence dieters’ perceptions of food healthfulness to a greater extent than those of nondieters.

Based on this, when a food item is framed as more versus less healthful by means of the product name, we posit that dieters, but not nondieters, will be more likely to confirm what has been presented to them (Deighton 1984; Hoch and Ha 1986) via the name of the item in their estimation of the food’s healthfulness. Because of their reliance on cues that signal a lack of healthfulness (i.e., their focus on forbidden food categories; Francis et al. 1997; Knight and Boland 1989), we expect dieters to perceive food items assigned relatively unhealthy product names as less healthful than do nondieters, whereas we expect to observe no significant difference between dieters’ and nondieters’ health perceptions of foods assigned relatively healthy names.

In sum, we expect dieters to engage in heuristic processing and to rely on the product name when evaluating foods, while nondieters’ evaluations are insensitive to changes in the product name. It is important to note here that we do not believe that the reason nondieters’ ratings are immune to the impact of food name is that these individuals tend to evaluate foods more systematically than dieters. In fact, we argue that the reason the product name does not influence nondieters’ evaluations is that they have neither the motivation to spontaneously evaluate the healthfulness of foods nor the implicit associations between certain food categories and healthfulness that dieters do (Francis et al. 1997; Knight and Boland 1989). As a result, when they do systematically process information about foods, we expect nondieters’ health perceptions to mirror those of dieters (we explore this effect in our studies). As such, we posit that the difference between dieters’ and nondieters’ perception of foods’ healthfulness is driven both by dieters’ reliance on name-based heuristics and by nondieters’ insensitivity to food cues.

In addition, we expect that the differential nutrition inferences made by dieters versus nondieters when foods are assigned relatively unhealthy product names will affect the taste of the food item and, in turn, actual consumption. Although less healthful food items are generally perceived to be tastier than more healthful options (i.e., the unhealthy = tasty intuition; Raghunathan et al. 2006), research also shows that taste can be self-manipulated, such that individuals alter the taste of unpleasant foods as a means of increasing the pleasure (or reducing the displeasure) of repeated consumption. For example, Gibbs (1991) demonstrates that compared to individuals expecting to taste a bitter liquid solution only one time, those expecting repeated consumption rated the first taste to be less unpleasant and also expected future tastes to be significantly less negative. This finding is consistent with findings in the nutrition literature that demonstrate that dietary changes can result in taste adaptations. For instance, over time, individuals on a low-salt diet—who initially exhibited a strong preference for high-sodium foods—preferred lower levels of salt (Beauchamp, Bertino, and Engelman 1983). Therefore, dieters—who actively seek to avoid unhealthful foods in order to behave in line with weight loss goals (Knight and Boland 1989)—are likely to distance themselves from unhealthful foods by manipulating the taste of these items, such that they are perceived as less palatable than the healthful foods they hope to regularly consume. Accordingly, we expect dieters to rate food items that are assigned less healthy product names to be less tasty than do nondieters, who lack the motivation to avoid these items.

In sum, when a food is assigned an unhealthy name, we expect dieters to perceive the item as less healthful and less tasty than do nondieters. Moreover, since taste perception is a primary factor driving consumption quantity (Vartanian, Herman, and Wansink 2008; Wansink and Park 2001), we expect these changes in taste ratings to differentially affect consumption. We test the predictions set forth in our model (see fig. 1) in four studies, described next.

Figure 1. 
Effects of Product Name and Dieting Tendency on Perceived Healthfulness, Tastiness, and Consumption

Study 1

Method

Seventy-six individuals (55% female) were randomly approached in the downtown area of a southeastern city and were paid $5 for their participation in the study. Participants were asked to imagine that they were ordering from their usual lunch restaurant when they noticed a new item on the menu. The item was described either as a “daily salad special” or a “daily pasta special” in accordance with participants’ random assignment to the product name condition. Pretest results showed that pasta is considered a less healthy product name relative to salad (specific information regarding the pretest is available from the authors). In both conditions, the item was described as a mixture of “diced tomatoes, onions, and red peppers tossed with pasta shells, salami, mozzarella cheese and dressed with a savory herb vinaigrette. Served chilled on a bed of fresh romaine lettuce.” In addition, we provided a picture of the food item to account for differences in portion size and the relative proportion of each ingredient in the menu item that might be implied by the product name (see appendix).

After reading about the item, participants were asked how healthy they considered it to be (1 = not at all healthy; 7 = very healthy) as well as how nutritious they considered it to be (1 = not at all nutritious; 7 = very nutritious). These items were averaged to form the dependent variable in subsequent analyses, perceived healthfulness (r = .75).

Participants next responded to the 5-point 14-item Cognitive Behavioral Dieting Scale (Martz et al. 1996) to assess differences in dieting behavior. Behaviors such as, “I have used the nutritional labels on foods to determine if I will eat a certain food or not” and “I have planned out what I am allowed to eat for the day” were rated in terms of their frequency (1 = never, 2 = hardly ever, 3 = sometimes, 4 = often, and 5 = always) and were averaged to form the predictor variable, dieting tendency (M = 2.56; SD = .90; α = .94).

In order to control for the effect of product name (salad or pasta) on participants’ perception of the level of satiation that would result from consuming the item, we also asked participants how “filling” and “substantial” they considered the item to be (1 = not at all; 5 = very much; r = .77). These two items were averaged to form an index of perceived fillingness of the food item. Finally, all participants reported their height, weight, gender, and age (rangeage = 19–73; Mage = 41.0; SDage = 13.4). We used the height and weight information to compute participants’ body mass index (BMI), which we controlled for in our study. BMI provides a measure of “body fatness” and is used to identify weight-related health conditions (e.g., underweight and obesity; Centers for Disease Control and Prevention 2009). Participants had an average BMI of 26.6 (classified as overweight according to this index; range = 17.4–56.6; SD = 6.76), which is in line with the BMI of the average American (mean of 27–28).

Results and Discussion

Before testing our predictions, we sought to assess the impact of our manipulations on the perceived fillingness of the food item. To do so, we regressed perceived fillingness on product name (coded as a dummy variable: 0 = salad; 1 = pasta), mean-centered dieting tendency, and the interaction of these variables. Results showed no significant simple or interactive effects (all p > .10), demonstrating that our manipulation did not result in differences in the perceived fillingness of the food item.

Next, we conducted a regression analysis predicting perceived healthfulness with product name, dieting tendency, and their interaction. BMI was included as a covariate. Although BMI was significant as a covariate (β = .039, t(75) = 2.08, p < .05), it did not interact with the independent variables (all p > .30). As expected, there was a significant two-way interaction of product name and dieting tendency (β = −.58, t(75) = −2.07, p < .05; see fig. 2).

Figure 2. 
Perceived Healthfulness of “Salad” versus “Pasta” by Dieting Tendency (Study 1)

To test our predictions, we first examined the slopes of the dieting tendency variable at each level of product name. As expected, when the food item was assigned a relatively unhealthy name, pasta, the slope of dieting tendency was negative and significant (β = −.37, t(37) = −1.94, p = .05); as dieting tendency increased, there was a decrease in the perceived healthfulness of the food item. However, when the food item was assigned a relatively healthy name, salad, dieting tendency did not have a significant impact on perceived healthfulness (β = .21, t(30) = 1.03, p > .30). In addition, we conducted a spotlight analysis (Aiken and West 1991; Fitzsimons 2008) 1 standard deviation below and above the mean of dieting tendency to assess differences in the perceived healthfulness of the food item on the basis of the product name at low (i.e., nondieters) versus high (i.e., dieters) levels of dieting tendency. The planned contrast for nondieters revealed no significant effect of product name (β = .37, t(75) = 1.47, p > .10); nondieting individuals did not differ in their assessment of the item’s perceived healthfulness on the basis of the name of the product. The planned contrast for dieters did demonstrate a simple negative effect of product name (β = −.41, t(75) = −2.05, p < .05), such that dieters perceived the item to be less healthy when it was classified as pasta (vs. salad).

These results support our contention that, while perceptions of healthfulness for items identified by healthy names do not vary with dieting tendency, dieters perceive foods assigned unhealthy names to be less healthful than do nondieters. Moreover, these findings support the notion that dieters are more likely than nondieters to rely on product name when evaluating the perceived healthfulness of food items; dieters rated the food item as lower in healthfulness when it was identified by a relatively unhealthy (vs. healthy) product name, while the assessments of nondieters were not affected by the name of the food item.

These findings are consistent with our explanation that dieters rely on food-related cues and tend to engage in heuristic processing, while nondieters are insensitive to such cues. In our next study, we sought to provide additional evidence of this process by investigating the role of a dispositional variable, need for cognition (NFC). NFC explains an individual’s likelihood of engaging in and enjoying effortful cognitive activities; in general, individuals with higher levels of NFC are more likely to engage in effortful processing across contexts, while individuals with lower levels of NFC are more likely to rely on heuristics (Cacioppo and Petty 1982). We reasoned that if dieters are basing their judgments of foods’ healthfulness on the product name because they generally rely on food-related cues and tend to engage in heuristic processing, then a chronic goal to process information in a systematic fashion (i.e., high NFC) should discourage the use of heuristic information processing (Drolet, Luce, and Simonson 2009); as a result, high-NFC dieters’ health perceptions should not be influenced by product name.

Further, measuring NFC also helps us to investigate the manner in which nondieters assess foods’ healthfulness. We posit that nondieters’ product ratings are insensitive to food-related cues—such as product name—because they lack the motivation to avoid particular foods and not because they, by default, systematically process information related to foods’ healthfulness. If this is the case, then we would expect nondieters with high (vs. low) NFC, like dieters with high (vs. low) NFC, to pay closer attention to item attributes, resulting in differences in product evaluations. If instead their ratings are due to the fact that they spontaneously process food information in a more systematic fashion than do dieters, then NFC should not influence the product evaluations of nondieters. Thus, in line with our proposed process account, we expect to observe the interactive effect of dieting tendency and product name only for participants with low NFC, while the health assessments of high-NFC nondieters should differ from those of low-NFC nondieters.

Study 2

Method

One hundred and forty-two undergraduates (57% female) participated in the experiment to fulfill a course requirement. Participants were provided with information (i.e., product name, picture, description, and list of ingredients; see appendix) for a product identified as either “fruit chews” or “candy chews” (product name). Pretest results showed that candy chews is considered a less healthy product name than fruit chews (specific information regarding the pretest is available from the authors). Participants were asked to review the product information and were then asked to rate the item’s healthfulness on the same 2-item scale used in study 1 (r = .80).

Next, we used the Cognitive Behavioral Dieting Scale (Martz et al. 1996) to measure participants’ dieting tendency (M = 2.45; SD = .88; α = .95). Participants then completed the 7-point 18-item NFC scale (Cacioppo and Petty 1982; M = 4.52; SD = .77; α = .88). A manipulation-check item, designed to ensure that participants attended to the product information (i.e., ingredients), asked participants to select all of the ingredients that the product contained from the following list: sugar, fruit juice, vitamin C, corn syrup, and milk. In order to assess the possible effect of product name on perceptions of item fillingness, we also asked participants how much a 20-piece serving of the product, if consumed, would leave them feeling “satiated” and “full” (1 = not at all; 7 = very much; r = .67). Finally, participants were asked to provide their gender.

Results and Discussion

Twenty-nine participants (16 from the candy chews condition and 13 from the fruit chews condition; mean NFC of these participants = 4.51 compared to overall mean NFC = 4.52) reported at least two out of five ingredients of the food item incorrectly. We excluded these participants from the data set in order to ensure that our results are driven by name-related inferences, rather than misconceptions regarding the true nature of the product (e.g., that the product contains fruit when named fruit chews but not when named candy chews). This resulted in 113 usable responses, although our results did not change significantly when these participants were included in the analyses. Further, regression analysis of perceived fillingness on product name, dieting tendency, NFC, and their interactions showed that perceived fillingness was not affected by any of the independent variables (all p > .20).

To test our predictions regarding the impact of NFC on the relationship between product name and dieting tendency on perceived healthfulness, we regressed perceived healthfulness on product name (0 = fruit chews; 1 = candy chews), mean-centered dieting tendency, mean-centered NFC, and all two- and three-way interactions between these variables. As expected, our results revealed a significant two-way interaction of product name and dieting tendency (β = −.60, t(112) = −2.38, p < .01) and a significant three-way interaction of NFC, product name, and dieting tendency (β = .97, t(112) = 2.60, p < .05).

To explore the nature of the three-way interaction, we first examined the interaction between product name and dieting tendency at each level of NFC by conducting a spotlight analysis 1 standard deviation above and below the mean of NFC. For participants with high levels of NFC, no significant interactive effect of product name and dieting tendency on the perceived healthfulness of the item was observed (β = .0017, t(112) = .01, p = .90). However, results for participants low in NFC revealed a significant two-way interaction of product name and dieting tendency (β = −.79, t(112) = −3.07, p < .01), which is illustrated in figure 3. In order to investigate the nature of this interaction, we conducted a median split on NFC (M = 4.52; SD = .77; median = 4.57) and ran regressions of perceived healthfulness with product name, dieting tendency, and the interaction of these variables as independent predictors at low and high levels of NFC separately.

Figure 3. 
Perceived Healthfulness of “Fruit Chews” versus “Candy Chews” by Need for Cognition and Dieting Tendency (Study 2)

Note.—A, Low need for cognition; B, high need for cognition.

Low NFC

A regression of product name, dieting tendency, and the interaction of these variables on perceived healthfulness revealed a simple effect of dieting tendency (β = −.67, t(59) = −3.54, p < .01) and a significant two-way interaction of product name and dieting tendency (β = −.54, t(59) = −2.19, p < .05). As predicted, when the item was presented as candy chews, the healthfulness ratings of low-NFC participants decreased with dieting tendency (β = −.42, t(55) = −3.24, p < .01); in other words, low-NFC dieters rated the item as less healthful than did low-NFC nondieters when it was identified by an unhealthy name. When the item was given a healthy name, fruit chews, dieting tendency had no significant effect on perceived healthfulness for low-NFC participants (β = −.03, t(56) = −.25, p > .80). Further, the planned contrast using spotlight analyses showed no effect of product name for low-NFC nondieters, demonstrating that nondieters’ assessments of the item’s perceived healthfulness did not differ on the basis of whether the item was presented as fruit chews or candy chews (β = .12, t(59) = .75, p > .40). However, the planned contrast for low-NFC dieters replicated the results of our prior study; these individuals perceived the food item to be significantly less healthful when the item was presented as candy chews, compared to fruit chews (β = −.36, t(59) = −2.42, p < .05; see fig. 3A).

High NFC

A regression of product name, dieting tendency, and the interaction of these variables on perceived healthfulness revealed no simple or interactive effects (all p > .60; see fig. 3B), indicating that neither the product name nor individuals’ dieting tendency influenced high-NFC individuals’ ratings of the perceived healthfulness of the food item. Thus, as expected, the health ratings for individuals with high NFC did not differ by product name or by dieting tendency. Further, high-NFC nondieters perceived the item—in both the candy and the fruit chews conditions—to be significantly less healthful than did low-NFC nondieters (p < .05), providing some support that the reason nondieters are insensitive to changes in food names is not that they systematically process information about the food item. In fact, when they do process information systematically (i.e., when they have high NFC), nondieters’ health perceptions mirror those of high-NFC dieters.

The results of study 2 demonstrate that the interactive effect of product name and dieting tendency on perceptions of a food’s healthfulness is mitigated for individuals high in NFC. These results provide support for our heuristic-based explanation of our observed naming effect as low- (vs. high-) NFC individuals are more likely to rely on heuristic processing (Chaiken 1980; Sujan 1985). Further, we show that nondieters evaluations vary with NFC, supporting the contention that nondieters’ apparent immunity to name-based cues is not based on a tendency to engage in systematic processing when evaluating foods. As well, these results are in line with the proposition that dieters’ impaired information processing capabilities can be overcome by the motivation to process information in a systematic fashion (i.e., high NFC), resulting in the attenuation of the effect of product name on judgments of foods’ healthfulness.

Building on these results, in our next study we sought to provide further evidence of the underlying process as well as to explore ways in which the interactive effect of product name and dieting tendency on health-related inferences might be mitigated. Prior research has shown that increasing the extent of processing discourages the use of heuristics in product evaluations (Sujan 1985) and, more specifically, individuals’ reliance on heuristics in food-related judgments (Chandon and Wansink 2007a). Therefore, in our next study we manipulated participants’ processing approach by having half of our respondents deliberate on the healthfulness of the attributes (i.e., ingredients) of a food item before rating its overall healthfulness. Such bottom-up information processing requires individuals to systematically process information about the food item, thus increasing the likelihood that individuals will rely on a food’s ingredients—rather than merely on its name—when evaluating the item’s healthfulness. Thus, similar to the effect of high NFC in study 2, we posit that processing health-related information in a systematic manner will attenuate the interactive effect of product name and dieting tendency on health perceptions. Hence, we expect to observe this effect only for participants who engage in top-down processing, wherein they evaluate the overall healthfulness of the item before its individual ingredients.

Study 3

Method

One hundred and thirty-four undergraduates (54% female) participated in the experiment to fulfill a course requirement. The stimuli (product name: pasta vs. salad) and the dependent variable (perceived healthfulness) were the same as those used in study 1. The key difference in this study was our manipulation of participants’ processing approach. Specifically, after viewing the stimuli, participants were asked to estimate the healthfulness of each ingredient of the food item either before they evaluated its overall healthfulness (bottom-up approach) or after they evaluated the overall healthfulness of the food item (top-down approach). Participants then responded to the Cognitive Behavioral Dieting Scale (Martz et al. 1996; M = 2.64; SD = .99; α = .94) to assess dieting tendency and were asked to provide their gender.

Results and Discussion

To test our predictions, we conducted regression analyses in which the perceived healthfulness of the food item served as the dependent variable. Processing approach (1 = bottom-up approach; 0 = top-down approach), product name (0 = salad; 1 = pasta), mean-centered dieting tendency, and all two- and three-way interactions between these variables were included as independent predictors. As expected, results revealed a significant two-way interaction of product name and dieting tendency (β = −.60, t(133) = −2.38, p < .01) and a significant three-way interaction of processing approach, product name, and dieting tendency (β = .97, t(133) = 2.60, p < .05). To explore the nature of the three-way interaction, we examined the interaction between product name and dieting tendency at each level of processing approach.

Top-Down Approach

As expected, although no simple effects were observed (all p > .20), there was a significant two-way interaction of product name and dieting tendency (β = −.60, t(66) = −2.53, p < .05; see fig. 4A) when participants used a top-down approach, wherein overall item healthfulness was rated before assessing the individual ingredients. Replicating the results of prior studies, the item’s perceived healthfulness decreased with dieting tendency when assigned a relatively unhealthy product name (i.e., pasta; β = −.52, t(33) = −3.47, p < .01); when the item was labeled as a healthier food (i.e., salad), dieting tendency had no significant effect on item’s perceived healthfulness (β = .043, t(32) = .27, p > .70). The planned contrast using spotlight analysis showed that nondieters did not differ in their ratings of the perceived healthfulness of the food item on the basis of whether it was presented as pasta or salad (β = .42, t(66) = 1.30, p > .20). However, the planned contrast for dieters replicated the results of our prior studies; dieters perceived the food item to be lower in nutritional value when the item was assigned a relatively unhealthy (vs. healthy) product name (β = −.77, t(66) = −2.22, p < .05).

Figure 4. 
Perceived Healthfulness of “Salad” versus “Pasta” by Processing Approach and Dieting Tendency (Study 3)

Note.—A, Top-down approach; B, bottom-up approach.

Bottom-Up Approach

When participants used a bottom-up approach, wherein the item’s ingredients were evaluated before overall healthfulness, we observed no significant simple or interactive effects of product name and dieting tendency on the perceived healthfulness of the food item (all p > .20; see fig. 4B). In addition, nondieters’ assessments of the healthfulness of the food item—while not varying with the name of the product—were lower (p < .05) relative to when they engaged in top-down processing. Moreover, they were not significantly different from those of dieters (p > .20). Similar to the results of study 2, this suggests that our finding that nondieters are seemingly insensitive to health-related cues implied by the product name is driven not by nondieters’ general reliance on systematic processing but rather by a lack of attention to product name or other food-related cues. Finally, regressions predicting the perceived healthfulness of each item ingredient (e.g., diced tomatoes, pasta shells) with processing approach, product name, dieting tendency, and their interactions showed neither an effect of product name nor significant interactive effects of the independent variables on the perceived healthfulness of any ingredient (all p > .10).

In sum, study 3 results show that the interactive effect of product name and dieting tendency on health evaluations of food items found in the previous studies is attenuated if bottom-up (i.e., systematic) processing is used. These findings lend further support to our contention that dieters use heuristic processing and rely on name-based cues to a greater extent than do nondieters. When dieters are asked to evaluate the healthfulness of each ingredient in a bottom-up fashion before assessing overall item healthfulness, they do not rely on name-based inferences to estimate the healthfulness of the food. This is in line with both the results of our previous study as well as other research in the food domain that shows that systematic processing reduces biases in food-related inference making (Chandon and Wansink 2007a).

Thus far, we have demonstrated the effect of assigning a relatively unhealthy versus healthy product name to a food item on perceptions of the item’s healthfulness; dieters rate identical food items as less healthful than nondieters do when they are assigned relatively unhealthy product names, while the perceived healthfulness of items assigned healthy names is not affected by dieting tendency. Moreover, we provide evidence that this effect occurs as a result of dieters’ reliance on cues that signal a lack of healthfulness, as well as nondieters’ inattentiveness to such cues. In our fourth study, we seek to explore the remainder of our model (see fig. 1) by assessing the impact of product name on consumers’ evaluations of product taste as well as consumption.

In line with prior studies, when a food item is assigned a relatively unhealthy product name we expect dieters to rate the food as lower in perceived healthfulness than do nondieters. Further, because dieters are likely to anticipate the need to avoid unhealthful foods as a means of attaining their dietary goals (Knight and Boland 1989), we predict that these individuals will self-manipulate the taste of unhealthful food items, such that they will rate them as less palatable than do nondieters, who rely to a much lesser extent on the name of the product when evaluating the healthfulness of foods. Finally, because taste perceptions often drive consumption (Vartanian et al. 2008; Wansink and Park 2001), we expect dieters to consume a larger quantity of the food item when it is presented as a healthful (vs. unhealthful) food by means of its name, due to the fact that they perceive these items to taste relatively better.

Study 4

Method

One hundred and sixty-eight undergraduates (53% female) participated in the experiment to fulfill a course requirement. After being seated at a private computer terminal where responses could not be observed by other participants, each individual received a bag containing exactly 20 Jelly Belly Assorted Gourmet Fruit Sours. Similar to the product name manipulations used in study 2, the product was identified as either “fruit chews” or “candy chews” (product name), even though all respondents received the same product. An equal number of each of five flavors was provided in each serving. Participants were asked to review product information (i.e., product name, description, and a list of ingredients), which appeared on the computer screen (see appendix). After reviewing this information, participants viewed a short video (approximately 9 minutes) that was unrelated to the study. They were told that they could enjoy the sample as a snack during the film and were informed that after the film they would respond to questions related to the taste of the product.

After having the opportunity to consume the product, participants rated the item’s healthfulness on the same 2-item scale used in prior studies (r = .81). Then, tastiness was measured by two items (“How do you think the candy/fruit chews taste?” 1 = very bad, 7 = very good; “I would describe this food item as … ”; 1 = not at all tasty, 7 = very tasty; r = .80). Next, we assessed participants’ perceptions of fillingness of the item using the same 2-item measure used in prior studies (r = .59). Similar to study 2, a manipulation-check item asked participants to select all of the ingredients that the product contained from the following list: sugar, fruit juice, vitamin C, corn syrup, and milk. After completing these items, participants were instructed to notify the experimenter who counted the number of items remaining in the bag. We calculated consumption quantity by subtracting this number from the 20 candies initially provided. Then, participants responded to the Cognitive Behavioral Dieting Scale (Martz et al. 1996) as a means of assessing dieting tendency (M = 2.65; SD = .84; α = .93) and provided their gender.

Results and Discussion

Twenty-eight participants reported at least two out of five ingredients of the food item incorrectly (14 in each product name condition), and five participants did not try the food item (four from the candy chews and one from the fruit chews condition), and, therefore, these individuals were excluded from the data set. This ensured that our results were driven by name-based effects, rather than inferences based on an incorrect understanding of the item, and that taste perceptions could be accurately measured. This resulted in 135 usable responses, although our results did not change significantly when the excluded responses were included in the data set. Preliminary regression of perceived fillingness on product name, dieting tendency, and their interactions showed no significant simple or interactive effects (all p > .10).

Next, we sought to assess the various relationships among product name, dieting tendency, perceived healthfulness, tastiness, and consumption quantity. Specifically, we propose a process of double mediation (e.g., Scholderer and Grunert 2005; Simpson et al. 2007), whereby product name and dieting tendency affect perceived healthfulness, perceived healthfulness affects tastiness, and, in turn, tastiness affects consumption quantity (see fig. 1). We followed the procedure used by Simpson et al. (2007) and conducted a series of five regression analyses to test this process, which are described in detail below. First, in three separate analyses we tested the interactive effect of product name and dieting tendency on (1) the perceived healthfulness of the food item, (2) the tastiness of the food item, and (3) consumption quantity. Next, we analyzed the mediating effect of perceived healthfulness on tastiness, and, finally, we analyzed the mediating effect of tastiness on consumption quantity.

Perceived Healthfulness

First, to test our prediction that dieters perceive food items as less healthful than do nondieters when given relatively unhealthy product names, we conducted a regression model predicting perceived healthfulness with product name (0 = fruit chews; 1 = candy chews), mean-centered dieting tendency, and the interaction between product name and dieting tendency. As predicted, the results revealed a significant interactive effect (β = −.093, t(134) = −.40, p < .05; see fig. 5A). As in previous studies, when the item was identified as candy chews its perceived healthfulness decreased with dieting tendency (β = −.43, t(67) = −2.71, p < .01), demonstrating that dieters rated the item as less healthful than did nondieters when it was assigned an unhealthy name. However, when labeled with a healthy product name, fruit chews, dieting tendency had no significant effect on the item’s perceived healthfulness (β = −.03, t(66) = −.27, p > .70). The planned contrasts using spotlight analyses showed that nondieters did not differ in their ratings of the item’s perceived healthfulness on the basis of product name (β = .29, t(134) = 1.14, p > .20), while dieters perceived the food item to be significantly less healthful when the item was presented as candy (vs. fruit) chews (β = −.50, t(134) = −1.97, p = .05).

Figure 5. 
Consumption Quantity, Perceived Healthfulness, and Taste of “Fruit Chews” versus “Candy Chews” by Dieting Tendency (Study 4)

Note.—A, Perceived healthfulness; B, tastiness; C, consumption quantity.

Tastiness

Next, we tested our prediction that dieters will perceive a food item to be less tasty than do nondieters when it is given a relatively unhealthy product name. In line with the perceived healthfulness analyses described above, we performed the same regression analyses with tastiness as the dependent variable. Our results revealed a significant interactive effect of product name and dieting tendency (β = −.67, t(134) = −2.00, p < .05; see fig. 5B). As predicted, when the item was identified as candy chews its tastiness decreased with dieting tendency (β = −.52, t(67) = −2.21, p < .05), demonstrating that dieters rated the item as less tasty than did nondieters when it was assigned an unhealthy name. However, when it was labeled with a healthy product name, fruit chews, dieting tendency had no significant effect on the item’s tastiness (β = .15, t(66) = .64, p > .50). The planned contrast using spotlight analysis showed that nondieters did not differ in their taste ratings on the basis of product name (β = .14, t(134) = .35, p > .70). However, the planned contrast for dieters showed that these individuals rated the food item as less tasty when the item was given a relatively unhealthy (vs. healthy) product name (β = −.93, t(134) = −2.13, p < .05).

Consumption Quantity

In order to assess differences in consumption when the item was assigned a relatively unhealthy versus healthy name, we next regressed consumption quantity on product name, dieting tendency, and the interaction between these variables. The results revealed a significant two-way interaction between product name and dieting tendency (β = −1.92, t(134) = −1.94, p = .05) that is illustrated in figure 5C. Interestingly, the pattern of this interaction was different from those related to health and taste perceptions. Specifically, when the item was identified as candy chews its consumption quantity did not significantly vary with dieting tendency (β = −.57, t(67) = −.85, p > .30); however, when it was labeled with a healthy product name, fruit chews, we observed a marginally significant increase in consumption as dieting tendency increased (β = .15, t(66) = 1.34, p < .10). The planned contrast for nondieters showed that their consumption quantity did not vary on the basis of the product name (β = .28, t(134) = .24, p > .80). The planned contrast for dieters, however, showed that consumption quantity was greater for these individuals when the item was given a healthy (vs. unhealthy) product name (β = −3.80, t(134) = −2.95, p < .01).

The results of these three analyses demonstrate that when the product name is relatively unhealthy, dieters perceive the food item to be less healthful and less tasty than do nondieters. In addition, dieters, but not nondieters, are likely to consume a greater quantity of the product when it is assigned a relatively healthy (vs. unhealthy) product name. Next, we explore the mediating effects of perceived healthfulness on tastiness and tastiness on consumption quantity.

Mediating Effect of Perceived Healthfulness on Tastiness

Next, we sought to investigate whether the perceived healthfulness of the food item mediated the moderating effect of dieting tendency and product name on tastiness. In line with Muller, Judd, and Yzerbyt (2005), we conducted a regression model predicting tastiness with product name, dieting tendency, perceived healthfulness, the interaction of product name and dieting tendency, and the interaction of perceived healthfulness and dieting tendency (all continuous variables were mean centered). The results revealed a significant positive simple effect of perceived healthfulness (β = .48, t(134) = 2.73, p < .01), while the interactive effect of product name and dieting tendency was nonsignificant (β = −.49, t(134) = −1.49, p > .10). Taken together with the previously reported regression results (i.e., the significant interactive effect of product name and dieting tendency on perceived healthfulness as well as the significant interactive effect of product name and dieting tendency on tastiness), these results indicate that perceived healthfulness mediated the moderating effect of product name and dieting tendency on perceived tastiness. The results of a Sobel test support this mediated moderation (z = 1.94, p = .05).

Mediating Effect of Tastiness on Consumption Quantity

To investigate whether the tastiness of the food item mediated the moderating effect of product name and dieting tendency on consumption quantity, in line with Muller et al. (2005) we conducted a regression model predicting consumption quantity with product name, dieting tendency, tastiness, the interaction of product name and dieting tendency, and the interaction of tastiness and dieting tendency (all continuous variables were mean centered). The results revealed a significant positive simple effect of tastiness (β = 1.28, t(134) = 3.87, p < .01), while the interactive effect of product name and dieting tendency was nonsignificant (β = −1.00, t(134) = −1.13, p > .20). Taken together with the previously reported regression results (i.e., the significant interactive effect of product name and dieting tendency on tastiness as well as the significant interactive effect of product name and dieting tendency on consumption quantity), these results indicate that tastiness mediated the moderating effect of product name and dieting tendency on consumption quantity. A Sobel test supports this mediated moderation (z = 1.96, p < .05). Further, a regression model predicting consumption quantity with product name, dieting tendency, perceived healthfulness, tastiness, and the interaction of product name and dieting tendency revealed a significant effect of tastiness on consumption quantity (β = 1.50, t(134) = 6.23, p < .0001), while the effect of perceived healthfulness was not significant (p > .40).

In sum, in addition to replicating the results of prior studies, which show that a food item’s perceived healthfulness is dependent on both product name and dieting tendency, the results of our fourth study show that health inferences translate into taste perceptions and, importantly, consumption behavior. As dieters are likely rely on cues that signal a lack of healthfulness, their perceptions and behavior are influenced by the name of the food item; nondieters, however, rely to a lesser extent on name-based inferences to evaluate the healthfulness of food items, and, as a result, their perceptions and consumption are not influenced by the health connotations associated with a food’s name.

General Discussion

The objective of this research was to understand the ways in which merely changing the name of a food item—without altering any other product attributes—influences the product evaluations and consumption of dieters and nondieters. The results of four studies show that when foods are assigned unhealthy names, dieters rate these items as lower in perceived healthfulness than do nondieters. Identical items that are assigned healthier product names are perceived as equally healthful by dieters and nondieters. These differences in food evaluations between dieters and nondieters are attributed to dieters’ reliance on food-related cues and learned associations, particularly those related to foods’ unhealthfulness, as well as nondieters’ apparent immunity to health-related signals conveyed by the name of the food item. This results in an increased tendency to engage in heuristic processing when evaluating foods for dieters, compared to nondieters. Consequently, we show that the effect of product name is mitigated for individuals who enjoy and tend to engage in more effortful processing (i.e., those high in NFC) and when individuals process additional information (i.e., ingredients) using a bottom-up processing approach. We also show that perceptions of health affect taste evaluations and consumption; dieters perceive food items identified by relatively unhealthy names as less tasty and consume such items to a lesser extent than do nondieters, whose taste perceptions and consumption amount are not influenced by the name of the food item. We discuss the theoretical contributions and practical implications of this research next.

Theoretical Contributions

Inferences about Foods’ Healthfulness

This work contributes to the growing, yet still limited, body of literature that explores the manner in which dieters respond to food-related stimuli. As our work shows, dieters (vs. nondieters) are more likely to use heuristic processing when evaluating foods. Further, we found in our studies that dieters pay more attention to cues related to foods’ unhealthfulness, rather than healthfulness: when a food item was given a relatively unhealthy product name (i.e., pasta, candy chews) there was a significant decrease in the perceived healthfulness of the food item as dieting tendency increased; however, when the food item was given a relatively healthy product name (i.e., salad, fruit chews), dieting tendency did not have a significant effect on perceived healthfulness of the food item. These results are in line with prior research that demonstrates dieters’ tendency to avoid items that are diet unfriendly (Knight and Boland 1989). Given that this attention to forbidden foods may result in inferences that are not based on objective product information, future research may further investigate when and why dieters or other individuals are more likely to attend to cues indicating unhealthy items to avoid, rather than healthy items to approach.

In addition to demonstrating the effect of product name on health perceptions and consumption by dieters, our work also explores the manner in which nondieters assess food healthfulness. As our findings demonstrate, nondieters’ health perceptions are not influenced by food name. Moreover, the results of studies 2 and 3 show that nondieters perceive food items as less healthful when they are high in NFC as well as when they systematically evaluate food’s healthfulness (i.e., using bottom-up processing). This provides some evidence that the differences in health perceptions between dieters and nondieters are not due to nondieters’ general tendency to engage in more systematic processing than dieters. However, the question remains as to what product information nondieters are using to arrive at their nutrition ratings. Additional analyses of our data suggest that nondieters’ perceptions may be based, at least in part, on their overall evaluation of the food item; while nondieters’ assessments of foods’ healthfulness were highly correlated with their attitude toward the food item (r ranges from .43 to .27 and is significant at p < .05), dieters’ health assessments were not significantly correlated with their attitude toward the item (r ranges from .12 to .22, and p > .10). Given the fact that in our first study approximately half of the overweight respondents were nondieters, exploring the manner in which nondieters process and respond to food-related cues in relation to this and other research may provide important insights regarding potential strategies for encouraging healthy food-related decisions.

While our findings show that dieters (vs. nondieters) perceive foods with unhealthy names as less healthful, findings from study 4 show a different pattern for consumption. Specifically, we found that when the item was assigned a relatively unhealthy product name (i.e., candy chews), consumption quantity did not change with dieting tendency; when the food item was given a relatively healthy product name (i.e., fruit chews), however, there was a significant increase in consumption quantity as dieting tendency increased. This difference in the patterns of dieters’ perceptions of food healthfulness and consumption quantity might be explained, at least in part, by the fact that dieters generally want to eat larger food portions and can satisfy this desire as long as they are able to justify their eating behavior (Wansink and Chandon 2006). In this case, they may be engaging in strategic behavior by perceiving the food item with the healthy name as more healthful and better in taste relative to the food with an unhealthy name, in order to justify consuming a larger quantity. Thus, while we show that dieters’ perceptions of foods’ healthfulness are based on the way they process food-related information (i.e., using name-based inferences), their consumption behavior may be at least partially influenced by motivational factors. Investigation of such motivational factors in food consumption—especially involving vulnerable populations like dieters—provides a potentially interesting and important area for further research.

Taste Perceptions

This research also demonstrates that when presented with an item assigned a relatively unhealthy product name, dieters infer that the item is less tasty than an identical item assigned a healthier product name. Thus, the relationship between perceived healthfulness and tastiness described by the unhealthy = tasty intuition (Raghunathan et al. 2006) may be more complex than initially thought, perhaps changing on the basis of not only beliefs and informational factors regarding food items but also motivational factors, like weight-loss goals. This finding is supported by research demonstrating that tastes can be self-manipulated in a manner that benefits expected future consumption (Gibbs 1991); in the context of our research, it may be that dieters rate unhealthful foods as less tasty in an effort to successfully avoid them at future consumption opportunities.

As described by Gibbs (1991), this process of self-manipulation is likely learned; the results of an experiment conducted by Brehm (1960) in which children were asked to eat and then evaluate a disliked vegetable showed no difference in the preference ratings between those who expected to eat the vegetable only once versus those who expected to eat the vegetable multiple times over the next few weeks. Gibbs suggests that children may be less skilled at learning to manipulate their tastes. Further, they are likely to lack the motivation of dieters to do so. The process underlying this effect may be important for dieters, as it has the potential to assist those attempting to avoid unhealthful items and approach healthful options. Yet learning to dislike unhealthful items is not likely to be a simple, easily adopted strategy because, if it were, avoiding such options would not be the constant struggle that it is for many dieters. If this behavior is learned, then perhaps avoiding temptations becomes easier the longer one diets, as the association between unhealthy and untasty becomes stronger. Or, if motivation underlies these effects, perhaps dieters are able to convince themselves that they do not enjoy the taste of unhealthful foods as much as they do healthful ones, but, like other self-control strategies, this behavior is challenged by lapses in willpower or distraction. Thus, the cognitive or motivational mechanisms underlying this process as well as additional outcomes of taste adaptation constitute interesting and important avenues for future research.

Moreover, other research has shown that framing certain food items as healthful (vs. unhealthful) may result in more favorable taste perceptions. For instance, Levin and Gaeth (1988) find that beef labeled as “75% lean” is evaluated more favorably in terms of healthfulness, taste, and quality than beef labeled as “25% fat.” Similarly, a study conducted by Wansink, Van Ittersum, and Painter (2004) demonstrates that individuals provided with a dessert labeled as “healthy” rate the item as better in taste than do those individuals provided with the same dessert without a label. These findings, along with the findings from our studies, suggest that the unhealthy = tasty intuition may not apply across all contexts. A healthy or unhealthy label, for instance, may result in additional product inferences, such as those related to quality observed by Levin and Gaeth (1988), that may affect taste. Research that explores the complex relationship between consumer inferences about foods’ healthfulness and taste perceptions is warranted.

Managerial and Public Policy Implications

As we observe here, the effect of food name on perceptions of healthfulness is pervasive; it does not subside with the presentation of pictures of food items and their ingredients, nor does it diminish when consumers have an opportunity to consume the product. Thus, even when provided with information that might be used to more accurately infer healthfulness, dieters continue to employ name-based inferences. Our results suggest two strategies that might be used by public policy makers to mitigate these effects. The first involves lessening the ambiguity in product naming. Current FDA regulations surrounding statements of identity on food labels require that common or usual food names be listed on product packaging in a manner that is not misleading (Food and Drug Administration 2009, sec. 102). For instance, regulations specify that only beverages that are 100% fruit juice may be labeled as “juice,” while the juice designation for those products with lower concentrations must be qualified with a term such as “beverage,” “drink,” or “cocktail” (sec. 102.33a). However, while regulations are quite descriptive for products including juices, certain fish products (sec. 102.45a), and peanut spreads (sec. 102.23a), specifications for the naming of products cover only a few potentially ambiguous food categories.

In response to these limitations, companies and consumers are doing their part to monitor the marketplace. For example, Nestlé’s complaint that competitor CytoSport’s Muscle Milk, a product promoted to athletes to replenish the body after workouts, is marketed deceptively because it contains no milk has been referred to the Federal Trade Commission and FDA for review (Newman 2009). Further, a class-action lawsuit filed in California contends that Coca-Cola Company’s Vitamin Water labels inaccurately tout the brand as a healthy alternative to soft drinks, despite the fact that its sugar content mimics that of soda (Teinowitz and Zmuda 2009). Future policy efforts might be geared toward investigating additional categories for similar labeling regulation in order to prevent product names from signaling undue healthfulness.

A second, and perhaps more practical, strategy is encouraging consumers to evaluate the attributes of food items in a systematic manner. Our results show that the effects of product name on health-related inferences are attenuated when individuals evaluate foods in a bottom-up, attribute-by-attribute fashion or when individuals have high NFC. In line with extant recommendations that have risen out of the marketing literature (e.g., Chandon and Wansink 2007a; Seiders and Petty 2004), this suggests that public policy efforts aimed at encouraging consumers to engage in more extensive processing of nutritional information might lead to better food-related decisions and healthy eating habits. Future research might consider methods that encourage individuals to elaborate on nutrition information, such as labeling strategies or educational programs that might mitigate the influence of product name and other food-related cues on consumer perceptions of the healthfulness of food items.

Findings from this research also provide directions for marketers of food products. First, although positioning food products as either healthy or tasty is a prevalent marketing strategy, our findings suggest that, at least when targeting certain consumer segments (e.g., dieters), healthy foods can also be promoted as tasty. Second, given increasing consumer health consciousness and the focus of media and consumer groups on the naming strategies used by food marketers, companies are likely to benefit—at least in the long run—from assigning their products representative names and providing their customers with the necessary information in a clear and conspicuous manner to help them accurately evaluate foods’ healthfulness.

Appendix

Study Stimuli

Figure A1. 
Stimulus Used in Studies 1 and 3

Figure A2. 
Stimulus Used in Studies 2 and 4

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  38. Oakes, Michael E. and Carole S. Slotterback (2001), “What’s in a Name? A Comparison of Men’s and Women’s Judgments about Food Names and Their Nutrient Contents,” Appetite, 36 (1), 29–40.
  39. Poynor, Cait and Kelly L. Haws (2009), “Lines in the Sand: The Role of Motivated Categorization in the Pursuit of Self-Control Goals,” Journal of Consumer Research, 35 (5), 772–87.
  40. Raghunathan, Rajagopal, Rebecca Walker Naylor, and Wayne D. Hoyer (2006), “The Unhealthy = Tasty Intuition and Its Effects on Taste Inferences, Enjoyment, and Choice of Food Products,” Journal of Marketing, 70 (4), 170–84.
  41. Roe, Brian, Alan S. Levy, and Brenda M. Derby (1999), “The Impact of Health Claims on Consumer Search and Product Evaluation Outcomes: Results from FDA Experimental Data,” Journal of Public Policy and Marketing, 18 (1), 89–105.
  42. Rozin, Paul, Michele Ashmore, and Maureen Markwith (1996), “Lay American Conceptions of Nutrition: Dose Insensitivity, Categorical Thinking, Contagion, and the Monotonic Mind,” Health Psychology, 15 (6), 438–47.
  43. Scholderer, Joachim and Klau G. Grunert (2005), “Consumers, Food and Convenience: The Long Way from Resource Constraints to Actual Consumption Patterns,” Journal of Economic Psychology, 26 (1), 105–28.
  44. Scott, Maura L., Stephen M. Nowlis, Naomi Mandel, and Andrea C. Morales (2008), “The Effects of Reduced Food Size and Package Size on the Consumption Behavior of Restrained and Unrestrained Eaters,” Journal of Consumer Research, 35 (3), 391–405.
  45. Seiders, Kathleen and Ross D. Petty (2004), “Obesity and the Role of Food Marketing: A Policy Analysis of Issues and Remedies,” Journal of Public Policy and Marketing, 23 (2), 153–69.
  46. Simpson, Jeffry A., W. Andrew Collins, SiSi Tran, and Katherine C. Haydon (2007), “Attachment and the Experience and Expression of Emotions in Romantic Relationships: A Developmental Perspective,” Journal of Personality and Social Psychology, 92 (2), 355–67.
  47. Sujan, Mita (1985), “Consumer Knowledge: Effects on Evaluation Strategies Mediating Consumer Judgments,” Journal of Consumer Research, 12 (1), 31–46.
  48. Teinowitz, Ira and Natalie Zmuda (2009), “Coca-Cola Sued for Marketing Vitaminwater as Healthy,” Advertising Age, January 15.
  49. Vartanian, Lenny R., C. Peter Herman, and Brian Wansink (2008), “Are We Aware of the External Factors That Influence Our Food Intake?” Health Psychology, 27 (5), 533–38.
  50. Wansink, Brian and Pierre Chandon (2006), “Can ‘Low-Fat’ Nutrition Labels Lead to Obesity?” Journal of Marketing Research, 43 (4), 605–17.
  51. Wansink, Brian and SeaBum Park (2001), “At the Movies: How External Cues and Perceived Taste Impact Consumption Volume,” Food Quality and Preference, 12 (1), 69–74.
  52. Wansink, Brian, Koert van Ittersum, and James E. Painter (2004), “How Diet and Health Labels Influence Taste and Satiation,” Journal of Food Science, 69 (9), 340–46.
  53. Ward, Andrew and Traci Mann (2000), “Don’t Mind If I Do: Disinhibited Eating under Cognitive Load,” Journal of Personality and Social Psychology, 78 (4), 753–63.

Enhancement

Appendix

Study Stimuli

Figure A1. 
Stimulus Used in Studies 1 and 3

Figure A2. 
Stimulus Used in Studies 2 and 4

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  38. Oakes, Michael E. and Carole S. Slotterback (2001), “What’s in a Name? A Comparison of Men’s and Women’s Judgments about Food Names and Their Nutrient Contents,” Appetite, 36 (1), 29–40.
  39. Poynor, Cait and Kelly L. Haws (2009), “Lines in the Sand: The Role of Motivated Categorization in the Pursuit of Self-Control Goals,” Journal of Consumer Research, 35 (5), 772–87.
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  41. Roe, Brian, Alan S. Levy, and Brenda M. Derby (1999), “The Impact of Health Claims on Consumer Search and Product Evaluation Outcomes: Results from FDA Experimental Data,” Journal of Public Policy and Marketing, 18 (1), 89–105.
  42. Rozin, Paul, Michele Ashmore, and Maureen Markwith (1996), “Lay American Conceptions of Nutrition: Dose Insensitivity, Categorical Thinking, Contagion, and the Monotonic Mind,” Health Psychology, 15 (6), 438–47.
  43. Scholderer, Joachim and Klau G. Grunert (2005), “Consumers, Food and Convenience: The Long Way from Resource Constraints to Actual Consumption Patterns,” Journal of Economic Psychology, 26 (1), 105–28.
  44. Scott, Maura L., Stephen M. Nowlis, Naomi Mandel, and Andrea C. Morales (2008), “The Effects of Reduced Food Size and Package Size on the Consumption Behavior of Restrained and Unrestrained Eaters,” Journal of Consumer Research, 35 (3), 391–405.
  45. Seiders, Kathleen and Ross D. Petty (2004), “Obesity and the Role of Food Marketing: A Policy Analysis of Issues and Remedies,” Journal of Public Policy and Marketing, 23 (2), 153–69.
  46. Simpson, Jeffry A., W. Andrew Collins, SiSi Tran, and Katherine C. Haydon (2007), “Attachment and the Experience and Expression of Emotions in Romantic Relationships: A Developmental Perspective,” Journal of Personality and Social Psychology, 92 (2), 355–67.
  47. Sujan, Mita (1985), “Consumer Knowledge: Effects on Evaluation Strategies Mediating Consumer Judgments,” Journal of Consumer Research, 12 (1), 31–46.
  48. Teinowitz, Ira and Natalie Zmuda (2009), “Coca-Cola Sued for Marketing Vitaminwater as Healthy,” Advertising Age, January 15.
  49. Vartanian, Lenny R., C. Peter Herman, and Brian Wansink (2008), “Are We Aware of the External Factors That Influence Our Food Intake?” Health Psychology, 27 (5), 533–38.
  50. Wansink, Brian and Pierre Chandon (2006), “Can ‘Low-Fat’ Nutrition Labels Lead to Obesity?” Journal of Marketing Research, 43 (4), 605–17.
  51. Wansink, Brian and SeaBum Park (2001), “At the Movies: How External Cues and Perceived Taste Impact Consumption Volume,” Food Quality and Preference, 12 (1), 69–74.
  52. Wansink, Brian, Koert van Ittersum, and James E. Painter (2004), “How Diet and Health Labels Influence Taste and Satiation,” Journal of Food Science, 69 (9), 340–46.
  53. Ward, Andrew and Traci Mann (2000), “Don’t Mind If I Do: Disinhibited Eating under Cognitive Load,” Journal of Personality and Social Psychology, 78 (4), 753–63.

Enhancement