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It takes some effort. How minimal physical effort reduces consumption volume
Appetite 71 (2013) 89–94
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It takes some effort. How minimal physical effort reduces consumption volume Thomas A. Brunner Bern University of Applied Sciences, HAFL, Food Science & Management, Laenggasse 85, CH-3052 Zollikofen, Switzerland ETH Zurich, Institute for Environmental Decisions (IED), Consumer Behavior, Universitaetstrasse 22, CH-8092 Zurich, Switzerland
a r t i c l e
i n f o
Article history: Received 11 January 2013 Received in revised form 12 July 2013 Accepted 30 July 2013 Available online 8 August 2013 Keywords: Effort Consumption volume Food intake Consumer behavior
a b s t r a c t Plenty of studies have demonstrated that effort influences food choice. However, few have been conducted to analyze the effect of effort on consumption volume. Moreover, the few studies that have measured consumption volume all have strong limitations. The goal of the present paper is to disentangle confounding variables in earlier research and to rule out various alternative explanations. In a tasting setting focusing on snacking behavior, either unwrapping a food product or grabbing it with sugar tongs was enough to significantly reduce consumption, regardless of whether an unhealthy or healthy food item was used. Hardly any cognitive resources seem to be necessary for the effect to occur, as cognitive load did not affect the findings. In light of obesity being a pressing concern, these findings might be valuable for individuals as well as for the food industry. Ó 2013 Elsevier Ltd. All rights reserved.
Introduction The ease with which we obtain food is considered a crucial factor for food intake (Cutler, Glaeser, & Shapiro, 2003). Wansink (2004) even stated that effort is one of the strongest influences on food intake. As early as the 1970s, researchers began to investigate how additional effort affects food intake. These first studies were conducted in the context of Schachter’s externality hypothesis (1971) proposing a differential influence of environmental factors on obese and normal-weight individuals. However, researchers found that not only were obese individuals affected by external factors, but normal-weight persons were affected as well. Over the years, this line of research faded, and if there were studies on effort, they focused on food selection rather than consumption volume. Only recently, researchers rediscovered the effect effort has on consumption volume. The present paper continues this line of research and analyzes effort in a series of carefully conducted lab experiments. The goals of this research project were to isolate the effect of effort and to rule out potential alternative explanations. Schachter and Friedman (1974) conducted one of the first studies on how effort affects food intake. They had participants fill out some questionnaires on a table with a bag of almonds. In one condition, the almonds had shells on them; in the other, they did not. The share of participants who ate almonds was significantly lower when they had to use a nutcracker than when almonds could be consumed without additional effort. However, this effect emerged E-mail address: [email protected] 0195-6663/$ - see front matter Ó 2013 Elsevier Ltd. All rights reserved. http://dx.doi.org/10.1016/j.appet.2013.07.014
only for obese participants; there was no effect for normal-weight participants. Similarly, Levitz (1976) reported a study where the closing of an ice cream cooler had a dramatic effect on dessert selection. In this study, normal-weight and obese persons were equally affected. Since then, other studies have confirmed the effect of effort on food choice (Durrant & Garrow, 1982; Lappalainen & Epstein, 1990; Lieux & Manning, 1992; Meiselman, Hedderley, Staddon, Pierson, & Symonds, 1994; Meyers & Stunkard, 1980; Rozin et al., 2011; Smith & Epstein, 1991; Wisdom, Downs, & Loewenstein, 2010), but only a few studies have examined consumption volume. An early exception was a study by Singh and Sikes (1974), which was also conducted according to Schachter’s externality hypothesis framework (but see Nisbett, 1968 as well). Participants were offered chocolates and cashews that were either aluminumfoil-wrapped or unwrapped. For the chocolates, neither obesity nor wrapping affected consumption volume. However, obese participants consumed fewer cashews if they were wrapped than if they were unwrapped, while normal-weight participants ate about the same number of nuts. Recently, Honselman et al. (2011) conducted a similar study using pistachio nuts. Their participants self-selected a portion of pistachios that they could eat during a class. One group of students was offered shelled pistachios while a second group was offered pistachios in the shell. Participants who had to shell the pistachios consumed significantly fewer calories than participants who did not have to exert the extra effort. The authors acknowledge that their study did not identify the reasons for decreased consumption since effort was confounded (among others) with the volume of the preselected portion. The
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average portion selected was of similar weight in both conditions, resulting in less volume of eatable pistachios in the shell-on condition. Since participants consumed about the same percentage of calories available from the selected portion, it is unclear whether effort, the selected portion size, or both reduced intake. Several studies have operationalized effort based on proximity. Engell, Kramer, Malafi, Salomon, and Lesher (1996), for example, found that participants with a water pitcher within reach on the dining table drank more water than participants who had to walk either 6 or 12 m to reach the pitcher. In two field studies in an office setting, Painter, Wansink, and Hieggelke (2002) and Wansink, Painter, and Lee (2006) confirmed these findings with chocolate candies. Participants ate more of the candies when the candies were situated on the desk than when they were 2 m away from the desk. Recently, Musher-Eizenman et al. (2010) confirmed the proximity effect in a sample of preschool and school-age children at a child care center. Another study that needs to be mentioned, although not measuring consumption volume, was conducted by Cheema and Soman (2008). They instructed participants to take home a box of chocolates: in one condition, unwrapped pieces were inside the box, and in the other condition, there were individually wrapped chocolates in foil. The results showed that participants receiving the unwrapped chocolates took fewer days to eat them than participants with wrapped chocolates. In addition, the effect was stronger for participants who had a greater aversion to overconsumption. Therefore, the authors concluded this was an effect of partitioning since partitions provide more decision-making opportunities for reluctant consumers to control consumption. It remains unclear whether the additional effort to unwrap the chocolates also affected food intake. To conclude, despite the urgent nature of the topic, very little research has been conducted to investigate the effect of effort on consumption volume. Moreover, the studies that have been done have serious limitations. For instance, Honselman et al.’s (2011) findings were confounded by selected portion size, and Cheema and Soman’s (2008) with partitions. Other studies were conducted in the field, which has the advantage of a naturalistic environment, but lacks proper monitoring. For example, it is not possible to control for other people who are in the immediate vicinity; participants might have even shared their candies with other coworkers in Painter et al.’s (2002) and Wansink et al.’s (2006) studies. The water pitcher study by Engell et al. (1996) was a controlled lab study, but like other research that operationalizes effort with proximity, the effort manipulation was confounded with cue prominence. The further away the water pitcher, the less salient and potent the cues were. Besides this confounding factor, Engell et al. let participants walk up to 12 m, which is a considerable amount of extra effort to get a glass of water. The present paper focuses on minimal physical effort, and it is suggested that the process by which effort results in reduced food intake has to do with eating being an automatic behavior (Brunner, 2010; Brunner, 2012; Brunner & Siegrist, 2012; Cohen & Farley, 2008; Wansink, 2004). Bargh (1994) identified four characteristics of automatic behavior: it occurs without awareness, without intent and without control, and it operates efficiently, i.e., without or with only little effort. Since automatic behavior operates without effort, it seems reasonable to assume that any additional effort somewhat disturbs this automatic process. The present author proposes that in case of food intake, additional effort disturbs the automaticity of food intake, which leads to a reduction of the amount consumed. The goal of the present research was to conduct a series of controlled lab studies disentangling the confounding variables in earlier studies and ruling out alternative explanations by showing that even a small amount of additional effort causes a reduction of food intake. Since most of the increase in caloric intake during the last
few decades stems from calories consumed during snacking (Cutler et al., 2003), the studies focus on snacking behavior. Study 1 draws upon existing research (Singh & Sikes, 1974) and investigates the additional effort of unwrapping chocolates. Study 2 eliminates confounding factors that accompany wrapping. Studies 3 and 4 demonstrate that cognitive resources do not impact the effect of effort. Study 1 The objective of Study 1 was to confirm that even a small amount of additional effort can lead to reduced food intake. Chocolate candies were used, wrapped in one condition and unwrapped in the other. The wrapped chocolates were very easy to open: as with other candies, participants only had to pull on both sides and the candy would just pop out. This constitutes minimal additional effort compared to already unwrapped chocolates. Method Participants and design A total of 60 female students, recruited from a mailing list, participated in exchange for money. They were invited for an individual chocolate tasting session. The mean age of the sample was 24.8 years (SD = 4.14 years) with a mean BMI of 21.5 (SD = 2.84). They were randomly assigned to one of three conditions: (1) wrapped candies with instructions to keep the wrappers on the table, (2) wrapped candies with instructions to put the wrappers in a small table bin, and (3) unwrapped candies. The second condition with the bin on the table was introduced to eliminate the potential effect of feedback in the first condition. Leaving the wrappers on the table provides feedback regarding how many candies a participant has already eaten, which could also affect food intake (e.g., Stuart & Davis, 1972). Materials For the tasting, Mangini Choco Cereals, single candies each weighing approximately 1.3 g, were used. Twenty candies were put in a bowl from which participants could help themselves. The questionnaire to evaluate the chocolate incorporated questions about participants’ general enjoyment of the chocolate, purchase probability, and their perceptions of taste, crispiness, texture, and sweetness (all measured on a five-point scale), as well as two open-ended questions about their likes and dislikes. The data stemming from this questionnaire were not analyzed since the questionnaire was only used to support the cover story of the tasting. After the tasting, another questionnaire was handed out including questions about age, height, and weight. Procedure Upon arriving at the laboratory, the participants were greeted and led to the experimental room by the female experimenter. On the table was the bowl of chocolates, the evaluation questionnaire, a cup of water for neutralizing, and in the second condition, the table bin. Participants were instructed to evaluate the chocolate using the questionnaire and to try as much chocolate as they wanted during the next 5 min. After 5 min, the experimenter collected the remaining candies and handed out the other small questionnaire on demographics. Results A one-factorial ANOVA was conducted on the participants’ intakes. This test revealed a significant main effect (F(2, 57) = 4.53, p < .05). A planned contrast confirmed that when the candies
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were wrapped and the wrappers were left on the table, participants consumed fewer candies than when the candies were unwrapped (M = 3.55 (SD = 1.61) vs. 5.25 (SD = 2.27), t(57) = 2.68, p < .01, one-tailed). Another planned contrast confirmed that participants also consumed fewer candies when the candies were wrapped and the wrapper had to be put in the bin than when the candies were unwrapped (M = 3.65 (SD = 2.08) vs. 5.25 (SD = 2.27), t(57) = 2.52, p < .01, one-tailed). The two wrapped conditions did not differ significantly (t(57) < 1). Figure 1 displays these results graphically. BMI did not affect food intake as investigated in further analyses. Discussion The small effort it takes to unwrap a piece of candy seems sufficient to cause consumers to eat less even though they have more than enough time and cannot use their time for anything other than chocolate consumption. For the condition where the wrappers were left on the table, an additional effect of feedback could not be ruled out, as participants could see how much chocolate they had already eaten. However, for the condition where the wrapper had to be put in a bin, this confounding factor of feedback was eliminated. Still, one can argue that cue prominence affected the results. In the case of the wrapped candies, participants could neither see nor smell the chocolate, which could have made the candies less tempting. To rule out these alternative explanations, Study 2 was conducted. Study 2 Study 2 replicates and extends Study 1 by using various conditions that no longer differ in cue prominence. Instead of leaving the commercial opaque wrappers, the candies were either wrapped in transparent foil or presented with no wrappers, but participants were asked to use sugar tongs to take them. Method Sixty-four female students (M = 23.1, SD = 5.93 years; BMI = 21.2, SD = 3.11), recruited from the same mailing list as in Study 1, participated in exchange for money. The researcher made sure that none of the participants already took part in Study 1. They were randomly assigned to one of three conditions: (1) candies wrapped in transparent foil, (2) unwrapped candies that participants had to pick up using sugar tongs, and (3) unwrapped candies that participants had to grab with their fingers. The procedure was identical to that of Study 1. As a cover story for the second condition, participants were asked to use the tongs for hygienic reasons.
Fig. 2. Participants’ chocolate consumption in Study 2. Error bars represent standard errors.
Results One participant was identified as an outlier regarding consumption (SD > 3) and was disregarded.1 A one-factorial ANOVA was conducted on the participants’ intakes. This test revealed a marginally significant main effect (F(2, 60) = 2.68, p = .076). A planned contrast confirmed that when the candies were wrapped in transparent foil, participants consumed fewer than when the candies were unwrapped (M = 3.48 (SD = 1.40) vs. 4.95 (SD = 2.96), t(60) = 2.10, p < .05, one-tailed). Another planned contrast confirmed that participants also consumed fewer candies when they had to use the sugar tongs than when they had to take the unwrapped candies with their fingers (M = 3.62 (SD = 2.20) vs. 4.95 (SD = 2.96), t(60) = 1.90, p < .05, one-tailed). The two effort conditions did not differ significantly (t(60) < 1). Figure 2 displays these results graphically. BMI did not affect food intake as investigated in further analyses. To investigate whether the various conditions influenced participants’ evaluation of the chocolate, the data from the evaluation questionnaire were analyzed. Multiple ANOVAs were calculated. None of them reached significance. Details can be found in Table 1. Discussion The findings of Study 2 rule out the cue prominence hypothesis. Even when the chocolate was visible, and even when participants could smell the chocolate, they consumed less if food intake was coupled with effort. It is intriguing that even a little additional effort, such as unwrapping a piece of candy or using comfortable sugar tongs, led to almost 30% less food intake in this study. The various conditions did not influence participants’ evaluation of the chocolate. One could argue, for example, that the use of the tongs resulted in a perception of higher quality and therefore, in a higher rating concerning liking. However, this was not the case. Neither the transparent wrapper nor the use of the tongs significantly impacted participants’ evaluation of the chocolate. Study 3 The author assumes that mere effort causes a reduction in food intake. However, there are other potential mechanisms besides cue prominence that could explain the present results. Participants
Fig. 1. Participants’ chocolate consumption in Study 1. Error bars represent standard errors.
1 When including the outlier, the ANOVA no longer reached significance (p = .208). The planned contrast between the transparent foil and the unwrapped condition was still significant (p < .05, one-tailed). However, since the outlier had to use the sugar tong, this condition no longer differed from the unwrapped condition (p = .160, onetailed).
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Table 1 Evaluation questionnaire results for Study 2. Item
M
SD
General liking Taste Crispness Bite Sweetness Willingness to buy
3.63 3.03 4.29 3.51 2.76 2.83
.867 1.14 1.07 .982 .615 1.20
ANOVA df
F
p
2 2 2 2 2 2
<1 2.57 <1 2.62 <1 1.14
.410 .085 .589 .081 .692 .326
Note: Measured on a 5-point scale.
always had to taste chocolate, a relatively unhealthy food item. It could be possible that the use of the sugar tongs rendered participants more vigilant of what they were about to eat. Some evidence for this reasoning can be found in Wansink et al.’s (2006) study. A majority of the participants in their study who had to walk the 2 m to reach the candies noted that this procedure gave them some extra time to reconsider whether they really needed another piece of candy. Applied to the present setting, if using sugar tongs is a more conscious process, participants in this condition could realize that they are consuming an unhealthy food product more so than in the control condition. This could make participants using sugar tongs eat fewer candies. It would not be the additional effort, but rather the type of food that caused the reduction in food intake. If this alternative explanation holds, then using a healthy food item should actually increase food intake. Participants using the sugar tongs would notice the healthiness of, for example, dried apricots and accordingly should eat more (or at least not less) than a control group. To be able to exclude this alternative explanation, Study 3 was conducted. Method Participants and design A total of 101 female students, recruited from the same mailing list as in the previous studies, participated in exchange for money. None of the participants took part in the previous studies. They were invited for an individual tasting session. The mean age of the sample was 24.8 years (SD = 5.30 years) with a mean BMI of 20.9 (SD = 2.42). A 2 (effort: sugar tongs vs. fingers) 2 (food: chocolate vs. dried apricots) design was applied. Participants were randomly assigned to one of the four conditions. Materials As a relatively unhealthy food item, milk chocolate with a cacao level of 38% was used, a single piece weighing approximately 1.6 g. As a relatively healthy food item, dried apricots cut in quarters were used. Twenty pieces were put in a bowl from which participants could help themselves. The questionnaire for the chocolate evaluation was similar to those used in Studies 1 and 2, and the one for the dried apricot tasting was adapted accordingly. After the tasting, another questionnaire was handed out including questions about age, height, and weight. Procedure For single sessions, two bowls of either chocolate or dried apricots were used. For the dried apricots in particular, using two bowls supported a more plausible cover story than using just one bowl. Participants were told that the food item in one of the bowls was produced according to organic standards, while the other was produced conventionally. Actually, the same food item was used for each of the bowls. For the dried apricots, it was highlighted that they were rich in vitamins and minerals to ensure that participants regarded them as healthy. In a pretest using a different sample of
Fig. 3. Participants’ consumption in Study 3. Error bars represent standard errors.
51 students, dried apricots were rated significantly healthier than chocolates (M = 4.52 (SD = 1.19) vs. M = 3.04 (SD = 1.08), on a 7point scale (t(49) = 4.66, p < .001). Otherwise, the procedure was identical to Studies 1 and 2. Results Two participants reported being on a diet; therefore, they were excluded from the analyses.2 As production type was only used to come up with a cover story, food intake was measured as the total number of pieces consumed without distinguishing the two bowls. A two-factorial ANOVA showed that the interaction between effort and food type was not significant (F(1, 98) = 1.29, p = .259). The main effect of effort was significant, with F(1, 98) = 9.37, p < .01. Participants consumed less food when they had to use the sugar tongs (M = 6.60 (SD = 2.86)) than when they could use their fingers (M = 8.58 (SD = 4.03)). This effect emerged marginally in the chocolate-eating group (M = 5.68 (SD = 2.90) vs. 6.92 (SD = 3.08), t(98) = 1.36, p < .09, one-tailed) and significantly more pronounced in the apricot-eating group (M = 7.52 (SD = 2.55) vs. 10.23 (SD = 4.23), t(98) = 2.97, p < .01, one-tailed). Figure 3 displays these results graphically. BMI did not affect food intake as investigated in further analyses. Discussion Study 3 provides further evidence that mere physical effort causes reduced food intake. Even with a healthy food item, participants consumed significantly less when a slight amount of extra effort was required. Therefore, participants did not seem to become more aware of the items’ healthiness when using the sugar tongs. Study 4 The goal of Study 4 was to generalize the findings of Study 3. It is hypothesized that the effort effect occurs without drawing on cognitive resources and that no mental processes are involved. To test for this hypothesis the well-known procedure of cognitive load was employed (e.g., Gilbert, Pelham, & Krull, 1988; Madzharov & Block, 2010). The rationale of this procedure is to put participants under high cognitive load and thereby minimize the cognitive resources that remain for other tasks, such as the experimental task. In the present study, the lack of cognitive 2
Analyses including the participants being on a diet yielded identical results.
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resources should moderate the effect of effort if it is due to factors that involve cognitive processes. It is hypothesized, however, that reduced food intake is due to additional effort and does not involve any cognitive processes. Therefore, putting participants under high cognitive load should not impact the effect of effort. Method Participants and design Unlike the previous studies, males and females were allowed to take part in the tasting to allow for an analysis of gender effects. Ninety-seven students (41 males, 56 females), recruited from the same mailing list as in the previous studies, participated in exchange for money. The researcher made sure that none of the participants took part in the previous studies. Participants were invited for an individual dried apricot tasting session. The mean age of the sample was 28.0 years (SD = 7.96 years) with a mean BMI of 21.8 (SD = 2.82). A 2 (effort: sugar tongs vs. fingers) 2 (cognitive load: low vs. high) design was applied. Participants were randomly assigned to one of the four conditions. Procedure Dried apricots were used, as in Study 3. However, only one bowl of 20 pieces was offered, as in Studies 1 and 2. Participants were told that the study investigated the effect of memory load on the sensoric experience. Thus, participants would have to memorize a number while they evaluated the apricots. For the low cognitive load condition, participants were shown a two-digit number (91), and for the high cognitive load condition, they saw a 10-digit number (9137675423). Participants were informed that they would be asked for the number after the tasting. Otherwise, the procedure was identical to the previous studies. Results A two-factorial ANOVA showed that there was not a significant interaction between effort and cognitive load (F(1, 93) < 1). The main effect of effort was significant, with F(1, 93) = 5.64, p < .05. Participants consumed less when they had to use the sugar tongs (M = 6.37 (SD = 4.58)) than when they used their fingers (M = 8.71 (SD = 5.26)). No significant effect of cognitive load was found (F(1, 93) = 1.16, p = .285). With regard to gender, men (M = 9.10 (SD = 5.14)) generally ate more than women (M = 6.43 (SD = 4.71), F(1, 89) = 6.87, p < .05); otherwise, gender did not affect the results (no interaction effects). Discussion Memorizing a 10-digit number is not an easy task while tasting and rating a food item. Therefore, it is safe to conclude from the results that hardly any cognitive resources are necessary for the effort effect to occur. Food intake was reduced once the participants had to use the sugar tongs, regardless of the cognitive resources that remained. Interestingly, no gender effects were found. Both males and females are thus prone to effort effects and decrease their food intake when intake is coupled with additional effort. General discussion Although previous research has examined effort on food intake, most studies have focused on food choice, not consumption volume. The few studies that have measured consumption volume all have significant limitations. The present research is the first to investigate the effect of a minimal amount of extra effort on con-
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sumption volume in a series of consecutive conducted lab experiments. The four experiments disentangled all confounding variables present in earlier research and provided evidence that the effect occurs without demanding any cognitive resources. In their study, Singh and Sikes (1974) offered their chocolates wrapped in aluminum-foil, a manipulation that comes quite close to the wrapped chocolates in the present research. However, these authors did not find any effect on food intake. How can the discrepancy to the present findings be explained? Participants in Singh and Sikes’ study were given two bowls of chocolates, and the task was to ascertain which bowl contained fresh and which bowl contained stale chocolates (actually, there was no difference in freshness). A possible explanation for the non-significant results of this study could be that the thought of eating stale chocolates could have rendered participants hesitant to eat them, especially when they were offered unwrapped, as this implies staleness more than when chocolates are still wrapped. This could have led to a decrease in consumption for the effortless condition, which resulted in a similar overall consumption level for the two groups. Actually, when Singh and Sikes did find a significant difference between wrapped and unwrapped cashew nuts, they did not use this cover story of freshness. This problem was eliminated in the present research by using only one bowl of chocolates. Wansink et al.’s (2006) notion that additional effort helps facilitate cognitive control was not supported by the present findings. If using the sugar tongs had given participants an extra second to reconsider whether they really wanted to eat another chocolate, the high cognitive load condition should have impacted their effort in some way, but the results remained the same. Could it be that Wansink et al.’s participants tried to rationalize their behavior when they came up with this idea during the debriefing interviews? Or does the amount of additional effort matter? In Wansink et al.’s study, participants had to walk 2 m, which requires much more effort than simply using sugar tongs. Perhaps, the minimal effort added in the present study did not allow participants to reconsider, but walking 2 m did. By using sugar tongs, the confounding variables inherent to earlier research were eliminated. Portion size (Honselman et al., 2011), partitions (Cheema & Soman, 2008), proximity, and therefore, cue prominence (Engell et al., 1996; Painter et al., 2002; Wansink et al., 2006) could not affect the present findings. One could argue that the use of sugar tongs might take more time than just taking the foods with one’s fingers. However, participants had 5 min to taste the foods, and they ate on average between four and six chocolates (and a few more apricots). Therefore, they had more than enough time for the tasting. In fact, most participants were done early and just waited for the study to end, regardless of whether they had to use the sugar tongs. The sugar tongs were quite comfortable to use, and the foods could be grabbed easily. All in all, it seems rather unlikely that the results were due to time effects. The present experiments concern mostly snacking behavior. Cutler et al. (2003) show that most of the increase in caloric intake during the last few decades stems from calories consumed while snacking. Therefore, it is relevant to investigate snacking behavior. However, one might also be interested in knowing whether these effects hold for complete dishes. Since most people finish what they put on their plates, the author suggests that the present findings are best applied during the serving stage. Making serving oneself more effortful, for example, by using special serving tools or smaller ladles should result in decreased consumption. Of course, more research is needed before coming to a conclusion in this regard. Future research should also investigate further the underlying processes of the effort effect. To do this, researchers could think of situations where more effort would lead to greater consumption.
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In certain cases, for example, effort might be used as a justification for indulgence, which could result in greater consumption (Mukhopadhyay & Venkataramani Johar, 2009). The four presented experiments were all lab studies. Future research should validate these findings in the field. Mishra, Mishra, and Masters (2012) found different results regarding the influence of bite size depending on whether they conducted their research in the lab or in the field. They explain this difference with people’s well-defined goal of satiating hunger when visiting a restaurant (field study). This goal is missing in lab studies. The present research investigated snacking behavior, for which most people do not have a well-defined goal of satiating hunger. Therefore, it is suggested that field studies on snacking should yield similar results as the lab studies provided in this paper. Nevertheless, future researchers should investigate this issue. The findings of the present studies suggest that effort could be a promising solution to the obesity problem. People who want to lose weight could think about how to make their food intake more exertive, for example, by boxing or wrapping foods, or by always using cutlery. Instead of making the consumption of unhealthy foods more effortful, individuals could also think about making the consumption of healthy foods less effortful. Fruits and vegetables seem particularly promising. A good example involves washed and cut salads. Since grocery shops have begun offering them, salad sales in general have increased dramatically (Sütterlin, 2009). References Bargh, J. (1994). The four horsemen of automaticity. Awareness, intention, efficiency, and control in social cognition. In R. Wyer & T. Srull (Eds.), Handbook of social cognition (pp. 1–40). Hillsdale, NJ: Lawrence Erlbaum Associates. Brunner, T. (2010). How weight-related cues affect food intake in a modeling situation. Appetite, 55, 507–511. Brunner, T. (2012). Matching effects on eating. Individual differences do make a difference! Appetite, 58, 429–431. Brunner, T., & Siegrist, M. (2012). Reduced food intake after exposure to subtle weight-related cues. Appetite, 58, 1109–1112. Cheema, A., & Soman, D. (2008). The effect of partitions on controlling consumption. Journal of Marketing Research, 45, 665–675. Cohen, D., & Farley, T. (2008). Eating as an automatic behavior. Preventive Chronic Disease, 5, 1–7. Cutler, D., Glaeser, E., & Shapiro, J. (2003). Why have Americans become more obese? Journal of Economic Perspectives, 17, 93–118. Durrant, M., & Garrow, J. (1982). The effect of increasing the relative cost of palatable food with respect to ordinary food on total-energy intake of eight obese inpatients. International Journal of Obesity, 6, 153–164. Engell, D., Kramer, M., Malafi, T., Salomon, M., & Lesher, L. (1996). Effects of effort and social modeling on drinking in humans. Appetite, 26, 129–138.
Gilbert, D., Pelham, B., & Krull, D. (1988). On cognitive busyness. When person perceivers meet persons perceived. Journal of Personality and Social Psychology, 54, 733–740. Honselman, C., Painter, J., Kennedy-Hagan, K., Halvorson, A., Rhodes, K., Brooks, T., et al. (2011). In-shell pistachio nuts reduce caloric intake compared to shelled nuts. Appetite, 57, 414–417. Lappalainen, R., & Epstein, L. (1990). A behavioral economics analysis of food choice in humans. Appetite, 14, 81–93. Levitz, L. (1976). The susceptibility of human feeding behavior to external controls. In G. Bray (Ed.), Obesity in perspective (pp. 53–60). Washington, D.C.: Government Printing Office. Lieux, E., & Manning, C. (1992). Evening meals selected by college students. Impact of the foodservice system. Journal of the American Dietetic Association, 92, 560–566. Madzharov, A., & Block, L. (2010). Effects of product unit image on consumption of snack foods. Journal of Consumer Psychology, 20, 398–409. Meiselman, H., Hedderley, D., Staddon, S., Pierson, B., & Symonds, C. (1994). Effect of effort on meal selection and meal acceptability in a student cafeteria. Appetite, 23, 43–55. Meyers, A., & Stunkard, A. (1980). Food accessibility and food choice. Archives of General Psychiatry, 37, 1133–1135. Mishra, A., Mishra, H., & Masters, T. (2012). The influence of bite size on quantity of food consumed. A field study. Journal of Consumer Research, 38, 791–795. Mukhopadhyay, A., & Venkataramani Johar, G. (2009). Indulgence as self-reward for prior shopping restraint. A justification-based mechanism. Journal of Consumer Psychology, 19, 334–345. Musher-Eizenman, D., Young, K., Laurene, K., Galliger, C., Hauser, J., & Wagner Oehlhof, M. (2010). Children’s sensitivity to external food cues. How distance to serving bowl influences children’s consumption. Health Education and Behavior, 37, 186–192. Nisbett, R. (1968). Determinants of food intake in obesity. Science, 159, 1254–1255. Painter, J., Wansink, B., & Hieggelke, J. (2002). How visibility and convenience influence candy consumption. Appetite, 38, 237–238. Rozin, P., Scott, S., Dingley, M., Urbanek, J., Jiang, H., & Kaltenbach, M. (2011). Nudge to nobesity I. Minor changes in accessibility decrease food intake. Judgment and Decision Making, 6, 323–332. Schachter, S. (1971). Some extraordinary facts about obese humans and rats. American Psychologist, 26, 129–144. Schachter, S., & Friedman, L. (1974). The effects of work and cue prominence on eating behavior. In S. Schachter & J. Rodin (Eds.), Obese humans and rats (pp. 11–14). Potomac, MD: Erlbaum. Singh, D., & Sikes, S. (1974). Role of past experience on food-motivated behavior of obese humans. Journal of Comparative and Physiological Psychology, 86, 503–508. Smith, J., & Epstein, L. (1991). Behavioral economic analysis of food choice in obese children. Appetite, 17, 91–95. Stuart, R., & Davis, B. (1972). Slim chance in a fat world. Champaign, IL: Research Press. Sütterlin, S. (2009). Beutelsalat. Frische aus dem Plastiksack. NZZ Folio, 12. Wansink, B. (2004). Environmental factors that increase the food intake and consumption volume of unknowing consumers. Annual Review of Nutrition, 24, 455–479. Wansink, B., Painter, J., & Lee, Y.-K. (2006). The office candy dish. Proximity’s influence on estimated and actual consumption. International Journal of Obesity, 30, 871–875. Wisdom, J., Downs, J., & Loewenstein, G. (2010). Promoting healthy choices. Information versus convenience. American Economic Journal. Applied Economics, 2, 164–178.
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Research report
It takes some effort. How minimal physical effort reduces consumption volume Thomas A. Brunner Bern University of Applied Sciences, HAFL, Food Science & Management, Laenggasse 85, CH-3052 Zollikofen, Switzerland ETH Zurich, Institute for Environmental Decisions (IED), Consumer Behavior, Universitaetstrasse 22, CH-8092 Zurich, Switzerland
a r t i c l e
i n f o
Article history: Received 11 January 2013 Received in revised form 12 July 2013 Accepted 30 July 2013 Available online 8 August 2013 Keywords: Effort Consumption volume Food intake Consumer behavior
a b s t r a c t Plenty of studies have demonstrated that effort influences food choice. However, few have been conducted to analyze the effect of effort on consumption volume. Moreover, the few studies that have measured consumption volume all have strong limitations. The goal of the present paper is to disentangle confounding variables in earlier research and to rule out various alternative explanations. In a tasting setting focusing on snacking behavior, either unwrapping a food product or grabbing it with sugar tongs was enough to significantly reduce consumption, regardless of whether an unhealthy or healthy food item was used. Hardly any cognitive resources seem to be necessary for the effect to occur, as cognitive load did not affect the findings. In light of obesity being a pressing concern, these findings might be valuable for individuals as well as for the food industry. Ó 2013 Elsevier Ltd. All rights reserved.
Introduction The ease with which we obtain food is considered a crucial factor for food intake (Cutler, Glaeser, & Shapiro, 2003). Wansink (2004) even stated that effort is one of the strongest influences on food intake. As early as the 1970s, researchers began to investigate how additional effort affects food intake. These first studies were conducted in the context of Schachter’s externality hypothesis (1971) proposing a differential influence of environmental factors on obese and normal-weight individuals. However, researchers found that not only were obese individuals affected by external factors, but normal-weight persons were affected as well. Over the years, this line of research faded, and if there were studies on effort, they focused on food selection rather than consumption volume. Only recently, researchers rediscovered the effect effort has on consumption volume. The present paper continues this line of research and analyzes effort in a series of carefully conducted lab experiments. The goals of this research project were to isolate the effect of effort and to rule out potential alternative explanations. Schachter and Friedman (1974) conducted one of the first studies on how effort affects food intake. They had participants fill out some questionnaires on a table with a bag of almonds. In one condition, the almonds had shells on them; in the other, they did not. The share of participants who ate almonds was significantly lower when they had to use a nutcracker than when almonds could be consumed without additional effort. However, this effect emerged E-mail address: [email protected] 0195-6663/$ - see front matter Ó 2013 Elsevier Ltd. All rights reserved. http://dx.doi.org/10.1016/j.appet.2013.07.014
only for obese participants; there was no effect for normal-weight participants. Similarly, Levitz (1976) reported a study where the closing of an ice cream cooler had a dramatic effect on dessert selection. In this study, normal-weight and obese persons were equally affected. Since then, other studies have confirmed the effect of effort on food choice (Durrant & Garrow, 1982; Lappalainen & Epstein, 1990; Lieux & Manning, 1992; Meiselman, Hedderley, Staddon, Pierson, & Symonds, 1994; Meyers & Stunkard, 1980; Rozin et al., 2011; Smith & Epstein, 1991; Wisdom, Downs, & Loewenstein, 2010), but only a few studies have examined consumption volume. An early exception was a study by Singh and Sikes (1974), which was also conducted according to Schachter’s externality hypothesis framework (but see Nisbett, 1968 as well). Participants were offered chocolates and cashews that were either aluminumfoil-wrapped or unwrapped. For the chocolates, neither obesity nor wrapping affected consumption volume. However, obese participants consumed fewer cashews if they were wrapped than if they were unwrapped, while normal-weight participants ate about the same number of nuts. Recently, Honselman et al. (2011) conducted a similar study using pistachio nuts. Their participants self-selected a portion of pistachios that they could eat during a class. One group of students was offered shelled pistachios while a second group was offered pistachios in the shell. Participants who had to shell the pistachios consumed significantly fewer calories than participants who did not have to exert the extra effort. The authors acknowledge that their study did not identify the reasons for decreased consumption since effort was confounded (among others) with the volume of the preselected portion. The
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average portion selected was of similar weight in both conditions, resulting in less volume of eatable pistachios in the shell-on condition. Since participants consumed about the same percentage of calories available from the selected portion, it is unclear whether effort, the selected portion size, or both reduced intake. Several studies have operationalized effort based on proximity. Engell, Kramer, Malafi, Salomon, and Lesher (1996), for example, found that participants with a water pitcher within reach on the dining table drank more water than participants who had to walk either 6 or 12 m to reach the pitcher. In two field studies in an office setting, Painter, Wansink, and Hieggelke (2002) and Wansink, Painter, and Lee (2006) confirmed these findings with chocolate candies. Participants ate more of the candies when the candies were situated on the desk than when they were 2 m away from the desk. Recently, Musher-Eizenman et al. (2010) confirmed the proximity effect in a sample of preschool and school-age children at a child care center. Another study that needs to be mentioned, although not measuring consumption volume, was conducted by Cheema and Soman (2008). They instructed participants to take home a box of chocolates: in one condition, unwrapped pieces were inside the box, and in the other condition, there were individually wrapped chocolates in foil. The results showed that participants receiving the unwrapped chocolates took fewer days to eat them than participants with wrapped chocolates. In addition, the effect was stronger for participants who had a greater aversion to overconsumption. Therefore, the authors concluded this was an effect of partitioning since partitions provide more decision-making opportunities for reluctant consumers to control consumption. It remains unclear whether the additional effort to unwrap the chocolates also affected food intake. To conclude, despite the urgent nature of the topic, very little research has been conducted to investigate the effect of effort on consumption volume. Moreover, the studies that have been done have serious limitations. For instance, Honselman et al.’s (2011) findings were confounded by selected portion size, and Cheema and Soman’s (2008) with partitions. Other studies were conducted in the field, which has the advantage of a naturalistic environment, but lacks proper monitoring. For example, it is not possible to control for other people who are in the immediate vicinity; participants might have even shared their candies with other coworkers in Painter et al.’s (2002) and Wansink et al.’s (2006) studies. The water pitcher study by Engell et al. (1996) was a controlled lab study, but like other research that operationalizes effort with proximity, the effort manipulation was confounded with cue prominence. The further away the water pitcher, the less salient and potent the cues were. Besides this confounding factor, Engell et al. let participants walk up to 12 m, which is a considerable amount of extra effort to get a glass of water. The present paper focuses on minimal physical effort, and it is suggested that the process by which effort results in reduced food intake has to do with eating being an automatic behavior (Brunner, 2010; Brunner, 2012; Brunner & Siegrist, 2012; Cohen & Farley, 2008; Wansink, 2004). Bargh (1994) identified four characteristics of automatic behavior: it occurs without awareness, without intent and without control, and it operates efficiently, i.e., without or with only little effort. Since automatic behavior operates without effort, it seems reasonable to assume that any additional effort somewhat disturbs this automatic process. The present author proposes that in case of food intake, additional effort disturbs the automaticity of food intake, which leads to a reduction of the amount consumed. The goal of the present research was to conduct a series of controlled lab studies disentangling the confounding variables in earlier studies and ruling out alternative explanations by showing that even a small amount of additional effort causes a reduction of food intake. Since most of the increase in caloric intake during the last
few decades stems from calories consumed during snacking (Cutler et al., 2003), the studies focus on snacking behavior. Study 1 draws upon existing research (Singh & Sikes, 1974) and investigates the additional effort of unwrapping chocolates. Study 2 eliminates confounding factors that accompany wrapping. Studies 3 and 4 demonstrate that cognitive resources do not impact the effect of effort. Study 1 The objective of Study 1 was to confirm that even a small amount of additional effort can lead to reduced food intake. Chocolate candies were used, wrapped in one condition and unwrapped in the other. The wrapped chocolates were very easy to open: as with other candies, participants only had to pull on both sides and the candy would just pop out. This constitutes minimal additional effort compared to already unwrapped chocolates. Method Participants and design A total of 60 female students, recruited from a mailing list, participated in exchange for money. They were invited for an individual chocolate tasting session. The mean age of the sample was 24.8 years (SD = 4.14 years) with a mean BMI of 21.5 (SD = 2.84). They were randomly assigned to one of three conditions: (1) wrapped candies with instructions to keep the wrappers on the table, (2) wrapped candies with instructions to put the wrappers in a small table bin, and (3) unwrapped candies. The second condition with the bin on the table was introduced to eliminate the potential effect of feedback in the first condition. Leaving the wrappers on the table provides feedback regarding how many candies a participant has already eaten, which could also affect food intake (e.g., Stuart & Davis, 1972). Materials For the tasting, Mangini Choco Cereals, single candies each weighing approximately 1.3 g, were used. Twenty candies were put in a bowl from which participants could help themselves. The questionnaire to evaluate the chocolate incorporated questions about participants’ general enjoyment of the chocolate, purchase probability, and their perceptions of taste, crispiness, texture, and sweetness (all measured on a five-point scale), as well as two open-ended questions about their likes and dislikes. The data stemming from this questionnaire were not analyzed since the questionnaire was only used to support the cover story of the tasting. After the tasting, another questionnaire was handed out including questions about age, height, and weight. Procedure Upon arriving at the laboratory, the participants were greeted and led to the experimental room by the female experimenter. On the table was the bowl of chocolates, the evaluation questionnaire, a cup of water for neutralizing, and in the second condition, the table bin. Participants were instructed to evaluate the chocolate using the questionnaire and to try as much chocolate as they wanted during the next 5 min. After 5 min, the experimenter collected the remaining candies and handed out the other small questionnaire on demographics. Results A one-factorial ANOVA was conducted on the participants’ intakes. This test revealed a significant main effect (F(2, 57) = 4.53, p < .05). A planned contrast confirmed that when the candies
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were wrapped and the wrappers were left on the table, participants consumed fewer candies than when the candies were unwrapped (M = 3.55 (SD = 1.61) vs. 5.25 (SD = 2.27), t(57) = 2.68, p < .01, one-tailed). Another planned contrast confirmed that participants also consumed fewer candies when the candies were wrapped and the wrapper had to be put in the bin than when the candies were unwrapped (M = 3.65 (SD = 2.08) vs. 5.25 (SD = 2.27), t(57) = 2.52, p < .01, one-tailed). The two wrapped conditions did not differ significantly (t(57) < 1). Figure 1 displays these results graphically. BMI did not affect food intake as investigated in further analyses. Discussion The small effort it takes to unwrap a piece of candy seems sufficient to cause consumers to eat less even though they have more than enough time and cannot use their time for anything other than chocolate consumption. For the condition where the wrappers were left on the table, an additional effect of feedback could not be ruled out, as participants could see how much chocolate they had already eaten. However, for the condition where the wrapper had to be put in a bin, this confounding factor of feedback was eliminated. Still, one can argue that cue prominence affected the results. In the case of the wrapped candies, participants could neither see nor smell the chocolate, which could have made the candies less tempting. To rule out these alternative explanations, Study 2 was conducted. Study 2 Study 2 replicates and extends Study 1 by using various conditions that no longer differ in cue prominence. Instead of leaving the commercial opaque wrappers, the candies were either wrapped in transparent foil or presented with no wrappers, but participants were asked to use sugar tongs to take them. Method Sixty-four female students (M = 23.1, SD = 5.93 years; BMI = 21.2, SD = 3.11), recruited from the same mailing list as in Study 1, participated in exchange for money. The researcher made sure that none of the participants already took part in Study 1. They were randomly assigned to one of three conditions: (1) candies wrapped in transparent foil, (2) unwrapped candies that participants had to pick up using sugar tongs, and (3) unwrapped candies that participants had to grab with their fingers. The procedure was identical to that of Study 1. As a cover story for the second condition, participants were asked to use the tongs for hygienic reasons.
Fig. 2. Participants’ chocolate consumption in Study 2. Error bars represent standard errors.
Results One participant was identified as an outlier regarding consumption (SD > 3) and was disregarded.1 A one-factorial ANOVA was conducted on the participants’ intakes. This test revealed a marginally significant main effect (F(2, 60) = 2.68, p = .076). A planned contrast confirmed that when the candies were wrapped in transparent foil, participants consumed fewer than when the candies were unwrapped (M = 3.48 (SD = 1.40) vs. 4.95 (SD = 2.96), t(60) = 2.10, p < .05, one-tailed). Another planned contrast confirmed that participants also consumed fewer candies when they had to use the sugar tongs than when they had to take the unwrapped candies with their fingers (M = 3.62 (SD = 2.20) vs. 4.95 (SD = 2.96), t(60) = 1.90, p < .05, one-tailed). The two effort conditions did not differ significantly (t(60) < 1). Figure 2 displays these results graphically. BMI did not affect food intake as investigated in further analyses. To investigate whether the various conditions influenced participants’ evaluation of the chocolate, the data from the evaluation questionnaire were analyzed. Multiple ANOVAs were calculated. None of them reached significance. Details can be found in Table 1. Discussion The findings of Study 2 rule out the cue prominence hypothesis. Even when the chocolate was visible, and even when participants could smell the chocolate, they consumed less if food intake was coupled with effort. It is intriguing that even a little additional effort, such as unwrapping a piece of candy or using comfortable sugar tongs, led to almost 30% less food intake in this study. The various conditions did not influence participants’ evaluation of the chocolate. One could argue, for example, that the use of the tongs resulted in a perception of higher quality and therefore, in a higher rating concerning liking. However, this was not the case. Neither the transparent wrapper nor the use of the tongs significantly impacted participants’ evaluation of the chocolate. Study 3 The author assumes that mere effort causes a reduction in food intake. However, there are other potential mechanisms besides cue prominence that could explain the present results. Participants
Fig. 1. Participants’ chocolate consumption in Study 1. Error bars represent standard errors.
1 When including the outlier, the ANOVA no longer reached significance (p = .208). The planned contrast between the transparent foil and the unwrapped condition was still significant (p < .05, one-tailed). However, since the outlier had to use the sugar tong, this condition no longer differed from the unwrapped condition (p = .160, onetailed).
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Table 1 Evaluation questionnaire results for Study 2. Item
M
SD
General liking Taste Crispness Bite Sweetness Willingness to buy
3.63 3.03 4.29 3.51 2.76 2.83
.867 1.14 1.07 .982 .615 1.20
ANOVA df
F
p
2 2 2 2 2 2
<1 2.57 <1 2.62 <1 1.14
.410 .085 .589 .081 .692 .326
Note: Measured on a 5-point scale.
always had to taste chocolate, a relatively unhealthy food item. It could be possible that the use of the sugar tongs rendered participants more vigilant of what they were about to eat. Some evidence for this reasoning can be found in Wansink et al.’s (2006) study. A majority of the participants in their study who had to walk the 2 m to reach the candies noted that this procedure gave them some extra time to reconsider whether they really needed another piece of candy. Applied to the present setting, if using sugar tongs is a more conscious process, participants in this condition could realize that they are consuming an unhealthy food product more so than in the control condition. This could make participants using sugar tongs eat fewer candies. It would not be the additional effort, but rather the type of food that caused the reduction in food intake. If this alternative explanation holds, then using a healthy food item should actually increase food intake. Participants using the sugar tongs would notice the healthiness of, for example, dried apricots and accordingly should eat more (or at least not less) than a control group. To be able to exclude this alternative explanation, Study 3 was conducted. Method Participants and design A total of 101 female students, recruited from the same mailing list as in the previous studies, participated in exchange for money. None of the participants took part in the previous studies. They were invited for an individual tasting session. The mean age of the sample was 24.8 years (SD = 5.30 years) with a mean BMI of 20.9 (SD = 2.42). A 2 (effort: sugar tongs vs. fingers) 2 (food: chocolate vs. dried apricots) design was applied. Participants were randomly assigned to one of the four conditions. Materials As a relatively unhealthy food item, milk chocolate with a cacao level of 38% was used, a single piece weighing approximately 1.6 g. As a relatively healthy food item, dried apricots cut in quarters were used. Twenty pieces were put in a bowl from which participants could help themselves. The questionnaire for the chocolate evaluation was similar to those used in Studies 1 and 2, and the one for the dried apricot tasting was adapted accordingly. After the tasting, another questionnaire was handed out including questions about age, height, and weight. Procedure For single sessions, two bowls of either chocolate or dried apricots were used. For the dried apricots in particular, using two bowls supported a more plausible cover story than using just one bowl. Participants were told that the food item in one of the bowls was produced according to organic standards, while the other was produced conventionally. Actually, the same food item was used for each of the bowls. For the dried apricots, it was highlighted that they were rich in vitamins and minerals to ensure that participants regarded them as healthy. In a pretest using a different sample of
Fig. 3. Participants’ consumption in Study 3. Error bars represent standard errors.
51 students, dried apricots were rated significantly healthier than chocolates (M = 4.52 (SD = 1.19) vs. M = 3.04 (SD = 1.08), on a 7point scale (t(49) = 4.66, p < .001). Otherwise, the procedure was identical to Studies 1 and 2. Results Two participants reported being on a diet; therefore, they were excluded from the analyses.2 As production type was only used to come up with a cover story, food intake was measured as the total number of pieces consumed without distinguishing the two bowls. A two-factorial ANOVA showed that the interaction between effort and food type was not significant (F(1, 98) = 1.29, p = .259). The main effect of effort was significant, with F(1, 98) = 9.37, p < .01. Participants consumed less food when they had to use the sugar tongs (M = 6.60 (SD = 2.86)) than when they could use their fingers (M = 8.58 (SD = 4.03)). This effect emerged marginally in the chocolate-eating group (M = 5.68 (SD = 2.90) vs. 6.92 (SD = 3.08), t(98) = 1.36, p < .09, one-tailed) and significantly more pronounced in the apricot-eating group (M = 7.52 (SD = 2.55) vs. 10.23 (SD = 4.23), t(98) = 2.97, p < .01, one-tailed). Figure 3 displays these results graphically. BMI did not affect food intake as investigated in further analyses. Discussion Study 3 provides further evidence that mere physical effort causes reduced food intake. Even with a healthy food item, participants consumed significantly less when a slight amount of extra effort was required. Therefore, participants did not seem to become more aware of the items’ healthiness when using the sugar tongs. Study 4 The goal of Study 4 was to generalize the findings of Study 3. It is hypothesized that the effort effect occurs without drawing on cognitive resources and that no mental processes are involved. To test for this hypothesis the well-known procedure of cognitive load was employed (e.g., Gilbert, Pelham, & Krull, 1988; Madzharov & Block, 2010). The rationale of this procedure is to put participants under high cognitive load and thereby minimize the cognitive resources that remain for other tasks, such as the experimental task. In the present study, the lack of cognitive 2
Analyses including the participants being on a diet yielded identical results.
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resources should moderate the effect of effort if it is due to factors that involve cognitive processes. It is hypothesized, however, that reduced food intake is due to additional effort and does not involve any cognitive processes. Therefore, putting participants under high cognitive load should not impact the effect of effort. Method Participants and design Unlike the previous studies, males and females were allowed to take part in the tasting to allow for an analysis of gender effects. Ninety-seven students (41 males, 56 females), recruited from the same mailing list as in the previous studies, participated in exchange for money. The researcher made sure that none of the participants took part in the previous studies. Participants were invited for an individual dried apricot tasting session. The mean age of the sample was 28.0 years (SD = 7.96 years) with a mean BMI of 21.8 (SD = 2.82). A 2 (effort: sugar tongs vs. fingers) 2 (cognitive load: low vs. high) design was applied. Participants were randomly assigned to one of the four conditions. Procedure Dried apricots were used, as in Study 3. However, only one bowl of 20 pieces was offered, as in Studies 1 and 2. Participants were told that the study investigated the effect of memory load on the sensoric experience. Thus, participants would have to memorize a number while they evaluated the apricots. For the low cognitive load condition, participants were shown a two-digit number (91), and for the high cognitive load condition, they saw a 10-digit number (9137675423). Participants were informed that they would be asked for the number after the tasting. Otherwise, the procedure was identical to the previous studies. Results A two-factorial ANOVA showed that there was not a significant interaction between effort and cognitive load (F(1, 93) < 1). The main effect of effort was significant, with F(1, 93) = 5.64, p < .05. Participants consumed less when they had to use the sugar tongs (M = 6.37 (SD = 4.58)) than when they used their fingers (M = 8.71 (SD = 5.26)). No significant effect of cognitive load was found (F(1, 93) = 1.16, p = .285). With regard to gender, men (M = 9.10 (SD = 5.14)) generally ate more than women (M = 6.43 (SD = 4.71), F(1, 89) = 6.87, p < .05); otherwise, gender did not affect the results (no interaction effects). Discussion Memorizing a 10-digit number is not an easy task while tasting and rating a food item. Therefore, it is safe to conclude from the results that hardly any cognitive resources are necessary for the effort effect to occur. Food intake was reduced once the participants had to use the sugar tongs, regardless of the cognitive resources that remained. Interestingly, no gender effects were found. Both males and females are thus prone to effort effects and decrease their food intake when intake is coupled with additional effort. General discussion Although previous research has examined effort on food intake, most studies have focused on food choice, not consumption volume. The few studies that have measured consumption volume all have significant limitations. The present research is the first to investigate the effect of a minimal amount of extra effort on con-
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sumption volume in a series of consecutive conducted lab experiments. The four experiments disentangled all confounding variables present in earlier research and provided evidence that the effect occurs without demanding any cognitive resources. In their study, Singh and Sikes (1974) offered their chocolates wrapped in aluminum-foil, a manipulation that comes quite close to the wrapped chocolates in the present research. However, these authors did not find any effect on food intake. How can the discrepancy to the present findings be explained? Participants in Singh and Sikes’ study were given two bowls of chocolates, and the task was to ascertain which bowl contained fresh and which bowl contained stale chocolates (actually, there was no difference in freshness). A possible explanation for the non-significant results of this study could be that the thought of eating stale chocolates could have rendered participants hesitant to eat them, especially when they were offered unwrapped, as this implies staleness more than when chocolates are still wrapped. This could have led to a decrease in consumption for the effortless condition, which resulted in a similar overall consumption level for the two groups. Actually, when Singh and Sikes did find a significant difference between wrapped and unwrapped cashew nuts, they did not use this cover story of freshness. This problem was eliminated in the present research by using only one bowl of chocolates. Wansink et al.’s (2006) notion that additional effort helps facilitate cognitive control was not supported by the present findings. If using the sugar tongs had given participants an extra second to reconsider whether they really wanted to eat another chocolate, the high cognitive load condition should have impacted their effort in some way, but the results remained the same. Could it be that Wansink et al.’s participants tried to rationalize their behavior when they came up with this idea during the debriefing interviews? Or does the amount of additional effort matter? In Wansink et al.’s study, participants had to walk 2 m, which requires much more effort than simply using sugar tongs. Perhaps, the minimal effort added in the present study did not allow participants to reconsider, but walking 2 m did. By using sugar tongs, the confounding variables inherent to earlier research were eliminated. Portion size (Honselman et al., 2011), partitions (Cheema & Soman, 2008), proximity, and therefore, cue prominence (Engell et al., 1996; Painter et al., 2002; Wansink et al., 2006) could not affect the present findings. One could argue that the use of sugar tongs might take more time than just taking the foods with one’s fingers. However, participants had 5 min to taste the foods, and they ate on average between four and six chocolates (and a few more apricots). Therefore, they had more than enough time for the tasting. In fact, most participants were done early and just waited for the study to end, regardless of whether they had to use the sugar tongs. The sugar tongs were quite comfortable to use, and the foods could be grabbed easily. All in all, it seems rather unlikely that the results were due to time effects. The present experiments concern mostly snacking behavior. Cutler et al. (2003) show that most of the increase in caloric intake during the last few decades stems from calories consumed while snacking. Therefore, it is relevant to investigate snacking behavior. However, one might also be interested in knowing whether these effects hold for complete dishes. Since most people finish what they put on their plates, the author suggests that the present findings are best applied during the serving stage. Making serving oneself more effortful, for example, by using special serving tools or smaller ladles should result in decreased consumption. Of course, more research is needed before coming to a conclusion in this regard. Future research should also investigate further the underlying processes of the effort effect. To do this, researchers could think of situations where more effort would lead to greater consumption.
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In certain cases, for example, effort might be used as a justification for indulgence, which could result in greater consumption (Mukhopadhyay & Venkataramani Johar, 2009). The four presented experiments were all lab studies. Future research should validate these findings in the field. Mishra, Mishra, and Masters (2012) found different results regarding the influence of bite size depending on whether they conducted their research in the lab or in the field. They explain this difference with people’s well-defined goal of satiating hunger when visiting a restaurant (field study). This goal is missing in lab studies. The present research investigated snacking behavior, for which most people do not have a well-defined goal of satiating hunger. Therefore, it is suggested that field studies on snacking should yield similar results as the lab studies provided in this paper. Nevertheless, future researchers should investigate this issue. The findings of the present studies suggest that effort could be a promising solution to the obesity problem. People who want to lose weight could think about how to make their food intake more exertive, for example, by boxing or wrapping foods, or by always using cutlery. Instead of making the consumption of unhealthy foods more effortful, individuals could also think about making the consumption of healthy foods less effortful. Fruits and vegetables seem particularly promising. A good example involves washed and cut salads. Since grocery shops have begun offering them, salad sales in general have increased dramatically (Sütterlin, 2009). References Bargh, J. (1994). The four horsemen of automaticity. Awareness, intention, efficiency, and control in social cognition. In R. Wyer & T. Srull (Eds.), Handbook of social cognition (pp. 1–40). Hillsdale, NJ: Lawrence Erlbaum Associates. Brunner, T. (2010). How weight-related cues affect food intake in a modeling situation. Appetite, 55, 507–511. Brunner, T. (2012). Matching effects on eating. Individual differences do make a difference! Appetite, 58, 429–431. Brunner, T., & Siegrist, M. (2012). Reduced food intake after exposure to subtle weight-related cues. Appetite, 58, 1109–1112. Cheema, A., & Soman, D. (2008). The effect of partitions on controlling consumption. Journal of Marketing Research, 45, 665–675. Cohen, D., & Farley, T. (2008). Eating as an automatic behavior. Preventive Chronic Disease, 5, 1–7. Cutler, D., Glaeser, E., & Shapiro, J. (2003). Why have Americans become more obese? Journal of Economic Perspectives, 17, 93–118. Durrant, M., & Garrow, J. (1982). The effect of increasing the relative cost of palatable food with respect to ordinary food on total-energy intake of eight obese inpatients. International Journal of Obesity, 6, 153–164. Engell, D., Kramer, M., Malafi, T., Salomon, M., & Lesher, L. (1996). Effects of effort and social modeling on drinking in humans. Appetite, 26, 129–138.
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