I Eat Healthier Than You: Differences in Healthy and Unhealthy Food Choices for Oneself and for Others

Sproesser, Gudrun; Kohlbrenner, Verena; Schupp, Harald T.; Renner, Britta

doi:10.3390/nu7064638

Cited by 27 publications

(33 citation statements)

References 38 publications

(55 reference statements)

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“…As in Schuldt and Schwarz's (2010; Experiment 2), our participants were asked to evaluate the behavior of another person (i.e., the target). There is data suggesting a self-other discrepancy in the eating behavior domain, such that individuals tend to view themselves as eating more healthily than others (Sproesser, Kohlbrenner, Schupp, & Renner, 2015). If so, our results suggest that the organic bias may be even stronger when individuals are deciding about their own exercise routines.…”

Section: Discussionmentioning

confidence: 63%

Deliberate choices or strong motives: Exploring the mechanisms underlying the bias of organic claims on leniency judgments

2016

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Organic claims can influence how a product is perceived in dimensions that are unrelated with the food production method (e.g., organic food is perceived as more healthful and less caloric than conventional food). Such claims can also bias how the consumers of organic food are perceived and how other people judge their behavior. Schuldt and Schwarz (2010) have shown that individuals evaluating a target with a weight-loss goal are more lenient in judging the target forgoing exercise when the target had an organic (vs. conventional) dessert. This impact of organic claims on leniency judgments has been interpreted either as a halo or a licensing effect. In the current research we aim to replicate and extend Schuldt and Schwarz's (2010) results by examining the mechanisms that are more likely to explain the observed leniency judgments. In Experiment 1, we observed that leniency towards a target that has consumed an organic meal is only observed when the target intentionally chooses such organic meal (vs. choice determined by the situation). These findings suggest that the impact of organic claims on leniency judgments is not merely based on a halo effect. Instead, a licensing account emerges as the most probable mechanism. In Experiment 2, we further found that stronger (vs. weaker) motives for forgoing exercise influenced leniency judgments to the same extent as having had an organic meal. Understanding the mechanisms that shape consumers' decisions may have important implications to prevent bias in their judgments about food and exercise.

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Section: Discussionmentioning

confidence: 63%

Deliberate choices or strong motives: Exploring the mechanisms underlying the bias of organic claims on leniency judgments

2016

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“…The FFB method has, for example, been used to investigate environmental influences such as plate size (3) , vegetable variety (7,8) in food choice, or the effect of the nutritional information and labels on food choice for a single meal (2,9) or for an entire day (5) . Fake foods were also used to investigate health perceptions (4,10) and social influences and attitudes to food choices (11,12) . Meanwhile, the FFB is an established research tool within several research facilities worldwide; research institutions in Germany, Switzerland, the UK and Australia are using a similar set of replica foods to address a variety of research questions.…”

Section: Relevant Workmentioning

confidence: 99%

Mixed deep learning and natural language processing method for fake-food image recognition and standardization to help automated dietary assessment

Mezgec

Eftimov

Bucher

et al. 2018

Public Health Nutr.

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Objective: The present study tested the combination of an established and a validated food-choice research method (the 'fake food buffet') with a new foodmatching technology to automate the data collection and analysis. Design: The methodology combines fake-food image recognition using deep learning and food matching and standardization based on natural language processing. The former is specific because it uses a single deep learning network to perform both the segmentation and the classification at the pixel level of the image. To assess its performance, measures based on the standard pixel accuracy and Intersection over Union were applied. Food matching firstly describes each of the recognized food items in the image and then matches the food items with their compositional data, considering both their food names and their descriptors. Results: The final accuracy of the deep learning model trained on fake-food images acquired by 124 study participants and providing fifty-five food classes was 92·18 %, while the food matching was performed with a classification accuracy of 93 %. Conclusions: The present findings are a step towards automating dietary assessment and food-choice research. The methodology outperforms other approaches in pixel accuracy, and since it is the first automatic solution for recognizing the images of fake foods, the results could be used as a baseline for possible future studies. As the approach enables a semi-automatic description of recognized food items (e.g. with respect to FoodEx2), these can be linked to any food composition database that applies the same classification and description system. Keywords Fake food buffetFood replica Food image recognition Food matching Food standardization Measuring dietary behaviour using traditional, non-automated, self-reporting technologies is associated with considerable costs, which means researchers have been particularly interested in developing new, automated approaches. There is a clear need in dietary assessment and health-care systems for easy-to-use devices and software solutions that can identify foods, quantify intake, record health behaviour and compliance, and measure eating contexts. The aim of the present study was to test the combination of an established and validated food-choice research method, the 'fake food buffet' (FFB), with a new food-matching technology to automate the data collection and analysis.The FFB was developed as an experimental method to study complex food choice, meal composition and portionsize choice under controlled laboratory conditions. The FFB is a selection of very authentic replica-food items, from which consumers are invited to choose. The FFB method was validated by a comparison of meals served from real and fake foods (1) . The food portions served from the fake foods correlated closely with the portions served from the real foods (1) . Furthermore, significant correlations between the participants' energy needs and the amounts served were found in several studies (1)(2)(3)(4) . It has also bee...

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“…To overcome these problems, we applied a method recently developed by Bucher et al (2012) using replica food items ( Figure 1 ) (see also Sproesser et al, 2015). The Fake Food method has been shown to be reliable and a valid assessment of real food choices (Bucher et al, 2012).…”

Section: Introductionmentioning

confidence: 99%

The Environment Makes a Difference: The Impact of Explicit and Implicit Attitudes as Precursors in Different Food Choice Tasks

et al. 2016

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Studies show that implicit and explicit attitudes influence food choice. However, precursors of food choice often are investigated using tasks offering a very limited number of options despite the comparably complex environment surrounding real life food choice. In the present study, we investigated how the assortment impacts the relationship between implicit and explicit attitudes and food choice (confectionery and fruit), assuming that a more complex choice architecture is more taxing on cognitive resources. Specifically, a binary and a multiple option choice task based on the same stimulus set (fake food items) were presented to ninety-seven participants. Path modeling revealed that both explicit and implicit attitudes were associated with relative food choice (confectionery vs. fruit) in both tasks. In the binary option choice task, both explicit and implicit attitudes were significant precursors of food choice, with explicit attitudes having a greater impact. Conversely, in the multiple option choice task, the additive impact of explicit and implicit attitudes was qualified by an interaction indicating that, even if explicit and implicit attitudes toward confectionery were inconsistent, more confectionery was chosen than fruit if either was positive. This compensatory ‘one is sufficient’-effect indicates that the structure of the choice environment modulates the relationship between attitudes and choice. The study highlights that environmental constraints, such as the number of choice options, are an important boundary condition that need to be included when investigating the relationship between psychological precursors and behavior.

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I Eat Healthier Than You: Differences in Healthy and Unhealthy Food Choices for Oneself and for Others

Cited by 27 publications

References 38 publications

Deliberate choices or strong motives: Exploring the mechanisms underlying the bias of organic claims on leniency judgments

Deliberate choices or strong motives: Exploring the mechanisms underlying the bias of organic claims on leniency judgments

Mixed deep learning and natural language processing method for fake-food image recognition and standardization to help automated dietary assessment

The Environment Makes a Difference: The Impact of Explicit and Implicit Attitudes as Precursors in Different Food Choice Tasks

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