Salient nutrition labels shift peoples' attention to healthy foods and exert more influence on their choices

Rramani, Qëndresa; Krajbich, Ian; Enax, Laura; Brustkern, Lisa; Weber, Bernd

doi:10.1016/j.nutres.2020.06.013

Cited by 18 publications

(25 citation statements)

References 39 publications

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“…Accounting for the effects of gaze on choice is important because a large body of research has shown that gaze to options correlates with choosing those options (Krajbich, 2019). Here we have seen that gaze to different attributes of options is also linked to choices, consistent with other recent work (Amasino et al, 2019; Fisher, 2021; Reeck et al, 2017; Rramani et al, 2020; Westbrook et al, 2020). Our maaDDM provides a quantitative account of both phenomena by modeling drift rate as a function of attribute values and gaze location.…”

Section: Discussionsupporting

confidence: 92%

“…The ability to extract information from the stimuli (e.g. fluency or attitude accessibility) may also impact the extent to which gaze amplifies the information (Oppenheimer, 2008;Gwinn & Krajbich, 2020), as we observed in the food + nutrition label tasks (Rramani et al, 2020). With this simple model, gaze is not sufficient to account for subjects' attribute weights.…”

Section: Figure 15mentioning

confidence: 85%

“…We refer to these as symmetric attributes. The other three datasets involved choices between options with meaningfully different attributes, including divisions of money between oneself and another (social value orientation/mini dictator game; Smith & Krajbich, 2018), clothing items coupled with brand labels (based on Philiastides & Ratcliff, 2013), and snack foods coupled with their nutrition labels (Rramani et al, 2020). Every study included eye-tracking.…”

Section: Methodsmentioning

confidence: 99%

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A dynamic computational model of gaze and choice in multi-attribute decisions.

Yang¹,

Krajbich²

2023

Psychological Review

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When making decisions, how people allocate their attention influences their choices. One empirical finding is that people are more likely to choose the option that they have looked at more. This relation has been formalized with the attentional drift-diffusion model (aDDM; Krajbich et al., 2010). However, options often have multiple attributes, and attention is also thought to govern the relative weighting of those attributes (Roe et al., 2001). Little is known about how these two distinct features of the choice process interact; we still lack a model (and tests of that model) that incorporate both option-and attribute-wise attention. Here, we propose a multi-attribute attentional drift-diffusion model (maaDDM) to account for attentional discount factors on both options and attributes. We then use five eye-tracking datasets (two-alternative, two-attribute preferential tasks) from different choice domains to test the model. We find very stable option-level and attribute-level attentional discount factors across datasets, though nonfixated options are consistently discounted more than nonfixated attributes. Additionally, we find that people generally discount the nonfixated attribute of the nonfixated option in a multiplicative way, and so that feature is consistently discounted the most. Finally, we also find that gaze allocation reflects attribute weights, with more gaze to higher-weighted attributes. In summary, our work uncovers an intricate interplay between attribute weights, gaze processes, and preferential choice.

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Section: Discussionsupporting

confidence: 92%

Section: Figure 15mentioning

confidence: 85%

Section: Methodsmentioning

confidence: 99%

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A dynamic computational model of gaze and choice in multi-attribute decisions.

Yang¹,

Krajbich²

2023

Psychological Review

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“…Others (such as Reference Intakes or Guideline Daily Amounts) provide factual information without any recommendation for the product's healthiness. Some formats (such as the TL) give a mix of factual and interpretive information ( 22 ).…”

Section: Introductionmentioning

confidence: 99%

Age, an Important Sociodemographic Determinant of Factors Influencing Consumers' Food Choices and Purchasing Habits: An English University Setting

2022

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The purchasing behaviors of university staff (n = 188) and their use of nutrition labels in making food choices were investigated by an online survey. The age of the participants significantly impacted their purchasing behaviors. This effect was not observed with other sociodemographic characteristics studied (level of education, gender, employment status and ethnicity). The impact of age on the extrinsic factors affecting food choice (personal preference, previous knowledge, convenience, religion/beliefs) and intrinsic factors (quantity, country of origin, method of preparation/serving, fat, salt, protein and added sugar contents) were further explored. The use of nutrition labels among different age groups when buying for the first time was significant for breakfast cereals and fruit juices.

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“…There are several ways food choice paradigms are used in basic and clinical research. Food choice paradigms are a critical tool for investigating the nature of the decision process itself at the behavioral, computational, and neural levels [6][7][8][9][10][11][12][13][14][15][16][17][18] . In addition, they can be used to compare groups [19][20][21][22][23] , evaluate the effectiveness of a separate intervention (e.g.…”

Section: Introductionmentioning

confidence: 99%

Healthier decisions in the cued-attribute food choice paradigm have high test-retest reliability across five task repetitions over 14 days

Barakchian

Hare

2021

Preprint

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Food choice paradigms are commonly used to study decision mechanisms, individual differences, and intervention efficacy. Here, we measured behavior from twenty-three healthy young adults who completed five repetitions of a cued-attribute food choice paradigm over two weeks. This task includes cues prompting participants to explicitly consider the healthiness of the food items before making a selection, or to choose naturally based on whatever freely comes to mind. We found that the average patterns of food choices following both cue types and ratings about the palatability (i.e. taste) and healthiness of the food items were similar across all five repetitions. At the individual level, the test-retest reliability for choices in both conditions and healthiness ratings was excellent. However, test-retest reliability for taste ratings was only fair, suggesting that estimates about palatability may vary more from day to day for the same individual.

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Salient nutrition labels shift peoples' attention to healthy foods and exert more influence on their choices

Cited by 18 publications

References 39 publications

A dynamic computational model of gaze and choice in multi-attribute decisions.

A dynamic computational model of gaze and choice in multi-attribute decisions.

Age, an Important Sociodemographic Determinant of Factors Influencing Consumers' Food Choices and Purchasing Habits: An English University Setting

Healthier decisions in the cued-attribute food choice paradigm have high test-retest reliability across five task repetitions over 14 days

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