Advertisement

Using Educational Videos and Perspective-Taking to Communicate Gene-By-Environment Interaction Concepts about Eating Behavior: Effects on Empathy and Weight Stigma

      Abstract

      Objective

      This study investigated whether education about gene-by-environment interaction (G × E) concepts could improve G × E knowledge and positively affect empathy and weight stigma.

      Design

      We conducted a randomized trial using a 2 × 2 between-subjects design.

      Setting

      Online.

      Participants

      Five hundred eighty-two American participants from the Prolific platform.

      Intervention

      Participants were randomly assigned to watch an educational or a control video. Participants then watched a set of vignette scenarios that depicted what it is like to have a predisposition toward obesogenic eating behaviors from either a first-person or third-person perspective.

      Main Outcome Measure(s)

      Participants completed questionnaires measuring G × E knowledge, causal attributions, weight stigma, and empathy postintervention.

      Analysis

      Two-by-two between-subjects ANOVAs and exploratory mediation analyses were conducted.

      Results

      Participants who watched the educational video demonstrated greater G × E knowledge, reported higher empathy toward the characters in the vignette scenarios and held fewer stigmatizing attitudes (notably blame) toward individuals with higher weight. Exploratory mediation analyses indicated that the educational video led to these positive downstream effects by increasing the extent to which participants attributed genetic causes to eating behaviors.

      Conclusions and Implications

      Education about G × E causes of eating behaviors can have beneficial downstream effects on attitudes toward people with higher weight.

      Key Words

      INTRODUCTION

      Weight stigma is pervasive in Western society.
      • Puhl RM
      • Heuer CA.
      The stigma of obesity: a review and update.
      Discriminatory attitudes against people with higher weight have been observed at comparable rates to racial and gender discrimination
      • Puhl RM
      • Andreyeva T
      • Brownell KD.
      Perceptions of weight discrimination: prevalence and comparison to race and gender discrimination in America.
      and are often more overt because weight stigma is viewed as a more socially acceptable form of negative bias.
      • Puhl RM
      • Heuer CA.
      The stigma of obesity: a review and update.
      ,
      • De Brún A
      • McCarthy M
      • McKenzie K
      • McGloin A.
      Weight stigma and narrative resistance evident in online discussions of obesity.
      Weight stigma involves a tendency to believe individuals are personally responsible for their weight. However, weight has a sizable genetic component, with twin studies estimating that genetic factors account for approximately 70% of the variance in body mass.
      • Sung J
      • Lee K
      • Song YM
      • Lee MK
      • Lee DH.
      Heritability of eating behavior assessed using the DEBQ (Dutch Eating Behavior Questionnaire) and weight-related traits: the healthy twin study.
      Communication about the role of genetics in weight may therefore help to alleviate weight stigma by reducing the extent to which individuals are blamed for their weight.
      However, genetic risk for obesity is accentuated by certain environments and diminished by others.
      • Reddon H
      • Guéant JL
      • Meyre D.
      The importance of gene-environment interactions in human obesity.
      This change in magnitude of genetic risk by the environment is known as a gene-by-environment interaction (G × E). An added complexity of G × E in the context of weight is that both genetic and environmental factors often affect weight indirectly via influencing behaviors, such as dietary intake.
      • McCaffery JM.
      Precision behavioral medicine: implications of genetic and genomic discoveries for behavioral weight loss treatment.
      Given the complexity of G × E concepts, it is not surprising that the general public poorly understands them.
      • Krakow M
      • Ratcliff CL
      • Hesse BW
      • Greenberg-Worisek AJ.
      Assessing genetic literacy awareness and knowledge gaps in the US population: results from the Health Information National Trends Survey.
      If the public better understands the role genetics play in eating, they may be less likely to blame people for their higher weight, thus increasing empathy and reducing stigma.
      • Hilbert A
      • Zenger M
      • Luck-Sikorski C
      • Brähler E.
      Weight stigma and disease and disability concepts of obesity: a survey of the German population.
      However, creating and delivering genetics education programming can be challenging. For example, individuals with lower health literacy and numeracy are less likely to understand genetic information presented in traditional printed formats.
      • Lea DH
      • Kaphingst KA
      • Bowen D
      • Lipkus I
      • Hadley DW.
      Communicating genetic and genomic information: health literacy and numeracy considerations.
      Carefully designed and validated educational interventions using alternative communication approaches are needed to improve the public's understanding of G × E influences on eating and related concepts.

      Gene-By-Environment In Weight And Eating Behavior

      The causal network of obesity is extremely complex. Researchers have identified more than 250 genetic loci associated with weight,
      • Ndiaye FK
      • Huyvaert M
      • Ortalli A
      • et al.
      The expression of genes in top obesity-associated loci is enriched in insula and substantia nigra brain regions involved in addiction and reward.
      and at least as many environmental factors that can interact with genes to influence an individual's weight status. Specific environmental factors that moderate the heritability of obesity include prenatal exposures, calorific food availability, built environment, education status, smoking and alcohol use, socioeconomic status, deprivation, and stress.
      • Reddon H
      • Guéant JL
      • Meyre D.
      The importance of gene-environment interactions in human obesity.
      Another influence on weight is eating behavior. Eating behaviors themselves are also highly heritable.
      • Grimm ER
      • Steinle NI.
      Genetics of eating behavior: established and emerging concepts.
      ,
      • Schur E
      • Carnell S.
      What twin studies tell us about brain responses to food cues.
      Heritability estimates for disinhibition and uncontrolled eating range from 21% to 77%.
      • Sung J
      • Lee K
      • Song YM
      • Lee MK
      • Lee DH.
      Heritability of eating behavior assessed using the DEBQ (Dutch Eating Behavior Questionnaire) and weight-related traits: the healthy twin study.
      ,
      • Schur E
      • Carnell S.
      What twin studies tell us about brain responses to food cues.
      ,
      • Tholin S
      • Rasmussen F
      • Tynelius P
      • Karlsson J.
      Genetic and environmental influences on eating behavior: the Swedish young male twins study.
      Genetic variants have been related to eating phenotypes such as higher consumption, snacking, binge-eating, eating without hunger, vegetable distaste, and higher fat and sweetness intake.
      • Grimm ER
      • Steinle NI.
      Genetics of eating behavior: established and emerging concepts.
      ,
      • Schur E
      • Carnell S.
      What twin studies tell us about brain responses to food cues.
      Eating behaviors are also governed by G × E mechanisms. Environmental factors such as learned habits and access to healthy foods can augment or attenuate the genetic influence on eating
      • Grimm ER
      • Steinle NI.
      Genetics of eating behavior: established and emerging concepts.
      ; for example, a person genetically predisposed to snacking when not hungry is likelier to eat such snacks in environments of plenty than scarcity.

      Secondary Effects Of Communicating About G × E

      The secondary effects of educating the public about genetic and G × E influences on weight have been investigated in depth, including the influence of educational interventions on causal attributions
      • Hilbert A.
      Weight stigma reduction and genetic determinism.
      • Lippa NC
      • Sanderson SC.
      Impact of information about obesity genomics on the stigmatization of overweight individuals: an experimental study.
      • Persky S
      • Goldring MR
      • El-Toukhy S
      • Ferrer RA
      • Hollister B.
      Parental defensiveness about multifactorial genomic and environmental causes of children‘s obesity risk.
      and weight stigma.
      • Hilbert A.
      Weight stigma reduction and genetic determinism.
      ,
      • Lippa NC
      • Sanderson SC.
      Impact of information about obesity genomics on the stigmatization of overweight individuals: an experimental study.
      ,
      • Ata RN
      • Thompson JK
      • Boepple L
      • Marek RJ
      • Heinberg LJ.
      Obesity as a disease: effects on weight-biased attitudes and beliefs.
      • Lippa NC
      • Sanderson SC.
      Impact of informing overweight individuals about the role of genetics in obesity: an online experimental study.
      • Persky S
      • Eccleston CP.
      Impact of genetic causal information on medical students‘ clinical encounters with an obese virtual patient: health promotion and social stigma.
      • Teachman BA
      • Gapinski KD
      • Brownell KD
      • Rawlins M
      • Jeyaram S.
      Demonstrations of implicit anti-fat bias: the impact of providing causal information and evoking empathy.
      However, little research has investigated the effects of communicating G × E causes of eating behaviors. We consider the potential secondary effects of communicating these concepts on participants’ causal attributions, weight stigma, dietary self-efficacy and intentions, and empathic concern.

      Causal attributions

      Although there is mounting evidence of G × E influences on weight and eating behaviors, the public generally does not acknowledge these variables as having a significant genetic component. British
      • Beeken RJ
      • Wardle J.
      Public beliefs about the causes of obesity and attitudes towards policy initiatives in Great Britain.
      and US
      • Willoughby EA
      • Love AC
      • McGue M
      • Iacono WG
      • Quigley J
      • Lee JJ.
      Free will, determinism, and intuitive judgments about the heritability of behavior.
      samples underestimate the importance of genetic influences on weight (eg, people in the US estimate a genetic contribution of 42%, compared with an actual heritability of approximately 63%).
      • Willoughby EA
      • Love AC
      • McGue M
      • Iacono WG
      • Quigley J
      • Lee JJ.
      Free will, determinism, and intuitive judgments about the heritability of behavior.
      The public is even less accepting of the notion that eating behaviors are highly influenced by genetics.
      • Persky S
      • Bouhlal S
      • Goldring MR
      • McBride CM.
      Beliefs about genetic influences on eating behaviors: characteristics and associations with weight management confidence.
      ,
      • Persky S
      • Yaremych HE
      • Goldring MR
      • Ferrer RA
      • Rose MK
      • Hollister BM.
      Investigating the efficacy of genetic, environmental, and multifactorial risk information when communicating obesity risk to parents of young children.
      Previous attempts to communicate with the public about G × E in the context of weight have found mixed results. For example, participants receiving G × E messages about weight generally endorse genetic causes of obesity more often than control groups, given no information about the etiology of weight
      • Hilbert A.
      Weight stigma reduction and genetic determinism.
      or environmental explanations of weight.
      • Lippa NC
      • Sanderson SC.
      Impact of information about obesity genomics on the stigmatization of overweight individuals: an experimental study.
      However, in some cases, G × E education materials about weight have lowered endorsement of genetic causes of obesity compared with controls, notably for parents of a child with higher weight.
      • Persky S
      • Goldring MR
      • El-Toukhy S
      • Ferrer RA
      • Hollister B.
      Parental defensiveness about multifactorial genomic and environmental causes of children‘s obesity risk.
      In contrast to weight-related research, there is no known research on how educational interventions on G × E causes of eating behaviors alter causal attributions for eating behaviors and/or weight.

      Weight stigma

      If G × E education leads individuals to change their causal attributions, it may also influence weight stigma. In some cases, genetic explanations for weight have been shown to reduce implicit anti-fat attitudes and increase explicit pro-fat attitudes compared with behavioral explanations.
      • Persky S
      • Eccleston CP.
      Impact of genetic causal information on medical students‘ clinical encounters with an obese virtual patient: health promotion and social stigma.
      ,
      • Teachman BA
      • Gapinski KD
      • Brownell KD
      • Rawlins M
      • Jeyaram S.
      Demonstrations of implicit anti-fat bias: the impact of providing causal information and evoking empathy.
      This is because weight stigma involves beliefs that people of higher weight status are to blame for their condition.
      • Crandall CS
      • D'Anello S
      • Sakalli N
      • Lazarus E
      • Nejtardt GW
      • Feather NT
      An attribution-value model of prejudice: anti-fat attitudes in six nations.
      ,
      • Wirtz C
      • van der Pligt J
      • Doosje B.
      Derogating obese individuals: the role of blame, contempt, and disgust.
      The efficacy of genetics-based weight stigma interventions may depend on how these interventions shift beliefs about the causes of weight. Gene-by-environment-based interventions may have similar effects by demonstrating how environments impact people's weight unequally depending on their genes, such that individuals with higher weights may not be seen as blameworthy.
      However, unlike genetic information alone, G × E also indicates that obesity is modifiable because environmental factors can be leveraged as a weight management strategy. This perceived modifiability may also impact weight stigma. Although believing a particular stigmatized attribute can be modified generally increases blame and perceived responsibility, recent research indicates that believing obesity is modifiable can also reduce stigma by increasing beliefs that higher weight can be offset and thus is not an inherent attribute.
      • Burnette JL
      • Hoyt CL
      • Dweck CS
      • Auster-Gussman L.
      Weight beliefs and messages: mindsets predict body-shame and anti-fat attitudes via attributions.
      To date, specific research on the effects of G × E education about weight has found mixed results on weight stigma. Some researchers have found a reduction in weight stigma,
      • Persky S
      • Goldring MR
      • El-Toukhy S
      • Ferrer RA
      • Hollister B.
      Parental defensiveness about multifactorial genomic and environmental causes of children‘s obesity risk.
      and others find no impact.
      • Lippa NC
      • Sanderson SC.
      Impact of information about obesity genomics on the stigmatization of overweight individuals: an experimental study.
      ,
      • Ata RN
      • Thompson JK
      • Boepple L
      • Marek RJ
      • Heinberg LJ.
      Obesity as a disease: effects on weight-biased attitudes and beliefs.
      ,
      • Lippa NC
      • Sanderson SC.
      Impact of informing overweight individuals about the role of genetics in obesity: an online experimental study.
      Again, to our knowledge, no research has determined whether G × E messages about eating behaviors can reduce weight stigma.

      Empathic concern

      Gene-by-environment education about eating behaviors may help individuals empathize with people who experience food differently from themselves. Following the same mechanism outlined above, G × E education may help individuals acknowledge the sizable genetic component in eating behaviors, which in turn may help them to understand the challenges faced by people with genetic predispositions that make obesogenic eating more likely. In other words, if G × E explanations demonstrate that environments impact people's weight unequally depending on their genes, people may feel more empathic concern for those who find themselves to be struggling because of their unique genetic and environmental circumstances.
      In addition to improving understanding of G × E concepts to increase empathic concern, another mechanism to arouse empathy is perspective-taking. Perspective-taking involves “actively imagining the world from another's vantage point”
      • Galinsky AD
      • Wang CS
      • Ku G.
      Perspective-takers behave more stereotypically.
      and is reliably associated with higher levels of empathic concern
      • Batson CD
      • Early S
      • Salvarani G.
      Perspective taking: imagining how another feels versus imaging how you would feel.
      ,
      • Todd AR
      • Galinsky AD.
      Perspective-taking as a strategy for improving intergroup relations: evidence, mechanisms, and qualifications.
      and reduced negative bias.
      • Batson CD.
      Altruism in Humans.
      Previous research has found that people who generally engage in more perspective-taking are less likely to endorse negative stereotypes and more likely to endorse positive stereotypes of people with higher weight.
      • Wu Y
      • Zhang Y.
      The impact of perspective taking on obesity stereotypes: the dual mediating effects of self-other overlap and empathy.
      Moreover, research that has asked people to take the perspective of characters with higher weights has successfully increased empathy and reduced weight stigma.
      • Gloor JL
      • Puhl RM.
      Empathy and perspective-taking: examination and comparison of strategies to reduce weight stigma.
      However, the way one engages in perspective-taking may matter. Empathy researchers differentiate between imagine-self perspective-taking and imagine-other-perspective-taking.
      • Batson CD
      • Early S
      • Salvarani G.
      Perspective taking: imagining how another feels versus imaging how you would feel.
      Imagine-self perspective-taking involves imagining how you would feel if you were the one in another person's situation, whereas imagine-other-perspective-taking involves imagining how someone else feels in their situation. A first-person story (ie, using I pronouns and experiencing from the main character's point-of-view) is likely to elicit imagine-self perspective-taking, whereas a third-person story would be more likely to induce imagine-other-perspective-taking. This is because first-person stories tend to lead to higher feelings of embodiment and transportation into the narrative than third-person stories
      • Brunyé TT
      • Ditman T
      • Mahoney CR
      • Augustyn JS
      • Taylor HA.
      When you and I share perspectives: pronouns modulate perspective taking during narrative comprehension.
      ,
      • Debarba HG
      • Molla E
      • Herbelin B
      • Boulic R.
      Characterizing embodied interaction in first and third person perspective viewpoints.
      and so are likely to prompt people to reflect on how they would feel in this situation.
      There are 2 reasons to suspect that a first-person perspective may yield more beneficial effects on G × E comprehension and weight-related attitudes than a third-person perspective. First, when describing statistical concepts such as G × E, engaging emotional arousal in first-person perspective may act as an attentional cue for self-relevance, which may also improve comprehension of the material.
      • Brilmayer I
      • Werner A
      • Primus B
      • Bornkessel-Schlesewsky I
      • Schlesewsky M.
      The exceptional nature of the first person in natural story processing and the transfer of egocentricity.
      Second, although both types of perspective-taking increase empathic concern, only imagine-self perspective-taking also increases perceived levels of similarity between the participant and the target. Perceived similarity has been theorized to be an additional route to prosocial behaviors beyond the effect of empathic concern.
      • Myers MW
      • Laurent SM
      • Hodges SD.
      Perspective taking instructions and self-other overlap: different motives for helping.

      Dietary self-efficacy and intentions

      If individuals understand the G × E forces shaping their eating behaviors and weight, they may gain self-efficacy about controlling these forces in the future. Studies examining this possibility have generally resulted in null effects in the context of weight.
      • Lippa NC
      • Sanderson SC.
      Impact of informing overweight individuals about the role of genetics in obesity: an online experimental study.
      Despite these null results, G × E education may have benefits over genetics-only education strategies, which are shown to negatively impact food choices.
      • Persky S
      • Yaremych HE
      • Goldring MR
      • Ferrer RA
      • Rose MK
      • Hollister BM.
      Investigating the efficacy of genetic, environmental, and multifactorial risk information when communicating obesity risk to parents of young children.
      Given the complexity of G × E and the mixed character of the existing literature, it is likely that the nature of these outcomes depends on how the concept is communicated. One potential strategy is to present concrete examples of G × E influences on eating behaviors. These examples would allow individuals to visualize themselves encountering similar challenges and imagining how they might overcome them. In line with classic social cognition research, the act of imagining successful resolutions can make those events seem more likely and serve to bring them about.
      • Johnson MK
      • Sherman SJ.
      Constructing and reconstructing the past and the future in the present.
      Specifically, mentally rehearsing hypothetical scenarios can increase people's motivation and expectations of success and prompt them to make concrete plans.
      • Taylor SE
      • Pham LB
      • Rivkin ID
      • Armor DA.
      Harnessing the imagination. Mental simulation, self-regulation, and coping.

      The Current Study

      We designed and created a short educational video about G × E influences on eating behaviors and 2 vignette scenarios to exemplify these concepts. An online randomized trial was conducted to evaluate these education materials on people's G × E knowledge and determine their secondary effects on participants’ attitudes toward people with higher weights. Before data collection, we preregistered our hypotheses and analysis plan with Open Science Foundation (OSF).

      OSF Home. Communicating genomic concepts using virtual reality. https://osf.io/tajhq/?view_only=40570f9be4de46e4aa94276426f09b9b. Accessed November 22, 2022.

      We hypothesized that (1) education materials would result in better comprehension of G × E concepts than control materials, (2) education materials would result in greater attitude change (higher empathy and lower weight stigma) than control materials, (3) first-person perspective vignettes would result in greater attitude change than third-person perspective vignettes, and (4) a significant interaction would emerge between education materials and vignette perspective on attitude change such that the impact of seeing the first-person perspective compared with a third-person perspective would depend on whether participants saw the educational materials or control materials first. We also explored whether the effects of education materials on attitudes were mediated by changes in causal attributions but did not preregister this hypothesis. Furthermore, we report results from 2 exploratory outcome measures: dietary self-efficacy and behavior change intentions.

      METHODS

      We evaluated the efficacy of the educational video and its accompanying vignettes using a 2 × 2 between-subjects design. Participants were randomly assigned to watch either the G × E education video or a control video. Participants then watched a set of 2 vignette scenarios, randomized in first-person or third-person perspective, that described what it is like to have a predisposition toward obesogenic eating behaviors. Finally, participants completed knowledge checks and a battery of empathy and weight stigma questionnaires. This study was ruled exempt by the Office of Human Subjects Research Protection of the National Human Genome Research Institute, and signed consent was not required. The study was performed in accordance with the Declaration of Helsinki.

      Participants

      Participants were recruited via the online platform Prolific (Prolific, 2022). To determine the sample size, we conducted an a priori power analysis for fixed effects omnibus ANOVA with an alpha of 0.05 and power of 0.80 for a 2 × 2 design. In this analysis, we used a conservative effect size associated with between-group differences in the assessment of digital learning materials wherein Cohen's f = 0.12.
      • Chen H-TM
      • Thomas M.
      Effects of lecture video styles on engagement and learning.
      Based on this effect size, we had a target n of 547. We oversampled to ensure a sufficient sample following data exclusions. Participants were excluded if they indicated they could not see or hear the video, did not complete the survey, did not pass attention checks, did not indicate they would answer truthfully from their knowledge, or indicated that their data should be excluded for any reason. Following these criteria, a total of 76 participants were excluded. Our final sample (n = 582) consisted of 253 men, 316 women, and 13 individuals of other genders. Gender was self-reported from a list including man, woman, genderqueer and/or nonbinary, or other (Table 1) .
      Table 1Demographic Characteristics of Participants
      Characteristicsn (%)Mean ± SD
      Age58234.1 ± 11.5
      BMI58227.2 ± 7.6
      Gender
       Man253 (43.5)
       Woman316 (54.3)
       Genderqueer, nonbinary, or other13 (2.2)
      Race
       Asian64 (11.0)
       Black51 (8.8)
       First Nations/Native American5 (0.9)
       White424 (72.9)
       >1 race reported27 (4.7)
       Other reported11 (1.9)
      Self-reported weight status
       Very overweight82 (14.1)
       Overweight211 (36.3)
       Just about right251 (43.1)
       Underweight36 (6.2)
       Very underweight2 (0.3)
      Employment status
       Full time245 (42.1)
       Part time106 (18.2)
       Student81 (13.9)
       Caretaker/Parent44 (7.6)
       Self-employed, unemployed, retired, other106 (18.2)
      Marital status
       Married199 (34.2)
       Never been married298 (51.2)
       Widowed/divorced/separated44 (7.5)
       Member of an unmarried couple41 (7.0)
      Highest Formal Education
       Elementary school1 (0.2)
       Some high school10 (1.7)
       High school77 (13.2)
       Some college205 (35.2)
       College graduate200 (34.4)
       Postgraduate89 (15.3)
      Parent Status
       Yes, I am a parent191 (32.8)
       No, I am not a parent391 (67.2)
      Notes: Demographics were self-reported from a list of response options. Response options are indicated in the table above. Some responses add up to > 100% because of rounding.

      Materials

      Gene-By-Environment education materials. Participants assigned to receive education on G × E concepts watched a 5-minute video created by the research team explaining these concepts with simple graphic animations and narrative voiceover. The educational video first explains what genes are and provides examples of their impact on physical characteristics and various tastes and preferences. The video then explains how a person's environment can interact with their genetics to influence eating behaviors. All video materials are available online via OSF.

      OSF Home. Communicating genomic concepts using virtual reality. https://osf.io/tajhq/?view_only=40570f9be4de46e4aa94276426f09b9b. Accessed November 22, 2022.

      Control education materials

      Participants assigned to the control condition watched a 5-minute video about spicy food with similar simple graphic animations and a narrative voiceover. This video was created by the research team.

      Vignette scenarios

      Participants watched 2 vignette scenarios that were designed for this study. Each scenario still had storyboard sketches with a narrative voiceover (Figure 1, Figure 2). Participants either watched these videos from a first- or third-person perspective. The first-person vignettes displayed the events through subjective shots that showed what the main character was viewing. The voiceover described the main character in the second-person language (eg, you). Note that although the language was second-person, the visual perspective was first-person, so that we will refer to this as the first-person perspective. The third-person vignettes described the main character as she or he, and the storyboard displayed the entire scene as if from the viewpoint of an unseen observer. Extensive informal piloting of these vignettes was conducted to ensure they were relatable and understandable to lay audiences.
      Figure 1
      Figure 1Summary of vignette elements for dinner party scenario.
      Figure 2
      Figure 2Summary of vignette elements for office worker scenario.
      In the first scenario (diner guest scenario), participants were exposed to a food choice situation from the perspective of a person with a genetic predisposition to strongly dislike bitter foods. The vignette character attends a dinner party in which the only non-calorie-dense food choices are bitter green vegetables (ie, brussels sprouts, kale). Their friends encourage them to try the green vegetables, and they reluctantly do, despite an overwhelming repulsion. They then move to eat more appealing, calorie-dense foods (ie, fried chicken, macaroni & cheese).
      The second scenario (office worker scenario) was designed to illustrate the perspective of an individual with a genetic predisposition to be highly attentive to palatable food cues in the environment. The vignette character is doing a repetitive file sorting task when a coworker appears with a plate of chocolate chip cookies, leaving them in front of the character. The vignette character becomes frustrated with the file sorting task as the cookies become increasingly distracting, and the character eventually eats the cookies.

      Measures

      Genetics knowledge

      General G × E understanding and literacy were measured with a 9-item subscale of the Public Understanding and Attitudes towards Genetics and Genomics questionnaire G × E subscale.
      • Carver RB
      • Castéra J
      • Gericke N
      • Evangelista NAM
      • El-Hani CN.
      Young adults’ belief in genetic determinism, and knowledge and attitudes towards modern genetics and genomics: the PUGGS questionnaire.
      Participants were given 1 point for each correct answer. Incorrect and “Don't know” answers were both considered incorrect (α = 0.74). Specific G × E knowledge about weight and eating behaviors was measured using a questionnaire designed by the study team. Some questions could be answered by simply remembering information in the educational materials; others required higher-level learning, such as application and generalization of knowledge. Participants answered 15 true-false questions with a focus on weight and eating behaviors. Example items included “Genes affect which flavors of food people enjoy,” and “Some lifestyle choices affect people differently because they have different genes.” Participants were given 1 point for each correct answer. Incorrect and “Don't know” responses were both considered incorrect (α = 0.73) (Figure 3). We preregistered the use of an open-ended knowledge check that asked participants to apply what they had learned about G × E concepts to a novel eating behavior. However, participants' responses were of poor quality and difficult to interpret. Therefore, we do not report the data here.
      Figure 3
      Figure 3Percentage of correct, incorrect, and do not know responses to Knowledge Check Questionnaire by education condition. F indicates false; G × E, gene-by-environment interaction; T, true.

      Genetic causal attributions

      Two items were used to assess participants’ endorsement of genetic causes of obesity and eating behaviors adapted from previous research.
      • Beeken RJ
      • Wardle J.
      Public beliefs about the causes of obesity and attitudes towards policy initiatives in Great Britain.
      Participants were presented with two 0–100 scales and were asked, “What percentage of someone's (obesity risk/eating behavior) is caused by genetics?”

      Weight stigma

      Stigma toward people with obesity was measured using the Anti-Fat Attitudes scale, which asks people to indicate how strongly they agree with 13 statements from 1 (strongly disagree) to 5 (strongly agree).
      • Crandall CS.
      Prejudice against fat people: ideology and self-interest.
      Participants’ dislike of people with higher weight was measured with the Dislike subscale, which includes 7 items, such as “I really do not like fat people much” (α = 0.88). Participants’ fear of becoming overweight was measured with the Fear subscale, which contains 3 items, such as “I worry about becoming fat” (α = 0.82). Participants’ tendency to blame people of higher weight for their weight status was measured with the Willpower subscale, which includes 3 items, such as “Fat people tend to be fat pretty much through their fault” (α = 0.71).

      Dietary self-efficacy and intentions

      A single item was used to measure participants’ confidence in controlling their diet: “How confident are you in your ability to control your diet?” Participants responded on a scale from 1 (not at all) to 5 (extremely). Dietary self-efficacy was assessed using 5 items from the Self-Efficacy and Eating Habits Survey,
      • Sallis JF
      • Pinski RB
      • Grossman RM
      • Patterson TL
      • Nader PR.
      The development of self-efficacy scales for health related diet and exercise behaviors.
      specifically the subscales related to the ability to stick to a diet and reduce calories. Items included “When I feel hungry: I will be able to choose healthy food over less-healthy options.” Participants responded on a 5-point scale from 1 (strongly disagree) to 5 (strongly agree) (α = 0.90). Dietary intentions were assessed using 2 items previously used to measure dietary intentions,
      • Persky S
      • Ferrer RA
      • Klein WM.
      Genomic information may inhibit weight-related behavior change inclinations among individuals in a fear state.
      “How likely is it that you will try to change your diet in the next 6 months?” and “I intend to make changes to my diet in the next 6 months.” Participants responded on a 5-point scale from 1 (not at all) to 5 (extremely) (α = 0.94).

      Empathic concern

      Participants were asked to what extent they felt 6 empathic emotions (tender, softhearted, warm, sympathetic, compassionate, moved) toward the (office worker/dinner guest) from 1 (none at all) to 5 (extremely).
      • Batson CD.
      The Altruism Question: Toward a Social-Psychological Answer.
      Ratings toward the 2 vignette characters were combined (α = 0.93). Using the same 6 empathic adjectives, participants were asked to rate how they felt toward people with obesity in general (α = 0.95).

      Manipulation check

      Participants were asked, “Was the (dinner party/office worker) scenario described from a second-person perspective (ie, you) or a third-person perspective (ie, he/she)?” Participants also had an option to indicate they were unsure.

      Data Analysis

      Two-by-two between-subjects ANOVAs were conducted to investigate the main effects of education materials and vignette perspectives on all knowledge and attitude measures and to investigate any interaction between these variables. Exploratory mediation analyses used the Hayes procedure.
      • Hayes AF
      • Preacher KJ.
      Conditional process modeling: using structural equation modeling to examine contingent causal processes.
      The data and syntax underlying these analyses are available via OSF.

      OSF Home. Communicating genomic concepts using virtual reality. https://osf.io/tajhq/?view_only=40570f9be4de46e4aa94276426f09b9b. Accessed November 22, 2022.

      RESULTS

      Impact of Education Materials And Perspective-Taking

      Genetics knowledge

      Participants’ genetics knowledge was significantly higher after watching the educational video than the control video. There was a significant main effect of the educational materials for the knowledge check (F(1,578) = 157.72, P < 0.001, Figure 3), and the Public Understanding and Attitudes towards Genetics and Genomics questionnaire (F(1,578) = 13.67, P < 0.001). There was no main effect of the vignette perspective on either measure of genetics knowledge (P > 0.05) and no interaction between education materials and vignette perspective (P >.05, Table 2).
      Table 2Mean and SD Values for All Preregistered Dependent Measures by Condition
      VariablesEducational VideoControl VideoMain Effect EducationMain Effect PerspectiveInteraction
      First-PersonThird-PersonFirst-PersonThird-PersonFPFPFP
      Genetics knowledge
       General G × E Knowledge (max range 0–9)6.1 (1.98)6.4 (2.12)5.6 (2.45)5.6 (2.42)13.67< 0.0010.400.530.370.54
       Specific G × E Knowledge (max range 0–15)12.9 (2.09)13.3 (1.58)10.8 (2.83)10.5 (2.59)157.72< 0.0010.150.693.790.05
      Genetic causal attributions
       Obesity (max range 0–100)45.4 (23.21)47.3 (20.52)40.7 (20.63)41.0 (22.48)9.230.0020.360.550.190.67
       Eating behaviors (max range 0–100)43.4 (23.66)46.2 (22.39)35.0 (20.93)34.9 (21.83)28.30< 0.0010.540.460.600.44
      Weight stigma
       Anti-fat attitudes total (max range 1–5)2.5 (0.73)2.4 (0.62)2.6 (0.64)2.6 (0.67)4.680.030.310.580.010.93
        Dislike subscale (max range 1–5)1.9 (0.86)1.8 (0.77)1.9 (0.83)1.9 (0.79)1.040.311.380.240.980.32
        Fear subscale (max range 1–5)3.1 (1.24)3.3 (1.19)3.3 (1.08)3.3 (1.19)1.600.210.470.492.210.14
        Willpower subscale (max range 1–5)3.1 (0.98)3.1 (0.89)3.4 (0.83)3.3 (0.88)9.920.0020.040.850.020.89
      Dietary self-efficacy and intentions
       Confidence to control diet (max range 1–5)3.3 (1.05)3.2 (1.00)3.2 (1.06)3.2 (1.14)0.800.370.930.340.080.77
       Dietary self-efficacy (max range 1–5)3.6 (0.98)3.5 (0.92)3.5 (0.90)3.5 (1.06)0.030.860.430.511.250.26
       Diet intentions (max range 1–5)2.9 (1.28)3.0 (1.29)3.1 (1.26)3.1 (1.34)2.670.100.340.560.030.87
      Empathic Concern
       Empathy for vignette characters (max range 1–5)2.5 (1.11)2.6 (0.99)2.4 (1.00)2.4 (1.01)4.270.041.150.280.040.84
       Empathy for people with obesity (max range 1–5)2.7 (1.13)2.9 (1.05)2.8 (1.07)2.8 (1.12)0.000.920.910.341.110.29
      G × E indicates gene-by-environment interaction.
      Note: Results of 2 × 2 ANOVAs are reported for each measure (α = 0.05).

      Causal attributions

      Participants were more likely to endorse genetic causes of obesity (F(1,578) = 9.23, P = 0.002) and eating behaviors (F(1,577) = 28.30, P < 0.001) after watching the educational video than the control video. There was no main effect of the vignette perspective on causal beliefs (P > 0.05) and no interaction between education materials and the vignette perspective (P > 0.05, Table 2).

      Weight stigma

      Participants reported significantly less blame toward people with higher weight after watching the educational videos than the control videos as measured by the Willpower subscale (Willpower subscale, F(1,578)= 9.92, P = 0.002). Anti-fat attitudes on the Fear and Dislike subscales were not significantly different between conditions (P > 0.05). There was no main effect of the vignette perspective on any Anti-fat attitude subscale (P > 0.05) and no interaction between education materials and the vignette perspective (P > 0.05, Table 2).

      Dietary self-efficacy and intentions

      Participants’ confidence and self-efficacy regarding their ability to change their diet were not influenced by education materials, vignette perspective, or interaction (P > 0.05, Table 2). Participants’ intentions to change their diet in the next 6 months were also not influenced by education materials, vignette perspective, or interaction (P > 0.05, Table 2).

      Empathic concern

      Participants’ empathy toward the main characters in the vignettes was significantly higher after watching the educational video than the control video (F(1,578)= 4.27, P = 0.04, Table 2). There was no main effect of the vignette perspective on empathy toward the main characters (P > 0.05) and no interaction between education materials and the vignette perspective (P > 0.05). Participants’ empathy toward people with obesity was not different between conditions. Participants reported similarly high levels of empathy toward people with obesity regardless of condition (F(1,578)= 0.00, p =.924, Table 2). There was no main effect of the vignette perspective on empathy toward people with obesity (P > 0.05) and no interaction between education materials and the vignette perspective (P > 0.05).

      Mediation Analyses

      We used the Hayes and Preacher
      • Hayes AF
      • Preacher KJ.
      Conditional process modeling: using structural equation modeling to examine contingent causal processes.
      procedure to investigate whether the educational video led to higher empathy and lower stigmatizing blame by increasing the extent to which participants attributed genetic causes to eating behaviors (Figure 4). We confirmed that genetic attributions significantly mediated the effect of education on empathy and stigmatizing blame (genetic attributions for obesity also fully mediated these relationships (bempathy = 0.11; 95% confidence interval [CI], 0.04–0.18; bstigma = −0.05; 95% CI. −0.08 to −0.02). Genetic attributions for obesity and genetic attributions for eating behavior were highly correlated (r = 0.84, P < 0.001), so we focus here on eating behaviors). Specifically, a significant indirect effect of education was found for empathy (b = 0.16; 95% CI, 0.09−0.23) and blame (b = −0.09; 95% CI, −0.16 to −0.03). The direct effect of education was rendered nonsignificant for empathy, indicating that genetic attributions fully mediated this relationship (b = −0.16, P = 0.07), whereas the direct effect on blame remained significant, indicating that genetic attributions partially mediated this relationship (b = −0.14, P = 0.037).
      Figure 4
      Figure 4Unstandardized regression coefficients for the relationship between condition and (weight stigma/empathy) as mediated by genetic causal beliefs. G × E indicates gene-by-environment interaction. *P < 0.001.
      We also conducted exploratory mediation analyses to determine whether the educational video positively affected blame via increasing empathy toward people with obesity. Our data were not consistent with this interpretation; the direct effect of education remained (b = −0.237, P < 0.001) and there was no significant indirect effect via empathy (b = 0.003; 95% CI, −0.05 to 0.05).

      Manipulation Efficacy

      Participants viewed both vignette scenarios in either first-person or third-person perspectives. However, not all participants correctly reported which perspective they had watched, indicating that the manipulation may have been too subtle, particularly in the first-person condition. For the dinner party scenario, only 69% of participants in the first-person perspective correctly identified their condition, whereas 90% of participants in the third-person condition did. Following the same pattern, only 64% correctly identified the first-person perspective for the office worker scenario, whereas 95% correctly identified the third-person perspective.

      Sensitivity analyses

      To assess a possible perspective effect within only those participants who correctly identified their condition, we re-ran the preregistered analyses with this smaller sample (n = 420, nfirst = 160, nthird = 260). Regardless, there were still no significant effects of perspective on any outcome measures and no significant interactions between perspective and education materials (P > 0.05).

      DISCUSSION

      Overall, the educational video about G × E influences on eating behaviors led to a better understanding of G × E concepts than controls and had some positive secondary effects on attitudes, including empathy and weight stigma. However, we found that participants’ attitudes were not influenced by whether they watched the vignette scenarios in first- or third-person perspective, and perspective did not moderate the efficacy of the education materials. Exploratory analyses suggest that secondary effects of G × E education were due to higher genetic causal attributions for eating behavior.
      Participants who watched the education materials better understood G × E concepts in general and understood their relevance to obesity and eating behaviors. We provide preliminary support for using video-based materials to successfully communicate the importance of G × E for eating behaviors. However, further evidence is needed to ensure the public can apply this knowledge to improve their diet and health.
      Education about G × E influences on eating behaviors also appears to have some beneficial secondary effects on reducing blame and increasing empathy. These attitude changes appear to result from heightened genetic causal attributions among those who received the educational videos. In line with previous research demonstrating that genetic explanations can reduce implicit anti-fat attitudes,
      • Persky S
      • Eccleston CP.
      Impact of genetic causal information on medical students‘ clinical encounters with an obese virtual patient: health promotion and social stigma.
      ,
      • Teachman BA
      • Gapinski KD
      • Brownell KD
      • Rawlins M
      • Jeyaram S.
      Demonstrations of implicit anti-fat bias: the impact of providing causal information and evoking empathy.
      G × E education may have convinced participants that people are not solely to blame for their weight. G × E education materials also increased empathy toward the vignette's main characters, but these increased empathic feelings did not generally extend to people with obesity.
      Gene-by-environment explanations indicate that obesity is, in part, controllable because environmental factors can be used to modify one's weight status. Thus, unlike presenting solely genetic explanations for obesity, G × E education has the potential to reduce stigma without undercutting dietary self-efficacy and motivation. In this study, participants who received the G × E education materials had similar dietary self-efficacy and confidence compared to controls, in line with previous research on G × E education
      • Lippa NC
      • Sanderson SC.
      Impact of informing overweight individuals about the role of genetics in obesity: an online experimental study.
      ,
      • Persky S
      • Yaremych HE
      • Goldring MR
      • Ferrer RA
      • Rose MK
      • Hollister BM.
      Investigating the efficacy of genetic, environmental, and multifactorial risk information when communicating obesity risk to parents of young children.
      and in contrast to previous research on genetics-only education, which has been shown to reduce dietary self-efficacy.
      • Persky S
      • Yaremych HE
      • Goldring MR
      • Ferrer RA
      • Rose MK
      • Hollister BM.
      Investigating the efficacy of genetic, environmental, and multifactorial risk information when communicating obesity risk to parents of young children.
      Although the absence of a backfire effect indicates G × E education is likely preferable to genetics-only education; further research is needed to improve dietary self-efficacy and confidence while communicating accurate information about the etiology and mechanisms behind obesity. One potential strategy is explicitly demonstrating how environmental changes can moderate genetic influences on eating (such as providing a concrete example of modifying one's environment by making alternative food choices available). Vignette examples could similarly be used to allow people to compare and contrast the impact of genetics in different environments.
      In contrast to our expectations, we found no effect of viewer perspective or interaction with perspective on any outcome variables. A potential explanation for this null result is that participants did not distinguish between the 2 conditions—a pattern suggested by our manipulation check. In particular, participants in the first-person condition did not appear to recognize it as such. Our perspective-taking manipulation may have failed because the language or storyboard imagery may have been too subtle or unclear. However, conscious memory of the manipulation might not be necessary for effects to be observed, and sensitivity analyses did not yield an effect of perspective even among participants who passed the manipulation check, suggesting that there are other reasons perspective was not influential.
      Although unexpected, this result is not unprecedented. Several studies have observed null effects when asking participants to engage in self-perspective-taking vs other-perspective-taking.
      • Galinsky AD
      • Wang CS
      • Ku G.
      Perspective-takers behave more stereotypically.
      ,
      • Davis MH
      • Conklin L
      • Smith A
      • Luce C.
      Effect of perspective taking on the cognitive representation of persons: a merging of self and other.
      • Davis MH
      • Soderlund T
      • Cole J
      • et al.
      Cognitions associated with attempts to empathize: how do we imagine the perspective of another?.
      • Finlay KA
      • Stephan WG.
      Reducing prejudice: The effects of empathy on intergroup attitudes.
      • Todd AR
      • Bodenhausen GV
      • Richeson JA
      • Galinsky AD.
      Perspective taking combats automatic expressions of racial bias.
      Such null effects may be especially likely when participants have very limited information about the target whose perspective they are asked to adopt.
      • Batson CD.
      Two forms of perspective taking: Imagining how another feels and imagining how you would feel.
      Future research should ensure that participants know enough about the vignette characters to engage in perspective-taking. Moreover, participants’ feelings about matching the avatars’ characteristics may have influenced our results in unknown ways.
      • Ferchaud A
      • Sanders MS.
      Seeing through the avatar's eyes: effects of point-of-view and gender match on identification and enjoyment.
      Participants may have also struggled to engage in perspective-taking because of a lack of knowledge about the lived experience of the vignette characters. It may be difficult for people to imagine the sensory and psychological aspects of a genetic predisposition toward obesogenic eating. Previous research has found that people are not very good at such imagination in general, but that experience with the situation can improve matters.
      • Van Boven L
      • Loewenstein G.
      Social projection of transient drive states.
      For genetic predispositions toward obesogenic eating, some participants may not have had related experiences in their own lives, making relying on imagination alone ineffective. Researchers have attempted to solve this issue in other domains by using physical props (such as visually distorting eyeglasses, wheelchairs, etc) to simulate sensory experiences such as partial-sightedness and physical disability.
      • Flower A
      • Burns MK
      • Bottsford-Miller NA.
      Meta-analysis of disability simulation research.
      In recent years, virtual reality has also become popular and has been used to some success to simulate bodily experiences such as a different height
      • Freeman D
      • Evans N
      • Lister R
      • Antley A
      • Dunn G
      • Slater M.
      Height, social comparison, and paranoia: an immersive virtual reality experimental study.
      or weight.
      • Ferrer-Garcia M
      • Porras-Garcia B
      • González-Ibañez C
      • et al.
      Does owning a “fatter” virtual body increase body anxiety in college students?.
      As such, virtual reality may have particular utility in simulating experiences that participants have not experienced themselves.
      • Ahn SJ
      • Le AMT
      • Bailenson J.
      The effect of embodied experiences on self-other merging, attitude, and helping behavior.
      In addition to the limitations regarding our perspective-taking manipulation discussed above, several other factors should be considered when interpreting our results. First, although we found a significant impact of education materials on attitudes toward people with obesity, the size of these effects was small. Whether these small shifts in attitudes translate into the more prosocial treatment of people with obesity remains to be seen. Indeed, it remains unlikely that any single intervention can lead to sustained improvements in attitudes. Nevertheless, our success may indicate a potential mechanism for reducing blame and increasing empathy—namely, enhancing people's comprehension of the G × E causes of obesogenic eating—which can be adapted into more long-lasting interventions.
      Second, our sample was more educated (49.7% with a bachelor's degree vs 32.9%) and more White (91.4% vs 75.8%) than the general US population,

      US Census Bureau. Quick Facts. 2020. https://www.census.gov/quickfacts/fact/table/US/PST045221. Accessed November 1, 2022.

      which limits its representativeness and generalizability. It is important not to generalize these results outside of the US, as anti-fat attitudes differ across cultures.
      • Crandall CS
      • D'Anello S
      • Sakalli N
      • Lazarus E
      • Nejtardt GW
      • Feather NT
      An attribution-value model of prejudice: anti-fat attitudes in six nations.
      Third, our vignettes presented dinner party and office work scenarios that, despite likely being common experiences for many Americans before the coronavirus disease 2019 pandemic, were subject to various levels of restrictions at the time of data collection. How this disconnect influenced participants’ ability to take the perspective of the vignette character is unknown.

      IMPLICATIONS FOR RESEARCH AND PRACTICE

      Communicating G × E causes of eating behaviors to the public is a useful way to improve attitudes toward people with higher weight. Therefore, we envision the potential for similar G × E education to be broadly disseminated as part of public health campaigns. Moreover, a greater understanding of these concepts may help improve patient-provider interactions around healthy eating and weight. Clinical encounters in which genetic influences on weight are discussed have been associated with a reduction in patients’ perceived weight-based stigma,
      • Sallis JF
      • Pinski RB
      • Grossman RM
      • Patterson TL
      • Nader PR.
      The development of self-efficacy scales for health related diet and exercise behaviors.
      ,
      • Persky S
      • Street R.
      Evaluating approaches for communicating about genomic influences on body weight.
      and less enacted bias on the part of the provider.
      • Persky S
      • Eccleston CP.
      Impact of genetic causal information on medical students‘ clinical encounters with an obese virtual patient: health promotion and social stigma.
      Similarly, focusing on G × E causes of eating may help tackle entrenched weight stigma among the general public and health care providers.
      Our research expands previous attempts to communicate G × E influences on weight by communicating G × E influences on eating behaviors. Compared with weight, the public is generally less accepting that eating behaviors have a genetic cause
      • Persky S
      • Bouhlal S
      • Goldring MR
      • McBride CM.
      Beliefs about genetic influences on eating behaviors: characteristics and associations with weight management confidence.
      ,
      • Persky S
      • Yaremych HE.
      Parents’ genetic attributions for children's eating behaviors: Relationships with beliefs, emotions, and food choice behavior.
      ; therefore, beliefs about eating behaviors may provide a greater opportunity for educational intervention. This research provides initial evidence of this utility, and future educational interventions may benefit from focusing on eating behaviors, specifically when attempting to improve attitudes toward people with higher weights.

      ACKNOWLEDGMENTS

      This research was funded by the Intramural Research Program of the National Human Genome Research Institute.

      References

        • Puhl RM
        • Heuer CA.
        The stigma of obesity: a review and update.
        Obesity (Silver Spring). 2009; 17: 941-964
        • Puhl RM
        • Andreyeva T
        • Brownell KD.
        Perceptions of weight discrimination: prevalence and comparison to race and gender discrimination in America.
        Int J Obes (Lond). 2008; 32: 992-1000
        • De Brún A
        • McCarthy M
        • McKenzie K
        • McGloin A.
        Weight stigma and narrative resistance evident in online discussions of obesity.
        Appetite. 2014; 72: 73-81
        • Sung J
        • Lee K
        • Song YM
        • Lee MK
        • Lee DH.
        Heritability of eating behavior assessed using the DEBQ (Dutch Eating Behavior Questionnaire) and weight-related traits: the healthy twin study.
        Obesity (Silver Spring). 2010; 18: 1000-1005
        • Reddon H
        • Guéant JL
        • Meyre D.
        The importance of gene-environment interactions in human obesity.
        Clin Sci (Lond). 2016; 130: 1571-1597
        • McCaffery JM.
        Precision behavioral medicine: implications of genetic and genomic discoveries for behavioral weight loss treatment.
        Am Psychol. 2018; 73: 1045-1055
        • Krakow M
        • Ratcliff CL
        • Hesse BW
        • Greenberg-Worisek AJ.
        Assessing genetic literacy awareness and knowledge gaps in the US population: results from the Health Information National Trends Survey.
        Public Health Genomics. 2017; 20: 343-348
        • Hilbert A
        • Zenger M
        • Luck-Sikorski C
        • Brähler E.
        Weight stigma and disease and disability concepts of obesity: a survey of the German population.
        Obes Facts. 2021; 14: 463-470
        • Lea DH
        • Kaphingst KA
        • Bowen D
        • Lipkus I
        • Hadley DW.
        Communicating genetic and genomic information: health literacy and numeracy considerations.
        Public Health Genomics. 2011; 14: 279-289
        • Ndiaye FK
        • Huyvaert M
        • Ortalli A
        • et al.
        The expression of genes in top obesity-associated loci is enriched in insula and substantia nigra brain regions involved in addiction and reward.
        Int J Obes (Lond). 2020; 44: 539-543
        • Grimm ER
        • Steinle NI.
        Genetics of eating behavior: established and emerging concepts.
        Nutr Rev. 2011; 69: 52-60
        • Schur E
        • Carnell S.
        What twin studies tell us about brain responses to food cues.
        Curr Obes Rep. 2017; 6: 371-379
        • Tholin S
        • Rasmussen F
        • Tynelius P
        • Karlsson J.
        Genetic and environmental influences on eating behavior: the Swedish young male twins study.
        Am J Clin Nutr. 2005; 81: 564-569
        • Hilbert A.
        Weight stigma reduction and genetic determinism.
        PLOS ONE. 2016; 11e0162993
        • Lippa NC
        • Sanderson SC.
        Impact of information about obesity genomics on the stigmatization of overweight individuals: an experimental study.
        Obesity (Silver Spring). 2012; 20: 2367-2376
        • Persky S
        • Goldring MR
        • El-Toukhy S
        • Ferrer RA
        • Hollister B.
        Parental defensiveness about multifactorial genomic and environmental causes of children‘s obesity risk.
        Child Obes. 2019; 15: 289-297
        • Ata RN
        • Thompson JK
        • Boepple L
        • Marek RJ
        • Heinberg LJ.
        Obesity as a disease: effects on weight-biased attitudes and beliefs.
        Stigma Health. 2018; 3: 406-416
        • Lippa NC
        • Sanderson SC.
        Impact of informing overweight individuals about the role of genetics in obesity: an online experimental study.
        Hum Hered. 2013; 75: 186-203
        • Persky S
        • Eccleston CP.
        Impact of genetic causal information on medical students‘ clinical encounters with an obese virtual patient: health promotion and social stigma.
        Ann Behav Med. 2011; 41: 363-372
        • Teachman BA
        • Gapinski KD
        • Brownell KD
        • Rawlins M
        • Jeyaram S.
        Demonstrations of implicit anti-fat bias: the impact of providing causal information and evoking empathy.
        Health Psychol. 2003; 22: 68-78
        • Beeken RJ
        • Wardle J.
        Public beliefs about the causes of obesity and attitudes towards policy initiatives in Great Britain.
        Public Health Nutr. 2013; 16: 2132-2137
        • Willoughby EA
        • Love AC
        • McGue M
        • Iacono WG
        • Quigley J
        • Lee JJ.
        Free will, determinism, and intuitive judgments about the heritability of behavior.
        Behav Genet. 2019; 49: 136-153
        • Persky S
        • Bouhlal S
        • Goldring MR
        • McBride CM.
        Beliefs about genetic influences on eating behaviors: characteristics and associations with weight management confidence.
        Eat Behav. 2017; 26: 93-98
        • Persky S
        • Yaremych HE
        • Goldring MR
        • Ferrer RA
        • Rose MK
        • Hollister BM.
        Investigating the efficacy of genetic, environmental, and multifactorial risk information when communicating obesity risk to parents of young children.
        Ann Behav Med. 2021; 55: 720-733
        • Crandall CS
        • D'Anello S
        • Sakalli N
        • Lazarus E
        • Nejtardt GW
        • Feather NT
        An attribution-value model of prejudice: anti-fat attitudes in six nations.
        Pers Soc Psychol Bull. 2001; 27: 30-37
        • Wirtz C
        • van der Pligt J
        • Doosje B.
        Derogating obese individuals: the role of blame, contempt, and disgust.
        J Appl Soc Psychol. 2016; 46: 216-228
        • Burnette JL
        • Hoyt CL
        • Dweck CS
        • Auster-Gussman L.
        Weight beliefs and messages: mindsets predict body-shame and anti-fat attitudes via attributions.
        J Appl Soc Psychol. 2017; 47: 616-624
        • Galinsky AD
        • Wang CS
        • Ku G.
        Perspective-takers behave more stereotypically.
        J Pers Soc Psychol. 2008; 95: 404-419
        • Batson CD
        • Early S
        • Salvarani G.
        Perspective taking: imagining how another feels versus imaging how you would feel.
        Pers Soc Psychol Bull. 1997; 23: 751-758
        • Todd AR
        • Galinsky AD.
        Perspective-taking as a strategy for improving intergroup relations: evidence, mechanisms, and qualifications.
        Soc Pers Psychol Compass. 2014; 8: 374-387
        • Batson CD.
        Altruism in Humans.
        Oxford University Press, 2011
        • Wu Y
        • Zhang Y.
        The impact of perspective taking on obesity stereotypes: the dual mediating effects of self-other overlap and empathy.
        Front Psychol. 2021; 12643708
        • Gloor JL
        • Puhl RM.
        Empathy and perspective-taking: examination and comparison of strategies to reduce weight stigma.
        Stigma Health. 2016; 1: 269-279
        • Brunyé TT
        • Ditman T
        • Mahoney CR
        • Augustyn JS
        • Taylor HA.
        When you and I share perspectives: pronouns modulate perspective taking during narrative comprehension.
        Psychol Sci. 2009; 20: 27-32
        • Debarba HG
        • Molla E
        • Herbelin B
        • Boulic R.
        Characterizing embodied interaction in first and third person perspective viewpoints.
        in: 2015 IEEE Symposium on 3D User Interfaces (3DUI). IEEE, 2015: 67-72
        • Brilmayer I
        • Werner A
        • Primus B
        • Bornkessel-Schlesewsky I
        • Schlesewsky M.
        The exceptional nature of the first person in natural story processing and the transfer of egocentricity.
        Lang Cogn Neurosci. 2019; 34: 411-427
        • Myers MW
        • Laurent SM
        • Hodges SD.
        Perspective taking instructions and self-other overlap: different motives for helping.
        Motiv Emot. 2014; 38: 224-234
        • Johnson MK
        • Sherman SJ.
        Constructing and reconstructing the past and the future in the present.
        in: Higgins E.T. Sorrentino R.M. Handbook of Motivation and Cognition: Foundations of Social Behavior. The Guilford Press, 1990: 482-526 (Vol 2)
        • Taylor SE
        • Pham LB
        • Rivkin ID
        • Armor DA.
        Harnessing the imagination. Mental simulation, self-regulation, and coping.
        Am Psychol. 1998; 53: 429-439
      1. OSF Home. Communicating genomic concepts using virtual reality. https://osf.io/tajhq/?view_only=40570f9be4de46e4aa94276426f09b9b. Accessed November 22, 2022.

        • Chen H-TM
        • Thomas M.
        Effects of lecture video styles on engagement and learning.
        Educ Tech Res Dev. 2020; 68: 2147-2164
        • Carver RB
        • Castéra J
        • Gericke N
        • Evangelista NAM
        • El-Hani CN.
        Young adults’ belief in genetic determinism, and knowledge and attitudes towards modern genetics and genomics: the PUGGS questionnaire.
        PLOS ONE. 2017; 12e0169808
        • Crandall CS.
        Prejudice against fat people: ideology and self-interest.
        J Pers Soc Psychol. 1994; 66: 882-894
        • Sallis JF
        • Pinski RB
        • Grossman RM
        • Patterson TL
        • Nader PR.
        The development of self-efficacy scales for health related diet and exercise behaviors.
        Health Educ Res. 1988; 3: 283-292
        • Persky S
        • Ferrer RA
        • Klein WM.
        Genomic information may inhibit weight-related behavior change inclinations among individuals in a fear state.
        Ann Behav Med. 2016; 50: 452-459
        • Batson CD.
        The Altruism Question: Toward a Social-Psychological Answer.
        Psychology Press, 2014
        • Hayes AF
        • Preacher KJ.
        Conditional process modeling: using structural equation modeling to examine contingent causal processes.
        in: Hancock GR Mueller RO Structural Equation Modeling: A Second Course. IAP Information Age Publishing, 2013: 219-266
        • Davis MH
        • Conklin L
        • Smith A
        • Luce C.
        Effect of perspective taking on the cognitive representation of persons: a merging of self and other.
        J Pers Soc Psychol. 1996; 70: 713-726
        • Davis MH
        • Soderlund T
        • Cole J
        • et al.
        Cognitions associated with attempts to empathize: how do we imagine the perspective of another?.
        Pers Soc Psychol Bull. 2004; 30: 1625-1635
        • Finlay KA
        • Stephan WG.
        Reducing prejudice: The effects of empathy on intergroup attitudes.
        J Appl Soc Psychol. 2000; 30: 1720-1737
        • Todd AR
        • Bodenhausen GV
        • Richeson JA
        • Galinsky AD.
        Perspective taking combats automatic expressions of racial bias.
        J Pers Soc Psychol. 2011; 100: 1027-1042
        • Batson CD.
        Two forms of perspective taking: Imagining how another feels and imagining how you would feel.
        in: Markman KD Klein WM Suhr JA Handbook of Imagination and Mental Simulation. Psychology Press, 2009: 267-279
        • Ferchaud A
        • Sanders MS.
        Seeing through the avatar's eyes: effects of point-of-view and gender match on identification and enjoyment.
        Imagin Cogn Pers. 2018; 38: 82-105
        • Van Boven L
        • Loewenstein G.
        Social projection of transient drive states.
        Pers Soc Psychol Bull. 2003; 29: 1159-1168
        • Flower A
        • Burns MK
        • Bottsford-Miller NA.
        Meta-analysis of disability simulation research.
        Remedial Spec Educ. 2007; 28: 72-79
        • Freeman D
        • Evans N
        • Lister R
        • Antley A
        • Dunn G
        • Slater M.
        Height, social comparison, and paranoia: an immersive virtual reality experimental study.
        Psychiatry Res. 2014; 218: 348-352
        • Ferrer-Garcia M
        • Porras-Garcia B
        • González-Ibañez C
        • et al.
        Does owning a “fatter” virtual body increase body anxiety in college students?.
        Annu Rev CyberTherapy Telemed. 2017; 15: 147-153
        • Ahn SJ
        • Le AMT
        • Bailenson J.
        The effect of embodied experiences on self-other merging, attitude, and helping behavior.
        Media Psychol. 2013; 16: 7-38
      2. US Census Bureau. Quick Facts. 2020. https://www.census.gov/quickfacts/fact/table/US/PST045221. Accessed November 1, 2022.

        • Persky S
        • Street R.
        Evaluating approaches for communicating about genomic influences on body weight.
        Ann Behav Med. 2015; 49: 675-684
        • Persky S
        • Yaremych HE.
        Parents’ genetic attributions for children's eating behaviors: Relationships with beliefs, emotions, and food choice behavior.
        Appetite. 2020; 155104824