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1.
J Med Internet Res ; 25: e43701, 2023 10 12.
Article in English | MEDLINE | ID: mdl-37824190

ABSTRACT

BACKGROUND: It is possible that tailoring dietary approaches to an individual's genomic profile could provide optimal dietary inputs for biological functioning and support adherence to dietary management protocols. The science required for such nutrigenetic and nutrigenomic profiling is not yet considered ready for broad application by the scientific and medical communities; however, many personalized nutrition products are available in the marketplace, creating the potential for hype and misleading information on social media. Twitter provides a unique big data source that provides real-time information. Therefore, it has the potential to disseminate evidence-based health information, as well as misinformation. OBJECTIVE: We sought to characterize the landscape of precision nutrition content on Twitter, with a specific focus on nutrigenetics and nutrigenomics. We focused on tweet authors, types of content, and presence of misinformation. METHODS: Twitter Archiver was used to capture tweets from September 1, 2020, to December 1, 2020, using keywords related to nutrition and genetics. A random sample of tweets was coded using quantitative content analysis by 4 trained coders. Codebook-driven, quantified information about tweet authors, content details, information quality, and engagement metrics were compiled and analyzed. RESULTS: The most common categories of tweets were precision nutrition products and nutrigenomic concepts. About a quarter (132/504, 26.2%) of tweet authors presented themselves as science experts, medicine experts, or both. Nutrigenetics concepts most frequently came from authors with science and medicine expertise, and tweets about the influence of genes on weight were more likely to come from authors with neither type of expertise. A total of 14.9% (75/504) of the tweets were noted to contain untrue information; these were most likely to occur in the nutrigenomics concepts topic category. CONCLUSIONS: By evaluating social media discourse on precision nutrition on Twitter, we made several observations about the content available in the information environment through which individuals can learn about related concepts and products. Tweet content was consistent with the indicators of medical hype, and the inclusion of potentially misleading and untrue information was common. We identified a contingent of users with scientific and medical expertise who were active in discussing nutrigenomics concepts and products and who may be encouraged to share credible expert advice on precision nutrition and tackle false information as this technology develops.


Subject(s)
Medicine , Nutrigenomics , Social Media , Humans , Communication , Nutritional Status
2.
J Nutr Educ Behav ; 55(1): 55-67, 2023 01.
Article in English | MEDLINE | ID: mdl-36621267

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.


Subject(s)
Empathy , Weight Prejudice , Humans , Gene-Environment Interaction , Attitude , Overweight , Feeding Behavior , Social Stigma
3.
Genet Med ; 24(11): 2389-2398, 2022 11.
Article in English | MEDLINE | ID: mdl-36053286

ABSTRACT

PURPOSE: To craft evidence-based educational approaches related to polygenic risk score (PRS) implementation, it is crucial to forecast issues and biases that may arise when PRS are introduced in clinical care. METHODS: Medical students (N = 84) were randomized to a simulated primary care encounter with a Black or White virtual reality-based patient and received either a direct-to-consumer-style PRS report for 5 common complex conditions or control information. The virtual patient inquired about 2 health concerns and her genetic report in the encounter. Data sources included participants' verbalizations in the simulation, care plan recommendations, and self-report outcomes. RESULTS: When medical students received PRSs, they rated the patient as less healthy and requiring more strict advice. Patterns suggest that PRSs influenced specific medical recommendations related to the patient's concerns, despite student reports that participants did not use it for that purpose. We observed complex patterns regarding the effect of patient race on recommendations and behaviors. CONCLUSION: Educational approaches should consider potential unintentional influences of PRSs on decision-making and evaluate ways that they may be applied inconsistently across patients from different racial groups.


Subject(s)
Students, Medical , Female , Humans , Multifactorial Inheritance/genetics , Racial Groups , Referral and Consultation , Risk Factors
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