Evidence map›Paper›PMID 37699308›Full record

ArticleEating behaviors2023

Evaluating eating behavior traits of virtual targets: Attitudes and empathy.

Siri C Ravuri, Alison Jane Martingano, Susan Persky

Abstract read
In one paragraph

Article in Eating behaviors, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Siri C RavuriSocial and Behavioral Research Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, United States.
Alison Jane MartinganoSocial and Behavioral Research Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, United States.
Susan PerskySocial and Behavioral Research Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, United States. Electronic address: perskys@mail.nih.gov.

Funding

Eating and Feeding Behavior: Exploring Phenotypes and Influencing OutcomesZIAHG200396 · NHGRI · NATIONAL HUMAN GENOME RESEARCH INSTITUTE · PI PERSKY, SUSAN · 2015 to 2025
$2.4M
Intramural NIH HHS ZIA HG200396
6 · The paper itself

Abstract

There are many common stereotypes related to food consumption and eating behaviors that are considered indicative of one's personal character. Negative evaluations of an individual based on their eating behaviors may lead to stigmatization and other harmful psychosocial outcomes. Using vignette scenarios, we examined 582 participants' attitudes towards two target characters who exhibited bitter food dislike and high reward-based eating drive respectively. In open-ended text responses, participants were more likely to respond negatively and use stigmatizing language when describing the character with high reward-based eating drive versus the character with bitter food dislike. In addition, empathic responses depended on whether participants believed they, themselves, exhibited reward-based eating drive. Participants tended to be more empathetic and more positive towards the target who shared their own reward-based eating behaviors. Interestingly, the same was not true for those who shared bitter food distaste. These results suggest that eating behaviors that are perceived as more controllable and unusual may be more negatively perceived. Targeted education or support to reduce negative attitudes about such traits may be beneficial.

Indexed as

AttitudeEmpathyFeeding BehaviorHumansBitter food avoidanceEating behaviorEmpathyReward-based eating driveStereotypesStigma

Identifiers

PMID37699308
PMCPMC11301783

What OpenQuestion holds

Textmetadata
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.