Evidence map›Paper›PMID 35103881›Full record

ArticleJournal of behavioral medicine2022

Exploring the impact of genetic beliefs about specific eating behaviors on dietary self-efficacy.

Macred O Gbenro, Alison Jane Martingano, Susan Persky

Open access · greenAbstract read
In one paragraph

Article in Journal of behavioral medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.4field-weighted citation impact, top 40% of its field
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

3 citing papers in PubMed, 2 citations in OpenAlex.

  1. Article
  2. Article
  3. 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 at 1 institution in 1 country.

Macred O GbenroSocial and Behavioral Research Branch, National Human Genome Research Institute, 31 Center Drive, B1B36, Bethesda, MD, 20892, USA.
Alison Jane MartinganoSocial and Behavioral Research Branch, National Human Genome Research Institute, 31 Center Drive, B1B36, Bethesda, MD, 20892, USA.
Susan PerskySocial and Behavioral Research Branch, National Human Genome Research Institute, 31 Center Drive, B1B36, Bethesda, MD, 20892, USA. perskys@mail.nih.gov.ORCID 0000-0002-7768-5744
National Human Genome Research Institute · US

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 HG200396NHGRI NIH HHS Z01-HG200396-06
6 · The paper itself

Abstract

Future personalized approaches to weight management are likely to include consideration of genetic influences on eating behaviors. This study explores whether genetic beliefs about eating behaviors influence dietary self-efficacy and confidence. In a survey of 261 individuals of various weight statuses, we find that endorsing genetic causes of two specific eating behaviors (taste preference and disinhibition) predicts poorer dietary self-efficacy for people who exhibit these eating behaviors. This suggests there may be utility to considering eating behaviors individually when it comes to predicting the influence of genetic information provision in the service of precision medicine interventions. Individuals with high disinhibited eating and/or bitter taster status may be particularly sensitive to interpreting genetic predisposition information in ways that undercut self-efficacy and confidence.

Indexed as

Feeding BehaviorSelf EfficacyBody Mass IndexDietEatingHumansSurveys and QuestionnairesConfidenceDietDisinhibitionEating BehaviorObesitySelf-efficacyWeight

Identifiers

PMID35103881
PMCPMC9995156
OpenAlexW4210801557

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

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.