Evidence map›Paper›PMID 33889111›Full record

ReviewFrontiers in psychology2021

How Digital Food Affects Our Analog Lives: The Impact of Food Photography on Healthy Eating Behavior.

Tjark Andersen, Derek Victor Byrne, Qian Janice Wang

Abstract readReview
In one paragraph

Review in Frontiers in psychology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Article
  5. Foods (Basel, Switzerland) · 2022
    Article
  6. Exploring the Linkages of Digital Food Communication and Analog Food Behavior: A Scoping Review.International journal of environmental research and public health · 2022
    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.

Tjark AndersenFood Quality Perception and Society, Department of Food Science, Faculty of Technical Sciences, Aarhus University, Aarhus, Denmark.
Derek Victor ByrneFood Quality Perception and Society, Department of Food Science, Faculty of Technical Sciences, Aarhus University, Aarhus, Denmark.
Qian Janice WangFood Quality Perception and Society, Department of Food Science, Faculty of Technical Sciences, Aarhus University, Aarhus, Denmark.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Obesity continues to be a global issue. In recent years, researchers have started to question the role of our novel yet ubiquitous use of digital media in the development of obesity. With the recent COVID-19 outbreak affecting almost all aspects of society, many people have moved their social eating activities into the digital space, making the question as relevant as ever. The bombardment of appetizing food images and photography - colloquially referred to as "food porn" - has become a significant aspect of the digital food experience. This review presents an overview of whether and how the (1) viewing, (2) creating, and (3) online sharing of digital food photography can influence consumer eating behavior. Moreover, this review provides an outlook of future research opportunities, both to close the gaps in our scientific understanding of the physiological and psychological interaction between digital food photography and actual eating behavior, and, from a practical viewpoint, to optimize our digital food media habits to support an obesity-preventive lifestyle. We do not want to rest on the idea that food imagery's current prevalence is a core negative influence

Indexed as

commensalityfood intakefood photographyfood porngrounded cognitionsocial media

Identifiers

PMID33889111
PMCPMC8056120

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.