Evidence map›Paper›PMID 37810925›Full record

ArticleFrontiers in nutrition2023

Assessing daily energy intake in adult women: validity of a food-recognition mobile application compared to doubly labelled water.

Michele Serra, Daniela Alceste, Florian Hauser, Paul J M Hulshof, Harro A J Meijer, Andreas Thalheimer, Robert E Steinert, Philipp A Gerber, Alan C Spector, Daniel Gero and 1 more

Open access · goldAbstract read
In one paragraph

Article in Frontiers in nutrition, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
2.6field-weighted citation impact, top 10% 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

4 citing papers in PubMed, 9 citations in OpenAlex.

  1. Review
  2. Article
  3. Article
  4. Review
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

11 authors at 5 institutions in 3 countries.

Michele SerraDepartment of Surgery and Transplantation, University Hospital Zurich, Zurich, Switzerland.
Daniela AlcesteDepartment of Surgery and Transplantation, University Hospital Zurich, Zurich, Switzerland.
Florian HauserFaculty of Medicine, University of Zurich (UZH), Zurich, Switzerland.
Paul J M HulshofDivision of Human Nutrition, Wageningen University, Wageningen, Netherlands.
Harro A J MeijerCentre for Isotope Research (CIO), Energy and Sustainability Research Institute Groningen, University of Groningen, Groningen, Netherlands.
Andreas ThalheimerDepartment of Surgery and Transplantation, University Hospital Zurich, Zurich, Switzerland.
Robert E SteinertDepartment of Surgery and Transplantation, University Hospital Zurich, Zurich, Switzerland.
Philipp A GerberDepartment of Endocrinology, Diabetology and Clinical Nutrition, University Hospital Zurich, Zurich, Switzerland.
Alan C SpectorDepartment of Psychology and Program in Neuroscience, Florida State University, Tallahassee, FL, United States.
Daniel GeroDepartment of Surgery and Transplantation, University Hospital Zurich, Zurich, Switzerland.
Marco BueterDepartment of Surgery and Transplantation, University Hospital Zurich, Zurich, Switzerland.
University Hospital of Zurich · CHUniversity of Zurich · CHFlorida State University · USUniversity of Groningen · NLWageningen University & Research · NL

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Accurate dietary assessment is crucial for nutrition and health research. Traditional methods, such as food records, food frequency questionnaires, and 24-hour dietary recalls (24HR), have limitations, such as the need for trained interviewers, time-consuming procedures, and inaccuracies in estimations. Novel technologies, such as image-based dietary assessment apps, have been developed to overcome these limitations. SNAQ is a novel image-based food-recognition app which, based on computer vision, assesses food type and volume, and provides nutritional information about dietary intake. This cross-sectional observational study aimed to investigate the validity of SNAQ as a dietary assessment tool for measuring energy and macronutrient intake in adult women with normal body weight (

Indexed as

artificial intelligencedietary assessmentdietary intakedoubly labelled waterenergy intakeimage-based food recognitionmHealth

Identifiers

PMID37810925
PMCPMC10556674
OpenAlexW4386967844

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.