Evidence map›Paper›PMID 37111077›Full record

ReviewNutrients2023

Digital Health Solutions for Weight Loss and Obesity: A Narrative Review.

Liam Irvin, Leigh A Madden, Phil Marshall, Rebecca V Vince

Open access · goldAbstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in Nutrients, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
21citing papers in PubMed, 2 pooled it
12.7field-weighted citation impact, top 1% 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

21 citing papers in PubMed, 2 syntheses or guidelines pooled it, 29 citations in OpenAlex.

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  8. ZENIA: Development of an AI-driven nutrition app to support immune health: An EAACI task force report.Pediatric allergy and immunology : official publication of the European Society of Pediatric Allergy and Immunology · 2026
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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

4 authors at 1 institution in 1 country.

Liam IrvinSchool of Sport, Exercise and Rehabilitation Sciences, University of Hull, Hull HU6 7RX, UK.
Leigh A MaddenCentre for Biomedicine, Hull York Medical School, University of Hull, Hull HU6 7RX, UK.ORCID 0000-0002-1503-1147
Phil MarshallSchool of Sport, Exercise and Rehabilitation Sciences, University of Hull, Hull HU6 7RX, UK.
Rebecca V VinceSchool of Sport, Exercise and Rehabilitation Sciences, University of Hull, Hull HU6 7RX, UK.ORCID 0000-0002-4150-0939
University of Hull · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Personal exercise programmes have long been used and prescribed for weight loss and the improvement of quality of life in obese patients. While individualised programmes are usually the preferred option, they can be more costly and challenging to deliver in person. A move to digital programmes with a wider reach has commenced, and demand has increased due to the SARS-CoV-2 pandemic. In this review, we evaluate the current status of digital exercise programme delivery and its evolution over the past decade, with a focus on personalisation. We used specific keywords to search for articles that met our predetermined inclusion and exclusion criteria in order to provide valuable evidence and insights for future research. We identified 55 studies in total in four key areas of focus, from the more recent development of apps and personal digital assistants to web-based programmes and text or phone call interventions. In summary, we observed that apps may be useful for a low-intensity approach and can improve adherence to programmes through self-monitoring, but they are not always developed in an evidence-based manner. Engagement and adherence are important determinants of weight loss and subsequent weight maintenance. Generally, professional support is required to achieve weight loss goals.

Indexed as

COVID-19Quality of LifeHumansObesitySARS-CoV-2Weight Lossdigital healthe-healthm-healthobesityweight loss

Identifiers

PMID37111077
PMCPMC10145832
OpenAlexW4365448803

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.