Evidence map›Paper›PMID 42409394›Full record

ArticleBMJ open2026

Real food-based nurse-delivered education to reduce ultra-processed food consumption in adults in community and outpatient chronic disease prevention and management: a scoping review protocol.

Jiejie Ge, Min Wang, Chunyan Li, Xiang Wang, Haiyang Song, Jun Yang, Yanyu Feng, Chuanying Zhang, Sijing Peng

Abstract read
In one paragraph

Article in BMJ open, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

9 authors.

Jiejie GeSchool of Nursing, Anhui University of Chinese Medicine, Hefei, Anhui, China.ORCID http://orcid.org/0009-0008-2600-0291
Min WangDepartment of Nursing, Huangshan City People's Hospital, Huangshan, Anhui, China.
Chunyan LiSchool of Nursing, Anhui University of Chinese Medicine, Hefei, Anhui, China.ORCID http://orcid.org/0009-0009-8773-9361
Xiang WangSchool of Nursing, Anhui University of Chinese Medicine, Hefei, Anhui, China.
Haiyang SongSchool of Nursing, Anhui University of Chinese Medicine, Hefei, Anhui, China.
Jun YangSchool of Nursing, Anhui University of Chinese Medicine, Hefei, Anhui, China.ORCID http://orcid.org/0009-0004-1327-1632
Yanyu FengSchool of Nursing, Anhui University of Chinese Medicine, Hefei, Anhui, China.
Chuanying ZhangSchool of Nursing, Anhui University of Chinese Medicine, Hefei, Anhui, China.
Sijing PengSchool of Nursing, Anhui University of Chinese Medicine, Hefei, Anhui, China pengsj@ahtcm.edu.cn.ORCID http://orcid.org/0000-0002-5069-5029

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionUltra-processed food (UPF) reduction has become an increasingly important target in chronic disease prevention and management. Although contemporary dietary guidance has moved towards food-based and skill-oriented approaches, it remains unclear how nurse-delivered education explicitly targeting UPF reduction has been conceptualised, implemented and evaluated in community and outpatient settings. This scoping review aims to map the extent, characteristics and knowledge gaps of evidence on real food-based, nurse-delivered education designed to reduce UPF consumption among adults in community and outpatient chronic disease prevention and management. METHODS AND ANALYSIS: This scoping review will be conducted in accordance with the Joanna Briggs Institute (JBI) methodology for scoping reviews and reported in line with the Preferred Reporting Items for Systematic Review and Meta-Analysis Protocols (PRISMA-P) adapted as appropriate for a scoping review protocol. Eligible evidence sources will include quantitative, qualitative and mixed-methods studies, as well as relevant reviews, programme reports, descriptive papers and text and opinion papers published in English or Chinese. Evidence will be included if it involves adults aged 19 years and older and examines nurse-delivered education explicitly targeting UPF reduction using the NOVA food classification system or an equivalent processing-based operationalisation, while supporting substitution towards unprocessed or minimally processed foods and whole foods, in community or outpatient chronic disease prevention or management contexts. Searches will cover records published from 1 January 2010 to the date of each final database search. Draft searches for the protocol were conducted on 22 February 2026 in selected databases. Final searches will be conducted in MEDLINE (PubMed), the Cumulative Index to Nursing and Allied Health Literature, Embase, Scopus, Web of Science Core Collection and major Chinese databases, supplemented by targeted grey literature searches and citation tracking. Two reviewers will independently screen records, assess full texts and chart data using a piloted data charting tool. Findings will be synthesised descriptively and presented in evidence tables, diagrams and narrative summaries. ETHICS AND DISSEMINATION: Ethical approval is not required because this review will synthesise data from publicly available sources and will not involve primary data collection from human participants. Findings will be disseminated through publication in a peer-reviewed journal, conference presentations and updates to the associated Open Science Framework project. TRIAL REGISTRATION DETAILS: Open Science Framework registration: https://osf.io/3xakz.

Indexed as

Fast FoodsPatient Education as TopicAdultChronic DiseaseFood, ProcessedHumansOutpatientsResearch DesignScoping Reviews as TopicChronic DiseaseHealth EducationNursing CarePrimary Health Care

Identifiers

PMID42409394
PMCPMC13343077

What OpenQuestion holds

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LicenceCC BY-NC
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Registered trials

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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.