Evidence map›Paper›PMID 42635550›Full record

ArticleInternational journal of nursing knowledge2026

Clinical validation of the nursing diagnosis of inadequate nutritional intake in children with cancer.

Iane Ximenes Teixeira, Natália Cabrera Matos, Marcos Venícios de Oliveira Lopes, Viviane Martins da Silva, Amanda Laryssa Gomes do Nascimento, Yanka Alcântara Cavalcante, Ana Beatriz Oliveira Marques Dos Santos, Daniele Paula Alves Mouta

Abstract readValidation Study
In one paragraph

Article in International journal of nursing knowledge, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

8 authors.

Iane Ximenes TeixeiraLuciano Feijão College, Sobral, Ceará, Brazil.ORCID 0000-0002-6790-6478
Natália Cabrera MatosAssis Chateaubriand Maternity School, Fortaleza, Ceará, Brazil.ORCID 0009-0007-0924-3702
Marcos Venícios de Oliveira LopesFederal University of Ceara, Fortaleza, Ceará, Brazil.ORCID 0000-0001-5867-8023
Viviane Martins da SilvaFederal University of Ceara, Fortaleza, Ceará, Brazil.ORCID 0000-0002-8033-8831
Amanda Laryssa Gomes do NascimentoCeará School of Public Health, Fortaleza, Ceará, Brazil.
Yanka Alcântara CavalcanteFederal University of Ceara, Fortaleza, Ceará, Brazil.ORCID 0000-0003-0152-9216
Ana Beatriz Oliveira Marques Dos SantosLuciano Feijão College, Sobral, Ceará, Brazil.ORCID 0009-0001-5229-961X
Daniele Paula Alves MoutaLuciano Feijão College, Sobral, Ceará, Brazil.ORCID 0000-0002-4312-7322

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

PurposeTo clinically validate the nursing diagnosis "Inadequate Nutritional Intake" based on elements identified within a specific situation theory framework in the context of children with cancer.MethodThis is a diagnostic accuracy study following the Standards for Reporting Diagnostic Accuracy Studies (STARD) protocol. Specifically, it refers to the clinical validation phase of the nursing diagnosis Inadequate nutritional intake, using a cross-sectional design. The study was conducted in a tertiary pediatric hospital with a sample of 69 children diagnosed with cancer.FindingsA total of 11 clinical indicators demonstrated diagnostic accuracy above 50%, including: ascites, low weight-for-age ≤2 SD, cachexia, mid-upper arm circumference < 10th percentile, fatigue, pale mucous membranes, dry mucosa, dry skin, weight loss greater than 5% within 1 month, compromised immune response, and delayed wound healing. The primary etiological factors identified in this study were chemotherapy, economic disadvantage, inadequate dietary pattern, insufficient dietary intake, rejection of hospital food, and family food culture. The nursing diagnosis had a prevalence of 7.25% among the participating children.ConclusionsDespite the low prevalence, this study highlights that inadequate nutritional intake is a real and complex health issue in this population, with multiple etiological factors requiring a precise and systematic assessment for early identification by healthcare professionals, particularly nurses. This underscores the importance of research focused on refining nursing diagnoses in specific populations.Implications for nursing practiceValidation studies such as this enhance the accuracy and evidence-based nature of nursing practice, while also supporting collaborative decision-making for addressing nutritional issues in children with cancer, considering the various etiological factors involved.

Indexed as

NeoplasmsNursing DiagnosisAdolescentChildChild, PreschoolCross-Sectional StudiesFemaleHumansMalechild nutritionfeeding and eating disordersnursing diagnosisoncologyvalidationvulnerable group nutrition

Identifiers

PMID42635550
PMCPMC13503987

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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.