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Record W940725801 · doi:10.1188/15.cjon.e87-e91

Wound Dressings During Radiotherapy for Cancer: A Survey of Practice

2015· article· en· W940725801 on OpenAlexaffabout
Siby Thomas, Sheryl Reimer‐Kirkham, Rosemary Kohr

Bibliographic record

VenueClinical journal of oncology nursing · 2015
Typearticle
Languageen
FieldMedicine
TopicEffects of Radiation Exposure
Canadian institutionsTrinity Western UniversityUniversity of the Fraser Valley
FundersNational Cancer Institute
KeywordsMedicineRadiation therapyClinical PracticeContext (archaeology)Nursing practiceRadiation oncologyNursingOncology nursingRelevance (law)Medical physicsNurse educationSurgery

Abstract

fetched live from OpenAlex

BACKGROUND: Patients undergoing radiotherapy may experience changes to the skin that require dressings. Recommendations regarding radiating through wound dressings have been variable and relate to the concern regarding surface dose increase or bolus effect. OBJECTIVES: The purpose of this article is to identify current evidence and practice through literature review and a national environmental scan. METHODS: Nurses from 18 radiation oncology centers in Canada were surveyed about current practice. In-depth telephone interviews were conducted with four nurse participants to further understand the context of this issue within the nursing practice environment. FINDINGS: The integrated results of the study were reviewed with five clinical experts to make recommendations for research, practice, leadership, and policy. Implications for clinical practice included the involvement of radiation oncology nurses in the treatment planning team, development of clinical practice tools, and the relevance of the Person-Centered Nursing framework for wound management during radiotherapy.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.007
metaresearch head score (Gemma)0.015
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.383
Threshold uncertainty score0.993

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.015
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.144
GPT teacher head0.541
Teacher spread0.397 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations2
Published2015
Admission routes2
Has abstractyes

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