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Priorities for Adult Cancer Nursing Research

2001· article· en· W2129326790 on OpenAlexaboutno aff
Stephanie Barrett, Linda J. Kristjanson, Tracey Sinclair, Suzanne Hyde

Bibliographic record

VenueCancer Nursing · 2001
Typearticle
Languageen
FieldSocial Sciences
TopicDelphi Technique in Research
Canadian institutionsnot available
Fundersnot available
KeywordsDelphi methodMedicineReferralNursingDelphiHealth careFamily medicine

Abstract

fetched live from OpenAlex

Two Delphi surveys have been conducted during the past 20 years to identify cancer nursing research priorities; one in the United States and one in Canada. Sir Charles Gairdner Hospital, the State Cancer Referral Centre in Western Australia, undertook a replication of this Delphi survey to identify nursing research priorities for adult cancer nursing. The aim of this replication was to identify possible changes in priorities and account for cultural difference in the healthcare systems. A total of 45 responses were received from the first Delphi round and 30 from the second. The top ten priorities identified by this sample were different from those identified in prior studies. The top ranked research topic was "What strategies would be most helpful in allowing nurses time to provide emotional support to cancer patients and carers?" These results may stimulate discussion and re-assessment of research priorities in other adult cancer care settings.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.212
metaresearch head score (Gemma)0.212
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.212
Threshold uncertainty score0.972

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.2120.212
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0090.007
Science and technology studies0.0100.006
Scholarly communication0.0130.010
Open science0.0030.015
Research integrity0.0080.010
Insufficient payload (model declined to judge)0.0080.002

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 head0.365
GPT teacher head0.624
Teacher spread0.260 · 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 source (direct Gemma or distilled Codex), not a consensus.

Study designQualitative
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

Citations34
Published2001
Admission routes1
Has abstractyes

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