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Record W2048603576 · doi:10.5737/1181912x1627987

Oncology nursing: Finding the balance in a changing health care system

2006· article· en· W2048603576 on OpenAlexaffvenueabout
Debra Bakker, Margaret I. Fitch, Esther Green, Lorna Butler, Kärin Olson

Bibliographic record

VenueCanadian Oncology Nursing Journal · 2006
Typearticle
Languageen
FieldNursing
TopicNursing education and management
Canadian institutionsCancer Care OntarioSunnybrook Health Science CentreLaurentian University
Fundersnot available
KeywordsWorkforceWorkloadNursingOncology nursingOncologyHealth careMedicineRestructuringInternal medicineNurse educationPsychologyPolitical science

Abstract

fetched live from OpenAlex

Health care restructuring has resulted in significant changes in the workload and work environment for oncology nurses. While recent studies describe the impact of these changes on the general nursing workforce in several countries, there have been no published studies that have focused on worklife issues of Canadian oncology nurses. Therefore, a qualitative study was conducted to gain insight about how oncology nursing has changed over the past decade and how Canadian oncology nurses are managing these changes. Analysis of telephone interviews with 51 practising oncology nurses employed across Canada revealed three major themes. The first theme, "health care milieu", portrayed a picture of the cancer care environment and patient and professional changes that occurred over the past decade. The second theme, "conflicting demands", reflects how the elements of change and social forces have challenged professional oncology nursing practice. The third theme, "finding the way", describes the patterns of behaviour that nurses used to manage the changing health care environment and make meaning out of nurses' work in cancer care. Overall, the findings portray a picture of Canadian oncology nurses in "survival mode". They face many workplace challenges, but are able to keep going "for now" because they find ways to balance their responsibilities on a daily basis and because they know and believe that their specialized nursing knowledge and skills make a difference in patient care.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.922
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0020.000
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 head0.019
GPT teacher head0.340
Teacher spread0.321 · 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 designNot applicable
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

Citations19
Published2006
Admission routes3
Has abstractyes

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