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Record W2129277375 · doi:10.1177/136140960000500606

Working with resistance, tension and objectivity: Conducting a randomised controlled trial of a nursing intervention for breathlessness

2000· article· en· W2129277375 on OpenAlexaff
Hilary Plant, Mary Bredin, Meinir Krishnasamy, Jessica Corner

Bibliographic record

VenueJournal of Research in Nursing · 2000
Typearticle
Languageen
FieldMedicine
TopicPalliative Care and End-of-Life Issues
Canadian institutionsInstitute of Cancer Research
Fundersnot available
KeywordsObjectivity (philosophy)Intervention (counseling)NursingResistance (ecology)Randomized controlled trialMedicinePsychology

Abstract

fetched live from OpenAlex

It is vital that nurses wishing to recommend or introduce new strategies are able to provide supporting evidence that is acceptable to their colleagues. The methodology from which to derive such evidence remains to be clearly defined, as the research process is complex, demanding and, to a certain extent, uncharted. This paper examines the experience of nurses collaborating in a multi-centre randomised controlled trial which evaluated a nursing intervention for the management of breathlessness in patients with lung cancer. The study raised several important methodological issues: resistance among colleagues to innovative nursing practice; the difficulty of measuring well-being in patients whose physical condition is deteriorating; maintaining uniformity of practice within a diverse group of collaborating nurse researchers; and the tension between the nursing role and the necessity of an ethically demanding research design. Analysis of the process of conducting a randomised controlled trial produced valuable insights which indicated the kind of support required to undertake research and successfully implement a new intervention into clinical practice. The study also highlighted the problems associated with asking ill people to complete standard measurement tools, particularly when such instruments might not be sensitive to the reality of the patient(s) problem, in this case, the experience of breathlessness.

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)0.004
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.158
Threshold uncertainty score0.271

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.291
GPT teacher head0.522
Teacher spread0.230 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designRandomized trial
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

Citations18
Published2000
Admission routes1
Has abstractyes

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