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Record W4240570487 · doi:10.32920/ryerson.14662611

Attitudes Of Transplant Nurses Toward Clinical Trials

2021· preprint· en· W4240570487 on OpenAlexaboutno aff
Olesya Kolisnyk

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldHealth Professions
TopicEthics in medical practice
Canadian institutionsnot available
Fundersnot available
KeywordsClinical trialMedicineNursingFamily medicineInternal medicine

Abstract

fetched live from OpenAlex

Nurses may have an important role in supporting patients' decision making about their participation in clinical trials. Nurses' views about clinical trials and patients' understanding of the clinical trial process may shape the role nurses play in these trials. Little is known about transplant nurses' attitudes and beliefs toward clinical trials. This quantitative study employed a survey method involving a convenience sample of transplant nurses (n=39) in an urban hospital in Southern Ontario to describe attitudes and beliefs of transplant nurses toward clinical trials. The results indicated that transplant nurses had positive attitudes and beliefs toward clinical trials. Specifically, outpatient coordinators and older nurses were more positive in their attitudes. Nurses perceived transplant patients were knowledgeable about clinical trials. The majority of nurses (85%) engaged in the conduct of clinical trials. Transplant nurses also suggested educational, administrative and financial support as beneficial to further enhance their participation in these trials.

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)0.016
metaresearch head score (Gemma)0.062
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.984
Threshold uncertainty score0.086

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0160.062
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.003
Scholarly communication0.0030.001
Open science0.0000.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.707
GPT teacher head0.710
Teacher spread0.003 · 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 designObservational
DomainMethods
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

Citations0
Published2021
Admission routes1
Has abstractyes

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