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Record W2027444996 · doi:10.1177/1043454214553706

Attitudes and Perceptions of Parents and Staff Toward the Rapid Hydration Protocol Prior to Chemotherapy in Children

2014· article· en· W2027444996 on OpenAlexaffabout
Ramona Samonis, Jane Hilliard, Tejinder Bains, Kathryn Hollis, Erin O’Shaughnessy, Régis Vaillancourt, Donna L. Johnston

Bibliographic record

VenueJournal of Pediatric Oncology Nursing · 2014
Typearticle
Languageen
FieldMedicine
TopicChildhood Cancer Survivors' Quality of Life
Canadian institutionsUniversity of OttawaChildren's Hospital of Eastern OntarioUniversity of Toronto
Fundersnot available
KeywordsLikert scaleProtocol (science)MedicinePerceptionNursingScale (ratio)Family medicinePsychologyAlternative medicineDevelopmental psychology

Abstract

fetched live from OpenAlex

The Children's Hospital of Eastern Ontario has implemented a rapid hydration protocol that may reduce the time required to achieve adequate hydration prior to chemotherapy. This study aims to assess parent satisfaction and the attitudes and perceptions of oncology staff with regard to the rapid hydration protocol. Patients who received both standard and rapid hydration were identified, and their parents were asked to rate the child's experiences on a 5-point Likert-type scale. Oncology staff were interviewed and common themes were identified. Parents perceived their child's experience with rapid hydration to be the same or better than with the standard hydration. Themes uncovered through staff interviews indicate an overall positive perception of rapid hydration, but there are some concerns with certain patients not meeting necessary urine parameters in a timely manner, and incorporating the rapid hydration preprinted order into the current chemotherapy preprinted order was a challenge. These results may be used to improve the current practice and inform hospitals planning to adopt rapid hydration, but further research is required to assess parent satisfaction.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.104
Threshold uncertainty score0.297

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.021
GPT teacher head0.377
Teacher spread0.357 · 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 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

Citations1
Published2014
Admission routes2
Has abstractyes

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