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Record W2991409038 · doi:10.1002/nop2.421

A comparative descriptive analysis of perceived quality of caring attitudes and behaviours between haemodialysis patients and their nurses

2019· article· en· W2991409038 on OpenAlexaff
Philippe Delmas, Matteo Antonini, Laurent Berthoud, Louise O’Reilly, Chantal Cara, Sylvain Brousseau, Tanja Bellier-Teichmann, Jean Weidmann, Delphine Roulet-Schwab, Isabelle Ledoux, Jérôme Pasquier, Evelyne Boillat, Vanessa Brandalesi, Mario Konishi

Bibliographic record

VenueNursing Open · 2019
Typearticle
Languageen
FieldHealth Professions
TopicPatient-Provider Communication in Healthcare
Canadian institutionsUniversité du Québec en OutaouaisUniversité de MontréalUniversité de Sherbrooke
FundersSchweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung
KeywordsNursingScale (ratio)MedicinePerceived qualityDescriptive statisticsDescriptive researchFamily medicinePsychology

Abstract

fetched live from OpenAlex

Aim: Despite its importance in nursing, perceived quality of the nurse-patient relationship has seldom been researched. This study sought to examine and compare the quality of caring attitudes and behaviours as perceived by haemodialysis patients and their nurses. Design: This comparative descriptive study involved 140 haemodialysis patients and 101 nurses caring for them in ten haemodialysis units in the French-speaking part of Switzerland. Methods: Participants completed a sociodemographic questionnaire and the Caring Nurse-Patient Interaction Scale (CNPI-70). Results: Both nurses and patients reported a high frequency of caring attitudes and behaviours. Patients gave higher ratings than nurses did on all the caring dimensions, except spirituality. Implications are discussed.

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)0.002
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
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 head0.397
GPT teacher head0.514
Teacher spread0.116 · 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.

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

Citations19
Published2019
Admission routes1
Has abstractyes

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