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Record W2602779200 · doi:10.12968/ijpn.2017.23.3.144

Understanding bladder management on a palliative care unit: a grounded theory study

2017· article· en· W2602779200 on OpenAlexaffabout
Iris Gutmanis, Melissa E. Hay, Joshua Shadd, Janette Byrne, Sarah McCallum, Kristen Bishop, Patricia Whitfield

Bibliographic record

VenueInternational Journal of Palliative Nursing · 2017
Typearticle
Languageen
FieldMedicine
TopicPalliative Care and End-of-Life Issues
Canadian institutionsSt Joseph's Health CareWestern UniversityMcMaster UniversityLawson Health Research Institute
Fundersnot available
KeywordsTimelineGrounded theoryConstructivist grounded theoryPalliative careContext (archaeology)NursingHumanityUnit (ring theory)MedicineQualitative researchPsychologySociology

Abstract

fetched live from OpenAlex

BACKGROUND: Research regarding factors associated with nursing-initiated changes to bladder management at end-of-life is sparse. OBJECTIVES: To explore the process of Palliative Care Unit (PCU) nurses' approach to bladder management changes. METHODS: Nursing staff from one PCU in London, Canada were interviewed regarding bladder management care practices. A constructivist grounded theory was generated. RESULTS: Four interconnected themes emerged: humanity (compassionate support of patients); journey (making the most of a finite timeline); health condition (illness, functional decline); and context (orders, policies, supplies). These overlapping themes must be considered in light of ongoing changes which prompt recycling through the framework. While bladder management necessitates shared decision-making and individualised care, nurses' phronetic experience may serve to detect the presence of change and the need to consider other alternatives. CONCLUSION: End-of-life bladder management requires nurses to continually reconsider the significance of humanity, journey, health condition and context in light of ongoing changes.

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)0.023
metaresearch head score (Gemma)0.020
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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.023
Threshold uncertainty score0.122

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0230.020
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0070.011
Scholarly communication0.0050.005
Open science0.0020.005
Research integrity0.0020.004
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 head0.422
GPT teacher head0.519
Teacher spread0.097 · 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

Citations1
Published2017
Admission routes2
Has abstractyes

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