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Record W4221081707 · doi:10.1097/rnj.0000000000000368

Pilot of Patient Engagement in Continence Care on Geriatric Rehabilitation Units

2022· article· en· W4221081707 on OpenAlexaff

Bibliographic record

VenueRehabilitation Nursing · 2022
Typearticle
Languageen
FieldMedicine
TopicPelvic floor disorders treatments
Canadian institutionsGlenrose Rehabilitation HospitalUniversity of Alberta
Fundersnot available
KeywordsGeriatric rehabilitationRehabilitationPatient-centered careMEDLINEGeriatric carePatient careFecal incontinence

Abstract

fetched live from OpenAlex

PURPOSE: The aim of this study was to pilot a process of engaging geriatric rehabilitation patients in the assessment and management of their continence concerns. DESIGN: A descriptive study was conducted. METHODS: The study has four phases: (1) staff education on continence with a pre-post knowledge quiz, (2) design of patient engagement process by a working group, (3) a 6-week pilot of a patient symptom questionnaire and process of engaging patients with audits of disciplinary admission histories and documentation, and (4) patient and staff feedback surveys. RESULTS: Patients in geriatric rehabilitation identify a range of bladder and bowel symptoms. However, there was little documented evidence from the interprofessional team that corresponded to patients' reported symptoms. CONCLUSION: Further research into symptoms bothersome to patients and engagement of both patients and the interprofessional team in addressing these in the rehabilitation setting is needed. CLINICAL RELEVANCE TO REHABILITATION NURSING: Patients admitted to geriatric rehabilitation have a range of bladder and bowel symptoms which need to be addressed.

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)0.020
metaresearch head score (Gemma)0.033
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.020
Threshold uncertainty score0.103

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0200.033
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0020.001
Scholarly communication0.0020.001
Open science0.0020.005
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0070.001

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 head0.015
GPT teacher head0.285
Teacher spread0.270 · 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 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

Citations0
Published2022
Admission routes1
Has abstractyes

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