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Record W3123941902 · doi:10.1097/rnj.0000000000000313

Older Persons and Nursing Staff’s Perspectives on Continence Care in Rehabilitation

2021· article· en· W3123941902 on OpenAlexaff
Kathleen F. Hunter, Sherry Dahlke, Nicholas Smith, Alina Lin, Saima Rajabali, Adrian Wagg

Bibliographic record

VenueRehabilitation Nursing · 2021
Typearticle
Languageen
FieldMedicine
TopicPelvic floor disorders treatments
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsToiletingRehabilitationNursingMedicineGeriatric rehabilitationNursing carePhysical therapyActivities of daily living

Abstract

fetched live from OpenAlex

PURPOSE: The aim of the study was to understand continence care in geriatric rehabilitation from the perspectives of older persons and nursing staff. DESIGN: This is a qualitative descriptive study. METHODS: Ten patients and 10 nursing staff participated in semistructured interviews. Observations of care were recorded in field notes. Content analysis was used to develop themes of patient and nursing staff perspectives. FINDINGS: Three themes were developed: Perceptions of Assessment, Continence Management, and Rehab: The Repair Shop. Patients had limited insight into continence assessment and management by nursing staff. For older persons, incontinence was embarrassing and created dependence; independence in toileting meant gaining control. Staff viewed continence as an important part of rehabilitation nursing but focused on containment and regular toileting, with patients seeing absorbent pads as commonly suggested. CONCLUSIONS: Continence care approaches that engage older persons during rehabilitation are needed. CLINICAL RELEVANCE: Restoration of continence through patient-centered care is core to older person rehabilitation.

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)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.371
Threshold uncertainty score0.770

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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 head0.007
GPT teacher head0.302
Teacher spread0.295 · 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 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

Citations5
Published2021
Admission routes1
Has abstractyes

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