MétaCan
Menu
Back to cohort

Functional and self‐efficacy changes of patients admitted to a Geriatric Rehabilitation Unit

2004· article· en· W2138687999 on OpenAlexaffabout
Rose McCloskey

Bibliographic record

VenueJournal of Advanced Nursing · 2004
Typearticle
Languageen
FieldMedicine
TopicFrailty in Older Adults
Canadian institutionsUniversity of New Brunswick
Fundersnot available
KeywordsGeriatric rehabilitationUnit (ring theory)RehabilitationMedicineGerontological nursingPhysical medicine and rehabilitationPhysical therapyGerontologyPsychologyNursing

Abstract

fetched live from OpenAlex

BACKGROUND: Geriatric Rehabilitation Units (GRUs) have been established to restore functional abilities of older hospitalized patients. Although considerable health care resources have been allocated to these units, few outcome-based research studies have been reported on Canadian GRUs. AIM: The aim of this paper is to report a study examining the effect of admission to a GRU on changes in patients' functional ability and self-efficacy in performing everyday activities at home. METHODS: Following Institutional Review Board approval, data were collected from 40 patients age 65-101 years (mean 83.8, sd 6.57) admitted to a 21-bed interdisciplinary GRUs over a 7-month period. All were living independently prior to hospital admission. Data were collected on admission to the unit and on discharge using two instruments: the Functional Independence Measure and Falls Efficacy Scale. RESULTS: Statistically significant improvements were found in functional ability and self-efficacy following admission to the GRUs. CONCLUSIONS: Although functional level and feelings of self-efficacy on admission to the unit were at levels which may have prevented participants from returning home, the majority were discharged to the community. Results suggest that admission to a GRU helps prepare patients to return to community living.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.935
Threshold uncertainty score0.319

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 head0.013
GPT teacher head0.291
Teacher spread0.278 · 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

Citations35
Published2004
Admission routes2
Has abstractyes

Explore more

Same venueJournal of Advanced NursingSame topicFrailty in Older AdultsFrench-language works237,207