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Record W3034657593 · doi:10.1177/2053434520937408

Physiotherapists’ role during hospital-to-home transition for older adults with hip fracture and mobility limitation: A research protocol

2020· article· en· W3034657593 on OpenAlexaff
Michael Kalu, Augustine C Okoh, Henrietha Nwankwo, Ebuka Miracle Anieto, Israel I. Adandom, Samuel U. Jumbo, Uduonu Ekezie, Emofe Diameta, Olayinka Akinrolie, Perpetua Obi, Chidinma A Omeje, Sadiq Mohammad, Michael S Ajulo, MacMillian Opara, Ukachukwu Okoroafor Abaraogu

Bibliographic record

VenueInternational Journal of Care Coordination · 2020
Typearticle
Languageen
FieldMedicine
TopicHip and Femur Fractures
Canadian institutionsUniversity of ManitobaWestern UniversityMcMaster University
Fundersnot available
KeywordsHip fractureThematic analysisRehabilitationMedicineFocus groupQualitative researchPhysical therapyIndependent livingActivities of daily livingGerontologyOsteoporosis

Abstract

fetched live from OpenAlex

Introduction Functional deficits such as gait speed, muscle strength or reduced activities in daily living after discharge are predictors for hospital readmission for older adults with hip fractures. However, physiotherapists (PTs) who are inherently mobility experts, do not actively participate during the hospital-to-home transition of older adults with hip fractures in the developing countries, including Nigeria. This qualitative study aims to describe and explore how PTs working within inpatient rehabilitation units prepare older adults (≥60 years) with a hip fracture for transfer to their home in the community. Methods We will adopt Sally Thorne’s Interpretive Description approach to purposively select 25 PTs with 5-years experience of participating in discharging older adults with hip fractures from inpatient rehabilitation-to-home. Data collection will include (a) semi-structured, one-on-one interviews with PTs, (b) discharge summaries of two older adults, and (c) final focus group discussion with PTs. We will ask the physiotherapists to provide discharge summaries of two older adults - one that they described as a “difficult” case and one that they described as an “easy” case during inpatient rehabilitation-to-home transition. Data will be analyzed employing Sally Thorne’s “borrowing techniques”- content and thematic analysis for the patients’ discharge summaries and PT interviews, respectively.

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)0.000
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 score0.825
Threshold uncertainty score0.333

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.339
Teacher spread0.326 · 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

Citations4
Published2020
Admission routes1
Has abstractyes

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