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Record W4409147191 · doi:10.1097/rnj.0000000000000494

Impact of Inpatient Stroke Rehabilitation on Caregivers’ Perceived Readiness for Patient Discharge

2025· article· en· W4409147191 on OpenAlexaff
Kathryn Williamson-Link, Megan Byrne, Samantha Hockings, Laura Wilemon, Larisa Lahey, Anne Hubling, Susan Brady

Bibliographic record

VenueRehabilitation Nursing · 2025
Typearticle
Languageen
FieldMedicine
TopicStroke Rehabilitation and Recovery
Canadian institutionsImpact
Fundersnot available
KeywordsRehabilitationPreparednessStroke (engine)MedicinePhysical therapyPath analysis (statistics)Discharge planningHospital dischargePsychologyNursingIntensive care medicine

Abstract

fetched live from OpenAlex

PURPOSE: The purpose of this study is to assess the extent to which caregivers' perceived readiness for discharge improves after participating in a stroke inpatient rehabilitation program, as measured by their self-reported preparedness for transitioning patients to the community. DESIGN: This was a prospective study involving pre- and postsurveys of caregivers. METHODS: The Preparedness Assessment for the Transition Home After Stroke (PATH-s) survey instrument was administered to caregivers of patients following a stroke at admission and discharge from inpatient rehabilitation. The PATH-s final score is an average that ranges from 1 to 4. A higher average score indicates higher readiness for discharge. RESULTS: Twenty-five patient-caregiver dyads complete the study protocol representing a 42% survey response rate of consented participants for both the initial and discharge PATH-s surveys. The initial mean PATH-s was 2.86 ( SD = 0.434), and the discharge mean PATH-s was 3.25 ( SD = 0.436). The differences between these scores were significant ( Z = -4.280, p ≤ .0001), suggesting participation with inpatient rehabilitation following a stroke improved the caregivers' self-reported readiness for discharge. CLINICAL RELEVANCE: It is important for rehabilitation nurses to be aware of the caregiver's self-reported readiness for discharge to address any issues identified to improve transition for discharge following a stroke. CONCLUSION: Caregiver readiness for discharge is an important issue yet it may be an undervalued aspect of the care delivery system.

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)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.476
Threshold uncertainty score0.849

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
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 head0.009
GPT teacher head0.324
Teacher spread0.315 · 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

Citations1
Published2025
Admission routes1
Has abstractyes

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