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Record W6889197415 · doi:10.25384/sage.c.6767319

The Role and Contributions of Nurses in Stroke Rehabilitation Units: An Integrative Review

2023· other· en· W6889197415 on OpenAlexaff

Bibliographic record

VenueSage Journals Data · 2023
Typeother
Languageen
Field
Topic
Canadian institutionsWestern University
Fundersnot available
KeywordsRehabilitationStroke (engine)Context (archaeology)MEDLINEStroke recoveryClinical Practice

Abstract

fetched live from OpenAlex

Nurses’ contributions to stroke rehabilitation have been viewed as pivotal, but therapeutically nonspecific. This integrative review synthesized empirical literature on the roles and contributions of nurses to inpatient stroke rehabilitation to answer three research questions: (a) What specific skills or tasks have been identified as the roles and contributions of nurses to inpatient stroke rehabilitation? (b) How do nurses perform these skills/tasks to support and promote inpatient stroke rehabilitation and recovery? and (c) What factors have been identified to impact nurses’ working conditions on inpatient stroke rehabilitation units? A systematic search of multiple electronic databases retrieved seven studies which provided significant context and examples to these questions. <i>What nurses do</i> in practice included, for example, maximizing patients’ independence in performing daily activities, preventing harm, and preserving integrity. <i>How nurses perform</i> their therapeutic roles included teaching, coaching, coordination, management, advocacy, collaboration. <i>Factors that impact nurses’ working conditions</i> consisted of time, resources, and knowledge. This review demonstrates our current understanding of nurses’ contributions to inpatient stroke rehabilitation, highlights their significant role, identifies current barriers/challenges of implementing stroke nursing care, and suggests ways of documenting and measuring nurses’ contributions.

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)0.004
metaresearch head score (Gemma)0.013
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.280
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.013
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.035
GPT teacher head0.383
Teacher spread0.347 · 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.

Study designNot applicable
Domainnot available
GenreReview

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
Published2023
Admission routes1
Has abstractyes

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Same venueSage Journals DataFrench-language works237,207