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Caregiver Strain and Caregiver Burden of Primary Caregivers of Stroke Survivors with and Without Aphasia

2006· review· en· W2069677913 on OpenAlexaff
Rosemarié E. Rombough, Ena Howse, Wally J. Bartfay

Bibliographic record

VenueRehabilitation Nursing · 2006
Typereview
Languageen
FieldMedicine
TopicStroke Rehabilitation and Recovery
Canadian institutionsOntario Tech UniversityQueen's University
Fundersnot available
KeywordsAphasiaCaregiver burdenStroke (engine)MedicineInclusion (mineral)Family caregiversPsychologyMEDLINEGerontologyPsychiatryDementiaDisease

Abstract

fetched live from OpenAlex

Little is known about how the burden and strain of caring for stroke patients with or without aphasia affects primary caregivers. This article (a) critically examines the literature on the burden and strain of care experienced by caregivers of stroke patients and (b) examines the relationship between aphasia and caregiver burden and strain. Two literature reviews of three databases were conducted. Fourteen articles (12 quantitative articles, 1 mixed-design article, and 1 qualitative article) were found to comply with the study criteria for the first literature search. A second literature search focused on the effects of stroke survivors' aphasia on caregiving; none of the articles retrieved met the inclusion criteria. This article suggests that there is a lack of research in this area and that several key initiatives are needed, including the development of an instrument with psychometric properties appropriate for assessing the burden and strain on caregivers of stroke patients. Implications for future nursing practice and research are highlighted.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.006
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.008
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0050.006
Science and technology studies0.0000.000
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.016
GPT teacher head0.300
Teacher spread0.284 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations51
Published2006
Admission routes1
Has abstractyes

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