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Problems of New Caregivers of Persons with Stroke

2006· article· en· W1967065087 on OpenAlexfundno aff
Linda L. Pierce, Victoria Steiner, Barbara Hicks, Allison Lea Holzaepfel

Bibliographic record

VenueRehabilitation Nursing · 2006
Typearticle
Languageen
FieldMedicine
TopicStroke Rehabilitation and Recovery
Canadian institutionsnot available
FundersReseau canadien de recherche respiratoire
KeywordsIntervention (counseling)RehabilitationPsychologyIndependence (probability theory)Stroke (engine)NursingGerontologyMedicinePhysical therapy

Abstract

fetched live from OpenAlex

Nine adult caregivers new to the role of caring for persons with stroke, upon discharge from rehabilitation centers in Ohio and Michigan and living farther away from formalized support services than urban caregivers, were enrolled for 3 months in a Web-based intervention project that examined the feasibility of the intervention and described the experience of caring. This article is an analysis of qualitative data from the intervention project that used a rigorous protocol to examine 68 perceived problems reported in caring. Problem themes in order of most to least frequent were 1) having independence issues, 2) dealing with emotions, 3) living with physical limitations, 4) managing co-morbid conditions, 5) balancing it all, 6) participating in physical therapy, and 7) having sleeping issues. These problems were related to four of Orem's universal self-care requisites. Although the total number of problems decreased over time, "balancing it all" was the only problem that increased. This may be due to the resumption of the caregivers' regular activities or increased caregiving responsibilities. Nurses could use these findings to identify and focus on self-care needs of caregivers and to implement problem-resolution strategies.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.299
Threshold uncertainty score0.316

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 head0.009
GPT teacher head0.260
Teacher spread0.250 · 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

Citations34
Published2006
Admission routes1
Has abstractyes

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