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Record W2116162996 · doi:10.3109/09638280903114394

Impact of caring for individuals with stroke on perceived physical health of informal caregivers

2010· review· en· W2116162996 on OpenAlexaff
Katherine Salter, Laura Zettler, Norine Foley, Robert Teasell

Bibliographic record

VenueDisability and Rehabilitation · 2010
Typereview
Languageen
FieldMedicine
TopicStroke Rehabilitation and Recovery
Canadian institutionsLawson Health Research Institute
Fundersnot available
KeywordsNormativePsychologyMental healthGerontologyDistressPhysical healthStroke (engine)Inclusion (mineral)Longitudinal studyHealth careClinical psychologyMedicinePsychiatrySocial psychology

Abstract

fetched live from OpenAlex

PURPOSE: Caring for a person who has experienced stroke can be a formidable task placing considerable demands upon the informal caregiver. Although the impact of caring on mental health has been well established, less convincing associations between caregiving and declining physical health have been reported. In order to examine the impact of caregiving over time on the physical health of individuals providing informal care for individuals with stroke, we conducted a review of the published literature. METHOD: Literature searches of three electronic databases were conducted for the years 1996-2008 to identify studies providing longitudinal data based on repeated quantitative assessment of physical health. Pooled analyses were conducted. RESULTS: Sixteen studies were identified for inclusion. On the basis of pooled analyses, perceived physical health appeared stable over time. When comparisons to normative values were possible, the experience of health did not differ substantially from age- and sex-matched norms. Associations between physical health and psychological distress or well-being were identified. CONCLUSIONS: Informal caregiving does not result, necessarily, in reduced physical health. Further study is required to examine the timing and nature of the relationship between psychological distress and physical health to inform provision of services intended to maintain caregiver health and well being.

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)0.001
metaresearch head score (Gemma)0.001
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: none
Teacher disagreement score0.832
Threshold uncertainty score0.875

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.024
GPT teacher head0.366
Teacher spread0.343 · 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

Citations49
Published2010
Admission routes1
Has abstractyes

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