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Record W2139640248 · doi:10.1136/ebn.8.4.119

Review: counselling and education may improve outcomes in caregivers of patients with stroke

2005· letter· en· W2139640248 on OpenAlexaff
Nancy Boaro, Karima Velji

Bibliographic record

VenueEvidence-Based Nursing · 2005
Typeletter
Languageen
FieldMedicine
TopicStroke Rehabilitation and Recovery
Canadian institutionsToronto Rehabilitation Institute
Fundersnot available
KeywordsMedicineStroke (engine)Psychological interventionWeb of scienceRandomized controlled trialPhysical therapyInternal medicinePsychiatryMeta-analysis

Abstract

fetched live from OpenAlex

Visser-Meily A, van Heugten C, Post M, et al . Intervention studies for caregivers of stroke survivors: a critical review. Patient Educ Couns 2005;56:257–67.[OpenUrl][1][CrossRef][2][PubMed][3][Web of Science][4] Q What is the effectiveness of different types of interventions for caregivers of patients with stroke? ### ![Graphic][5]</img>Data sources: Medline (1966 to March 2003), PsycINFO (1984 to March 2003), AMED (1985 to March 2003), and CINAHL (1982 to March 2003). ### ![Graphic][6]</img>Study selection and assessment: randomised controlled trials (RCTs), clinical trials, or uncontrolled trials with pretest and post-test measurement (published in English, German, or Dutch) that evaluated interventions for caregivers of patients with stroke or interventions for patients with stroke and their caregivers if the intervention for caregivers was described; and reported relevant outcome measures for caregivers. ### ![Graphic][7]</img>Outcomes: caregiver quality of life, emotional state, burden, family functioning, social activity in daily life, coping, satisfaction with care, knowledge about stroke, and … [1]: {openurl}?query=rft.jtitle%253DPatient%2Beducation%2Band%2Bcounseling%26rft.stitle%253DPatient%2BEduc%2BCouns%26rft.aulast%253DVisser-Meily%26rft.auinit1%253DA.%26rft.volume%253D56%26rft.issue%253D3%26rft.spage%253D257%26rft.epage%253D267%26rft.atitle%253DIntervention%2Bstudies%2Bfor%2Bcaregivers%2Bof%2Bstroke%2Bsurvivors%253A%2Ba%2Bcritical%2Breview.%26rft_id%253Dinfo%253Adoi%252F10.1016%252Fj.pec.2004.02.013%26rft_id%253Dinfo%253Apmid%252F15721967%26rft.genre%253Darticle%26rft_val_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Ajournal%26ctx_ver%253DZ39.88-2004%26url_ver%253DZ39.88-2004%26url_ctx_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Actx [2]: /lookup/external-ref?access_num=10.1016/j.pec.2004.02.013&link_type=DOI [3]: /lookup/external-ref?access_num=15721967&link_type=MED&atom=%2Febnurs%2F8%2F4%2F119.atom [4]: /lookup/external-ref?access_num=000227590200002&link_type=ISI [5]: /embed/inline-graphic-1.gif [6]: /embed/inline-graphic-2.gif [7]: /embed/inline-graphic-3.gif

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)0.005
metaresearch head score (Gemma)0.034
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: Commentary · Consensus signal: none
Teacher disagreement score0.017
Threshold uncertainty score0.057

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.034
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0040.004
Bibliometrics0.0050.007
Science and technology studies0.0010.000
Scholarly communication0.0030.002
Open science0.0020.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0170.001

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 head0.015
GPT teacher head0.296
Teacher spread0.281 · 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
GenreCommentary

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

Citations3
Published2005
Admission routes1
Has abstractyes

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