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Peer Support Intervention Trials for Individuals with Heart Disease: A Systematic Review

2009· review· en· W2022390584 on OpenAlexaff
Monica Parry, Judy Watt‐Watson

Bibliographic record

VenueEuropean Journal of Cardiovascular Nursing · 2009
Typereview
Languageen
FieldMedicine
TopicCardiac Health and Mental Health
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMedicineIntervention (counseling)DiseaseSocial supportPeer supportHeart diseasePeer reviewGerontologyIntensive care medicinePhysical therapyPsychiatryPathologyPsychotherapistPsychology

Abstract

fetched live from OpenAlex

BACKGROUND: Heart disease is a major cause of illness, disability and death worldwide with high personal, community and healthcare costs. Social support affects psychological and physical morbidity, mortality, and adjustment to chronic disease. Peer support, a specific type of social support, has been shown to be an effective intervention for a variety of populations. AIM: The aim of this paper is to critically examine the effects of peer support interventions on health outcomes in individuals with heart disease. METHODS: Searches were made of ACP Journal Club, EBM, CDSR, DARE, CCTR (1982-2005), MEDLINE (1966-2005), PsycINFO (1975-July 2005), HealthSTAR (1975-June 2005), and CINAHL (1982-July 2005) using text words and MeSH headings. RESULTS: Electronic and hand searching yielded 27 studies and reviews. Six studies met the inclusion criteria and were assessed using guidelines from The Evidence-Based Medicine Working Group and The Cochrane Collaboration. Inferences about the results were limited to critical appraisal. The trials demonstrated some positive effects of peer support for individuals with heart disease, including higher levels of self-efficacy, improved activity, reduced pain, and fewer emergency room visits. CONCLUSION: Despite some evidence supporting peer support for individuals with heart disease, methodological problems preclude generalizations. Further research with greater methodological rigor is warranted.

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)0.048
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Meta-epidemiology (broad)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.450
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0480.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0120.014
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.107
GPT teacher head0.424
Teacher spread0.317 · 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 designSystematic review
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

Citations126
Published2009
Admission routes1
Has abstractyes

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