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Record W1974784363 · doi:10.1177/1359105307088141

Self-efficacy for Exercise in Cardiac Rehabilitation

2008· review· en· W1974784363 on OpenAlexaff
Jennifer Woodgate, Lawrence R. Brawley

Bibliographic record

VenueJournal of Health Psychology · 2008
Typereview
Languageen
FieldMedicine
TopicCardiac Health and Mental Health
Canadian institutionsUniversity of SaskatchewanMcMaster University
Fundersnot available
KeywordsSelf-efficacyRehabilitationPsychosocialMedicinePhysical therapyPsychologyClinical psychologyPsychiatryPsychotherapist

Abstract

fetched live from OpenAlex

Despite the numerous physical and psychosocial benefits of exercise for coronary heart disease survivors, non-adherence to cardiac rehabilitation (CR) exercise is a major problem. Adherence to the lifestyle behavior change associated with CR involves both physical and self-regulatory skills. While self-regulatory efficacy is clearly linked to exercise adherence and adjustment, the literature on the relationship between self-efficacy and exercise among CR participants has not been systematically reviewed. A search of relevant databases identified 41 CR studies. Few studies measured self-regulatory efficacy for actions that facilitate adherence. Most studies examined self-efficacy during the intensive center-based phase of CR, with little attention to long-term maintenance. The CR literature could benefit by examining (a) self-efficacy as a major rehabilitation outcome, (b) measurement of self-regulatory efficacy for behavior change, (c) suspected moderators of self-efficacy (i.e. gender, age), and (d) self-efficacy relative to maintenance.

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)0.004
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 score0.004
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0030.003
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.082
GPT teacher head0.512
Teacher spread0.430 · 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

Citations173
Published2008
Admission routes1
Has abstractyes

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