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Record W2103144397 · doi:10.1037/rep0000024

Self-efficacy and outcome expectations in cardiac rehabilitation: Associations with women’s physical activity.

2015· article· en· W2103144397 on OpenAlexafffund
Christopher M. Blanchard, Heather M. Arthur, Elizabeth Gunn

Bibliographic record

VenueRehabilitation Psychology · 2015
Typearticle
Languageen
FieldMedicine
TopicCardiac Health and Mental Health
Canadian institutionsMcMaster UniversityDalhousie University
FundersCanada Research Chairs
KeywordsSelf-efficacyOutcome (game theory)PsychologySocial cognitive theoryTask (project management)RehabilitationPhysical therapyClinical psychologyMedicineDevelopmental psychologySocial psychology

Abstract

fetched live from OpenAlex

OBJECTIVE: Little is known regarding the social-cognitive correlates of physical activity (PA) during and after cardiac rehabilitation (CR) in a female sample. The objective of the current study was to identify distinct trajectories for task self-efficacy, barrier self-efficacy, and outcome expectations and examine their association with PA. METHOD: A total of 203 women with cardiovascular disease completed a survey that included the self-efficacy, outcome-expectation, and PA measures at the beginning and end of CR, and 6 and 12 months after completing CR. RESULTS: Latent class growth analyses showed that multiple trajectories existed for task self-efficacy, barrier self-efficacy, and outcome expectations. Dual trajectory analyses showed that women in less favorable task self-efficacy, barrier self-efficacy, and outcome-expectation trajectories had a greater probability of being in an inactive PA trajectory. CONCLUSION/IMPLICATIONS: Women in trajectories with higher task and barrier self-efficacy and outcome expectations are more likely to be active, whereas the opposite is true for women with lower efficacy and outcome expectancies. As such, it is critical that health-care practitioners incorporate strategies into their CR programs or professional practice after CR to increase women's confidence in engaging in PA, overcome barriers to engage in PA, and promote positive outcomes related to PA to increase their PA levels.

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)0.001
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
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)0.0020.000

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 head0.031
GPT teacher head0.413
Teacher spread0.382 · 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 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

Citations43
Published2015
Admission routes2
Has abstractyes

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