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Record W2128245668 · doi:10.1177/1090198109332599

The Role of Self-Efficacy on the Relationship Between the Workplace Environment and Physical Activity: A Longitudinal Mediation Analysis

2009· article· en· W2128245668 on OpenAlexaff
Ronald C. Plotnikoff, Michael A. Pickering, Laura M. Flaman, John C. Spence

Bibliographic record

VenueHealth Education & Behavior · 2009
Typearticle
Languageen
FieldMedicine
TopicPhysical Activity and Health
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsMediationSelf-efficacyPsychologyPhysical activityLongitudinal studySocial psychologyDevelopmental psychologyGerontologyMedicineSociologyPhysical therapy

Abstract

fetched live from OpenAlex

Cross-sectional studies show that self-efficacy (SE) serves as a partial mediator of the effect that perceptions of workplace environment have on self-reported workplace physical activity (PA). To further explore the role SE plays in the relationship between perceptions of the workplace environment and workplace PA, cross-sectional mediation analyses were performed on adult employees at baseline (n = 897), 6 months (n = 616), and 12 months (n = 612); a longitudinal time-sequence was incorporated into the mediation model; and correlates of residual change version of the mediation were tested. The R (2) ranged from .05 to .08 for the three cross-sectional analyses, .03 for the longitudinal analyses, and from .02 to .03 for the residual analyses. The results from the residual change model analyses supported those of the cross-sectional and longitudinal analyses, suggesting the relationship between perceived workplace environment and PA was partially mediated by SE. Future research should include similar studies with different population groups and in different settings.

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)0.018
metaresearch head score (Gemma)0.028
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 score0.018
Threshold uncertainty score0.097

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0180.028
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.002
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0060.000

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 head0.075
GPT teacher head0.388
Teacher spread0.313 · 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

Citations20
Published2009
Admission routes1
Has abstractyes

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