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Record W2089034511 · doi:10.1080/07448480903295326

Does Physical Activity Intensity Moderate Social Cognition and Behavior Relationships?

2009· article· en· W2089034511 on OpenAlexaff
Felicity Scott, Ryan E. Rhodes, Danielle Symons Downs

Bibliographic record

VenueJournal of American College Health · 2009
Typearticle
Languageen
FieldPsychology
TopicBehavioral Health and Interventions
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsTheory of planned behaviorPsychologySocial cognitive theoryStructural equation modelingIntensity (physics)Physical activityCognitionVariance (accounting)Sample (material)Social psychologyClinical psychologyDevelopmental psychologyGerontologyMedicinePhysical therapyStatistics

Abstract

fetched live from OpenAlex

OBJECTIVE: Public health messaging about physical activity (PA) sometimes combines moderate and vigorous intensity, but the variance/invariance of the motives for PA by intensity has received scant attention. Thus, the purpose of this study was to examine the beliefs and motivations associated with regular moderate- and vigorous-intensity PA in a college sample using the framework of Ajzen's Theory of Planned Behavior (TPB). PARTICIPANTS AND METHODS: A college sample of 337 participants was randomly assigned to complete measures of the TPB framed for either vigorous- or moderate-intensity PA and subsequently completed self-reported measures of PA 2 weeks later. RESULTS: Mean comparisons indicated that participants held higher mean behavioral beliefs about the benefits of vigorous PA for improving appearance and fitness, but vigorous PA was perceived to take more time than moderate-intensity activities. A stacked structural equation model and follow-up Fisher z tests, however, suggested no differences between the associations of TPB constructs with intention or PA by intensity. CONCLUSIONS: The findings provide support for the current public health approach of combining moderate and vigorous physical activity messaging through the general invariance of motives by intensity.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.965
Threshold uncertainty score0.354

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 integrity0.0000.001
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 head0.083
GPT teacher head0.427
Teacher spread0.344 · 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.

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

Citations18
Published2009
Admission routes1
Has abstractyes

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