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Record W1984564721 · doi:10.1177/13591053030084004

Translating Exercise Intentions into Behavior: Personality and Social Cognitive Correlates

2003· article· en· W1984564721 on OpenAlexaff
Ryan E. Rhodes, Kerry S. Courneya, Lee W. Jones

Bibliographic record

VenueJournal of Health Psychology · 2003
Typearticle
Languageen
FieldPsychology
TopicBehavioral Health and Interventions
Canadian institutionsUniversity of AlbertaUniversity of Victoria
Fundersnot available
KeywordsExtraversion and introversionPsychologyPersonalitySocial cognitive theoryCognitionTheory of planned behaviorClinical psychologySocial psychologyBig Five personality traitsControl (management)Psychiatry

Abstract

fetched live from OpenAlex

The purpose of this study was to detail the variability found in the exercise intention-behavior relationship and investigate social cognitive and personality correlates of successful intention translation. Participants were 300 undergraduate students who completed measures of exercise social cognition (theory of planned behavior), personality (five-factor model) and a two-week follow-up of exercise behavior. Results suggested intention translation at a frequency of zero was significantly more successful than intending to exercise at all other weekly frequencies. Moreover, intending to exercise one or two times per week resulted in better intention translation than intending to exercise four or more bouts per week. Discriminant function analysis and follow-up F-tests found instrumental attitude, affective attitude and perceived behavioral control (PBC) discriminated between nonintenders, unsuccessful intenders and successful intenders. Further, extroversion predicted unsuccessful intenders versus successful intenders. Results underscore the importance of attitude, PBC and extroversion as action control constructs in the exercise domain.

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)0.010
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 score0.001
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.136
GPT teacher head0.497
Teacher spread0.361 · 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

Citations102
Published2003
Admission routes1
Has abstractyes

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