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Record W2104048508 · doi:10.1123/jsep.2014-0102

Is Variety a Spice of (an Active) Life?: Perceived Variety, Exercise Behavior, and the Mediating Role of Autonomous Motivation

2014· article· en· W2104048508 on OpenAlexaff
Benjamin D. Sylvester, Martyn Standage, Tavinder K. Ark, Shane N. Sweet, Peter R.E. Crocker, Bruno D. Zumbo, Mark R. Beauchamp

Bibliographic record

VenueJournal of Sport and Exercise Psychology · 2014
Typearticle
Languageen
FieldPsychology
TopicMotivation and Self-Concept in Sports
Canadian institutionsMcGill UniversityUniversity of British Columbia
Fundersnot available
KeywordsDeci-PsychologySelf-determination theoryCompetence (human resources)AutonomyVariety (cybernetics)Social psychologyStructural equation modelingDevelopmental psychology

Abstract

fetched live from OpenAlex

In this study, we examined whether perceived variety in exercise prospectively predicts unique variance in exercise behavior when examined alongside satisfaction of the three basic psychological needs (for competence, relatedness, and autonomy) embedded within self-determination theory (Ryan & Deci, 2002), through the mediating role of autonomous and controlled motivation. A convenience sample of community adults (N = 363) completed online questionnaires twice over a 6-week period. The results of structural equation modeling showed perceived variety and satisfaction of the needs for competence and relatedness to be unique indirect positive predictors of exercise behavior (through autonomous motivation) 6 weeks later. In addition, satisfaction of the need for autonomy was found to negatively predict controlled motivation. Perceived variety in exercise complemented satisfaction of the needs for competence, relatedness, and autonomy in predicting motivation and (indirectly) exercise behavior, and may act as a salient mechanism in the prediction of autonomous motivation and behavior in exercise 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 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)0.001
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.193
Threshold uncertainty score0.780

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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)0.0010.000

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 head0.015
GPT teacher head0.290
Teacher spread0.274 · 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

Citations46
Published2014
Admission routes1
Has abstractyes

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