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Examining Relationships Between Perceived Psychological Need Satisfaction and Behavioral Regulations in Exercise

2008· article· en· W1972738211 on OpenAlexafffund
Philip M. Wilson, W. Todd Rogers

Bibliographic record

VenueJournal of Applied Biobehavioral Research · 2008
Typearticle
Languageen
FieldPsychology
TopicMotivation and Self-Concept in Sports
Canadian institutionsCentre for Advancing Health OutcomesUniversity of Alberta
FundersKillam Trusts
KeywordsAutonomyPsychologyCompetence (human resources)PerceptionSelf-determination theoryStructural equation modelingSocial psychologyClinical psychology

Abstract

fetched live from OpenAlex

The purpose of this study was to examine the proposition that psychological need satisfaction plays a role in the motives regulating exercise behavior. Participants completed self‐report instruments assessing perceived psychological need satisfaction and exercise regulation at the outset and end of a 12‐week structured exercise class. Greater perceived psychological need satisfaction predicted endorsement of more self‐determined exercise regulations in the structural equation modeling analysis. Change score analyses revealed that increased perceived need fulfillment was positively correlated with more self‐determined exercise regulations, although this pattern was most prominent for competence and autonomy. Collectively, these findings indicate perceptions of competence and autonomy—and to a lesser extent relatedness—and represent important factors shaping exercise motivation. Continued investigation of basic psychological need fulfillment via exercise appears justified.

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)0.002
metaresearch head score (Gemma)0.009
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 score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.009
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 science0.0000.001
Research integrity0.0000.001
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 head0.391
GPT teacher head0.460
Teacher spread0.069 · 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

Citations54
Published2008
Admission routes2
Has abstractyes

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