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Record W4308771287 · doi:10.1080/08870446.2022.2141484

Psychological needs and exercise behaviour: a comparison of two psychological needs models

2022· article· en· W4308771287 on OpenAlexafffund
Colin M. Wierts, Guy Faulkner, Ryan E. Rhodes, Bruno D. Zumbo, Mark R. Beauchamp

Bibliographic record

VenuePsychology and Health · 2022
Typearticle
Languageen
FieldPsychology
TopicMotivation and Self-Concept in Sports
Canadian institutionsUniversity of VictoriaUniversity of British Columbia
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsPsychologySelf-determination theoryCompetence (human resources)OperationalizationSocial psychologyNeed theoryApplied psychologyAutonomyMaslow's hierarchy of needs

Abstract

fetched live from OpenAlex

OBJECTIVE: Psychological need satisfaction, from a self-determination theory (SDT) perspective, has been applied extensively to understand predictors of exercise behaviour. Dweck proposed a psychological needs framework that includes basic needs (optimal predictability, competence, acceptance), compound needs derived from combinations of basic needs (self-esteem/status, trust, control), and a superordinate compound need for self-coherence that includes identity and meaning. The purpose was to examine whether psychological needs operationalized within Dweck's model account for variance in exercise behaviour in ways that the SDT model does not. METHODS AND MEASURES: A community sample of 403 adults completed measures of demographics, psychological needs, and exercise motivation at Time 1, and self-reported moderate-to-vigorous minutes of exercise at both Times 1 and 2 four weeks later. RESULTS: Two structural equation models operationalizing Dweck's needs framework and SDT (basic needs and motivation) were examined in relation to exercise behaviour. In both models, exercise identity and integrated regulation (conceptually similar) were the most salient correlates of prospectively measured exercise behaviour, and both accounted for the relationship between competence and exercise behaviour. CONCLUSION: The results support the importance of identity in the context of exercise behaviour. Future research should investigate factors associated with adopting and maintaining an exercise identity.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.254
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.157
GPT teacher head0.464
Teacher spread0.308 · 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.

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

Citations7
Published2022
Admission routes2
Has abstractyes

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