MétaCan
Menu
Back to cohort
Record W2016888797 · doi:10.1080/1091367x.2012.693340

Assessing Psychological Need Satisfaction in Exercise Contexts: Issues of Score Invariance, Item Modification, and Context

2012· article· en· W2016888797 on OpenAlexaff
Katie E. Gunnell, Philip M. Wilson, Bruno D. Zumbo, Diane E. Mack, Peter R.E. Crocker

Bibliographic record

VenueMeasurement in Physical Education and Exercise Science · 2012
Typearticle
Languageen
FieldPsychology
TopicMotivation and Self-Concept in Sports
Canadian institutionsBrock UniversityUniversity of British Columbia
Fundersnot available
KeywordsMeasurement invariancePsychologyCompetence (human resources)Context (archaeology)Scale (ratio)Social psychologyAutonomyPopulationClinical psychologyApplied psychologyStructural equation modelingStatisticsConfirmatory factor analysisMathematicsMedicine

Abstract

fetched live from OpenAlex

The researchers examined if scores from the original Psychological Need Satisfaction in Exercise Scale (Wilson, Rogers, Rodgers, & Wild, 2006 Wilson, P. M., Rogers, W. T., Rodgers, W. M. and Wild, T. C. 2006. The psychological need satisfaction in exercise scale. Journal of Sport & Exercise Psychology, 28: 231–251. [Crossref], [Web of Science ®] , [Google Scholar]) were invariant from a modified version specific to physical activity and then examined measurement invariance of scores across groups on the modified scale. Three groups were examined: (a) Students/staff from a university (N = 283), (b) a sample drawn from the general population (N = 214), and (c) individuals living with osteoporosis (N = 221). Measurement invariance was tested with four nested models using increased equality constraints per model. Results of invariance tests between two versions of the Psychological Need Satisfaction in Exercise Scale and between groups that completed the Psychological Need Satisfaction in Exercise Scale modified to physical activity supported configural and weak invariance of scores (i.e., equivalent factor structure and loadings). As such, the constructs of competence, autonomy, and relatedness were construed similarly across versions of the instrument and across two groups. Strong invariance (i.e., equivalent intercepts) was not supported, and therefore, direct score comparisons should be made with caution.

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 score0.420
Threshold uncertainty score0.551

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
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 head0.095
GPT teacher head0.389
Teacher spread0.293 · 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

Citations30
Published2012
Admission routes1
Has abstractyes

Explore more

Same venueMeasurement in Physical Education and Exercise ScienceSame topicMotivation and Self-Concept in SportsFrench-language works237,207