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Record W4210842718 · doi:10.1080/1091367x.2022.2034164

German, Portuguese and Spanish Versions of the Revised Short Form of the Physical Self-Inventory (PSI-S-<i>R</i>)

2022· article· en· W4210842718 on OpenAlexaff
Christophe Maïano, Alexandre J. S. Morin, Maike Tietjens, Tânia Bastos, Maxime Luiggi, Rui Corredeira, Jean Griffet, David Sánchez‐Oliva

Bibliographic record

VenueMeasurement in Physical Education and Exercise Science · 2022
Typearticle
Languageen
FieldPsychology
TopicMotivation and Self-Concept in Sports
Canadian institutionsConcordia UniversityUniversité du Québec en Outaouais
Fundersnot available
KeywordsGermanPortuguesePsychologyEuropean PortugueseMeasurement invarianceDifferential item functioningExploratory factor analysisSample (material)Developmental psychologySocial psychologyStructural equation modelingPsychometricsStatisticsItem response theoryConfirmatory factor analysisLinguisticsMathematics

Abstract

fetched live from OpenAlex

The present study sought to examine the psychometric properties of new German, Portuguese, and Spanish versions of the Revised Short Form of the Physical Self-Inventory (PSI-S-R), and to contrast these properties against those from the original French version of this instrument. Participants (n = 1802) were 288 French youth, 177 German youth, 848 Portuguese youths and 489 Spanish youth. Results from exploratory structural equation modeling (ESEM) analyses supported the factor validity and reliability of PSI-S-R across the overall sample and each linguistic sample. Subsequent analyses supported the weak, partial strong, and strict invariance of this measure, and revealed a lack of differential item functioning (i.e., measurement bias) as a function of age, body mass index, sex and sport involvement across all linguistic versions. However, latent mean differences were observed as a function of these predictors and countries.

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)0.003
metaresearch head score (Gemma)0.008
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 score0.004
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.001

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 head0.027
GPT teacher head0.306
Teacher spread0.278 · 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

Citations6
Published2022
Admission routes1
Has abstractyes

Explore more

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