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Record W2147279159 · doi:10.1123/jsep.29.1.100

Longitudinal Patterns of Stability and Change in Coping across Three Competitions: A Latent Class Growth Analysis

2007· article· en· W2147279159 on OpenAlexaff
Benoît Louvet, Patrick Gaudreau, André Menaut, Jacques Genty, Pascale Deneuve

Bibliographic record

VenueJournal of Sport and Exercise Psychology · 2007
Typearticle
Languageen
FieldPsychology
TopicMotivation and Self-Concept in Sports
Canadian institutionsWilfrid Laurier UniversityUniversity of Ottawa
Fundersnot available
KeywordsCoping (psychology)Disengagement theoryPsychologyLongitudinal studyLatent class modelDevelopmental psychologySocial psychologyClinical psychologyStatisticsMathematicsGerontology

Abstract

fetched live from OpenAlex

An unresolved issue in the coping literature concerns the traitlike versus statelike nature of coping utilization. The aim of this study was to illustrate the benefits of moving beyond the sole reliance on mean-level and rank-order analyses in order to identify heterogeneous patterns of longitudinal stability and change in coping utilization. More specifically, this study hypothesized that not all athletes would change their coping across competitions, nor do all "changers" change in a similar manner. Male soccer players (N = 107) completed a self-reported coping measure after three competitions held over a 6-month period. Results of latent class growth modeling showed three distinct trajectories for each coping dimension (i.e., task, distraction, and disengagement coping), not only indicating linear or quadratic change, but also stability in longitudinal coping utilization. These results highlight the need to account for the multinomial heterogeneity in longitudinal coping utilization and to identify the correlates associated with distinct trajectories of change and stability of coping across competitions.

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 score0.009
Threshold uncertainty score0.889

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 head0.062
GPT teacher head0.361
Teacher spread0.299 · 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

Citations50
Published2007
Admission routes1
Has abstractyes

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