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Record W2119420090 · doi:10.1123/jsep.35.5.514

Applying Self-Compassion in Sport: An Intervention With Women Athletes

2013· article· en· W2119420090 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Sport and Exercise Psychology · 2013
Typearticle
Languageen
FieldPsychology
TopicMindfulness and Compassion Interventions
Canadian institutionsUniversity of SaskatchewanUniversity of British Columbia
Fundersnot available
KeywordsPsychologySelf-compassionSelf-criticismRuminationBasketballMultivariate analysis of varianceAthletesMindfulnessPsychoeducationIntervention (counseling)Coping (psychology)Clinical psychologyPsychotherapistCognitionPhysical therapyPsychiatryMedicine

Abstract

fetched live from OpenAlex

This study investigated the effects of a self-compassion intervention on negative cognitive states and self-compassion in varsity women athletes. Athletes who self-identified as being self-critical were randomly assigned to a self-compassion intervention (n = 29) or attention control group (n = 22). The self-compassion intervention consisted of a psychoeducation session and writing components completed over a 7-day period. Measures of self-compassion, state self-criticism, state rumination, and concern over mistakes were collected pretreatment, at 1 week posttreatment, and at a 4-week follow-up. A mixed factorial MANOVA with follow-up post hoc tests demonstrated moderate-to-strong effects for the intervention at posttest and follow-up (Wilks's Λ = .566, F (8, 42) = 4.03, p < .01, η2 = .43). The findings demonstrate the effectiveness of the self-compassion intervention in managing self-criticism, rumination, and concern over mistakes. Fostering self-compassionate mind frames is a potential coping resource for women athletes dealing with negative events in sport.

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.

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 categoriesInsufficient 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 score0.296
Threshold uncertainty score0.992

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)0.0090.000

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 head0.015
GPT teacher head0.309
Teacher spread0.294 · 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