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Record W4394748715 · doi:10.1038/s41598-024-59238-6

Examining the relationship between self-efficacy, career development, and subjective wellbeing in physical education students

2024· article· en· W4394748715 on OpenAlexaff
Yikeranmu Yiming, Bing Shi, Sumaira Kayani, Michele Biasutti

Bibliographic record

VenueScientific Reports · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicCareer Development and Diversity
Canadian institutionsUniversity of Toronto
FundersShaanxi Normal University
KeywordsSelf-efficacyAffect (linguistics)PsychologyLife satisfactionMediationPersonal developmentAdaptabilityClinical psychologyDevelopmental psychologySocial psychologyPsychotherapist

Abstract

fetched live from OpenAlex

We investigated the relationship between self-efficacy and career development via subjective well-being of students majoring in physical education. Life satisfaction, positive affect, and negative affect were the componennts of subjective well-being. Participants were the 1381 adolescents with major in physical education with an age range of 18-22 years (Mage = 19.5 ± 1; females = 34.76%). Hayes PROCESS model was used to develop a multiple mediation model. The results suggest that higher self-efficacy leads to better career development. Further, a significant mediating role was played by negative and positive affect in case of the relationship between self-efficacy and career exploration, but life-satisfaction is not significant mediator. Conversely, life satisfaction and positive affect are significant mediators between self-efficacy and career adaptability but negative affect is not. The findings suggest that self-efficacy and subjective well-being benefit career development of adolescents in the physical education field.

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)0.001
metaresearch head score (Gemma)0.004
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 score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.072
GPT teacher head0.332
Teacher spread0.260 · 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

Citations17
Published2024
Admission routes1
Has abstractyes

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