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Record W4285029340 · doi:10.1080/07448481.2022.2093610

Managing daily responsibilities among collegiate student-athletes: Examining the roles of stress, sleep, and sense of belonging

2022· article· en· W4285029340 on OpenAlexaffabout
Quinn K. Storey, Paul L. Hewitt, John S. Ogrodniczuk

Bibliographic record

VenueJournal of American College Health · 2022
Typearticle
Languageen
FieldPsychology
TopicSport Psychology and Performance
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsAthletesPsychologyStress managementMediationStress (linguistics)Sleep (system call)Association (psychology)Clinical psychologyApplied psychologyMedicinePhysical therapy

Abstract

fetched live from OpenAlex

Objectives: Student-athletes are unique in their undertaking of full-time academic and athletic roles. Their dual roles impose a multitude of responsibilities in their daily lives, yet little is known about the factors that may negatively impact their ability to effectively manage these responsibilities. Participants: Data from a large sample of Canadian varsity athletes (N = 1,353) were used for the present study. Methods: The association between stress and difficulties managing daily responsibilities, while simultaneously investigating the roles of sleep difficulties and sense of belonging as contributing factors was examined. Results: Findings indicated that the moderated mediation model was significant, revealing that sleep difficulties were a significant mediator in the relationship between stress and difficulties managing daily responsibilities and that sense of belonging moderated the relationship between stress and sleep difficulties. Conclusions: The results expose complex ways that student-athletes’ performances (academic and athletic) can be impaired, signaling the need to develop strategic actions toward prevention and management of stress among student-athletes.

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)0.003
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 score0.185
Threshold uncertainty score0.523

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.020
GPT teacher head0.326
Teacher spread0.306 · 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

Citations7
Published2022
Admission routes2
Has abstractyes

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