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Record W7057270205

The Impact of an Online Psychological Skills Training Program on the Mental Health of Varsity Athletes

2024· dissertation· en· W7057270205 on OpenAlexaboutno aff

Bibliographic record

VenueScholarship at UWindsor (University of Windsor) · 2024
Typedissertation
Languageen
FieldEngineering
TopicLaser Design and Applications
Canadian institutionsnot available
Fundersnot available
KeywordsMental healthAthletesAnxietyDepression (economics)Computer-assisted web interviewingPsychological interventionHealth professionalsSport psychology
DOInot available

Abstract

fetched live from OpenAlex

Mental health concerns in Canada continue to rise, this is especially apparent for young adults, and those attending University (Giamos et al., 2017). In comparison to non-athlete students, varsity athletes attending University must balance the same academic priorities as non-athletes, while also maintaining the responsibilities associated with their sport (Moreland et al., 2018). Due to this, varsity athletes can be faced with enhanced mental health concerns, such as increased symptoms of anxiety and depression (Neal et al., 2013). This is concerning, as varsity athletes often report low levels of mental health treatment seeking (Armstrong et al., 2015). Knowing this, the goal of the present study was to provide varsity athletes with an asynchronous online psychological skills training (PST) program with the goal to improve mental health. Athletes were given access to six PST modules, including the following skills: goal-setting, imagery, self-talk, routines, managing emotions, relaxation/psyching up (Ely, Munroe-Chandler, et al., 2023). The study followed a pre-post design, where athletes completed questionnaires prior to completing the modules, which measured overall mental health, psychological resilience, and satisfaction with life. Following the six-week period where athletes completed the modules, they were asked to complete the same series of questionnaires. A total of 26 varsity athletes completed the study. It was hypothesized that athletes would report improved mental health following the completion of the online modules (e.g., lower levels of anxiety). Following the intervention, there were no significant differences in scores on mental health measures or satisfaction with life. However, there was a statistically significant increase in mean scores on the brief resilience scale. Possible reasons for the lack of significant findings include a small sample size, as well as the asynchronous online delivery of PST amongst the busy schedules of 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 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)0.002
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.045
Threshold uncertainty score0.090

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.039
GPT teacher head0.310
Teacher spread0.272 · 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

Citations0
Published2024
Admission routes1
Has abstractyes

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