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Record W3115175609 · doi:10.3390/ijerph18010002

Potentially Prolonged Psychological Distress from Postponed Olympic and Paralympic Games during COVID-19—Career Uncertainty in Elite Athletes

2020· article· en· W3115175609 on OpenAlexaff
Anders Håkansson, Karin Moesch, Caroline Jönsson, Göran Kenttä

Bibliographic record

VenueInternational Journal of Environmental Research and Public Health · 2020
Typearticle
Languageen
FieldPsychology
TopicSport Psychology and Performance
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsAthletesElite athletesElitePandemicCoronavirus disease 2019 (COVID-19)PsychologyDistressPsychological distressMental healthPerspective (graphical)MedicineDiseasePhysical therapyPsychiatryPolitical scienceClinical psychology

Abstract

fetched live from OpenAlex

The coronavirus disease 2019 (COVID-19) pandemic has had a significant impact on the world of sports due to periods of home quarantine, bans against public gatherings, travel restrictions, and a large number of postponed or canceled major sporting events. The literature hitherto is sparse, but early indications display signs of psychological impact on elite athletes due to the pandemic. However, beyond acute effects from lockdown and short-term interrupted athletic seasons, the postponed and still uncertain Olympic and Paralympic Games may represent a major career insecurity to many athletes world-wide, and may lead to severe changes to everyday lives and potentially prolonged psychological distress. Given the long-term perspective of these changes, researchers and stakeholders should address mental health and long-term job insecurity in athletes, including a specific focus on those with small financial margins, such as many female athletes, parasports athletes, athletes in smaller sports, and athletes from developing countries. Implications and the need for research are discussed.

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 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 score0.134
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.107
GPT teacher head0.415
Teacher spread0.309 · 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.

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

Citations51
Published2020
Admission routes1
Has abstractyes

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