Symptoms of depression and anxiety among elite high school student-athletes in Sweden during the COVID-19 pandemic: A repeated cross-sectional study
Bibliographic record
Abstract
The COVID-19 pandemic precipitated numerous changes in daily life, including the cancellation and restriction of sports globally. Because sports participation contributes positively to the development of student-athletes, restricting these activities may have led to long-term mental health changes in this population. Using a repeated cross-sectional study design, we measured rates of depression using the Patient Health Questionnaire-2 and anxiety using the Generalized Anxiety Disorder-2 scale in student-athletes attending elite sport high schools in Sweden during the second wave of the pandemic (February 2021; n = 7021) and after all restrictions were lifted (February 2022; n = 6228). Depression among student-athletes decreased from 19.8% in 2021 to 17.8% in 2022 (p = .008, V = .026), while anxiety screening did not change significantly (17.4% to 18.4%, p > .05). Comparisons between classes across years revealed older students exhibited decreases in depressive symptoms, while younger cohorts experienced increases in symptoms of anxiety from 2021 to 2022. Logistic regressions revealed that being female, reporting poorer mental health due to COVID-19, and excessive worry over one’s career in sports were significant predictors of both depression and anxiety screenings in 2022. Compared to times when sports participation was limited, the lifting of restrictions was associated with overall reduced levels of depression, but not anxiety.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".