Mental health among elite athletes in Norway during a selected period of the COVID-19 pandemic
Bibliographic record
Abstract
OBJECTIVE: To investigate the prevalence of mental health problems and satisfaction with life among different groups of elite athletes during a selected period of the COVID-19 pandemic and examine how COVID-19 related consequences were associated with these variables. DESIGN: Cross-sectional data collection during a selected period of the COVID-19 pandemic in Norway. PARTICIPANTS: 378 elite athletes, mean age 26.86 (range 18-59), 159 females and 219 males, divided into Olympic-level and Paralympic-level athletes (n=194) and elite and semielite athletes (n=184). MAIN OUTCOME MEASURES: Hopkins Symptoms Check List - 10; symptoms of anxiety and depression; Bergen Insomnia Scale; Eating Disorder Examination Questionnaire Short; Canadian Problem Gambling Index and Satisfaction with Life Scale. In addition, we included specific COVID-19 questions (eg, financial concern, keeping daily routines, perceived coping and motivation). RESULTS: Symptoms of insomnia (38.3%) and depression (22.3%) were most prevalent within the sample. Symptoms of eating disorders more prevalent among female athletes (8.8% vs 1.4%) while symptoms of gambling problems were higher among male athletes (8.6% vs 1.3%). Olympic and Paralympic athletes reported lower levels of anxiety and depression symptoms than elite and semielite athletes. Financial concerns were associated with an increased risk of mental health problems, while daily routines and perception of coping were associated with less mental health problems and higher satisfaction with life. CONCLUSION: Symptoms of insomnia and depression were the two most common mental health problems reported during this selected phase of the COVID-19 pandemic. Elite and semielite athletes reported financial concerns as a risk factor for mental health problems at a larger degree than Olympic and Paralympic athletes.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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 teacher head, 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".