Threat of coronavirus and depressive symptoms in adolescents: do 24-hour movement behaviors mediate this relationship?
Bibliographic record
Abstract
BACKGROUND: The COVID-19 pandemic has disrupted the lives of adolescents worldwide, increasing their risk of mental health issues such as anxiety and depression. Daily behaviors like physical activity, screen use, and sleep are thought to influence emotional well-being, but it remains unclear how they interact with pandemic-related stressors. This study investigated whether these 24-hour movement behaviors help explain the link between adolescents’ perceived threat of the coronavirus and symptoms of depression. METHODS: We conducted a cross-sectional survey with 1,303 adolescents (50.96% female; average age = 16.32 years, SD = 1.10) in Northeast Brazil between August and October 2021. Depressive symptoms were assessed using the Center for Epidemiologic Studies Depression Scale. Structural equation modeling was used to test whether physical activity, recreational screen time, and sleep duration mediated the association between perceived coronavirus threat and depressive symptoms. RESULTS: The perceived threat of the coronavirus was directly associated with higher depressive symptoms (ß: 0.163; p value < 0.001). Additionally, each movement behavior showed a significant association with depression: more physical activity (ß: -0.084; p value < 0.01) and longer sleep (ß: -0.167; p value < 0.001) were linked to fewer symptoms, while greater recreational screen time was related to more (ß: 0.130; p value < 0.001). However, none of these behaviors explained the pathway between perceived threat and depressive symptoms, suggesting that other factors—such as emotional regulation, social support, or family dynamics—may better account for this link. CONCLUSION: While the movement behaviors did not mediate the effect of the perceived coronavirus threat on depression, they were still independently related to mental health. These findings support the value of promoting healthy daily routines among adolescents during pandemics and as part of broader mental health strategies. Public health interventions should consider these behaviors as protective factors that may help reduce the burden of depression in future crises.
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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 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".