Physical activity and its benefits on adolescents' mental health through self-esteem
Bibliographic record
Abstract
Background: Since the onset of the COVID-19 pandemic, the scientific community has been concerned about the high rates of psychological distress among adolescents. The pandemic not only tested adolescents' adaptation, but also disrupted key areas of their development. This demonstrates the need to study their psychological adjustment over time during this critical period to better guide services. Objective: This study sought to explore the extent to which physical activity and its association with self-esteem in the first months of the pandemic impacted adolescents' psychological distress, six months later. Methods: Two hundred and ninety-four adolescents (73% girls) between the ages of 12 and 17 participated in a longitudinal study launched at the start of the COVID-19 pandemic. The number of hours spent engaging in physical activity (HPA) in the past week and self-esteem were measured at Time 1 (T1; summer 2020). Psychological distress was measured at T1 and Time 2 (T2; winter 2021). Results: More HPA in the past week were related to greater self-esteem at T1. Greater self-esteem at T1 was related to lower psychological distress, six months later (T2). Lastly, HPA in the past week was not directly linked to psychological distress at T2, which confirms a fully indirect model. Conclusion: Results suggest that physical activity is a key factor in promoting better mental health adjustment through its benefits in terms of self-esteem, even during times of turmoil. Findings reinforce the recommendation of promoting the practice of sports and athletic activity in difficult times.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".