Relationship between Depression Scores, Sleep Quality, Chronotype and Cardiorespiratory Fitness among Undergraduate Health Students
Bibliographic record
Abstract
Introduction: University students face challenges that impact both their physical and mental health. However, studies that integrate depressive symptoms, sleep quality, chronotype, and cardiorespiratory fitness remain scarce. Objective: This study aimed to analyze the relationships among these factors in a sample of university students. Materials and Methods: The Beck Depression Inventory (BDI) was used to assess depressive symptoms, the Pittsburgh Sleep Quality Index (PSQI), the Morningness–Eveningness Questionnaire by Horne and Östberg (1976), and the University of Montreal Track Test (UMTT) to estimate cardiorespiratory fitness. Results: The findings revealed a high prevalence of depressive symptoms (46.9%) and poor sleep quality (75.5%), as well as low cardiorespiratory fitness levels compared to population standards. A moderate negative correlation was identified between depressive symptoms and sleep quality (r = -0.524; p = 0.0002), reinforcing the reciprocal influence between mental health and sleep. Conclusion: These findings highlight the need for multidimensional interventions that support both the psychological well-being and physical health of this population.
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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 | 0.000 | 0.001 |
| 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 | 0.000 | 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 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".