Influence of physical activity and mobile phone addiction tendency on depression among Chinese undergraduates
Bibliographic record
Abstract
Objective: This study explored the influence of physical activity (PA) and mobile phone addiction tendency (MPAT) on depression among Chinese undergraduate students, testing the mediating effect of MPAT and the moderating effect of gender. Methods: The International Physical Activity Questionnaire-Short Form (IPAQ-SF), the Mobile Phone Addiction Tendency Scale (MPATS), and the Center for Epidemiologic Studies Depression Scale (CESD-S) were administered to 2,121 Chinese undergraduates (46.25% male, aged 19.74 ± 1.822 years) from 10 public and private colleges and universities. Analyses on the mediating effects of mobile phone addiction tendency and the moderating effects of gender were conducted using the PROCESS macro (Version 3.5). Results: < 0.001). The mediating effect of MPAT on PA affecting depression was significant, with a mediating effect size of 15.0%. Moreover, gender moderated the influence of PA on depression, and it also moderated the influence of MPAT on depression. Conclusion: The conclusions corroborate and clarify that MPAT partially mediated the association between PA and depression, and the mediation effects were moderated via gender. This indicates that increasing undergraduates' PA level could effectively avoid MPAT and thus alleviate their depression. Although caution needs to be taken when inferring causal relationships in a cross-sectional design, the present study advances understanding of how undergraduates' PA was related to depression. It also illustrates that educators and parents should pay more attention to undergraduates' PA.
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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) | 0.001 | 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".