Examining the interplay between physical activity, problematic internet use and the negative emotional state of depression, anxiety and stress: insights from a moderated mediation path model in university students
Bibliographic record
Abstract
Abstract Background The aim of this study was to investigate the relationship between Problematic Internet Use (PIU), emotional states of stress, anxiety and depression, and the practice of physical activity among Tunisian students. Methods Cross-sectional data were collected from 976 university students aged 20.76 ± 1.63 years (46.8% female). They filled out an online survey comprised of a socio-demographic questionnaire, the depression, anxiety and stress scale– 21 items (DASS-21), the international physical activity questionnaire (IPAQ) and the compulsive internet use scale (CIUS). Students were divided, based on their economic levels, into three groups: low (n = 256, 26.23%), medium (n = 523, 53.59%) and high (n = 197, 20.18%). Results Mediation analysis: Indirect effects of IPAQ and gender on DASS-21 were highlighted: β= -0.18 (p < 0.01) and β= -0.04, P < 0.01) respectively. In addition, a significant and negative effect of IPAQ on CIUS was demonstrated (β = -0.45, P < 0.01). In addition, the effect of CIUS on DASS-21 was significant (β = 0.39, P < 0.01). Also, the effect of gender on CIUS was significant (β=-0.10, P < 0.01) However, its effect on DASS-21 was not significant (β = 0.05, p = 0.078). The total effect of IPAQ on DASS21 was significant (β= -0.52, p < 0.01) but the effect of Gender on DASS-21 was not significant (β = 0.01, p = 0.817). Moderation analysis: the results showed a significant moderation effect of the interaction between IPAQ and Gender on CIUS (β = 0.07, p < 0.01). However, it was not significant between Gender and CIUS on DASS-21 (β = 0.09, p = 0.390) and between IPAQ and Gender on DASS21 (β = 0.01, p = 0.736) Also, the interaction between IPAQ and CIUS did not have a significant moderation effect on DASS-21 (β = 0.15, p = 0.115). Conclusions Findings suggest that relationships between PIU and negative emotional state of depression, anxiety and stress are mediated via physical exercise. These results underscore the importance of the physical activity factor in the studies analyzing longitudinal effects of PIU on mental health outcomes.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".