Associations between sedentary behavior and negative emotions in adolescents during home confinement: Mediating role of social support and sleep quality
Bibliographic record
Abstract
Background: Prolonged periods of sedentary behaviour, for instance, engendered by home confinement in Shenzhen city, has led to negative mental health consequences, especially in adolescents. Previous research suggests, in general, that sedentary behavior can increase negative emotions. However, the specific mechanism driving the relationship between sedentary behavior and negative emotions is still relatively unclear. Social support and sleep quality might partly explain the effect of sedentary behavior on negative emotions. Thus, the current study aimed to examine the associations between sedentary behavior and negative emotions, and to investigate if social support and sleep quality mediate such a relationship. Method: During home confinement due to the COVID-19 Omicron variant outbreak, 1179 middle and high school students in Shenzhen were invited to voluntarily complete an e-questionnaire, including the 21-item Depression Anxiety Stress Scale (DASS-21), the short form of the International Physical Activity Questionnaire (IPAQ-SF), the Social Support Rating Scale (SSRS) and the Pittsburgh Sleep Quality Index (PSQI). Data from 1065 participants were included in the analysis. Results: < .01), even after controlling for sex, age, only-child case, body mass index, and metabolic equivalent level. In addition, social support and sleep quality partially mediated the association between sedentary behavior and negative emotions. Conclusion: The findings of the current study suggest that social support and sleep quality partially mediate the relationship between sedentary behavior and negative emotions in middle and high school students during home confinement in Shenzhen city.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".