Combined Patterns Of Physical Activity And Screen-Related Sedentary Behavior Among Chinese Adolescents And Their Correlations With Depression, Anxiety And Self-Injurious Behaviors
Bibliographic record
Abstract
Mingli Liu,1–3 Jie Zhang,2 Elwin Hu,4 Huilan Yang,5 Chang Cheng,3 Shuqiao Yao3 1Department of Psychology, Hunan University of Science and Technology, Xiangtan, Hunan 411201, People’s Republic of China; 2State University of New York Buffalo State Department of Sociology, NewYork, NY, USA; 3Medical Psychological Institute, Second Xiangya Hospital of Central South University, Changsha, Hunan 410011, People’s Republic of China; 4School of Psychology, Counselling and Psychotherapy, Cairnmillar Institute, Hawthorn East, VIC, Australia; 5Department of Psychology, University of Western Ontario, London, Ontario N6A 5C2, CanadaCorrespondence: Shuqiao YaoMedical Psychological Institute, Second Xiangya Hospital of Central South University, 139 Middle Renmin Road Changsha, Hunan 410011, People’s Republic of ChinaTel +86 137 8612 0325Email shuqiaoyao@csu.edu.cnMingli LiuDepartment of Psychology, Hunan University of Science and Technology, 2 Taoyuan Road Xiangtan, Hunan 411201, People’s Republic of ChinaTel +86 139 7522 3596Email mlliupsy@163.comBackground and purpose: There are increasing concern about independent associations between physical activity, screen-based sedentary behavior (SSB), and psychological problems, but only a few studies have attempted to explore combined patterns of physical activity and SSB in adolescents and their correlations with psychological problems. This study was aimed at identifying combined patterns of moderate-to-vigorous physical activity (MVPA) and SSB and examining the prevalence of different combined patterns and their correlations with depression, anxiety, and self-injurious behavior among Chinese adolescents.Methods: Junior and senior high school students (N = 13,659; mean age 15.18±1.89) were recruited. Latent class analysis was conducted to identify combined patterns of MVPA and SSB. Associations between subgroups of MVPA and SSB and socio-demographic characteristics were assessed by logistic regression. Their correlation with depression, anxiety, and self-injurious behaviors was assessed by analysis of variance with analysis stratified by gender.Results: Four latent classes were identified: high MVPA/low SSB group (64.7%), low MVPA/low SSB (26.7%), low MVPA/high SSB (4.8%), and low MVPA/moderate SSB (3.9%). Generally, the high MVPA/low SSB class was a relatively healthy group. The low MVPA/high SSB class was at risk of enduring depression, anxiety, and self-injurious behavior, with boys being more at risk than girls.Conclusion: Four latent subgroups of MVPA and SSB were identified in Chinese adolescents. The findings highlight the potential role of concurrent MVPA and SSB, with gender-specific characteristics in the primary prevention of adolescent depression, anxiety, and self-injurious behaviors.Keywords: exercise, internet, media use, subgroups, mental health, suicide
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 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 | 0.001 | 0.001 |
| 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".