Maternal COVID-19 Distress and Chinese Preschool Children’s Problematic Media Use: A Moderated Serial Mediation Model
Bibliographic record
Abstract
Juan Li,1 Yuanyuan Zhai,1 Bowen Xiao,2 Xiaoying Xia,3 Jingyao Wang,1 Yanan Zhao,1 Li Ye,1 Yan Li1 1Shanghai Institute of Early Childhood Education, Shanghai Normal University, Shanghai, People’s Republic of China; 2Psychology Department, Carleton University, Ottawa, Ontario, Canada; 3School of Early Childhood Education, Shanghai Normal University Tianhua College, Shanghai, People’s Republic of ChinaCorrespondence: Yan Li, Shanghai Institute of Early Childhood Education, Shanghai Normal University, 100 Guilin Road, Xuhui District, Shanghai, People’s Republic of China, Email liyan@shnu.edu.cnIntroduction: Maternal distress increased during the COVID-19 pandemic, significantly impacting children’s media use. The purpose of this study was to explore the influence mechanism of maternal COVID-19 distress on preschoolers’ problematic media us through a moderated mediation model; specifically, we examined the possible mediating roles of parenting stress and negative instrumental use of media in parenting and the moderating role of supportive co-parenting.Methods: An online survey was conducted in a sample of 1357 children (Mage = 4.01, SD = 1.06; 47.4% boys) and their parents from six public kindergartens in Shanghai, China. The mothers provided information by completing measures on their levels of distress related to COVID-19, parenting stress levels, digital parenting practices, and perception of supportive co-parenting from their partners. Additionally, both parents rated their children’s problematic media use.Results: (1) maternal COVID-19 distress was significantly and positively related to children’s problematic media use; (2) this relationship was sequentially mediated by parenting stress and parents’ negative instrumental use of media in parenting; and (3) supportive co-parenting moderated the serial mediation path by reducing the effect of maternal COVID-19 distress on parenting stress.Conclusion: The findings provide some support and guidance for preventing children’s problematic media use and enhancing parental adaptation during the COVID-19 pandemic or in potentially adverse situations.Keywords: maternal COVID-19 distress, children’s problematic media use, parenting stress, negative instrumental use of media in parenting, supportive co-parenting
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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 | 0.002 | 0.007 |
| 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 | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".