Maternal Phubbing and Problematic Media Use in Preschoolers: The Independent and Interactive Moderating Role of Children’s Negative Affectivity and Effortful Control
Bibliographic record
Abstract
Purpose: Given that mother plays the main nurturing role in a family unit and their unique influence on children’s development, the current study aimed to examine the influence of maternal phubbing on children’s problematic media use and the independent and interactive moderating role of children’s negative affectivity and effortful control. Methods: Participants were 1986 children aged 3 to 6 years in Shanghai, China. Their mothers were asked to complete a series of questionnaires including parental phubbing scale, problematic media use measure, and child behavior questionnaire. To investigate the moderating influence of children’s negative affectivity and effortful control, hierarchical linear regression analyses were conducted using SPSS 24.0. Simple slopes analyses and the Johnson–Neyman technique were further used to depict moderation effects. Results: Maternal phubbing was associated with higher levels of problematic media use in preschool children ( β = 0.18, p < .001, [0.14, 0.22]). Children’s negative affectivity acts as a risk factor, exacerbating the adverse effects of maternal phubbing on children’s problematic media use ( β = 0.05, t = 2.69, p < 0.05), whereas children’s effortful control acts as a protective factor, buffering the link between maternal phubbing and children’s problematic media use ( β = − 0.10, t = − 5.00, p < 0.001). Conclusion: These results suggest that interventions seeking to promote appropriate digital development in preschoolers should take the child’s temperament into account and be complemented by active parental mediation and involvement. Keywords: maternal phubbing, problematic media use, negative affectivity, effortful control, preschoolers
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".