From family to school: the dual protection of father-child relationship and teacher-student relationship on children’s mental health problems
Bibliographic record
Abstract
Mental health problems among children are a significant public health concern. Family dynamics and early educational environments are critical in shaping children's mental health. This study explores the impact of maternal authoritarian parenting on preschool children's mental health, considering the mediating role of children's emotion regulation abilities and the moderating effects of father-child and teacher-child relationships. Participants included 412 preschool children from three kindergartens in Shanghai, along with their parents and teachers. Data were collected in two phases through questionnaires at an interval of 6 months. Results indicated that children's emotion regulation abilities fully mediated the relationship between maternal authoritarian parenting and children's mental health problems. The interaction between maternal authoritarian parenting and father-child relationships significantly predicted children's emotion regulation abilities (β = 0.163, p < 0.05), while the interaction between children's emotion regulation abilities and teacher-child relationships significantly predicted children's mental health problems (β = 0.145, p < 0.001). This study innovatively used the Polynomial Curved Surface Fitting (PSCF) technique to validate the existence of a dual moderated mediation effect. This finding supports the positive role of the cumulative advantage effect of father-child and teacher-child relationships in promoting children's mental health. These findings also have important practical implications for the development of intervention strategies and educational policies.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".