The longitudinal impact of parental depression on child happiness and self-value: the mediating role of empathy and social support
Bibliographic record
Abstract
Abstract Background Parental depression is a prevalent issue that significantly affects children across various domains of development. Children of depressed parents are at an increased risk for emotional difficulties, including heightened anxiety, depression, and lower self-esteem. Objectives This longitudinal study investigates the impact of parental depression on child happiness and self-value, exploring the mediating roles of empathy and social support. Methods Data were collected through surveys at two time points (Time 1 and Time 2), with participants including 660 fathers, 826 mothers, and 756 children at Time 1, and 372 fathers, 403 mothers, and 371 children at Time 2. Results The results revealed via regression analyses that child social support at Time 1 (β = 0.375, p < .001) and Time 2 (β = 0.521, p < .001) significantly predict child happiness, with minimal direct effects from both father and mother depression. Child social support also emerged as a significant predictor of child self-value at both time points (β = 0.401, p < .001 at T1, β = 0.592, p < .001 at T2), while empathy, though positively associated with child well-being, did not show significant mediating effects. Conclusion These findings emphasize the crucial role of social support in fostering children’s psychological resilience, highlighting its potential as an effective intervention for children of depressed parents and the need for further research on targeted interventions to enhance child well-being.
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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 | 0.004 |
| 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 | 0.000 |
| 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".