Maternal depressive symptoms and sensitivity are related to young children's facial expression recognition: The Generation R Study
Bibliographic record
Abstract
A vast body of literature shows that maternal depression has long-term adverse consequences for children. However, only very few studies have documented the effect of maternal depression on children's ability to process emotional expressions and even fewer incorporated measures of observed maternal sensitivity to further tease apart whether it is the symptoms per se or the associated impact via maternal sensitivity that affects children's developing emotion-processing abilities. In a large community sample of Dutch preschoolers (N = 770), we examined independent and mediated effects of maternal depressive symptoms and sensitivity on children's ability to recognize emotional expressions using a nonverbal and a verbal task paradigm. Maternal depressive symptoms predicted less accurate emotion labeling in children, while maternal sensitivity was associated with more accurate emotion matching, especially for sadness and anger. Maternal sensitivity did not mediate the observed associations between mothers' depressive symptoms and children's emotion recognition, and effects were similar for boys and girls. Given that maternal depressive symptoms and sensitivity affected nonoverlapping areas of young children's emotion recognition, prevention and intervention efforts should focus on both alleviating maternal depressive symptoms and improving maternal sensitivity at the same time in order to maximize benefit.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".