Early Maternal Parenting Profiles and Subsequent Child Well‐Being in an Asian Cohort
Bibliographic record
Abstract
ABSTRACT Objective To identify parenting profiles among Singaporean mothers of young children and to examine the longitudinal implications of these profiles for children's well‐being during middle childhood. Background The universality of traditional parenting styles (e.g., authoritative, authoritarian), established in Western contexts, and their implications for child well‐being, has been called into question, with studies conducted with Asian populations suggesting these styles may not be universally applicable. Method Our sample consisted of 411 mother–child dyads drawn from a prebirth cohort in Singapore, where mothers reported on their parenting at child age 4.5 years, and children reported on their evaluation of their mothers' parenting and their own depressive symptoms at ages 9 and 10 years, respectively. Results Three latent class profiles of maternal parenting emerged at child age 4.5 years: Supportive (high use of supportive practices and low use of harsh practices), Supportive‐Harsh (high use of both supportive and harsh practices), and Unsupportive (moderate use of both supportive and harsh practices). Children of Unsupportive mothers reported greater maternal indifference at age 9 years and depressive symptoms at age 10 years compared to children of Supportive or Supportive‐Harsh mothers. Children's evaluation of maternal indifference mediated the association between early maternal parenting profiles and later child depressive symptoms. Conclusion Our findings highlight the variation in parenting profiles in Singapore from well‐established parenting styles, and the greater implications of supportive, compared to harsh, parenting practices for children's 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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.001 | 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".