Parenting Behaviors, Perceptions, and Psychosocial Risk: Impacts on Young Children's Development
Bibliographic record
Abstract
OBJECTIVE: The goal of this study was to assess which parenting behaviors, perceptions, and risk factors were associated with optimal versus delayed development. METHODS: A total of 382 families from the national Brigance Infant and Toddler Screens standardization and validation study participated. Data sources included parent questionnaires, child testing, and examiner observations of parent-child interactions. Parenting styles research was operationalized with the Brigance Parent-Child Interactions Scale, a brief measure of parenting behaviors and perceptions. RESULTS: Six positive parenting behaviors and perceptions predicted average to above-average development on the Brigance screens. Conversely, <2 positive parenting behaviors and negative perceptions of children indicated child performance nearly 2 SDs below the mean on Brigance screens. Psychosocial risk factors associated with fewer positive parenting behaviors and with negative perceptions included >3 children in the home, multiple moves, limited English, and parental depression. CONCLUSIONS: A dearth of positive parenting behaviors plus negative perceptions of children, with or without psychosocial risk factors, negatively affect child development, which is apparent as early as 6 months of age. The older the child is, the greater the performance gaps are. Language development is particularly at risk when parenting is problematic. Findings underscore the importance of early development promotion with parents, focusing on their talking, playing, and reading with children, and the need for interventions regarding psychosocial risk factors.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.001 | 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".