O-168 Risk And Resilience Factors For Early Child Development: A Community-based Cohort Study In Alberta, Canada
Bibliographic record
Abstract
Background and aims One in six children experience developmental problems at school entry. Early intervention is more effective than later remediation; however, to date, we lack a comprehensive understanding of risk and protective factors. The objectives of this study were to describe the key risk factors for poor child development at age 12 months and to identify factors that reduce the potentially adverse influence of poor maternal mental health and low socioeconomic status on child development. Methods We used data from the All Our Babies (AOB) study, a prospective pregnancy cohort in Calgary, Alberta. Five domains of child development at age 12 months were assessed via parent report using the Ages and Stages Questionnaire (ASQ) from approximately 1500 mothers. The associations between putative risk factors and poor child development were examined in bivariate and multivariable analyses. A bivariate resilience analysis was also conducted to identify factors related to positive child development in the presence of maternal mental health or sociodemographic risk. Results Key risk factors for poor child development at age 12 months included poor maternal mental health during pregnancy, and low community resource use and lack of adult interaction in the first postpartum year. In addition to parenting efficacy, uptake of community resources and increased adult interaction were protective of poor child development among children most at risk for this outcome. Conclusions As many of the identified risk and protective factors are modifiable, these results can inform community based strategies to optimise early childhood development.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".