The contributions of child–mother attachment, maternal parenting stress, and military status to the prediction of child behavior problems
Bibliographic record
Abstract
Studies show that children with a military parent are at heightened risk of the development of behavior problems. However, there is limited work examining how other factors experienced by military families may also influence behavior problems. In the current study, we recruited three types of Canadian families with a preschooler: families with a deployed military member, families with a nondeployed military member, and nonmilitary families. We examined whether the nonmilitary parent's (in all cases the mother) parenting stress and attachment relationship with the child are associated with behavior problems, and whether deployment status further contributes to the prediction. Child-mother dyads participated in an observed attachment assessment, and mothers reported on their stress levels and their child's behavior. Results showed that both child attachment insecurity and parenting stress were associated with elevated levels of internalizing problems; however, only parenting stress was associated with conduct problems. Military deployment predicted higher levels of internalizing and conduct problems beyond the contributions of attachment and stress. Furthermore, having a father in the military (whether deployed or not) also contributed to internalizing problems. These findings shed light on how the military lifestyle impacts early childhood mental health through the complex interplay between various parts of their environment.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.002 | 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".