Associations between observed temperament in preschoolers and parent psychopathology
Bibliographic record
Abstract
Parent history of psychopathology is an established marker of children's own risk for later disorder and can therefore be used as a means of validating other risks, such as child temperament. While associations between children's temperament and parent psychopathology have been reported, few studies have used observational measures of child temperament or examined trait interactions, particularly between children's affective and regulatory traits such as effortful control (EC). In this bottom-up family study of 968 three-year-olds and their parents, we examined interactions between preschoolers' observed positive and negative affectivity (NA) and EC as predictors of a known marker of psychopathology risk: parent history of disorder. Children with lower positive affectivity had an increased probability of paternal depression history in the context of higher child NA. In addition, children with lower EC and higher NA had an increased probability of maternal anxiety. Findings shed new light on the main effects and interactions that account for associations between child temperament and parent history of disorder, one of the best-established markers of an individual's own risk for future disorder, implicating reactive and regulatory traits that merit special consideration in future longitudinal work. Copyright © 2017 John Wiley & Sons, Ltd.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 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".