A Tri-Directional Examination of Parental Personality, Parenting Behaviors, and Contextual Factors in Influencing Adolescent Behavioral Outcomes
Bibliographic record
Abstract
Abstract Links between parental personality, parenting, and adolescent behavior have been well established. However, extant research is limited by the sole focus on parental Big Five personality, and not taking home and family context into account. These gaps were addressed in two studies. In study 1, context, parental personality, and their interactions were examined as predictors of parenting in separate mother and father models (parents only). In study 2, context, parental personality, and parenting were examined as predictors of adolescent behavioral outcomes (parent–adolescent dyads). Parents (N = 283, 45.6% mothers, Mage = 45.51 years) completed assessments of socioeconomic status (SES), adverse childhood experiences (ACEs), personality (Big Five, Dark Triad), and parenting. Adolescents (N = 257, 51.4% female, Mage = 13.65 years) completed an assessment of behavior. Parent Dark Triad domains explained more variance in parental warmth and hostility than the Big Five, but equivalent variance in adolescent behavior. SES interacted with maternal personality, whereas ACEs interacted with paternal personality, to predict parenting behavior. The results showcase the importance of assessing a wider spectrum of parental personality, and examining contextual factors, in affecting adolescent development.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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) | 0.001 | 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".