Longitudinal associations between impulsivity and lie‐telling in childhood and adolescence
Bibliographic record
Abstract
Abstract Lie‐telling and impulsivity levels peak during late childhood to early adolescence and have been suggested to be related. Heightened impulsivity may lead adolescents to lie in favor of short‐term benefits without consideration for the potential consequences of deception. The present study assessed longitudinal relations between self‐reported impulsivity and lie‐telling frequency. Participants from a large‐scale longitudinal study ( N = 1148; M age = 11.55, SD = 1.69, 9–15 years at Time 1) reported on their impulsivity (Barratt Impulsiveness Scale) and their frequency of lie‐telling to parents, to teachers, to friends, and about cheating across two time points 1 year apart. Cross‐lagged path analysis revealed greater impulsivity was associated with more frequent lie‐telling to parents, friends, and teachers, and about cheating over time. Our findings demonstrate the role of impulsivity in the development of lie‐telling behaviors. Research Highlights Impulsivity predicts lying across time in multiple contexts (to parents, friends, teachers, and about cheating). Previous research has demonstrated the role of top‐down influences on lie‐telling, but the current study suggests that bottom‐up processes are also influential.
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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 | 0.005 |
| 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 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.002 |
| 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".