Examining the association between cognitive ability and emotional problems across childhood using a genetically informative design: could there be a causal relationship?
Bibliographic record
Abstract
BACKGROUND: Emotional problems co-occur with difficulties in verbal and nonverbal cognitive ability, yet the pathways underlying their association remain poorly understood: It is unclear whether effects may be causal, and to what extent they may run from cognition to emotion, or vice versa. METHODS: Our preregistered analyses included 5,124 twin pairs from the Twins Early Development Study (TEDS). At ages 7, 9 and 12, emotional problems were assessed through the strengths and difficulties questionnaire, and cognition was assessed using task-based measures. Cross-lagged models examined the influence of cognition and subdomains of verbal and nonverbal abilities on emotional problems and vice versa, across development. Genetic cross-lagged models examined the effect of cognition on emotional problems and vice versa, after controlling for shared genetic and environmental influence. RESULTS: Cross-lagged paths in both directions were observed between cognitive ability and emotional problems (from -0.11 to -0.05). Cross-lagged associations that persisted after accounting for common genetic and environmental influences were between nonverbal ability and emotional problems. Higher emotional problems at age 7 predicted lower nonverbal ability at age 9, with 22% of the phenotypic association remaining. This, in turn, predicted greater emotional problems at age 12, with 13% of the association remaining. CONCLUSIONS: Genetic and environmental factors accounted for a large proportion of the cross-lagged associations. Emotional problems in early childhood could result in a cascade effect, leading to lower nonverbal cognition in middle childhood, which increases the risk of emotional problems in late childhood. These findings highlight the importance of age- and domain-specific interventions.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".