Convergence in maternal and child reports of impulsivity, depressive symptoms, and trait anxiety, and their predictive utility for binge‐eating behaviors
Bibliographic record
Abstract
OBJECTIVE: Early detection of binge-eating (BE) behaviors and their risk factors is associated with better outcomes. A multi-informant approach for assessing BE psychopathology and risk factors has been emphasized to increase the probability and accuracy of early detection. Impulsivity (particularly negative and positive urgency), trait anxiety, and depressive symptoms are associated with BE behaviors. The present study examined maternal-child convergence of reports of child BE, impulsivity, trait anxiety, and depressive symptoms and examined the predictive power of maternal reports for child-reported BE behaviors. METHOD: Participants included 927 female twins (aged 8-16 years) and 468 mothers from the Michigan State University Twin Registry. Risk factors and BE were assessed with self-report questionnaires. RESULTS: Intraclass correlation coefficients showed fair-to-moderate inter-rater agreement (ICCs = .31-.41) between maternal and child reports of risk factors and low-to-fair agreement for BE (ICCs = .05-.29). Controlling for the effects of age, pubertal status, body mass index, and family relatedness, multilevel models showed that maternal reports of child impulsivity, anxiety, and depressive symptoms did not add predictive power above and beyond child reports. DISCUSSION: Results call into question the utility and practical implications of using maternal reports to supplement child reports for BE and its risk factors.
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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 | 0.003 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 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".