Unpacking the effects of child maltreatment subtypes on emotional competence in emerging adults.
Bibliographic record
Abstract
OBJECTIVE: Child maltreatment is often studied as a general category or individually as a subtype, but maltreatment subtypes are rarely studied simultaneously. Despite a breadth of research in the effects of child maltreatment on emotional competence, discrepant findings emerge when child maltreatment subtypes are explored. The present study aims to better understand the differential effects of childhood maltreatment subtypes on facets of emotion regulation and the recognition of specific emotions. METHOD: A sample of 573 emerging adults (87% female) aged 18-25 was recruited to complete an online survey that asked about child maltreatment history, difficulty with emotion regulation, and involved an emotion recognition task. RESULTS: Path analyses indicated that emotional maltreatment had a global effect on the facets of emotion regulation and the recognition of negatively valanced emotions (anger, fear, and sadness). Neglect predicted difficulties with managing impulsive behavior; sexual abuse predicted difficulties engaging in goal-directed behavior. Physical abuse was associated with poorer recognition of fear. Multigroup analysis suggested that patterns did not differ between clinically distressed and nondistressed participants. CONCLUSIONS: These results highlight the importance of including a standard set of child maltreatment subtypes in prediction models of emotional competence to avoid the misattribution or overestimation of the effects of child maltreatment subtype on emotional competence. (PsycInfo Database Record (c) 2023 APA, all rights reserved).
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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 | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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 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".