Childhood emotional maltreatment and mental disorders: Results from a nationally representative adult sample from the United States
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Child maltreatment is a public health concern with well-established sequelae. However, compared to research on physical and sexual abuse, far less is known about the long-term impact of emotional maltreatment on mental health. The overall purpose of this study was to examine the association of emotional abuse, emotional neglect, and both emotional abuse and neglect with other types of child maltreatment, a family history of dysfunction, and lifetime diagnoses of several Axis I and Axis II mental disorders. Data were from the National Epidemiological Survey on Alcohol and Related Conditions collected in 2004 and 2005 (n=34,653). The most prevalent form of emotional maltreatment was emotional neglect only (6.2%), followed by emotional abuse only (4.8%), and then both emotional abuse and neglect (3.1%). All categories of emotional maltreatment were strongly related to other forms of child maltreatment (odds ratios [ORs] ranged from 2.1 to 68.0) and a history of family dysfunction (ORs ranged from 2.2 to 8.3). In models adjusting for sociodemographic characteristics, all categories of emotional maltreatment were associated with increased odds of almost every mental disorder assessed in this study (adjusted ORs ranged from 1.2 to 7.4). Many relationships remained significant independent of experiencing other forms of child maltreatment and a family history of dysfunction (adjusted ORs ranged from 1.2 to 3.0). The effects appeared to be greater for active (i.e., emotional abuse) relative to passive (i.e., emotional neglect) forms of emotional maltreatment. Childhood emotional maltreatment, particularly emotionally abusive acts, is associated with increased odds of lifetime diagnoses of several Axis I and Axis II mental disorders.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 it