The co-occurrence of adverse childhood experiences and mental health among Latina/o adults: A latent class analysis approach
Bibliographic record
Abstract
Adverse childhood experiences (ACEs) have been linked to poor mental health among Latina/os. Few studies, however, have attempted to understand the extent to which ACEs co-occur and whether different forms of ACE co-occurrence differentially shape poor mental health patterns among Latina/os. The present study begins to address this gap by (1) identifying latent classes of ACEs and (2) determining whether and how different ACE classes shape high depressive symptoms among Latina/o adults. Data were drawn from two waves of the Hispanic Community Health Study/Study of Latinos, a longitudinal, community-based sample of Latina/os living in four urban communities. Latent Class Analysis (LCA) was used to identify subgroups of Latina/os who were exposed to co-occurring forms of maltreatment. Results from the LCA revealed four classes: (1) high ACEs, (2) emotional and physical abuse, (3) low ACEs, and (4) household alcohol/drug use and parental separation/divorce. Regression analyses indicate, when compared to the low ACEs class, Latina/os in the high ACEs class and emotional/physical abuse class were more likely to report high depressive symptoms. Findings from this study demonstrate ACEs co-occur in distinct classes of maltreatment and different combinations of ACEs uniquely shape the risk of poor mental health among Latina/os. Results from this study can help inform tailored mental health interventions for Latina/os that have a history of ACE exposure.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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".