Addressing adults with adverse childhood experiences requires a team approach
Bibliographic record
Abstract
Objective The primary care office is an ideal setting to identify and address adverse childhood experiences, which is a strong predictor of chronic health outcomes and morbidity. This study sought to understand the experiences of primary care from the perspective of patients who experienced trauma. Method Purposive sampling was used to select eligible and interested participants who identify a high adverse childhood experience score at a residency-based community health center, which offers integrated behavioral health services in primary care. Semistructured in-depth interviews conducted by doctoral-level behavioral health clinicians were audio-recorded, transcribed, and analyzed thematically. Results Subjects ( n = 6) described aspects of medical setting, including removal of clothing or physical touch, that trigger their past trauma, which often resulted in maladaptive stress responses. Subjects also reported sensing when their complexity resulted in negative interpersonal dynamics between team members, and they described fearing abandonment from their team during these heightened stress states. The behavioral health clinician on the health care team served as an advocate, enhanced trust, and allowed for increased continuity and access to care. Conclusions Given the role of adverse childhood experiences in health outcomes and the results of this study, incorporating a trauma-informed approach is essential to treating patients with adverse childhood experiences. We propose that integrating mental health professionals into primary care settings better serves patients with trauma histories.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".