Provider Knowledge and Confidence with Implementing Pediatric Adverse Childhood Experiences (ACEs) Screening Tool in an Alaskan Family Practice Clinic
Bibliographic record
Abstract
Adverse childhood experiences (ACEs) have been known to be associated with negative developmental and long-term health sequalae since Felitti and colleagues (1998) presented their groundbreaking research nearly a quarter of a century ago. Pediatric and primary care settings have been relatively slow to implement any type of ACEs screening at regular intervals such as at well-child exams (WCEs). A scholarly project implementation was used to present ACEs education and screening training to pediatric primary care providers in a small, private, rural family health care practice in Alaska. The goal of the project was to determine if providers felt more knowledgeable and confident with pediatric ACEs screening after an educational intervention and if screening would increase in clinical practice as a result. Three quantitative Likert-style surveys were administered to providers pre- and post-education as well as three months postimplementation (two qualitative questions were also asked on each survey). A total of 225 pediatric patients aged nine months to 18 years were screened at WCEs by six nurse practitioners over the three-month intervention timeframe. Providers demonstrated a statistically significant increase in ACEs knowledge, especially related to the Center for Youth and Wellness ACE Questionnaire (CYW ACE-Q; p < 0.001), and screening confidence (p = 0.005) from pre- to post ACEs education. Qualitative provider feedback postimplementation was generally positive and included statements like learned so much, enjoyed educating patients, great process, and highly valuable. Pediatric ACEs screening was found to be feasible in primary care with provider ACEs education and training, which improved provider knowledge and confidence with ACEs screenings at WCEs.
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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 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.002 | 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 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".