The HEADS-ED
Bibliographic record
Abstract
OBJECTIVES: This effectiveness study aimed to evaluate the clinical use of the HEADS-ED tool for patients presenting to a pediatric emergency department (PED) for mental health (MH) care. METHODS: In this pragmatic trial, PED physicians used the HEADS-ED to guide their assessment and identify areas of MH need in 639 patients (mean [SD], 15.16 [1.40] years; female, 72.6%) who presented to the emergency department with MH concerns between May 2013 and March 2014. RESULTS: The HEADS-ED guided consultation to psychiatry/crisis, with 86% receiving a recommended consult. Those with a HEADS-ED score of greater than or equal to 8 and suicidality of 2 (relative risk, 2.64; confidence interval, 2.28-3.06) had a 164% increased risk of physicians requesting a consult compared with those with a score of less than 8 or greater than or equal to 8 with no suicidality of 2. The HEADS-ED mean score was significantly higher for those who received a consult (M = 6.91) than those who did not (M = 4.70; P = 0.000). Similarly, the mean score for those admitted was significantly higher (M = 7.21) than those discharged (M = 5.28; P = 0.000). Agreement on needs requiring action between PED physicians and crisis intervention workers was obtained for a subset of 140 patients and ranged from 62% to 93%. CONCLUSIONS: Results support the HEADS-ED's use by PED physicians to help guide the assessment and referral process and for discussing the clinical needs of patients among health care providers using a common action-oriented language.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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 | 0.002 | 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 | 0.001 |
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; both teacher heads agree on what is shown here.
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".