A Rapid-Response Outpatient Model for Reducing Hospitalization Rates Among Suicidal Adolescents
Bibliographic record
Abstract
OBJECTIVE: The authors studied the clinical outcomes of suicidal adolescents who were treated within a rapid-response outpatient model in a setting in which a ten-day wait was usually required before outpatient treatment could be started, leaving hospitalization as the only immediately available alternative. METHODS: A total of 286 suicidal adolescents aged 12 to 17 years who came to the emergency department of a pediatric hospital were assigned to receive rapid-response outpatient follow-up (the experimental group) or to a control group. Demographic and clinical data were obtained at baseline, and outcomes data were obtained at two and six months. RESULTS: The demographic and clinical characteristics of the two groups were similar at baseline. Hospitalization rates in the experimental and control groups, respectively, were 10 percent and 40 percent at baseline, 17 percent and 41 percent at two-month follow-up, and 18 percent and 43 percent at six-month follow-up, corresponding to a relative risk of hospitalization of.41 in the experimental group at six months. No between-group differences were observed in changes in levels of suicidality or in overall functioning over the follow-up period, and none of the patients had died at six months. CONCLUSIONS: Suicidal adolescents who received rapid-response outpatient follow-up had a lower hospitalization rate than those who did not. The two groups achieved similar increases in levels of functioning and decrease in levels of suicidality, suggesting that suicidal adolescents can be treated within a rapid-response outpatient model and thus avoid hospitalization.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".