Family Factors and Repeat Pediatric Emergency Department Visits for Mental Health: A Retrospective Cohort Study.
Bibliographic record
Abstract
OBJECTIVES: Approximately 45% of youth presenting to the emergency department (ED) for mental health (MH) concerns will have a repeat ED visit. Since youth greatly depend on their caregivers to access MH services, the objective of this study was to determine if family characteristics were associated with repeat ED visits. METHODS: A retrospective cohort study of youth aged 6-18 years (62% female) treated at a tertiary pediatric ED for a discharge diagnosis related to MH was conducted. Data were gathered from medical records, telephone interviews, and questionnaires. Family factor contribution was analyzed using a multivariable logistic regression model controlling for demographic, clinical and service utilization factors. Variables associated with earlier and more frequent visits were determined using cox regression and negative binomial regression. RESULTS: Of 266 participants, 70 (26%) had a repeat visit. While caregiver history of MH treatment decreased the odds of having a repeat ED visit, family functioning and perceived family burden were not associated with repeat visits. Post-visit MH services, prior psychiatric hospitalization, higher severity of symptoms, and living closer to the hospital increased the odds of repeat visits. CONCLUSIONS: This study examined the contribution of multiple family factors in predicting repeat MH visits to the ED. Results suggest caregiver characteristics may impact the decision to return. Healthcare providers should therefore consider caregiver and youth service utilization factors to inform patient management and discharge planning.
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 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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| 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 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".