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Record W2914806201 · doi:10.3389/fpsyt.2019.00026

Changes in the Use of Emergency Care for the Youth With Mental Health Problems Over Decades: A Repeated Cross Sectional Study

2019· article· en· W2914806201 on OpenAlexaff
Xavier Benarous, Vanessa Milhiet, Alice Oppetit, Sylvie Viaux‐Savelon, Nadjia Mahi El Kamel, Vincent Guinchat, Jean-Marc Guilé, Doron Cohen

Bibliographic record

VenueFrontiers in Psychiatry · 2019
Typearticle
Languageen
FieldPsychology
TopicChild and Adolescent Psychosocial and Emotional Development
Canadian institutionsMcGill University
Fundersnot available
KeywordsOvercrowdingMental healthContext (archaeology)MedicinePsychological interventionEmergency departmentAnxietyReferralPsychiatryMedical emergencyFamily medicine

Abstract

fetched live from OpenAlex

To understand whether changes exist in the types of youths mental health problems addressed in emergency in a context of increasing demand, we conducted a retrospective chart review in an emergency care outpatient unit. Data from children and adolescents admitted at four different time periods (years 1981, 1992, 2002, and 2017) were compared to determine trends in terms of patients' characteristics, nature of the mental health problems and final care decisions. Between 1981 and 2017 there was a 3.85 times increase in the annual number of patients presenting to the emergency consultations. The proportion of youths being referred for anxiety or depressive symptoms sharply increased over time, while no differences were found for the proportion of aggressive behaviors and suicidal attempts. Anxiety disorders became the most frequent discharge psychiatric disorder in youths admitted in the emergency unit, rising from 5% in 1981 to 34% in 2017. Significant changes were also observed in the source of referral to the emergency unit; in particular emergency consultations in 2017 were about twice as likely as in 1981 to be requested directly by the family. This data suggested that the increased use of emergency services observed over the last decades is associated with significant changes in the patient and his/her family's demands about mental health difficulties. Such findings are worth considering for mental health interventions that aim to address the emergency overcrowding issue.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.025
Threshold uncertainty score0.350

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.037
GPT teacher head0.315
Teacher spread0.278 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations31
Published2019
Admission routes1
Has abstractyes

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