A Systematic Review of Instruments to Identify Mental Health and Substance Use Problems Among Children in the Emergency Department
Notice bibliographique
Résumé
OBJECTIVE: Specialized instruments to screen and diagnose mental health problems in children and adolescents are not yet standard components of clinical assessments in emergency departments (EDs). We conducted a systematic review to investigate the psychometric properties, accuracy, and performance metrics of instruments used in the ED to identify pediatric mental health and substance use problems. METHODS: We searched seven electronic databases and the gray literature for psychometric validation studies, diagnostic studies, and cohort studies that assessed any instrument to screen for or diagnose mental illness, emotional or behavioral problems, or substance use disorders. Studies had to include children and adolescents with mental health presentations or positive screens for substance use. Two reviewers independently screened studies for relevance and quality. Diagnostic study quality was assessed with the four QUADAS-2 domains. Psychometric study quality was assessed with published criteria for instrument reliability, validity, and usability. We present a descriptive analysis of the reported psychometric properties and diagnostic performance of instruments for each study. RESULTS: Of the 4,832 references screened, 14 met inclusion criteria. Included studies evaluate 18 instruments for identifying suicide risk (six studies), alcohol use disorders (six studies), mood disorders (one study), and ED decision making (need for assessment, admission; one study). Nine studies include a psychometric focus but quality varies, with no studies fully meeting criteria for reliability, validity, and usability. Seven studies examine diagnostic performance of an instrument, but no study has a low risk of bias for all QUADAS-2 domains. The HEADS-ED instrument has good inter-rater reliability (r = 0.785) for identifying general mental health problems and modest evidence for ruling in patients requiring hospital admission (positive likelihood ratio [LR+] = 6.30). Internal consistency (reliability) varies for instruments to screen for suicide risk (α = 0.46-0.97), and no instruments have both high sensitivity and high specificity. The Ask Suicide-Screening Questions (ASQ) is highly sensitive (98%) and has strong evidence for ruling out risk (negative likelihood ratio [LR-] = 0.04). Among screening instruments for alcohol use disorders, internal consistency is high for the consumption subscale of the Alcohol Use Disorders Identification Test (α = 0.83-0.88) and the Adolescent Drinking Index (α = 0.92). Both instruments also had sound internal validity. Diagnostically, a two-item instrument based on DSM-IV criteria is the most accurate in identifying patients with a disorder (area under the curve = 0.89) and has modest evidence for ruling in and out risk (LR+ = 8.80, LR- = 0.13). CONCLUSIONS: From available evidence, we recommend that ED clinicians use 1) the HEADS-ED to rule in ED admission among pediatric patients with visits for mental health care, 2) the ASQ to rule out suicide risk among pediatric patients with any visit type, and 3) the DSM-IV two-item instrument to rule in/rule out alcohol use disorders among pediatric patients currently using alcohol. These instruments require minimal to no training or time commitment. We also recommend that clinicians become familiar with each instrument's psychometric properties to understand the quality of the evidence base. In this review, however, we identify methodologic limitations in the evidence base. To develop a robust evidence base, additional research is necessary.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,004 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,004 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».