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Enregistrement W4392392433 · doi:10.1016/j.jaac.2024.02.009

A Systematic Review and Meta-Analysis: Child and Adolescent Healthcare Utilization for Eating Disorders During the COVID-19 Pandemic

2024· review· en· W4392392433 sur OpenAlexaff
Sheri Madigan, Tracy Vaillancourt, Gina Dimitropoulos, Shainur Premji, Selena M. Kahlert, Katie Zumwalt, Daphne J. Korczak, Kristin M. von Ranson, Paolo Pador, Heather Ganshorn, Ross D. Neville

Notice bibliographique

RevueJournal of the American Academy of Child & Adolescent Psychiatry · 2024
Typereview
Langueen
DomainePsychology
ThématiqueEating Disorders and Behaviors
Établissements canadiensHospital for Sick ChildrenUniversity of TorontoUniversity of OttawaHotchkiss Brain InstituteAlberta Children's HospitalUniversity of Calgary
Organismes subventionnairesnon disponible
Mots-clésPsycINFOMeta-analysisMedicineEating disordersMEDLINEPandemicEmergency departmentModerationRelative riskPediatricsHealth careInpatient carePsychiatryConfidence intervalCoronavirus disease 2019 (COVID-19)PsychologyInternal medicineDisease

Résumé

récupéré en direct d'OpenAlex

OBJECTIVE: To conduct a meta-analysis documenting healthcare service utilization rates for pediatric (age <19 years) eating disorders during compared to before the COVID-19 pandemic. METHOD: PsycINFO, MEDLINE, Embase, and Web of Science Core Collection were searched for studies published up to May 19, 2023. Studies with pediatric visits to primary care, inpatient, outpatient, and emergency department for eating disorders before and during the pandemic were included. This preregistered review (PROSPERO CRD42023413392) was reported using PRISMA guidelines. Data were analyzed with random-effects meta-analyses. RESULTS: A total of 52 studies reporting >148,000 child and adolescent eating disorder-related visits to >300 health settings across 15 countries were included (mean age, 12.7 years; SD = 4.1 years; 87% girls). There was strong evidence of an increase in healthcare use for eating disorders during the pandemic (rate ratio [RR] = 1.54, 95% CI = 1.38-1.71). Moderator analysis revealed larger rate increases among girls (RR = 1.48, 95% CI = 1.28-1.71) compared to boys (RR = 1.24, 95% CI = 1.06-1.45) and for adolescents (age ≥12 to 19 years) (RR = 1.53, 95% CI = 1.29-1.81) compared to children (RR = 0.87, 95% CI = 0.53-1.43). Moderator analysis demonstrated strong evidence of increased use of emergency department (RR = 1.70, 95% CI = 1.48-1.97), inpatient (RR = 1.56, 95% CI = 1.33-1.84), and outpatient (RR = 1.62, 95% CI = 1.35-1.95) services, as well as strong evidence of increased rates of anorexia nervosa (RR = 1.48, 95% CI = 1.24-1.75). CONCLUSION: Healthcare use for pediatric eating disorders increased substantially during the COVID-19 pandemic, particularly among girls and adolescents. It is important to continue to monitor whether changes in healthcare use associated with acute pediatric mental distress are sustained beyond the COVID-19 pandemic. PLAIN LANGUAGE SUMMARY: In this study, the authors analyzed data from 52 studies from 15 countries and found a significant increase in healthcare utilization for eating disorders during the COVID-19 pandemic. The study findings suggest a larger rate increase among adolescents as compared to children, in girls versus boys, and for anorexia nervosa in particular. Results also indicate increased use of emergency department, inpatient and outpatient services for eating disorders during the pandemic. STUDY PREREGISTRATION INFORMATION: Risk factors for eating disorders for youth during the COVID-19 pandemic; https://www.crd.york.ac.uk/; CRD42023413392. DIVERSITY & INCLUSION STATEMENT: One or more of the authors of this paper self-identifies as a member of one or more historically underrepresented racial and/or ethnic groups in science. One or more of the authors of this paper self-identifies as living with a disability. We actively worked to promote sex and gender balance in our author group. We actively worked to promote inclusion of historically underrepresented racial and/or ethnic groups in science in our author group. While citing references scientifically relevant for this work, we also actively worked to promote sex and gender balance in our reference list. While citing references scientifically relevant for this work, we also actively worked to promote inclusion of historically underrepresented racial and/or ethnic groups in science in our reference list. The author list of this paper includes contributors from the location and/or community where the research was conducted who participated in the data collection, design, analysis, and/or interpretation of the work. One or more of the authors of this paper self-identifies as a member of one or more historically underrepresented sexual and/or gender groups in science.

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 machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,028
score de la tête « metaresearch » (Gemma)0,065
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Méta-analyse · Signal consensuel: Méta-analyse
GenreSignal candidat: Synthèse · Signal consensuel: Synthèse
Score de désaccord entre enseignants0,028
Score d'incertitude au seuil0,147

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0280,065
Méta-épidémiologie (sens strict)0,0040,002
Méta-épidémiologie (sens large)0,0260,063
Bibliométrie0,0090,008
Études des sciences et des technologies0,0010,001
Communication savante0,0050,003
Science ouverte0,0030,002
Intégrité de la recherche0,0030,003
Charge utile insuffisante (le modèle a refusé de juger)0,0040,000

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.

Tête enseignante Opus0,085
Tête enseignante GPT0,420
Écart entre enseignants0,335 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeMéta-analyse
Domainenon disponible
GenreSynthèse

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations36
Publié2024
Routes d'admission1
Résumé présentoui

Explorer davantage

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