The influence of COVID-19 on attention-deficit/hyperactivity disorder diagnosis and treatment rates across age, gender, and socioeconomic status: A 20-year national cohort study.

ADHD Adolescents COVID-19 Children Diagnosis Machine-learning Prevalence

Journal

Psychiatry research
ISSN: 1872-7123
Titre abrégé: Psychiatry Res
Pays: Ireland
ID NLM: 7911385

Informations de publication

Date de publication:
06 Jul 2024
Historique:
received: 06 01 2024
revised: 27 06 2024
accepted: 30 06 2024
medline: 26 7 2024
pubmed: 26 7 2024
entrez: 25 7 2024
Statut: aheadofprint

Résumé

Infection and lockdowns resulting from COVID-19 have been suggested to increase the prevalence and treatment rates of Attention Deficit/Hyperactivity Disorder (ADHD). To accurately estimate the pandemic's effects, pre-pandemic data can be used to estimate diagnosis and treatment rates during the COVID-19 years as if the COVID-19 pandemic did not occur. However, accurate predictions require a broad dataset, both in terms of the number of cases and the pre-pandemic timeframe. In the current study, we modeled monthly ADHD diagnosis and treatment rates over the 18 years preceding the COVID-19 pandemic. The dataset included ∼3 million cases for individuals aged 6 to 18 from the Clalit Health Services' electronic database. Using a trained model, we projected monthly rates for post-lockdown and post-infection periods, enabling us to estimate the expected diagnosis and treatment rates without the COVID-19 pandemic. We then compared these predictions to observed data, stratified by age groups, gender, and socioeconomic status. Our findings suggest no influence of the COVID-19 pandemic on ADHD diagnosis or treatment rates. We show that a narrower timeframe for pre-COVID-19 data points can lead to incorrect conclusions that COVID-19 affected ADHD diagnosis rates. Findings are discussed, given the assumed impact of the COVID-19 pandemic on ADHD.

Identifiants

pubmed: 39053214
pii: S0165-1781(24)00362-7
doi: 10.1016/j.psychres.2024.116077
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

116077

Informations de copyright

Copyright © 2024. Published by Elsevier B.V.

Déclaration de conflit d'intérêts

Declaration of competing interest The authors declare no conflicts or competing interests relevant to this article.

Auteurs

Vered Shkalim Zemer (V)

Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel; Dan-Petach-Tikva District, Clalit Health Services, Israel. Electronic address: shine6@walla.co.il.

Iris Manor (I)

Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel; Dan-Petach-Tikva District, Clalit Health Services, Israel; Geha Mental Health Center, Petah Tikva, Israel.

Abraham Weizman (A)

Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel; Dan-Petach-Tikva District, Clalit Health Services, Israel; Sagol School of Neuroscience, Tel Aviv University, Tel Aviv, Israel.

Herman Avner Cohen (HA)

Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel; Pediatric Ambulatory Community Clinic, Petach Tikva, Israel.

Moshe Hoshen (M)

Dan-Petach-Tikva District, Clalit Health Services, Israel; Bioinformatics Department, Jerusalem College of Technology, Jerusalem, Israel.

Noa Menkes Caspi (N)

Geha Mental Health Center, Petah Tikva, Israel.

Shira Cohen (S)

Geha Mental Health Center, Petah Tikva, Israel.

Stephen V Faraone (SV)

Departments of Psychiatry and Neuroscience and Physiology, SUNY Upstate Medical University, Syracuse, NY, USA.

Nitzan Shahar (N)

The School of Psychological Sciences, Tel Aviv University, Tel Aviv, Israel; Sagol School of Neuroscience, Tel Aviv University, Tel Aviv, Israel.

Classifications MeSH