Abstract
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.
| Original language | English |
|---|---|
| Article number | 116077 |
| Journal | Psychiatry Research |
| Volume | 339 |
| DOIs | |
| State | Published - Sep 2024 |
| Externally published | Yes |
Bibliographical note
Publisher Copyright:© 2024
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
Keywords
- ADHD
- Adolescents
- COVID-19
- Children
- Diagnosis
- Machine-learning
- Prevalence
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