Evidence map›Paper›PMID 42291675›Full record

ArticleJCPP advances2026

Attention-deficit hyperactivity disorder in children and young persons during the COVID-19 pandemic. A temporal trends analysis of electronic heath records in Greater Manchester, England.

Louise Hussey, Evangelos Kontopantelis, Pearl L H Mok, Darren M Ashcroft, Shruti Garg, Carolyn A Chew-Graham, Karina Lovell, Roger T Webb

Abstract read
In one paragraph

Article in JCPP advances, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Louise HusseyDivision of Psychology and Mental Health Manchester Academic Health Sciences Centre The University of Manchester Manchester UK.ORCID https://orcid.org/0000-0001-6108-5085
Evangelos KontopantelisNational Institute for Health and Care Research (NIHR) Applied Research Collaboration - Greater Manchester (ARC-GM) The University of Manchester Manchester UK.ORCID https://orcid.org/0000-0001-6450-5815
Pearl L H MokCentre for Pharmacoepidemiology & Drug Safety Division of Pharmacy and Optometry School of Health Sciences Manchester Academic Health Sciences Centre The University of Manchester Manchester UK.ORCID https://orcid.org/0000-0001-9983-6374
Darren M AshcroftCentre for Pharmacoepidemiology & Drug Safety Division of Pharmacy and Optometry School of Health Sciences Manchester Academic Health Sciences Centre The University of Manchester Manchester UK.ORCID https://orcid.org/0000-0002-2958-915X
Shruti GargDivision of Psychology and Mental Health Manchester Academic Health Sciences Centre The University of Manchester Manchester UK.ORCID https://orcid.org/0000-0002-4472-4583
Carolyn A Chew-GrahamFaculty of Medicine and Health Sciences School of Medicine Keele University Newcastle-under-Lyme UK.ORCID https://orcid.org/0000-0002-9722-9981
Karina LovellNational Institute for Health and Care Research (NIHR) Applied Research Collaboration - Greater Manchester (ARC-GM) The University of Manchester Manchester UK.ORCID https://orcid.org/0000-0001-8821-895X
Roger T WebbDivision of Psychology and Mental Health Manchester Academic Health Sciences Centre The University of Manchester Manchester UK.ORCID https://orcid.org/0000-0001-8532-2647

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: The incidence of attention-deficit hyperactivity disorder (ADHD) in children and young people has increased in recent years. Disease frequency varies according to sociodemographic characteristics. There are seasonal patterns in ADHD diagnosis and prescribing with rates falling during school holidays. COVID-19 societal restrictions may have exacerbated ADHD symptoms. Electronic health records were utilised to examine temporal trends throughout the pandemic in the diagnosis and treatment of ADHD by ethnicity and social deprivation in Greater Manchester, England. Methods: We conducted a time-series analysis of all diagnosed episodes of ADHD and associated medication prescribing among patients aged 1-24 years using the Greater Manchester Care Record (GMCR). The 60-month observation period was split into four temporal phases: Pre-pandemic (1/2019-2/2020); Pandemic Phase 1 (3/2020-6/2021); Pandemic Phase 2 (7/2021-12/2022) and Post-Pandemic (1/2023-12/2023). Rate ratios by sex, age, ethnicity, and neighbourhood-level Indices of Multiple Deprivation (IMD) quintile were modelled using negative binomial regression. Results: Overall, ADHD incidence and medication prescribing rates increased throughout the study period. Rates of increase were much higher in females than in males. Particularly large increases in ADHD incidence and medication prescribing were observed in Asian females, with post-pandemic incidence rates being seven times higher compared to the Pre-Pandemic phase. In addition, the ADHD medication prescribing rate was 90% higher for Asian females than for White females. Results showed a large increase in incidence and prescribing rates in the least deprived group, particularly in males where incidence rates increased by 83% compared to the most deprived quintile. Conclusions: ADHD incidence and prescribing rates differ between sociodemographic groups, plausibly due to cultural and behavioural differences in the way ADHD symptoms are presented or perceived. It is therefore important that there is greater understanding of how different demographic subgroups exhibit ADHD behaviour to help ensure timely diagnosis and access to the required support.

Indexed as

ADHDchildren and young peopleCOVID‐19deprivationethnicity

Identifiers

PMID42291675
PMCPMC13260708

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.