Evidence map›Paper›PMID 38344903›Full record

ArticleBJPsych open2024

Variation in symptoms of common mental disorders in the general population during the COVID-19 pandemic: longitudinal cohort study.

Rob Saunders, Joshua E J Buckman, Jae Won Suh, Peter Fonagy, Stephen Pilling, Feifei Bu, Daisy Fancourt

Abstract read
In one paragraph

Article in BJPsych open, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

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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

7 authors.

Rob SaundersCORE Data Lab, Centre for Outcomes Research and Effectiveness (CORE), Research Department of Clinical, Educational & Health Psychology, University College London, UK.ORCID https://orcid.org/0000-0002-7077-8729
Joshua E J BuckmanCORE Data Lab, Centre for Outcomes Research and Effectiveness (CORE), Research Department of Clinical, Educational & Health Psychology, University College London, UK; and iCope Psychological Therapies Service, Camden & Islington NHS Foundation Trust, St Pancras Hospital, London, UK.ORCID https://orcid.org/0000-0002-2281-0907
Jae Won SuhCORE Data Lab, Centre for Outcomes Research and Effectiveness (CORE), Research Department of Clinical, Educational & Health Psychology, University College London, UK.
Peter FonagyResearch Department of Clinical, Educational and Health Psychology, University College London, UK.ORCID https://orcid.org/0000-0003-0229-0091
Stephen PillingCORE Data Lab, Centre for Outcomes Research and Effectiveness (CORE), Research Department of Clinical, Educational & Health Psychology, University College London, UK; and Camden & Islington NHS Foundation Trust, London, UK.ORCID https://orcid.org/0000-0002-7361-8202
Feifei BuDepartment of Behavioural Science and Health, University College London, UK.ORCID https://orcid.org/0000-0003-2060-3768
Daisy FancourtDepartment of Behavioural Science and Health, University College London, UK.ORCID https://orcid.org/0000-0002-6952-334X

Funding

Wellcome TrustWellcome Trust 205407/Z/16/ZWellcome Trust 221400/Z/20/Z
6 · The paper itself

Abstract

backgroundA significant rise in mental health disorders was expected during the COVID-19 pandemic. However, referrals to mental health services dropped for several months before rising to pre-pandemic levels.

aimsTo identify trajectories of incidence and risk factors for common mental disorders among the general population during 14 months of the COVID-19 pandemic, to inform potential mental health service needs.

methodA cohort of 33 703 adults in England in the University College London COVID-19 Social Study provided data from March 2020 to May 2021. Growth mixture modelling was used to identify trajectories based on the probability of participants reporting symptoms of depression (Patient Health Questionnaire-9) or anxiety (Generalised Anxiety Disorder-7) in the clinical range, for each month. Sociodemographic and personality-related characteristics associated with each trajectory class were explored.

resultsFive trajectory classes were identified for depression and anxiety. Participants in the largest class (62%) were very unlikely to report clinically significant symptom levels. Other trajectories represented participants with a high likelihood of clinically significant symptoms throughout, early clinically significant symptoms that reduced over time, clinically significant symptoms that emerged as the pandemic unfolded and a moderate likelihood of clinically significant symptoms throughout. Females, younger adults, carers, those with existing mental health diagnoses, those that socialised frequently pre-pandemic and those with higher neuroticism scores were more likely to experience depression or anxiety.

conclusionsNearly 40% of participants followed trajectories indicating risk of clinically significant symptoms of depression or anxiety. The identified risk factors could inform public health interventions to target individuals at risk in future health emergencies.

Indexed as

Anxiety or fear-related disorderscohort studydepressive disordersepidemiologystatistical methodology

Identifiers

PMID38344903
PMCPMC10897705

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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.