Evidence map›Paper›PMID 39803610›Full record

ArticleCurrent epidemiology reports2024

Psychiatric Epidemiology During the COVID-19 Pandemic.

Jerzy Eisenberg-Guyot, Rachel Presskreischer, John R Pamplin

Abstract read
In one paragraph

Article in Current epidemiology reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Review
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

3 authors.

Jerzy Eisenberg-GuyotDepartment of Epidemiology, Mailman School of Public Health, Columbia University, NY, NY.
Rachel PresskreischerDepartment of Epidemiology, Mailman School of Public Health, Columbia University, NY, NY.
John R PamplinDepartment of Epidemiology, Mailman School of Public Health, Columbia University, NY, NY.

Funding

RESEARCH TRAINING PROGRAM IN PSYCHIATRIC EPIDEMIOLOGYT32MH013043 · NIMH · COLUMBIA UNIV NEW YORK MORNINGSIDE · PI Katherine M. Keyes · 1985 to 2026
$11.7M
Racial Inequities in Opioid Overdose Prevention: The role of local context in the effectiveness of state-level overdose prevention policiesK01DA058085 · NIDA · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI John Richard Pamplin · 2023 to 2026
$743k
NCCDPHP CDC HHS U48 DP006396NIDA NIH HHS K01 DA058085NIMH NIH HHS T32 MH013043
6 · The paper itself

Abstract

Purpose of review: Our review critically examines research on trends in mental health among US adults following the COVID-19 pandemic's onset and makes recommendations for research on the topic. Recent findings: Studies comparing pre-pandemic nationally representative government surveys ("benchmark surveys") with pandemic-era non-benchmark surveys generally estimated 3-4-fold increases in the prevalence of adverse mental-health outcomes following the pandemic's onset. However, studies analyzing trends in repeated waves of a single survey, which may carry a lower risk of bias, generally estimated much smaller increases in adverse outcomes. Likewise in our analysis of benchmark surveys, we estimated <1% increases in the prevalence of adverse outcomes from 2018/2019-2021. Finally, studies analyzing vital-statistics data estimated spiking fatal-overdose rates, but stable suicide rates. Summary: Although fatal-overdose rates increased substantially following the pandemic's onset, evidence suggests the population prevalence of other adverse mental-health outcomes may have departed minimally from prior years' trends, at least through 2021. Future research on trends through the pandemic's later stages should prioritize leveraging repeated waves of benchmark surveys to minimize risk of bias.

Indexed as

COVID-19epidemiologymental disordersmental healthmood disorderspsychiatric

Identifiers

PMID39803610
PMCPMC11720142

What OpenQuestion holds

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Registered trials

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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.