Evidence map›Paper›PMID 37920404›Full record

ArticleAJPM focus2023

Evolution of Depression and Anxiety During the COVID-19 Pandemic and Across Demographic Groups in a Large Sample of U.S. Adults.

Catherine K Ettman, Elena Badillo-Goicoechea, Elizabeth A Stuart

Open access · goldAbstract read
In one paragraph

Article in AJPM focus, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed, 1 pooled it
4.4field-weighted citation impact, top 5% of its field
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

6 citing papers in PubMed, 1 synthesis or guideline pooled it, 14 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
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 at 1 institution in 1 country.

Catherine K EttmanDepartment of Mental Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland.
Elena Badillo-GoicoecheaDepartment of Mental Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland.
Elizabeth A StuartDepartment of Mental Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland.
Johns Hopkins University · US

Funding

Combining data sources to identify effect moderation for personalized mental health treatmentR01MH126856 · NIMH · JOHNS HOPKINS UNIVERSITY · PI STUART, ELIZABETH A. · 2021 to 2024
$1.7M
NIMH NIH HHS R01 MH126856
6 · The paper itself

Abstract

Introduction: This study aimed to document the trends of feelings of depression and anxiety over the course of the COVID-19 pandemic within and across age, gender, education, and employment groups. Methods: Using a large, national, serial cross-sectional sample of adults in the U.S. collected through the COVID-19 Trends and Impact Survey conducted in partnership with Facebook, we examined trends in feelings of depression and anxiety from April 2020 through June 2022 (N=21,359,165). Results: Over time, differences in feelings of anxiety and depression widened for educational attainment, stayed consistent between employment groups, and narrowed for female versus male and age groups. The odds of frequent feelings of anxiety or depression were significantly lower in the studied final quarter (April-June 2022) than in the studied first quarter (October-December 2020) for the overall population ( Conclusions: The risk factors most highly associated with poor mental health 2 years into the pandemic were young age, nonbinary gender, and low educational attainment.

Indexed as

anxiety, COVID-19 pandemicDepressiongender identitymental health

Identifiers

PMID37920404
PMCPMC10618701
OpenAlexW4385776839

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

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.